Learning and Improving in Quality Improvement Collaboratives: Which Collaborative Features Do Participants Value Most?

PubMed Central

Nembhard, Ingrid M

2009-01-01

Objective To understand participants' views on the relative helpfulness of various features of collaboratives, why each feature was helpful and which features the most successful participants viewed as most central to their success. Data Sources Primary data collected from 53 teams in four 2004–2005 Institute for Healthcare Improvement (IHI) Breakthrough Series collaboratives; secondary data from IHI and demographic sources. Study Design Cross-sectional analyses were conducted to assess participants' views of 12 features, and the relationship between their views and performance improvement. Data Collection Methods Participants' views on features were obtained via self-administered surveys and semi-structured telephone interviews. Performance improvement data were obtained from IHI and demographic data from secondary sources. Principal Findings Participants viewed six features as most helpful for advancing their improvement efforts overall and knowledge acquisition in particular: collaborative faculty, solicitation of their staff's ideas, change package, Plan-Do-Study-Act cycles, Learning Session interactions, and collaborative extranet. These features also provided participants with motivation, social support, and project management skills. Features enabling interorganizational learning were rated higher by teams whose organizations improved significantly than by other teams. Conclusions Findings identify features of collaborative design and implementation that participants view as most helpful and highlight the importance of interorganizational features, at least for those organizations that most improve. PMID:19040423

Linguistic feature analysis for protein interaction extraction

PubMed Central

2009-01-01

Background The rapid growth of the amount of publicly available reports on biomedical experimental results has recently caused a boost of text mining approaches for protein interaction extraction. Most approaches rely implicitly or explicitly on linguistic, i.e., lexical and syntactic, data extracted from text. However, only few attempts have been made to evaluate the contribution of the different feature types. In this work, we contribute to this evaluation by studying the relative importance of deep syntactic features, i.e., grammatical relations, shallow syntactic features (part-of-speech information) and lexical features. For this purpose, we use a recently proposed approach that uses support vector machines with structured kernels. Results Our results reveal that the contribution of the different feature types varies for the different data sets on which the experiments were conducted. The smaller the training corpus compared to the test data, the more important the role of grammatical relations becomes. Moreover, deep syntactic information based classifiers prove to be more robust on heterogeneous texts where no or only limited common vocabulary is shared. Conclusion Our findings suggest that grammatical relations play an important role in the interaction extraction task. Moreover, the net advantage of adding lexical and shallow syntactic features is small related to the number of added features. This implies that efficient classifiers can be built by using only a small fraction of the features that are typically being used in recent approaches. PMID:19909518

Mentoring Postsecondary Tenure-Track Faculty: A Theory-Building Case Study and Implications for Institutional Policy

ERIC Educational Resources Information Center

Davis, Dannielle Joy; Boyer, Patricia; Russell, Isela

2011-01-01

The featured research uses theory-building case study to understand the experiences of junior faculty in a mentoring program. Findings suggest the importance of professional interaction for faculty members' integration into their campus communities. An explanatory model illustrates the findings and supplements discussion of the implications for…

Traditional Ecological Knowledge and Global Environmental Change: Research findings and policy implications

PubMed Central

Gómez-Baggethun, Erik; Corbera, Esteve; Reyes-García, Victoria

2015-01-01

This paper introduces the special feature of Ecology and Society entitled “Traditional Ecological Knowledge and Global Environmental Change. The special feature addresses two main research themes. The first theme concerns the resilience of Traditional Ecological Knowledge (hereafter TEK) and the conditions that might explain its loss or persistence in the face of global change. The second theme relates to new findings regarding the way in which TEK strengthens community resilience to respond to the multiple stressors of global environmental change. Those themes are analyzed using case studies from Africa, Asia, America and Europe. Theoretical insights and empirical findings from the studies suggest that despite the generalized worldwide trend of TEK erosion, substantial pockets of TEK persist in both developing and developed countries. A common trend on the studies presented here is hybridization, where traditional knowledge, practices, and beliefs are merged with novel forms of knowledge and technologies to create new knowledge systems. The findings also reinforce previous hypotheses pointing at the importance of TEK systems as reservoirs of experiential knowledge that can provide important insights for the design of adaptation and mitigation strategies to cope with global environmental change. Based on the results from papers in this feature, we discuss policy directions that might help to promote maintenance and restoration of living TEK systems as sources of social-ecological resilience. PMID:26097492

A survey of stakeholder perspectives on exoskeleton technology.

PubMed

Wolff, Jamie; Parker, Claire; Borisoff, Jaimie; Mortenson, W Ben; Mattie, Johanne

2014-12-19

Exoskeleton technology has potential benefits for wheelchair users' health and mobility. However, there are practical barriers to their everyday use as a mobility device. To further understand potential exoskeleton use, and facilitate the development of new technologies, a study was undertaken to explore perspectives of wheelchair users and healthcare professionals on reasons for use of exoskeleton technology, and the importance of a variety of device characteristics. An online survey with quantitative and qualitative components was conducted with wheelchair users and healthcare professionals working directly with individuals with mobility impairments. Respondents rated whether they would use or recommend an exoskeleton for four potential reasons. Seventeen design features were rated and compared in terms of their importance. An exploratory factor analysis was conducted to categorize the 17 design features into meaningful groupings. Content analysis was used to identify themes for the open ended questions regarding reasons for use of an exoskeleton. 481 survey responses were analyzed, 354 from wheelchair users and 127 from healthcare professionals. The most highly rated reason for potential use or recommendation of an exoskeleton was health benefits. Of the design features, 4 had a median rating of very important: minimization of falls risk, comfort, putting on/taking off the device, and purchase cost. Factor analysis identified two main categories of design features: Functional Activities and Technology Characteristics. Qualitative findings indicated that health and physical benefits, use for activity and access reasons, and psychosocial benefits were important considerations in whether to use or recommend an exoskeleton. This study emphasizes the importance of developing future exoskeletons that are comfortable, affordable, minimize fall risk, and enable functional activities. Findings from this study can be utilized to inform the priorities for future development of this technology.

Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

NASA Astrophysics Data System (ADS)

Sultana, Maryam; Bhatti, Naeem; Javed, Sajid; Jung, Soon Ki

2017-09-01

Facial expression recognition (FER) is an important task for various computer vision applications. The task becomes challenging when it requires the detection and encoding of macro- and micropatterns of facial expressions. We present a two-stage texture feature extraction framework based on the local binary pattern (LBP) variants and evaluate its significance in recognizing posed and nonposed facial expressions. We focus on the parametric limitations of the LBP variants and investigate their effects for optimal FER. The size of the local neighborhood is an important parameter of the LBP technique for its extraction in images. To make the LBP adaptive, we exploit the granulometric information of the facial images to find the local neighborhood size for the extraction of center-symmetric LBP (CS-LBP) features. Our two-stage texture representations consist of an LBP variant and the adaptive CS-LBP features. Among the presented two-stage texture feature extractions, the binarized statistical image features and adaptive CS-LBP features were found showing high FER rates. Evaluation of the adaptive texture features shows competitive and higher performance than the nonadaptive features and other state-of-the-art approaches, respectively.

How important is vehicle safety for older consumers in the vehicle purchase process?

PubMed

Koppel, Sjaan; Clark, Belinda; Hoareau, Effie; Charlton, Judith L; Newstead, Stuart V

2013-01-01

This study aimed to investigate the importance of vehicle safety to older consumers in the vehicle purchase process. Older (n = 102), middle-aged (n = 791), and younger (n = 109) participants throughout the eastern Australian states of Victoria, New South Wales, and Queensland who had recently purchased a new or used vehicle completed an online questionnaire about their vehicle purchase process. When asked to list the 3 most important considerations in the vehicle purchase process (in an open-ended format), older consumers were mostly likely to list price as their most important consideration (43%). Similarly, when presented with a list of vehicle factors (such as price, design, Australasian New Car Assessment Program [ANCAP] rating), older consumers were most likely to identify price as the most important vehicle factor (36%). When presented with a list of vehicle features (such as automatic transmission, braking, air bags), older consumers in the current study were most likely to identify an antilock braking system (41%) as the most important vehicle feature, and 50 percent of older consumers identified a safety-related vehicle feature as the highest priority vehicle feature (50%). When asked to list up to 3 factors that make a vehicle safe, older consumers in the current study were most likely to list braking systems (35%), air bags (22%), and the driver's behavior or skill (11%). When asked about the influence of safety in the new vehicle purchase process, one third of older consumers reported that all new vehicles are safe (33%) and almost half of the older consumers rated their vehicle as safer than average (49%). A logistic regression model was developed to predict the profile of older consumers more likely to assign a higher priority to safety features in the vehicle purchasing process. The model predicted that the importance of safety-related features was influenced by several variables, including older consumers' beliefs that they could protect themselves and their family from a crash, their traffic infringement history, and whether they had children. These findings are consistent with previous research that suggests that, though older consumers highlight the importance of safety features (i.e., seat belts, air bags, braking), they often downplay the role of safety in their vehicle purchasing process and are more likely to equate vehicle safety with the presence of specific vehicle safety features or technologies rather than the vehicle's crash safety/test results or crashworthiness. The findings from this study provide a foundation to support further research in this area that can be used by policy makers, manufacturers, and other stakeholders to better target the promotion and publicity of vehicle safety features to particular consumer groups (such as older consumers). Better targeted campaigns may help to emphasize the value of safety features and their role in reducing the risk of injury/death. If older consumers are better informed of the benefits of safety features when purchasing a vehicle, a further reduction in injuries and deaths related to motor vehicle crashes may be realized.

Low Testosterone and Men's Health

MedlinePlus

... Cancer Featured Resource Find an Endocrinologist Search Low Testosterone Download PDFs English Espanol Editors Glenn R. Cunningham, ... Association Mayo Clinic What is the role of testosterone in men’s health? Testosterone is the most important ...

A real-time method to predict social media popularity

NASA Astrophysics Data System (ADS)

Chen, Xiao; Lu, Zhe-Ming

How to predict the future popularity of a message or video on online social media (OSM) has long been an attractive problem for researchers. Although many difficulties are still ahead, recent studies suggest that temporal and topological features of early adopters generally play a very important role. However, with the increase of the adopters, the feature space will grow explosively. How to select the most effective features is still an open issue. In this work, we investigate several feature extraction methods over the Twitter platform and find that most predictive power concentrates on the second half of the propagation period, and that not only a model trained on one platform generalizes well to others as previous works observed, but also a model trained on one dataset performs well on predicting the popularity for other datasets with different number of observed early adopters. According to these findings, at least for the best features by far, the data used to extract features can be halved without loss of evident accuracy and we provide a way to roughly predict the growth trend of a social-media item in real-time.

Conserved patterns of incomplete reporting in pre-vaccine era childhood diseases

PubMed Central

Gunning, Christian E.; Erhardt, Erik; Wearing, Helen J.

2014-01-01

Incomplete observation is an important yet often neglected feature of observational ecological timeseries. In particular, observational case report timeseries of childhood diseases have played an important role in the formulation of mechanistic dynamical models of populations and metapopulations. Yet to our knowledge, no comprehensive study of childhood disease reporting probabilities (commonly referred to as reporting rates) has been conducted to date. Here, we provide a detailed analysis of measles and whooping cough reporting probabilities in pre-vaccine United States cities and states, as well as measles in cities of England and Wales. Overall, we find the variability between locations and diseases greatly exceeds that between methods or time periods. We demonstrate a strong relationship within location between diseases and within disease between geographical areas. In addition, we find that demographic covariates such as ethnic composition and school attendance explain a non-trivial proportion of reporting probability variation. Overall, our findings show that disease reporting is both variable and non-random and that completeness of reporting is influenced by disease identity, geography and socioeconomic factors. We suggest that variations in incomplete observation can be accounted for and that doing so can reveal ecologically important features that are otherwise obscured. PMID:25232131

Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

NASA Astrophysics Data System (ADS)

Jegadeeshwaran, R.; Sugumaran, V.

2015-02-01

Hydraulic brakes in automobiles are important components for the safety of passengers; therefore, the brakes are a good subject for condition monitoring. The condition of the brake components can be monitored by using the vibration characteristics. On-line condition monitoring by using machine learning approach is proposed in this paper as a possible solution to such problems. The vibration signals for both good as well as faulty conditions of brakes were acquired from a hydraulic brake test setup with the help of a piezoelectric transducer and a data acquisition system. Descriptive statistical features were extracted from the acquired vibration signals and the feature selection was carried out using the C4.5 decision tree algorithm. There is no specific method to find the right number of features required for classification for a given problem. Hence an extensive study is needed to find the optimum number of features. The effect of the number of features was also studied, by using the decision tree as well as Support Vector Machines (SVM). The selected features were classified using the C-SVM and Nu-SVM with different kernel functions. The results are discussed and the conclusion of the study is presented.

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels

PubMed Central

Hyun, Seung Won; Wong, Weng Kee

2016-01-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs. PMID:26565557

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels.

PubMed

Hyun, Seung Won; Wong, Weng Kee

2015-11-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs.

Comparative phenomenology of ataques de nervios, panic attacks, and panic disorder.

PubMed

Lewis-Fernández, Roberto; Guarnaccia, Peter J; Martínez, Igda E; Salmán, Ester; Schmidt, Andrew; Liebowitz, Michael

2002-06-01

This article examines a clinical sample of 66 Dominican and Puerto Rican subjects who reported ataques de nervios and also psychiatric disorder, and disentangles the phenomenological experiences of ataque de nervios, panic attacks, and panic disorder. In-depth cultural interviews assessed the symptomatic phenomenology of ataque episodes from the local perspective as well as in terms of key panic features, such as recurrence, rapid peaking of symptoms, and lack of provocation. Independent diagnostic assessments of panic attacks and disorder were also used to establish the phenomenological overlap between ataque and panic. Our findings indicate that 36 percent of ataques de nervios fulfill criteria for panic attacks and between 17 percent and 33 percent for panic disorder, depending on the overlap method used. The main features distinguishing ataques that fulfill panic criteria from ataques that do not include whether the episodes were provoked by an upsetting event in the person's life and the rapidity of crescendo of the actual attack. A key finding is that ataques often share individual phenomenological features with panic episodes, but that these features usually do not "run together" during the ataque experience. This confirms previous findings that ataque is a more inclusive construct than panic disorder. The importance of these findings for the clinical diagnosis and treatment of persons with ataques is discussed.

Dynamical organization towards consensus in the Axelrod model on complex networks

NASA Astrophysics Data System (ADS)

Guerra, Beniamino; Poncela, Julia; Gómez-Gardeñes, Jesús; Latora, Vito; Moreno, Yamir

2010-05-01

We analyze the dynamics toward cultural consensus in the Axelrod model on scale-free networks. By looking at the microscopic dynamics of the model, we are able to show how culture traits spread across different cultural features. We compare the diffusion at the level of cultural features to the growth of cultural consensus at the global level, finding important differences between these two processes. In particular, we show that even when most of the cultural features have reached macroscopic consensus, there are still no signals of globalization. Finally, we analyze the topology of consensus clusters both for global culture and at the feature level of representation.

Boosted Multivariate Trees for Longitudinal Data

PubMed Central

Pande, Amol; Li, Liang; Rajeswaran, Jeevanantham; Ehrlinger, John; Kogalur, Udaya B.; Blackstone, Eugene H.; Ishwaran, Hemant

2017-01-01

Machine learning methods provide a powerful approach for analyzing longitudinal data in which repeated measurements are observed for a subject over time. We boost multivariate trees to fit a novel flexible semi-nonparametric marginal model for longitudinal data. In this model, features are assumed to be nonparametric, while feature-time interactions are modeled semi-nonparametrically utilizing P-splines with estimated smoothing parameter. In order to avoid overfitting, we describe a relatively simple in sample cross-validation method which can be used to estimate the optimal boosting iteration and which has the surprising added benefit of stabilizing certain parameter estimates. Our new multivariate tree boosting method is shown to be highly flexible, robust to covariance misspecification and unbalanced designs, and resistant to overfitting in high dimensions. Feature selection can be used to identify important features and feature-time interactions. An application to longitudinal data of forced 1-second lung expiratory volume (FEV1) for lung transplant patients identifies an important feature-time interaction and illustrates the ease with which our method can find complex relationships in longitudinal data. PMID:29249866

How the Use of Cognitive Psychology Findings Can Raise the Productivity of Computer-Assisted Instruction.

ERIC Educational Resources Information Center

Hodges, Daniel L.

An overview is provided of the principles of cognitive psychology that can be used to enhance the effectiveness of computer-assisted instruction (CAI). First, the paper looks at the features of classical and operant conditioning that provide the foundation for important parts of mastery learning and CAI programs. Next, findings from four areas of…

The role of attention in item-item binding in visual working memory.

PubMed

Peterson, Dwight J; Naveh-Benjamin, Moshe

2017-09-01

An important yet unresolved question regarding visual working memory (VWM) relates to whether or not binding processes within VWM require additional attentional resources compared with processing solely the individual components comprising these bindings. Previous findings indicate that binding of surface features (e.g., colored shapes) within VWM is not demanding of resources beyond what is required for single features. However, it is possible that other types of binding, such as the binding of complex, distinct items (e.g., faces and scenes), in VWM may require additional resources. In 3 experiments, we examined VWM item-item binding performance under no load, articulatory suppression, and backward counting using a modified change detection task. Binding performance declined to a greater extent than single-item performance under higher compared with lower levels of concurrent load. The findings from each of these experiments indicate that processing item-item bindings within VWM requires a greater amount of attentional resources compared with single items. These findings also highlight an important distinction between the role of attention in item-item binding within VWM and previous studies of long-term memory (LTM) where declines in single-item and binding test performance are similar under divided attention. The current findings provide novel evidence that the specific type of binding is an important determining factor regarding whether or not VWM binding processes require attention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

SigFlux: a novel network feature to evaluate the importance of proteins in signal transduction networks.

PubMed

Liu, Wei; Li, Dong; Zhang, Jiyang; Zhu, Yunping; He, Fuchu

2006-11-27

Measuring each protein's importance in signaling networks helps to identify the crucial proteins in a cellular process, find the fragile portion of the biology system and further assist for disease therapy. However, there are relatively few methods to evaluate the importance of proteins in signaling networks. We developed a novel network feature to evaluate the importance of proteins in signal transduction networks, that we call SigFlux, based on the concept of minimal path sets (MPSs). An MPS is a minimal set of nodes that can perform the signal propagation from ligands to target genes or feedback loops. We define SigFlux as the number of MPSs in which each protein is involved. We applied this network feature to the large signal transduction network in the hippocampal CA1 neuron of mice. Significant correlations were simultaneously observed between SigFlux and both the essentiality and evolutionary rate of genes. Compared with another commonly used network feature, connectivity, SigFlux has similar or better ability as connectivity to reflect a protein's essentiality. Further classification according to protein function demonstrates that high SigFlux, low connectivity proteins are abundant in receptors and transcriptional factors, indicating that SigFlux candescribe the importance of proteins within the context of the entire network. SigFlux is a useful network feature in signal transduction networks that allows the prediction of the essentiality and conservation of proteins. With this novel network feature, proteins that participate in more pathways or feedback loops within a signaling network are proved far more likely to be essential and conserved during evolution than their counterparts.

Repetition Is the Feature Behind the Attentional Bias for Recognizing Threatening Patterns.

PubMed

Shabbir, Maryam; Zon, Adelynn M Y; Thuppil, Vivek

2018-01-01

Animals attend to what is relevant in order to behave in an effective manner and succeed in their environments. In several nonhuman species, there is an evolved bias for attending to patterns indicative of threats in the natural environment such as dangerous animals. Because skins of many dangerous animals are typically repetitive, we propose that repetition is the key feature enabling recognition of evolutionarily important threats. The current study consists of two experiments where we measured participants' reactions to pictures of male and female models wearing clothing of various repeating (leopard skin, snakeskin, and floral print) and nonrepeating (camouflage, shiny, and plain) patterns. In Experiment 1, when models wearing patterns were presented side by side with total fixation duration as the measure, the repeating floral pattern was the most provocative, with total fixation duration significantly longer than all other patterns. Leopard and snakeskin patterns had total fixation durations that were significantly longer than the plain pattern. In Experiment 2, we employed a visual-search task where participants were required to find models wearing the various patterns in a setting of a crowded airport terminal. Participants detected leopard skin pattern and repetitive floral pattern significantly faster than two of the nonpatterned clothing styles. Our experimental findings support the hypothesis that repetition of specific visual features might facilitate target detection, especially those characterizing evolutionary important threats. Our findings that intricate, but nonthreatening repeating patterns can have similar attention-grabbing properties to animal skin patterns have important implications for the fashion industry and wildlife trade.

Wavelet-based energy features for glaucomatous image classification.

PubMed

Dua, Sumeet; Acharya, U Rajendra; Chowriappa, Pradeep; Sree, S Vinitha

2012-01-01

Texture features within images are actively pursued for accurate and efficient glaucoma classification. Energy distribution over wavelet subbands is applied to find these important texture features. In this paper, we investigate the discriminatory potential of wavelet features obtained from the daubechies (db3), symlets (sym3), and biorthogonal (bio3.3, bio3.5, and bio3.7) wavelet filters. We propose a novel technique to extract energy signatures obtained using 2-D discrete wavelet transform, and subject these signatures to different feature ranking and feature selection strategies. We have gauged the effectiveness of the resultant ranked and selected subsets of features using a support vector machine, sequential minimal optimization, random forest, and naïve Bayes classification strategies. We observed an accuracy of around 93% using tenfold cross validations to demonstrate the effectiveness of these methods.

The mechanisms of feature inheritance as predicted by a systems-level model of visual attention and decision making.

PubMed

Hamker, Fred H

2008-07-15

Feature inheritance provides evidence that properties of an invisible target stimulus can be attached to a following mask. We apply a systemslevel model of attention and decision making to explore the influence of memory and feedback connections in feature inheritance. We find that the presence of feedback loops alone is sufficient to account for feature inheritance. Although our simulations do not cover all experimental variations and focus only on the general principle, our result appears of specific interest since the model was designed for a completely different purpose than to explain feature inheritance. We suggest that feedback is an important property in visual perception and provide a description of its mechanism and its role in perception.

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

Designing attractive gamification features for collaborative storytelling websites.

PubMed

Hsu, Shang Hwa; Chang, Jen-Wei; Lee, Chun-Chia

2013-06-01

Gamification design is considered as the predictor of collaborative storytelling websites' success. Although aforementioned studies have mentioned a broad range of factors that may influence gamification, they neither depicted the actual design features nor relative attractiveness among them. This study aims to identify attractive gamification features for collaborative storytelling websites. We first constructed a hierarchical system structure of gamification design of collaborative storytelling websites and conducted a focus group interview with eighteen frequent users to identify 35gamification features. After that, this study determined the relative attractiveness of these gamification features by administrating an online survey to 6333 collaborative storytelling websites users. The results indicated that the top 10 most attractive gamification features could account for more than 50% of attractiveness among these 35 gamification features. The feature of unpredictable time pressure is important to website users, yet not revealed in previous relevant studies. Implications of the findings were discussed.

Sensor-oriented feature usability evaluation in fingerprint segmentation

NASA Astrophysics Data System (ADS)

Li, Ying; Yin, Yilong; Yang, Gongping

2013-06-01

Existing fingerprint segmentation methods usually process fingerprint images captured by different sensors with the same feature or feature set. We propose to improve the fingerprint segmentation result in view of an important fact that images from different sensors have different characteristics for segmentation. Feature usability evaluation, which means to evaluate the usability of features to find the personalized feature or feature set for different sensors to improve the performance of segmentation. The need for feature usability evaluation for fingerprint segmentation is raised and analyzed as a new issue. To address this issue, we present a decision-tree-based feature-usability evaluation method, which utilizes a C4.5 decision tree algorithm to evaluate and pick the best suitable feature or feature set for fingerprint segmentation from a typical candidate feature set. We apply the novel method on the FVC2002 database of fingerprint images, which are acquired by four different respective sensors and technologies. Experimental results show that the accuracy of segmentation is improved, and time consumption for feature extraction is dramatically reduced with selected feature(s).

Bone marrow features in Pearson syndrome with neonatal onset: A case report and review of the literature.

PubMed

Tadiotto, Elisa; Maines, Evelina; Degani, Daniela; Balter, Rita; Bordugo, Andrea; Cesaro, Simone

2018-04-01

Pearson syndrome (PS) is a rare mitochondrial disorder that usually presents with transfusion-dependent macrocytic anemia, exocrine pancreatic dysfunction, and lactic acidosis. Typical bone marrow (BM) features are vacuolization in hematopoietic progenitors, hypocellularity, and ringed sideroblasts. At the neonatal age, PS may have a variable clinical onset. Moreover, there is little information about BM features at this age and the timing of their presentation. We report a neonatal case of PS that presented with refractory anemia and atypical BM features. We reviewed the BM findings in neonatal-onset PS cases to stress the importance and limitations of BM evaluation at this age. © 2017 Wiley Periodicals, Inc.

Changes in selected features of a male face and assessment of their influence on facial recognition.

PubMed

Lewandowski, Zdzisław

2011-01-01

The project aimed at finding the answers to the following two research questions: --To what extent does a change in size, height or width of the selected face feature influence the assessment of likeness between an original composite portrait and a modified one? --How does the sex of a person who judges the images have an impact on the perception of likeness of the face features? The results indicate that there are significant differences in the assessment of likeness of the portraits with some features modified to the original ones. The images with changes in size and height of the nose received the lowest scores on the likeness scale, which indicates that these changes were perceived by the subjects as the most important. The photos with changes in height and width of the lips, and height and width of the eye slit, in turn, received high scores of likeness, in spite of big changes. This signifies that these modifications were perceived to be of the least importance (compared to the other features investigated).

Additivity of Feature-Based and Symmetry-Based Grouping Effects in Multiple Object Tracking

PubMed Central

Wang, Chundi; Zhang, Xuemin; Li, Yongna; Lyu, Chuang

2016-01-01

Multiple object tracking (MOT) is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the “laws of perceptual organization” proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape) among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. “Additive effect” refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The “where” and “what” pathways might have played an important role in the additive grouping effect. PMID:27199875

Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

PubMed

Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

2018-05-01

Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our findings suggest that SVM, using features from a combination of diffusion models, improves prediction accuracy for differentiation of benign versus malignant breast tumors, and may further assist in subtyping of breast cancer. 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1205-1216. © 2017 International Society for Magnetic Resonance in Medicine.

The development of organized visual search

PubMed Central

Woods, Adam J.; Goksun, Tilbe; Chatterjee, Anjan; Zelonis, Sarah; Mehta, Anika; Smith, Sabrina E.

2013-01-01

Visual search plays an important role in guiding behavior. Children have more difficulty performing conjunction search tasks than adults. The present research evaluates whether developmental differences in children's ability to organize serial visual search (i.e., search organization skills) contribute to performance limitations in a typical conjunction search task. We evaluated 134 children between the ages of 2 and 17 on separate tasks measuring search for targets defined by a conjunction of features or by distinct features. Our results demonstrated that children organize their visual search better as they get older. As children's skills at organizing visual search improve they become more accurate at locating targets with conjunction of features amongst distractors, but not for targets with distinct features. Developmental limitations in children's abilities to organize their visual search of the environment are an important component of poor conjunction search in young children. In addition, our findings provide preliminary evidence that, like other visuospatial tasks, exposure to reading may influence children's spatial orientation to the visual environment when performing a visual search. PMID:23584560

Patient Preferences for Features of Health Care Delivery Systems: A Discrete Choice Experiment.

PubMed

Mühlbacher, Axel C; Bethge, Susanne; Reed, Shelby D; Schulman, Kevin A

2016-04-01

To estimate the relative importance of organizational-, procedural-, and interpersonal-level features of health care delivery systems from the patient perspective. We designed four discrete choice experiments (DCEs) to measure patient preferences for 21 health system attributes. Participants were recruited through the online patient portal of a large health system. We analyzed the DCE data using random effects logit models. DCEs were performed in which respondents were provided with descriptions of alternative scenarios and asked to indicate which scenario they prefer. Respondents were randomly assigned to one of the three possible health scenarios (current health, new lung cancer diagnosis, or diabetes) and asked to complete 15 choice tasks. Each choice task included an annual out-of-pocket cost attribute. A total of 3,900 respondents completed the survey. The out-of-pocket cost attribute was considered the most important across the four different DCEs. Following the cost attribute, trust and respect, multidisciplinary care, and shared decision making were judged as most important. The relative importance of out-of-pocket cost was consistently lower in the hypothetical context of a new lung cancer diagnosis compared with diabetes or the patient's current health. This study demonstrates the complexity of patient decision making processes regarding features of health care delivery systems. Our findings suggest the importance of these features may change as a function of an individual's medical conditions. © Health Research and Educational Trust.

Feature diagnosticity and task context shape activity in human scene-selective cortex.

PubMed

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

Associations Between Sibling Relationship Quality and Friendship Quality in Early Adolescence: Looking at the Case of Twins.

PubMed

Bekkhus, Mona; Brendgen, Mara; Czajkowski, Nikolai O; Vitaro, Frank; Dionne, Ginette; Boivin, Michel

2016-04-01

Bidirectional pathways between twin relationship quality and friendship quality were investigated in a large longitudinal twin cohort. We examined negative and positive relationship features in 313 monozygotic (MZ) twins and 238 same-sex dizygotic (DZ) twins from ages 13 to 14 years, using latent structural modeling. Results showed stronger stability of the twin relationship quality compared to friendship quality. Positive features in the sibling relationship were associated with increased positive features in the relationship with the best friend a year later. In contrast, no significant association between negative sibling relationship features and change in negative friendship quality features was found. These findings speak to the important role of the sibling relationship in the development of good quality friendship relations in twins.

Student Voice and the Community Forum: Finding Ways of "Being Heard" at an Alternative School for Disenfranchised Young People

ERIC Educational Resources Information Center

Baroutsis, Aspa; Mills, Martin; McGregor, Glenda; te Riele, Kitty; Hayes, Debra

2016-01-01

Opportunities for students to speak and to be heard are important elements of democratic schooling processes but research into student voice has shown that a culture of silence is a more common feature of schooling. Efforts to re-engage young people in learning often recognise the importance of schooling processes that provide them with…

Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification.

PubMed

Huang, Chuen-Der; Lin, Chin-Teng; Pal, Nikhil Ranjan

2003-12-01

The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And in the next level we have another set of classifiers, which further classifies the protein features into 27 folds. The third novel idea is to induce the indirect coding features from the amino-acid composition sequence of proteins based on the N-gram concept. This provides us with more representative and discriminative new local features of protein sequences for multiclass protein fold classification. The proposed HLA with new indirect coding features increases the protein fold classification accuracy by about 12%. Moreover, the gating neural network is found to reduce the number of features drastically. Using only half of the original features selected by the gating neural network can reach comparable test accuracy as that using all the original features. The gating mechanism also helps us to get a better insight into the folding process of proteins. For example, tracking the evolution of different gates we can find which characteristics (features) of the data are more important for the folding process. And, of course, it also reduces the computation time.

User Evaluation of Hypermedia Encyclopedias.

ERIC Educational Resources Information Center

Gillham, Mark; Buckner, Kathy

1997-01-01

To establish evaluation criteria for home multimedia products, this study examined 13 case studies of experienced users of CD-ROM encyclopedias aimed at the home consumer. Findings ranked seven features from most to least important: searching; textual content; browsing; multimedia; aesthetics; interactivity; and system performance. Results suggest…

Basic Features of Customer Satisfaction with Train Schedules

NASA Astrophysics Data System (ADS)

Murakoshi, Akiko; Kunimatsu, Taketoshi; Saito, Ayano

This paper aims to reveal the fundamental features of customer satisfaction with train schedules, which is one of the most basic services provided by a railway company. A customer satisfaction survey of passengers who frequently utilize three lines in the metropolitan area was conducted; we obtained the following findings: (a) out of nine factors to evaluate a train schedule from a passenger's viewpoint, the four most important ones are the frequency of trains running, punctuality, congestion rate, and time distance; (b) the ride-frequency influences the degree of satisfaction with train schedules in a particular line; and (c) it is important to set a numeric goal for the level of customer satisfaction by grasping the relationship between the transport service and a passenger's satisfaction with that service. The difference between customer satisfaction and passenger disutility is also discussed. The findings are expected to help conduct customer satisfaction surveys and also to form the basis for establishing a method by which to evaluate a train schedule from passengers' satisfaction ratings.

Migration and Tissue Tropism of Innate Lymphoid Cells

PubMed Central

Kim, Chang H.; Hashimoto-Hill, Seika; Kim, Myunghoo

2016-01-01

Innate lymphoid cell (ILCs) subsets differentially populate various barrier and non-barrier tissues, where they play important roles in tissue homeostasis and tissue-specific responses to pathogen attack. Recent findings have provided insight into the molecular mechanisms that guide ILC migration into peripheral tissues, revealing common features among different ILC subsets as well as important distinctions. Recent studies have also highlighted the impact of tissue-specific cues on ILC migration, and the importance of the local immunological milieu. We review these findings here and discuss how the migratory patterns and tissue tropism of different ILC subsets relate to the development and differentiation of these cells, and to ILC-mediated tissue-specific regulation of innate and adaptive immune responses. In this context we outline open questions and important areas of future research. PMID:26708278

Titan's surface from Cassini RADAR SAR and high resolution radiometry data of the first five flybys

USGS Publications Warehouse

Paganelli, F.; Janssen, M.A.; Stiles, B.; West, R.; Lorenz, R.D.; Lunine, J.I.; Wall, S.D.; Callahan, P.; Lopes, R.M.; Stofan, E.; Kirk, R.L.; Johnson, W.T.K.; Roth, L.; Elachi, C.; ,

2007-01-01

The first five Titan flybys with Cassini's Synthetic Aperture RADAR (SAR) and radiometer are examined with emphasis on the calibration and interpretation of the high-resolution radiometry data acquired during the SAR mode (SAR-radiometry). Maps of the 2-cm wavelength brightness temperature are obtained coincident with the SAR swath imaging, with spatial resolution approaching 6 km. A preliminary calibration shows that brightness temperature in these maps varies from 64 to 89 K. Surface features and physical properties derived from the SAR-radiometry maps and SAR imaging are strongly correlated; in general, we find that surface features with high radar reflectivity are associated with radiometrically cold regions, while surface features with low radar reflectivity correlate with radiometrically warm regions. We examined scatterplots of the normalized radar cross-section ??0 versus brightness temperature, finding differing signatures that characterize various terrains and surface features. Implications for the physical and compositional properties of these features are discussed. The results indicate that volume scattering is important in many areas of Titan's surface, particularly Xanadu, while other areas exhibit complex brightness temperature variations consistent with variable slopes or surface material and compositional properties. ?? 2007 Elsevier Inc.

A Systematic Investigation of Computation Models for Predicting Adverse Drug Reactions (ADRs)

PubMed Central

Kuang, Qifan; Wang, MinQi; Li, Rong; Dong, YongCheng; Li, Yizhou; Li, Menglong

2014-01-01

Background Early and accurate identification of adverse drug reactions (ADRs) is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs. Principal Findings In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper. Conclusion Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms. PMID:25180585

Integration of heterogeneous features for remote sensing scene classification

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Exploring the Association Between Emotional Abuse and Childhood Borderline Personality Features: The Moderating Role of Personality Traits

PubMed Central

Gratz, Kim L.; Latzman, Robert D.; Tull, Matthew T.; Reynolds, Elizabeth K.; Lejuez, C. W.

2012-01-01

Most of the extant literature on borderline personality disorder has focused on the course, consequences, and correlates of this disorder among adults. However, little is known about childhood borderline personality (BP) features, or the factors associated with the emergence of BP pathology in childhood. A greater understanding of childhood BP features and associated risk factors has important implications for the development of primary and secondary prevention programs. The goal of the present study was to examine the interrelationships among two BP-relevant traits (affective dysfunction and impulsivity), a BP-relevant environmental stressor (emotional abuse), and BP features in a sample of 225 children aged 11 to 14 years. Results provide support for the role of both trait vulnerabilities and environmental stressors in childhood BP features. Further, findings highlight the moderating role of affective dysfunction in the relationship between emotional abuse and childhood BP features. PMID:21658531

HIV-1 protease cleavage site prediction based on two-stage feature selection method.

PubMed

Niu, Bing; Yuan, Xiao-Cheng; Roeper, Preston; Su, Qiang; Peng, Chun-Rong; Yin, Jing-Yuan; Ding, Juan; Li, HaiPeng; Lu, Wen-Cong

2013-03-01

Knowledge of the mechanism of HIV protease cleavage specificity is critical to the design of specific and effective HIV inhibitors. Searching for an accurate, robust, and rapid method to correctly predict the cleavage sites in proteins is crucial when searching for possible HIV inhibitors. In this article, HIV-1 protease specificity was studied using the correlation-based feature subset (CfsSubset) selection method combined with Genetic Algorithms method. Thirty important biochemical features were found based on a jackknife test from the original data set containing 4,248 features. By using the AdaBoost method with the thirty selected features the prediction model yields an accuracy of 96.7% for the jackknife test and 92.1% for an independent set test, with increased accuracy over the original dataset by 6.7% and 77.4%, respectively. Our feature selection scheme could be a useful technique for finding effective competitive inhibitors of HIV protease.

Autosomal dominant cerebellar ataxia with retinal degeneration (ADCA II): clinical and neuropathological findings in two pedigrees and genetic linkage to 3p12-p21.1.

PubMed

Jöbsis, G J; Weber, J W; Barth, P G; Keizers, H; Baas, F; van Schooneveld, M J; van Hilten, J J; Troost, D; Geesink, H H; Bolhuis, P A

1997-04-01

To investigate relations between clinical and neuropathological features and age of onset, presence of anticipation, and genetic linkage in autosomal dominant cerebellar ataxia type II (ADCA II). The natural history of ADCA II was studied on the basis of clinical and neuropathological findings in two pedigrees and genetic linkage studies were carried out with polymorphic DNA markers in the largest, four generation, pedigree. Ataxia was constant in all age groups. Retinal degeneration with early extinction of the electroretinogram constituted an important component in juvenile and early adult (< 25 years) onset but was variable in late adult presentation. Neuromuscular involvement due to spinal anterior horn disease was an important contributing factor to illness in juvenile cases. Postmortem findings in four patients confirm the general neurodegenerative nature of the disease, which includes prominent spinal anterior horn involvement and widespread involvement of grey and white matter. Genetic linkage was found with markers to chromosome 3p12-p21.1 (maximum pairwise lod score 4.42 at D3S1285). The sequence of clinical involvement seems related to age at onset. Retinal degeneration is variable in late onset patients and neuromuscular features are important in patients with early onset. Strong anticipation was found in subsequent generations. Linkage of ADCA II to chromosome 3p12-p21.1 is confirmed.

Outcomes of Diagnostic Exome Sequencing in Patients With Diagnosed or Suspected Autism Spectrum Disorders.

PubMed

Rossi, Mari; El-Khechen, Dima; Black, Mary Helen; Farwell Hagman, Kelly D; Tang, Sha; Powis, Zöe

2017-05-01

Exome sequencing has recently been proved to be a successful diagnostic method for complex neurodevelopmental disorders. However, the diagnostic yield of exome sequencing for autism spectrum disorders has not been extensively evaluated in large cohorts to date. We performed diagnostic exome sequencing in a cohort of 163 individuals with autism spectrum disorder (66.3%) or autistic features (33.7%). The diagnostic yield observed in patients in our cohort was 25.8% (42 of 163) for positive or likely positive findings in characterized disease genes, while a candidate genetic etiology was reported for an additional 3.3% (4 of 120) of patients. Among the positive findings in the patients with autism spectrum disorder or autistic features, 61.9% were the result of de novo mutations. Patients presenting with psychiatric conditions or ataxia or paraplegia in addition to autism spectrum disorder or autistic features were significantly more likely to receive positive results compared with patients without these clinical features (95.6% vs 27.1%, P < 0.0001; 83.3% vs 21.2%, P < 0.0001, respectively). The majority of the positive findings were in recently identified autism spectrum disorder genes, supporting the importance of diagnostic exome sequencing for patients with autism spectrum disorder or autistic features as the causative genes might evade traditional sequential or panel testing. These results suggest that diagnostic exome sequencing would be an efficient primary diagnostic method for patients with autism spectrum disorders or autistic features. Moreover, our data may aid clinicians to better determine which subset of patients with autism spectrum disorder with additional clinical features would benefit the most from diagnostic exome sequencing. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Divide and Conquer: Sub-Grouping of ASD Improves ASD Detection Based on Brain Morphometry.

PubMed

Katuwal, Gajendra J; Baum, Stefi A; Cahill, Nathan D; Michael, Andrew M

2016-01-01

Low success (<60%) in autism spectrum disorder (ASD) classification using brain morphometry from the large multi-site ABIDE dataset and inconsistent findings on brain morphometric abnormalities in ASD can be attributed to the ASD heterogeneity. In this study, we show that ASD brain morphometry is highly heterogeneous, and demonstrate that the heterogeneity can be mitigated and classification improved if autism severity (AS), verbal IQ (VIQ) and age are used with morphometric features. Morphometric features from structural MRIs (sMRIs) of 734 males (ASD: 361, controls: 373) of ABIDE were derived using FreeSurfer. Applying the Random Forest classifier, an AUC of 0.61 was achieved. Adding VIQ and age to morphometric features, AUC improved to 0.68. Sub-grouping the subjects by AS, VIQ and age improved the classification with the highest AUC of 0.8 in the moderate-AS sub-group (AS = 7-8). Matching subjects on age and/or VIQ in each sub-group further improved the classification with the highest AUC of 0.92 in the low AS sub-group (AS = 4-5). AUC decreased with AS and VIQ, and was the lowest in the mid-age sub-group (13-18 years). The important features were mainly from the frontal, temporal, ventricular, right hippocampal and left amygdala regions. However, they highly varied with AS, VIQ and age. The curvature and folding index features from frontal, temporal, lingual and insular regions were dominant in younger subjects suggesting their importance for early detection. When the experiments were repeated using the Gradient Boosting classifier similar results were obtained. Our findings suggest that identifying brain biomarkers in sub-groups of ASD can yield more robust and insightful results than searching across the whole spectrum. Further, it may allow identification of sub-group specific brain biomarkers that are optimized for early detection and monitoring, increasing the utility of sMRI as an important tool for early detection of ASD.

Divide and Conquer: Sub-Grouping of ASD Improves ASD Detection Based on Brain Morphometry

PubMed Central

Baum, Stefi A.; Cahill, Nathan D.; Michael, Andrew M.

2016-01-01

Low success (<60%) in autism spectrum disorder (ASD) classification using brain morphometry from the large multi-site ABIDE dataset and inconsistent findings on brain morphometric abnormalities in ASD can be attributed to the ASD heterogeneity. In this study, we show that ASD brain morphometry is highly heterogeneous, and demonstrate that the heterogeneity can be mitigated and classification improved if autism severity (AS), verbal IQ (VIQ) and age are used with morphometric features. Morphometric features from structural MRIs (sMRIs) of 734 males (ASD: 361, controls: 373) of ABIDE were derived using FreeSurfer. Applying the Random Forest classifier, an AUC of 0.61 was achieved. Adding VIQ and age to morphometric features, AUC improved to 0.68. Sub-grouping the subjects by AS, VIQ and age improved the classification with the highest AUC of 0.8 in the moderate-AS sub-group (AS = 7–8). Matching subjects on age and/or VIQ in each sub-group further improved the classification with the highest AUC of 0.92 in the low AS sub-group (AS = 4–5). AUC decreased with AS and VIQ, and was the lowest in the mid-age sub-group (13–18 years). The important features were mainly from the frontal, temporal, ventricular, right hippocampal and left amygdala regions. However, they highly varied with AS, VIQ and age. The curvature and folding index features from frontal, temporal, lingual and insular regions were dominant in younger subjects suggesting their importance for early detection. When the experiments were repeated using the Gradient Boosting classifier similar results were obtained. Our findings suggest that identifying brain biomarkers in sub-groups of ASD can yield more robust and insightful results than searching across the whole spectrum. Further, it may allow identification of sub-group specific brain biomarkers that are optimized for early detection and monitoring, increasing the utility of sMRI as an important tool for early detection of ASD. PMID:27065101

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

PubMed Central

Zheng, Jiaping; Yu, Hong

2016-01-01

Background Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients’ notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them. Interventions can then be developed by giving them targeted education to improve their EHR comprehension and the quality of care. Objective We aimed to develop a supervised natural language processing (NLP) system called Finding impOrtant medical Concepts most Useful to patientS (FOCUS) that automatically identifies and ranks medical terms in EHR notes based on their importance to the patients. Methods First, we built an expert-annotated corpus. For each EHR note, 2 physicians independently identified medical terms important to the patient. Using the physicians’ agreement as the gold standard, we developed and evaluated FOCUS. FOCUS first identifies candidate terms from each EHR note using MetaMap and then ranks the terms using a support vector machine-based learn-to-rank algorithm. We explored rich learning features, including distributed word representation, Unified Medical Language System semantic type, topic features, and features derived from consumer health vocabulary. We compared FOCUS with 2 strong baseline NLP systems. Results Physicians annotated 90 EHR notes and identified a mean of 9 (SD 5) important terms per note. The Cohen’s kappa annotation agreement was .51. The 10-fold cross-validation results show that FOCUS achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.940 for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FOCUS for identifying important terms from EHR notes was 0.866 AUC-ROC. Both performance scores significantly exceeded the corresponding baseline system scores (P<.001). Rich learning features contributed to FOCUS’s performance substantially. Conclusions FOCUS can automatically rank terms from EHR notes based on their importance to patients. It may help develop future interventions that improve quality of care. PMID:27903489

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations.

PubMed

Chen, Jinying; Zheng, Jiaping; Yu, Hong

2016-11-30

Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients' notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them. Interventions can then be developed by giving them targeted education to improve their EHR comprehension and the quality of care. We aimed to develop a supervised natural language processing (NLP) system called Finding impOrtant medical Concepts most Useful to patientS (FOCUS) that automatically identifies and ranks medical terms in EHR notes based on their importance to the patients. First, we built an expert-annotated corpus. For each EHR note, 2 physicians independently identified medical terms important to the patient. Using the physicians' agreement as the gold standard, we developed and evaluated FOCUS. FOCUS first identifies candidate terms from each EHR note using MetaMap and then ranks the terms using a support vector machine-based learn-to-rank algorithm. We explored rich learning features, including distributed word representation, Unified Medical Language System semantic type, topic features, and features derived from consumer health vocabulary. We compared FOCUS with 2 strong baseline NLP systems. Physicians annotated 90 EHR notes and identified a mean of 9 (SD 5) important terms per note. The Cohen's kappa annotation agreement was .51. The 10-fold cross-validation results show that FOCUS achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.940 for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FOCUS for identifying important terms from EHR notes was 0.866 AUC-ROC. Both performance scores significantly exceeded the corresponding baseline system scores (P<.001). Rich learning features contributed to FOCUS's performance substantially. FOCUS can automatically rank terms from EHR notes based on their importance to patients. It may help develop future interventions that improve quality of care. ©Jinying Chen, Jiaping Zheng, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 30.11.2016.

Perceptions of Public Relations Education.

ERIC Educational Resources Information Center

Stacks, Don W.; Botan, Carl; Turk, Judy VanSlyke

1999-01-01

Surveys 258 public-relations educators and practitioners, finding they agree that public-relations education is on track; that systematic assessment is an important feature of public-relations education; and that they agreed on how public-relations education should be structured, and demonstrated a high degree of similarity in their preferences…

Neuroscience and Positive Psychology: Implications for School Counselors

ERIC Educational Resources Information Center

Stickel, Sue A.; Callaway, Yvonne L.

2007-01-01

Increasing research findings are pointing out that using positive psychology and wellness strategies in counseling and therapy are helpful in fostering healthy human development (Snyder & Lopez, 2001). Positive psychology is addressing the importance of positive emotions, character traits, and features of enabling institutions such as the 'good…

Soft-Tissue Sarcomas of the Abdomen and Pelvis: Radiologic-Pathologic Features, Part 2-Uncommon Sarcomas.

PubMed

Levy, Angela D; Manning, Maria A; Miettinen, Markku M

2017-01-01

Soft-tissue sarcomas occurring in the abdomen and pelvis are an uncommon but important group of malignancies. Recent changes to the World Health Organization classification of soft-tissue tumors include the movement of gastrointestinal stromal tumors (GISTs) into the soft-tissue tumor classification. GIST is the most common intraperitoneal sarcoma. Liposarcoma is the most common retroperitoneal sarcoma, and leiomyosarcoma is the second most common. GIST, liposarcoma, and leiomyosarcoma account for the majority of sarcomas encountered in the abdomen and pelvis and are discussed in part 1 of this article. Undifferentiated pleomorphic sarcoma (previously called malignant fibrous histiocytoma), dermatofibrosarcoma protuberans, solitary fibrous tumor, malignant peripheral nerve sheath tumor, rhabdomyosarcoma, extraskeletal chondro-osseous sarcomas, vascular sarcomas, and sarcomas of uncertain differentiation uncommonly arise in the abdomen and pelvis and the abdominal wall. Although these lesions are rare sarcomas and their imaging features overlap, familiarity with the locations where they occur and their imaging features is important so they can be diagnosed accurately. The anatomic location and clinical history are important factors in the differential diagnosis of these lesions because metastasis, more-common sarcomas, borderline fibroblastic proliferations (such as desmoid tumors), and endometriosis have imaging findings that overlap with those of these uncommon sarcomas. In this article, the clinical, pathologic, and imaging findings of uncommon soft-tissue sarcomas of the abdomen and pelvis and the abdominal wall are reviewed, with an emphasis on their differential diagnosis.

Soft-Tissue Sarcomas of the Abdomen and Pelvis: Radiologic-Pathologic Features, Part 2—Uncommon Sarcomas

PubMed Central

Manning, Maria A.; Miettinen, Markku M.

2017-01-01

Soft-tissue sarcomas occurring in the abdomen and pelvis are an uncommon but important group of malignancies. Recent changes to the World Health Organization classification of soft-tissue tumors include the movement of gastrointestinal stromal tumors (GISTs) into the soft-tissue tumor classification. GIST is the most common intraperitoneal sarcoma. Liposarcoma is the most common retroperitoneal sarcoma, and leiomyosarcoma is the second most common. GIST, liposarcoma, and leiomyosarcoma account for the majority of sarcomas encountered in the abdomen and pelvis and are discussed in part 1 of this article. Undifferentiated pleomorphic sarcoma (previously called malignant fibrous histiocytoma), dermatofibrosarcoma protuberans, solitary fibrous tumor, malignant peripheral nerve sheath tumor, rhabdomyosarcoma, extraskeletal chondro-osseous sarcomas, vascular sarcomas, and sarcomas of uncertain differentiation uncommonly arise in the abdomen and pelvis and the abdominal wall. Although these lesions are rare sarcomas and their imaging features overlap, familiarity with the locations where they occur and their imaging features is important so they can be diagnosed accurately. The anatomic location and clinical history are important factors in the differential diagnosis of these lesions because metastasis, more-common sarcomas, borderline fibroblastic proliferations (such as desmoid tumors), and endometriosis have imaging findings that overlap with those of these uncommon sarcomas. In this article, the clinical, pathologic, and imaging findings of uncommon soft-tissue sarcomas of the abdomen and pelvis and the abdominal wall are reviewed, with an emphasis on their differential diagnosis. PMID:28493803

Protein attributes contribute to halo-stability, bioinformatics approach

PubMed Central

2011-01-01

Halophile proteins can tolerate high salt concentrations. Understanding halophilicity features is the first step toward engineering halostable crops. To this end, we examined protein features contributing to the halo-toleration of halophilic organisms. We compared more than 850 features for halophilic and non-halophilic proteins with various screening, clustering, decision tree, and generalized rule induction models to search for patterns that code for halo-toleration. Up to 251 protein attributes selected by various attribute weighting algorithms as important features contribute to halo-stability; from them 14 attributes selected by 90% of models and the count of hydrogen gained the highest value (1.0) in 70% of attribute weighting models, showing the importance of this attribute in feature selection modeling. The other attributes mostly were the frequencies of di-peptides. No changes were found in the numbers of groups when K-Means and TwoStep clustering modeling were performed on datasets with or without feature selection filtering. Although the depths of induced trees were not high, the accuracies of trees were higher than 94% and the frequency of hydrophobic residues pointed as the most important feature to build trees. The performance evaluation of decision tree models had the same values and the best correctness percentage recorded with the Exhaustive CHAID and CHAID models. We did not find any significant difference in the percent of correctness, performance evaluation, and mean correctness of various decision tree models with or without feature selection. For the first time, we analyzed the performance of different screening, clustering, and decision tree algorithms for discriminating halophilic and non-halophilic proteins and the results showed that amino acid composition can be used to discriminate between halo-tolerant and halo-sensitive proteins. PMID:21592393

Qualitative research methods: key features and insights gained from use in infection prevention research.

PubMed

Forman, Jane; Creswell, John W; Damschroder, Laura; Kowalski, Christine P; Krein, Sarah L

2008-12-01

Infection control professionals and hospital epidemiologists are accustomed to using quantitative research. Although quantitative studies are extremely important in the field of infection control and prevention, often they cannot help us explain why certain factors affect the use of infection control practices and identify the underlying mechanisms through which they do so. Qualitative research methods, which use open-ended techniques, such as interviews, to collect data and nonstatistical techniques to analyze it, provide detailed, diverse insights of individuals, useful quotes that bring a realism to applied research, and information about how different health care settings operate. Qualitative research can illuminate the processes underlying statistical correlations, inform the development of interventions, and show how interventions work to produce observed outcomes. This article describes the key features of qualitative research and the advantages that such features add to existing quantitative research approaches in the study of infection control. We address the goal of qualitative research, the nature of the research process, sampling, data collection and analysis, validity, generalizability of findings, and presentation of findings. Health services researchers are increasingly using qualitative methods to address practical problems by uncovering interacting influences in complex health care environments. Qualitative research methods, applied with expertise and rigor, can contribute important insights to infection prevention efforts.

The mental representation of living and nonliving things: differential weighting and interactivity of sensorial and non-sensorial features.

PubMed

Ventura, Paulo; Morais, José; Brito-Mendes, Carlos; Kolinsky, Régine

2005-02-01

Warrington and colleagues (Warrington & McCarthy, 1983, 1987; Warrington & Shallice, 1984) claimed that sensorial and functional-associative (FA) features are differentially important in determining the meaning of living things (LT) and nonliving things (NLT). The first aim of the present study was to evaluate this hypothesis through two different access tasks: feature generation (Experiment 1) and cued recall (Experiment 2). The results of both experiments provided consistent empirical support for Warrington and colleagues' assumption. The second aim of the present study was to test a new differential interactivity hypothesis that combines Warrington and colleagueS' assumption with the notion of a higher number of intercorrelations and hence of a stronger connectivity between sensorial and non-sensorial features for LTs than for NLTs. This hypothesis was motivated by previoUs reports of an uncrossed interaction between domain (LTs vs NLTs) and attribute type (sensorial vs FA) in, for example, a feature verification task (Laws, Humber, Ramsey, & McCarthy, 1995): while FA attributes are verified faster than sensorial attributes for NLTs, no difference is observed for LTs. We replicated and generalised this finding using several feature verification tasks on both written words and pictures (Experiment 3), including in conditions aimed at minimising the intervention of priming biases and strategic or mnemonic processes (Experiment 4). The whole set of results suggests that both privileged relations between features and categories, and the differential importance of intercorrelations between features as a function of category, modulate access to semantic features.

The Role of Attention in Item-Item Binding in Visual Working Memory

ERIC Educational Resources Information Center

Peterson, Dwight J.; Naveh-Benjamin, Moshe

2017-01-01

An important yet unresolved question regarding visual working memory (VWM) relates to whether or not binding processes within VWM require additional attentional resources compared with processing solely the individual components comprising these bindings. Previous findings indicate that binding of surface features (e.g., colored shapes) within VWM…

Conflict and Friendship in Sibling Relationships: A Review.

ERIC Educational Resources Information Center

Newman, Joan

1994-01-01

Reviews research findings about the nature and development of typical sibling relationships. Discusses two important themes, the role of children's social cognition skills, and the role of the demands of the relationship. Addresses two questions: (1) the prevalence and features of sibling rivalry and conflict; and (2) the characteristics of…

Shadow detection of moving objects based on multisource information in Internet of things

NASA Astrophysics Data System (ADS)

Ma, Zhen; Zhang, De-gan; Chen, Jie; Hou, Yue-xian

2017-05-01

Moving object detection is an important part in intelligent video surveillance under the banner of Internet of things. The detection of moving target's shadow is also an important step in moving object detection. On the accuracy of shadow detection will affect the detection results of the object directly. Based on the variety of shadow detection method, we find that only using one feature can't make the result of detection accurately. Then we present a new method for shadow detection which contains colour information, the invariance of optical and texture feature. Through the comprehensive analysis of the detecting results of three kinds of information, the shadow was effectively determined. It gets ideal effect in the experiment when combining advantages of various methods.

Walking and Walkability: Is Wayfinding a Missing Link? Implications for Public Health Practice.

PubMed

Vandenberg, Ann E; Hunter, Rebecca H; Anderson, Lynda A; Bryant, Lucinda L; Hooker, Steven P; Satariano, William A

2016-02-01

Research on walking and walkability has yet to focus on wayfinding, the interactive, problem-solving process by which people use environmental information to locate themselves and navigate through various settings. We reviewed the literature on outdoor pedestrian-oriented wayfinding to examine its relationship to walking and walkability, 2 areas of importance to physical activity promotion. Our findings document that wayfinding is cognitively demanding and can compete with other functions, including walking itself. Moreover, features of the environment can either facilitate or impede wayfinding, just as environmental features can influence walking. Although there is still much to be learned about wayfinding and walking behaviors, our review helps frame the issues and lays out the importance of this area of research and practice.

Predicting Presynaptic and Postsynaptic Neurotoxins by Developing Feature Selection Technique

PubMed Central

Yang, Yunchun; Zhang, Chunmei; Chen, Rong; Huang, Po

2017-01-01

Presynaptic and postsynaptic neurotoxins are proteins which act at the presynaptic and postsynaptic membrane. Correctly predicting presynaptic and postsynaptic neurotoxins will provide important clues for drug-target discovery and drug design. In this study, we developed a theoretical method to discriminate presynaptic neurotoxins from postsynaptic neurotoxins. A strict and objective benchmark dataset was constructed to train and test our proposed model. The dipeptide composition was used to formulate neurotoxin samples. The analysis of variance (ANOVA) was proposed to find out the optimal feature set which can produce the maximum accuracy. In the jackknife cross-validation test, the overall accuracy of 94.9% was achieved. We believe that the proposed model will provide important information to study neurotoxins. PMID:28303250

Methods and strategies of object localization

NASA Technical Reports Server (NTRS)

Shao, Lejun; Volz, Richard A.

1989-01-01

An important property of an intelligent robot is to be able to determine the location of an object in 3-D space. A general object localization system structure is proposed, some important issues on localization discussed, and an overview given for current available object localization algorithms and systems. The algorithms reviewed are characterized by their feature extracting and matching strategies; the range finding methods; the types of locatable objects; and the mathematical formulating methods.

American Thyroid Association statement on the essential elements of interdisciplinary communication of perioperative information for patients undergoing thyroid cancer surgery.

PubMed

Carty, Sally E; Doherty, Gerard M; Inabnet, William B; Pasieka, Janice L; Randolph, Gregory W; Shaha, Ashok R; Terris, David J; Tufano, Ralph P; Tuttle, R Michael

2012-04-01

Thyroid cancer specialists require specific perioperative information to develop a management plan for patients with thyroid cancer, but there is not yet a model for effective interdisciplinary data communication. The American Thyroid Association Surgical Affairs Committee was asked to define a suggested essential perioperative dataset representing the critical information that should be readily available to participating members of the treatment team. To identify and agree upon a multidisciplinary set of critical perioperative findings requiring communication, we examined diverse best-practice documents relating to thyroidectomy and extracted common features felt to enhance precise, direct communication with nonsurgical caregivers. Suggested essential datasets for the preoperative, intraoperative, and immediate postoperative findings and management of patients undergoing surgery for thyroid cancer were identified and are presented. For operative reporting, the essential features of both a dictated narrative format and a synoptic computer format are modeled in detail. The importance of interdisciplinary communication is discussed with regard to the extent of required resection, the final pathology findings, surgical complications, and other factors that may influence risk stratification, adjuvant treatment, and surveillance. Accurate communication of the important findings and sequelae of thyroidectomy for cancer is critical to individualized risk stratification as well as to the clinical issues of thyroid cancer care that are often jointly managed in the postoperative setting. True interdisciplinary care is essential to providing optimal care and surveillance.

Spectrum of high-resolution computed tomography imaging in occupational lung disease

PubMed Central

Satija, Bhawna; Kumar, Sanyal; Ojha, Umesh Chandra; Gothi, Dipti

2013-01-01

Damage to the lungs caused by dusts or fumes or noxious substances inhaled by workers in certain specific occupation is known as occupational lung disease. Recognition of occupational lung disease is especially important not only for the primary worker, but also because of the implications with regard to primary and secondary disease prevention in the exposed co-workers. Although many of the disorders can be detected on chest radiography, high-resolution computed tomography (HRCT) is superior in delineating the lung architecture and depicting pathology. The characteristic radiological features suggest the correct diagnosis in some, whereas a combination of clinical features, occupational history, and radiological findings is essential in establishing the diagnosis in others. In the presence of a history of exposure and consistent clinical features, the diagnosis of even an uncommon occupational lung disease can be suggested by the characteristic described HRCT findings. In this article, we briefly review the HRCT appearance of a wide spectrum of occupational lung diseases. PMID:24604929

Spectrum of high-resolution computed tomography imaging in occupational lung disease.

PubMed

Satija, Bhawna; Kumar, Sanyal; Ojha, Umesh Chandra; Gothi, Dipti

2013-10-01

Damage to the lungs caused by dusts or fumes or noxious substances inhaled by workers in certain specific occupation is known as occupational lung disease. Recognition of occupational lung disease is especially important not only for the primary worker, but also because of the implications with regard to primary and secondary disease prevention in the exposed co-workers. Although many of the disorders can be detected on chest radiography, high-resolution computed tomography (HRCT) is superior in delineating the lung architecture and depicting pathology. The characteristic radiological features suggest the correct diagnosis in some, whereas a combination of clinical features, occupational history, and radiological findings is essential in establishing the diagnosis in others. In the presence of a history of exposure and consistent clinical features, the diagnosis of even an uncommon occupational lung disease can be suggested by the characteristic described HRCT findings. In this article, we briefly review the HRCT appearance of a wide spectrum of occupational lung diseases.

Using deep learning to quantify the beauty of outdoor places.

PubMed

Seresinhe, Chanuki Illushka; Preis, Tobias; Moat, Helen Susannah

2017-07-01

Beautiful outdoor locations are protected by governments and have recently been shown to be associated with better health. But what makes an outdoor space beautiful? Does a beautiful outdoor location differ from an outdoor location that is simply natural? Here, we explore whether ratings of over 200 000 images of Great Britain from the online game Scenic-Or-Not , combined with hundreds of image features extracted using the Places Convolutional Neural Network, might help us understand what beautiful outdoor spaces are composed of. We discover that, as well as natural features such as 'Coast', 'Mountain' and 'Canal Natural', man-made structures such as 'Tower', 'Castle' and 'Viaduct' lead to places being considered more scenic. Importantly, while scenes containing 'Trees' tend to rate highly, places containing more bland natural green features such as 'Grass' and 'Athletic Fields' are considered less scenic. We also find that a neural network can be trained to automatically identify scenic places, and that this network highlights both natural and built locations. Our findings demonstrate how online data combined with neural networks can provide a deeper understanding of what environments we might find beautiful and offer quantitative insights for policymakers charged with design and protection of our built and natural environments.

Content management systems and E-commerce: a comparative case study

NASA Astrophysics Data System (ADS)

Al Rasheed, Amal A.; El-Masri, Samir D.

2011-12-01

The need for CMS's to create and edit e-commerce websites has increased with the growing importance of e-commerce. In this paper, the various features essential for e-commerce CMS's are explored. The aim of the paper was to find the best CMS solution for e-commerce which includes the best of both CMS and store management. Accordingly, we conducted a study on three popular open source CMS's for e-commerce: VirtueMart from Joomla!, Ubercart from Drupal, and Magento. We took into account features like hosting and installation, performance, support/community, content management, add on modules and functional features. We concluded with improvements that could be made in order to alleviate problems.

Visual observations over oceans

NASA Technical Reports Server (NTRS)

Terry, R. D.

1979-01-01

Important factors in locating, identifying, describing, and photographing ocean features from space are presented. On the basis of crew comments and other findings, the following recommendations can be made for Earth observations on Space Shuttle missions: (1) flyover exercises must include observations and photography of both temperate and tropical/subtropical waters; (2) sunglint must be included during some observations of ocean features; (3) imaging remote sensors should be used together with conventional photographic systems to document visual observations; (4) greater consideration must be given to scheduling earth observation targets likely to be obscured by clouds; and (5) an annotated photographic compilation of ocean features can be used as a training aid before the mission and as a reference book during space flight.

Borderline Personality Features, Anger, and Intimate Partner Violence: An Experimental Manipulation of Rejection.

PubMed

Armenti, Nicholas A; Babcock, Julia C

2018-04-01

Individuals with borderline personality features may be susceptible to react to situational stressors with negative and interpersonally maladaptive emotionality (e.g., anger) and aggression. The current study attempted to test two moderated mediation models to investigate dispositional risk factors associated with borderline personality features and intimate partner violence (IPV). Results from an experimental rejection induction paradigm were examined using moderated regression to observe contextual reactions to imagined romantic rejection from a current romantic partner among individuals with borderline personality features. An ethnically diverse sample of 218 undergraduates at a large public university in the southwestern United States was recruited. Participants responded to demographic questions and self-report measures, and engaged in an experimental rejection induction paradigm. Borderline personality features was positively associated with rejection sensitivity, physical assault, and psychological aggression. Contrary to initial hypotheses, rejection sensitivity did not serve as a mediator of the relations between borderline personality features and physical assault and psychological aggression. However, trait anger mediated the relation between borderline personality features and psychological aggression. As such, trait anger may be an important explanatory variable in the relation between borderline personality features and psychological aggression specifically. Results of the rejection induction paradigm indicated that, for individuals who were asked to imagine an ambiguous rejection, the relation between borderline personality features and state anger post-rejection was strengthened. For individuals who imagined a critical rejection, there was no significant relation between borderline personality features and state anger post-rejection. Findings suggest that trait anger may be an important dispositional factor in the link between borderline personality features and IPV. In addition, contextual factors, such as ambiguous rejection by an intimate partner, may be especially relevant in activating anger or aggression in individuals with borderline personality features.

Optimal chroma-like channel design for passive color image splicing detection

NASA Astrophysics Data System (ADS)

Zhao, Xudong; Li, Shenghong; Wang, Shilin; Li, Jianhua; Yang, Kongjin

2012-12-01

Image splicing is one of the most common image forgeries in our daily life and due to the powerful image manipulation tools, image splicing is becoming easier and easier. Several methods have been proposed for image splicing detection and all of them worked on certain existing color channels. However, the splicing artifacts vary in different color channels and the selection of color model is important for image splicing detection. In this article, instead of finding an existing color model, we propose a color channel design method to find the most discriminative channel which is referred to as optimal chroma-like channel for a given feature extraction method. Experimental results show that both spatial and frequency features extracted from the designed channel achieve higher detection rate than those extracted from traditional color channels.

Quantitative EEG features selection in the classification of attention and response control in the children and adolescents with attention deficit hyperactivity disorder.

PubMed

Bashiri, Azadeh; Shahmoradi, Leila; Beigy, Hamid; Savareh, Behrouz A; Nosratabadi, Masood; N Kalhori, Sharareh R; Ghazisaeedi, Marjan

2018-06-01

Quantitative EEG gives valuable information in the clinical evaluation of psychological disorders. The purpose of the present study is to identify the most prominent features of quantitative electroencephalography (QEEG) that affect attention and response control parameters in children with attention deficit hyperactivity disorder. The QEEG features and the Integrated Visual and Auditory-Continuous Performance Test ( IVA-CPT) of 95 attention deficit hyperactivity disorder subjects were preprocessed by Independent Evaluation Criterion for Binary Classification. Then, the importance of selected features in the classification of desired outputs was evaluated using the artificial neural network. Findings uncovered the highest rank of QEEG features in each IVA-CPT parameters related to attention and response control. Using the designed model could help therapists to determine the existence or absence of defects in attention and response control relying on QEEG.

Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

PubMed

Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

2018-02-01

The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

Comparing ground-penetrating radar (GPR) techniques in 18th-century yard spaces

NASA Astrophysics Data System (ADS)

Carducci, Christiane M.

Yards surrounding historical homesteads are the liminal space between private houses and public space, and contain artifactural and structural remains that help us understand how the residents interfaced with the world. Comparing different yards means collecting reliable evidence, and what is missing is just as important as what is found. Excavations can rely on randomly placed 50-cm shovel test pits to locate features, but this can miss important features. Shallow geophysics, in particular ground-penetrating radar (GPR), can be used to identify features and reliably and efficiently collect evidence. GPR is becoming more integrated into archaeological investigations due to the potential to quickly and nondestructively identify archaeological features and to recent advancements in processing software that make these methods more user-friendly. The most efficacious GPR surveys must take into consideration what is expected to be below the surface, what features look like in GPR outputs, the best methods for detecting features, and the limitations of GPR surveys. Man-made landscape features are expected to have existed within yard spaces, and the alteration of these features shows how the domestic economy of the residence changed through time. This study creates an inventory of these features. By producing a standardized sampling method for GPR in yard spaces, archaeologists can quickly map subsurface features and carry out broad comparisons between yards. To determine the most effective sampling method, several GPR surveys were conducted at the 18th-century Durant-Kenrick House in Newton, Massachusetts, using varied line spacing, line direction, and bin size. Examples of the GPR signatures of features, obtained using GPR-Slice software, from the Durant-Kenrick House and similar sites were analyzed. The efficacy of each method was determined based on the number of features distinguished, clarity of the results, and the time involved. The survey at Newton showed that ground surface conditions are extremely important when using GPR. Furthermore, GPR and archaeological excavations together provide the most complete interpretation because GPR has the ability to detect large-scale features that might be missed with test units, while excavation provides more detailed information, finds small-scale objects, and can be used to test false negatives seen in GPR surveys.

The materials processing research base of the Materials Processing Center. Report for FY 1982

NASA Technical Reports Server (NTRS)

Flemings, M. C.

1983-01-01

The work described, while involving research in the broad field of materials processing, has two common features: the problems are closed related to space precessing of materials and have both practical and fundamental significance. An interesting and important feature of many of the projects is that the interdisciplinary nature of the problem mandates complementary analytical modeling/experimental approaches. An other important aspect of many of the projects is the increasing use of mathematical modeling techniques as one of the research tools. The predictive capability of these models, when tested against measurements, plays a very important role in both the planning of experimental programs and in the rational interpretation of the results. Many of the projects described have a space experiment as their ultimate objective. Mathematical models are proving to be extremely valuable in projecting the findings of ground - based experiments to microgravity conditions.

What distinguishes the small fraction of tropical ocean storms with lightning? An examination of the environment, organization, and evolution of radar features over Kwajalein

NASA Astrophysics Data System (ADS)

Bang, S. D.; Zipser, E. J.

2017-12-01

Lightning over the tropical ocean, though much rarer than over land, is predominantly observed in large, mostly mature convective systems. The implication is that these may require external forcing or organization in order to develop updrafts sufficiently strong to loft and sustain graupel and supercooled water above the freezing level and thereby produce lightning. We examine three years of radar data from the Kwajalein Atoll in the Marshall Islands in the tropical Pacific Ocean, which we subject to the Warning Decisions Support System - Integrated Information (WDSS-II) tracking algorithm in order to create an evolutionary radar feature dataset. In conjunction with ERA-interim reanalysis environmental data and World Wide Lightning Location Network (WWLLN) lightning data, we are able to observe the lifecycles of electrified convection over Kwajalein and examine the characteristics leading up to a lightning flash for radar features throughout the intensity spectrum. We find that lightning over Kwajalein exhibits the same tendency to occur in large, mature radar features, and the probability of lightning increases with increasing size and, to a certain extent, age. However, there is little evidence to support the role of singular environmental parameters in the development into large features. We continue to struggle to find the reasons that may influence or control the evolution of small features into large, organized convective systems, a major issue that has importance well beyond whether the feature is electrified.

The interaction of feature and space based orienting within the attention set.

PubMed

Lim, Ahnate; Sinnett, Scott

2014-01-01

The processing of sensory information relies on interacting mechanisms of sustained attention and attentional capture, both of which operate in space and on object features. While evidence indicates that exogenous attentional capture, a mechanism previously understood to be automatic, can be eliminated while concurrently performing a demanding task, we reframe this phenomenon within the theoretical framework of the "attention set" (Most et al., 2005). Consequently, the specific prediction that cuing effects should reappear when feature dimensions of the cue overlap with those in the attention set (i.e., elements of the demanding task) was empirically tested and confirmed using a dual-task paradigm involving both sustained attention and attentional capture, adapted from Santangelo et al. (2007). Participants were required to either detect a centrally presented target presented in a stream of distractors (the primary task), or respond to a spatially cued target (the secondary task). Importantly, the spatial cue could either share features with the target in the centrally presented primary task, or not share any features. Overall, the findings supported the attention set hypothesis showing that a spatial cuing effect was only observed when the peripheral cue shared a feature with objects that were already in the attention set (i.e., the primary task). However, this finding was accompanied by differential attentional orienting dependent on the different types of objects within the attention set, with feature-based orienting occurring for target-related objects, and additional spatial-based orienting for distractor-related objects.

The interaction of feature and space based orienting within the attention set

PubMed Central

Lim, Ahnate; Sinnett, Scott

2014-01-01

The processing of sensory information relies on interacting mechanisms of sustained attention and attentional capture, both of which operate in space and on object features. While evidence indicates that exogenous attentional capture, a mechanism previously understood to be automatic, can be eliminated while concurrently performing a demanding task, we reframe this phenomenon within the theoretical framework of the “attention set” (Most et al., 2005). Consequently, the specific prediction that cuing effects should reappear when feature dimensions of the cue overlap with those in the attention set (i.e., elements of the demanding task) was empirically tested and confirmed using a dual-task paradigm involving both sustained attention and attentional capture, adapted from Santangelo et al. (2007). Participants were required to either detect a centrally presented target presented in a stream of distractors (the primary task), or respond to a spatially cued target (the secondary task). Importantly, the spatial cue could either share features with the target in the centrally presented primary task, or not share any features. Overall, the findings supported the attention set hypothesis showing that a spatial cuing effect was only observed when the peripheral cue shared a feature with objects that were already in the attention set (i.e., the primary task). However, this finding was accompanied by differential attentional orienting dependent on the different types of objects within the attention set, with feature-based orienting occurring for target-related objects, and additional spatial-based orienting for distractor-related objects. PMID:24523682

Autosomal dominant cerebellar ataxia with retinal degeneration (ADCA II): clinical and neuropathological findings in two pedigrees and genetic linkage to 3p12-p21.1.

PubMed Central

Jöbsis, G J; Weber, J W; Barth, P G; Keizers, H; Baas, F; van Schooneveld, M J; van Hilten, J J; Troost, D; Geesink, H H; Bolhuis, P A

1997-01-01

OBJECTIVES: To investigate relations between clinical and neuropathological features and age of onset, presence of anticipation, and genetic linkage in autosomal dominant cerebellar ataxia type II (ADCA II). METHODS: The natural history of ADCA II was studied on the basis of clinical and neuropathological findings in two pedigrees and genetic linkage studies were carried out with polymorphic DNA markers in the largest, four generation, pedigree. RESULTS: Ataxia was constant in all age groups. Retinal degeneration with early extinction of the electroretinogram constituted an important component in juvenile and early adult (< 25 years) onset but was variable in late adult presentation. Neuromuscular involvement due to spinal anterior horn disease was an important contributing factor to illness in juvenile cases. Postmortem findings in four patients confirm the general neurodegenerative nature of the disease, which includes prominent spinal anterior horn involvement and widespread involvement of grey and white matter. Genetic linkage was found with markers to chromosome 3p12-p21.1 (maximum pairwise lod score 4.42 at D3S1285). CONCLUSIONS: The sequence of clinical involvement seems related to age at onset. Retinal degeneration is variable in late onset patients and neuromuscular features are important in patients with early onset. Strong anticipation was found in subsequent generations. Linkage of ADCA II to chromosome 3p12-p21.1 is confirmed. Images PMID:9120450

The Role of Early Visual Attention in Social Development

ERIC Educational Resources Information Center

Wagner, Jennifer B.; Luyster, Rhiannon J.; Yim, Jung Yeon; Tager-Flusberg, Helen; Nelson, Charles A.

2013-01-01

Faces convey important information about the social environment, and even very young infants are preferentially attentive to face-like over non-face stimuli. Eye-tracking studies have allowed researchers to examine which features of faces infants find most salient across development, and the present study examined scanning of familiar (i.e.,…

Cyberbullying Bystanders and Moral Engagement: A Psychosocial Analysis for Pastoral Care

ERIC Educational Resources Information Center

Kyriacou, Chris; Zuin, Antônio

2018-01-01

One of the new challenges facing pastoral care in schools is dealing with the rapid growth of cyberbullying by school-aged children. Within digital cyberspace, cyberbullies are finding more opportunities to express their aggression towards others as social networks become technologically more sophisticated. An important feature of cyberbullying is…

Visual Communication in PowerPoint Presentations in Applied Linguistics

ERIC Educational Resources Information Center

Kmalvand, Ayad

2014-01-01

PowerPoint knowledge presentation as a digital genre has established itself as the main software by which the findings of theses are disseminated in the academic settings. Although the importance of PowerPoint presentations is typically realized in academic settings like lectures, conferences, and seminars, the study of the visual features of…

Farming. Canada at Work Series.

ERIC Educational Resources Information Center

Love, Ann; Drake, Jane

This book is part of the Canada At Work series that introduces children to the people, machines, work and environmental concerns involved in bringing to market the products from important Canadian natural resources. This volume features a year-round look at two kinds of agriculture in Canada. On the vegetable farm, children find out about spring…

Hostel User Study.

ERIC Educational Resources Information Center

Allen, Phyllis

Findings from a study of living accommodations for young people are given in the first part. Features are identified that are regarded as important by management and residents. Suggestions are made as to how user response may be predicted and the responses of the residents to eight schemes are examined in detail. Also considered are--(1) the…

User Experience on Display

ERIC Educational Resources Information Center

Schmidt, Aaron

2010-01-01

What do a pink door, reading glasses, a website, and a Beetle Kill Pine ceiling have in common? Yes, readers will find them all in this collection of great design in libraries. But the reason they're featured is their important commonality: they were intentionally and thoughtfully placed in a library to meet people's needs or otherwise engage…

Prioritizing Improvements in Internet Instruction Based on Learning Styles and Strategies

ERIC Educational Resources Information Center

Speth, Carol A.; Lee, Donald J.; Hain, Patricia M.

2006-01-01

How can various features of internet-based instruction be adapted to help students with different learning styles to grasp important science concepts? Are there ways of defining and measuring these differences that instructors without much background in educational psychology might find easier to apply than some of the better-known examples? How…

Where's Wally: the influence of visual salience on referring expression generation.

PubMed

Clarke, Alasdair D F; Elsner, Micha; Rohde, Hannah

2013-01-01

REFERRING EXPRESSION GENERATION (REG) PRESENTS THE CONVERSE PROBLEM TO VISUAL SEARCH: given a scene and a specified target, how does one generate a description which would allow somebody else to quickly and accurately locate the target?Previous work in psycholinguistics and natural language processing has failed to find an important and integrated role for vision in this task. That previous work, which relies largely on simple scenes, tends to treat vision as a pre-process for extracting feature categories that are relevant to disambiguation. However, the visual search literature suggests that some descriptions are better than others at enabling listeners to search efficiently within complex stimuli. This paper presents a study testing whether participants are sensitive to visual features that allow them to compose such "good" descriptions. Our results show that visual properties (salience, clutter, area, and distance) influence REG for targets embedded in images from the Where's Wally? books. Referring expressions for large targets are shorter than those for smaller targets, and expressions about targets in highly cluttered scenes use more words. We also find that participants are more likely to mention non-target landmarks that are large, salient, and in close proximity to the target. These findings identify a key role for visual salience in language production decisions and highlight the importance of scene complexity for REG.

From automata to animate beings: the scope and limits of attributing socialness to artificial agents.

PubMed

Hortensius, Ruud; Cross, Emily S

2018-05-11

Understanding the mechanisms and consequences of attributing socialness to artificial agents has important implications for how we can use technology to lead more productive and fulfilling lives. Here, we integrate recent findings on the factors that shape behavioral and brain mechanisms that support social interactions between humans and artificial agents. We review how visual features of an agent, as well as knowledge factors within the human observer, shape attributions across dimensions of socialness. We explore how anthropomorphism and dehumanization further influence how we perceive and interact with artificial agents. Based on these findings, we argue that the cognitive reconstruction within the human observer is likely to be far more crucial in shaping our interactions with artificial agents than previously thought, while the artificial agent's visual features are possibly of lesser importance. We combine these findings to provide an integrative theoretical account based on the "like me" hypothesis, and discuss the key role played by the Theory-of-Mind network, especially the temporal parietal junction, in the shift from mechanistic to social attributions. We conclude by highlighting outstanding questions on the impact of long-term interactions with artificial agents on the behavioral and brain mechanisms of attributing socialness to these agents. © 2018 New York Academy of Sciences.

Incidental finding of lamellar calcification of the falx cerebri leading to the diagnosis of gorlin-goltz syndrome.

PubMed

Saulite, I; Voykov, B; Mehra, T; Hoetzenecker, W; Guenova, E

2013-01-01

Here, we report the case of an incidental finding of lamellar calcification of the falx cerebri in a routine computed tomography scan of the head after an accidental trauma. This lamellar calcification led to the diagnosis of Gorlin-Goltz syndrome (GGS) in the patient and her daughter. Lamellar calcification of the falx cerebri is a pathognomonic feature of GGS. Our case report highlights the importance of a multidisciplinary diagnostic approach to GGS.

Incidental Finding of Lamellar Calcification of the Falx Cerebri Leading to the Diagnosis of Gorlin-Goltz Syndrome

PubMed Central

Saulite, I.; Voykov, B.; Mehra, T.; Hoetzenecker, W.; Guenova, E.

2013-01-01

Here, we report the case of an incidental finding of lamellar calcification of the falx cerebri in a routine computed tomography scan of the head after an accidental trauma. This lamellar calcification led to the diagnosis of Gorlin-Goltz syndrome (GGS) in the patient and her daughter. Lamellar calcification of the falx cerebri is a pathognomonic feature of GGS. Our case report highlights the importance of a multidisciplinary diagnostic approach to GGS. PMID:24403894

Face processing in autism: Reduced integration of cross-feature dynamics.

PubMed

Shah, Punit; Bird, Geoffrey; Cook, Richard

2016-02-01

Characteristic problems with social interaction have prompted considerable interest in the face processing of individuals with Autism Spectrum Disorder (ASD). Studies suggest that reduced integration of information from disparate facial regions likely contributes to difficulties recognizing static faces in this population. Recent work also indicates that observers with ASD have problems using patterns of facial motion to judge identity and gender, and may be less able to derive global motion percepts. These findings raise the possibility that feature integration deficits also impact the perception of moving faces. To test this hypothesis, we examined whether observers with ASD exhibit susceptibility to a new dynamic face illusion, thought to index integration of moving facial features. When typical observers view eye-opening and -closing in the presence of asynchronous mouth-opening and -closing, the concurrent mouth movements induce a strong illusory slowing of the eye transitions. However, we find that observers with ASD are not susceptible to this illusion, suggestive of weaker integration of cross-feature dynamics. Nevertheless, observers with ASD and typical controls were equally able to detect the physical differences between comparison eye transitions. Importantly, this confirms that observers with ASD were able to fixate the eye-region, indicating that the striking group difference has a perceptual, not attentional origin. The clarity of the present results contrasts starkly with the modest effect sizes and equivocal findings seen throughout the literature on static face perception in ASD. We speculate that differences in the perception of facial motion may be a more reliable feature of this condition. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Computer-aided diagnosis of melanoma using border and wavelet-based texture analysis.

PubMed

Garnavi, Rahil; Aldeen, Mohammad; Bailey, James

2012-11-01

This paper presents a novel computer-aided diagnosis system for melanoma. The novelty lies in the optimised selection and integration of features derived from textural, borderbased and geometrical properties of the melanoma lesion. The texture features are derived from using wavelet-decomposition, the border features are derived from constructing a boundaryseries model of the lesion border and analysing it in spatial and frequency domains, and the geometry features are derived from shape indexes. The optimised selection of features is achieved by using the Gain-Ratio method, which is shown to be computationally efficient for melanoma diagnosis application. Classification is done through the use of four classifiers; namely, Support Vector Machine, Random Forest, Logistic Model Tree and Hidden Naive Bayes. The proposed diagnostic system is applied on a set of 289 dermoscopy images (114 malignant, 175 benign) partitioned into train, validation and test image sets. The system achieves and accuracy of 91.26% and AUC value of 0.937, when 23 features are used. Other important findings include (i) the clear advantage gained in complementing texture with border and geometry features, compared to using texture information only, and (ii) higher contribution of texture features than border-based features in the optimised feature set.

Kindler syndrome: a study of five Egyptian cases with evaluation of severity.

PubMed

Nofal, Eman; Assaf, Magda; Elmosalamy, Khaled

2008-07-01

Kindler syndrome (KS) is a rare genodermatosis characterized by four major features (acral blisters, photosensitivity, poikiloderma, and cutaneous atrophy) and many associated findings. The diagnosis of KS includes clinical features, ultrastructural findings, and, recently, immunostaining and genetic studies. Varying degrees of severity of the syndrome have been described. Five patients with clinical features consistent with KS were included in this study. All patients were subjected to histopathologic and ultrastructural studies. Cases 1 and 2 presented with severe major features, severe mucosal involvement, and many other associated findings. Case 3 presented with severe major features, but mild and limited mucosal involvement and other associated findings. Cases 4 and 5 showed mild major features and few other findings. Histopathology revealed nonspecific poikiloderma. Marked thickening of the lamina densa and splitting of the lamina lucida were the main ultrastructural findings. KS may be classified into mild, moderate, and severe according to the severity of the major features and mucosal involvement. Because histopathologic and ultrastructural findings are not pathognomonic, clinical features remain the mainstay for the diagnosis of KS, and the need for immunostaining with kindlin antibody and genetic studies may be restricted to early cases with incomplete features.

Feature selection in feature network models: finding predictive subsets of features with the Positive Lasso.

PubMed

Frank, Laurence E; Heiser, Willem J

2008-05-01

A set of features is the basis for the network representation of proximity data achieved by feature network models (FNMs). Features are binary variables that characterize the objects in an experiment, with some measure of proximity as response variable. Sometimes features are provided by theory and play an important role in the construction of the experimental conditions. In some research settings, the features are not known a priori. This paper shows how to generate features in this situation and how to select an adequate subset of features that takes into account a good compromise between model fit and model complexity, using a new version of least angle regression that restricts coefficients to be non-negative, called the Positive Lasso. It will be shown that features can be generated efficiently with Gray codes that are naturally linked to the FNMs. The model selection strategy makes use of the fact that FNM can be considered as univariate multiple regression model. A simulation study shows that the proposed strategy leads to satisfactory results if the number of objects is less than or equal to 22. If the number of objects is larger than 22, the number of features selected by our method exceeds the true number of features in some conditions.

Tele-Autonomous control involving contact. Final Report Thesis; [object localization

NASA Technical Reports Server (NTRS)

Shao, Lejun; Volz, Richard A.; Conway, Lynn; Walker, Michael W.

1990-01-01

Object localization and its application in tele-autonomous systems are studied. Two object localization algorithms are presented together with the methods of extracting several important types of object features. The first algorithm is based on line-segment to line-segment matching. Line range sensors are used to extract line-segment features from an object. The extracted features are matched to corresponding model features to compute the location of the object. The inputs of the second algorithm are not limited only to the line features. Featured points (point to point matching) and featured unit direction vectors (vector to vector matching) can also be used as the inputs of the algorithm, and there is no upper limit on the number of the features inputed. The algorithm will allow the use of redundant features to find a better solution. The algorithm uses dual number quaternions to represent the position and orientation of an object and uses the least squares optimization method to find an optimal solution for the object's location. The advantage of using this representation is that the method solves for the location estimation by minimizing a single cost function associated with the sum of the orientation and position errors and thus has a better performance on the estimation, both in accuracy and speed, than that of other similar algorithms. The difficulties when the operator is controlling a remote robot to perform manipulation tasks are also discussed. The main problems facing the operator are time delays on the signal transmission and the uncertainties of the remote environment. How object localization techniques can be used together with other techniques such as predictor display and time desynchronization to help to overcome these difficulties are then discussed.

Real-Time Feature Tracking Using Homography

NASA Technical Reports Server (NTRS)

Clouse, Daniel S.; Cheng, Yang; Ansar, Adnan I.; Trotz, David C.; Padgett, Curtis W.

2010-01-01

This software finds feature point correspondences in sequences of images. It is designed for feature matching in aerial imagery. Feature matching is a fundamental step in a number of important image processing operations: calibrating the cameras in a camera array, stabilizing images in aerial movies, geo-registration of images, and generating high-fidelity surface maps from aerial movies. The method uses a Shi-Tomasi corner detector and normalized cross-correlation. This process is likely to result in the production of some mismatches. The feature set is cleaned up using the assumption that there is a large planar patch visible in both images. At high altitude, this assumption is often reasonable. A mathematical transformation, called an homography, is developed that allows us to predict the position in image 2 of any point on the plane in image 1. Any feature pair that is inconsistent with the homography is thrown out. The output of the process is a set of feature pairs, and the homography. The algorithms in this innovation are well known, but the new implementation improves the process in several ways. It runs in real-time at 2 Hz on 64-megapixel imagery. The new Shi-Tomasi corner detector tries to produce the requested number of features by automatically adjusting the minimum distance between found features. The homography-finding code now uses an implementation of the RANSAC algorithm that adjusts the number of iterations automatically to achieve a pre-set probability of missing a set of inliers. The new interface allows the caller to pass in a set of predetermined points in one of the images. This allows the ability to track the same set of points through multiple frames.

MIIB: A Metric to Identify Top Influential Bloggers in a Community.

PubMed

Khan, Hikmat Ullah; Daud, Ali; Malik, Tahir Afzal

2015-01-01

Social networking has revolutionized the use of conventional web and has converted World Wide Web into the social web as users can generate their own content. This change has been possible due to social web platforms like forums, wikis, and blogs. Blogs are more commonly being used as a form of virtual communication to express an opinion about an event, product or experience and can reach a large audience. Users can influence others to buy a product, have certain political or social views, etc. Therefore, identifying the most influential bloggers has become very significant as this can help us in the fields of commerce, advertisement and product knowledge searching. Existing approaches consider some basic features, but lack to consider some other features like the importance of the blog on which the post has been created. This paper presents a new metric, MIIB (Metric for Identification of Influential Bloggers), based on various features of bloggers' productivity and popularity. Productivity refers to bloggers' blogging activity and popularity measures bloggers' influence in the blogging community. The novel module of BlogRank depicts the importance of blog sites where bloggers create their posts. The MIIB has been evaluated against the standard model and existing metrics for finding the influential bloggers using dataset from the real-world blogosphere. The obtained results confirm that the MIIB is able to find the most influential bloggers in a more effective manner.

A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs).

PubMed

Kuang, Qifan; Wang, MinQi; Li, Rong; Dong, YongCheng; Li, Yizhou; Li, Menglong

2014-01-01

Early and accurate identification of adverse drug reactions (ADRs) is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs. In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper. Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms.

Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

PubMed

Cao, Yinhe; Tung, Wen-Wen; Gao, J B

2004-01-01

With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.

Hepatocellular Adenoma: Evaluation with Contrast-Enhanced Ultrasound and MRI and Correlation with Pathologic and Phenotypic Classification in 26 Lesions

PubMed Central

Manichon, Anne-Frédérique; Bancel, Brigitte; Durieux-Millon, Marion; Ducerf, Christian; Mabrut, Jean-Yves; Lepogam, Marie-Annick; Rode, Agnès

2012-01-01

Purpose. To review the contrast-enhanced ultrasonographic (CEUS) and magnetic resonance (MR) imaging findings in 25 patients with 26 hepatocellular adenomas (HCAs) and to compare imaging features with histopathologic results from resected specimen considering the new immunophenotypical classification. Material and Methods. Two abdominal radiologists reviewed retrospectively CEUS cineloops and MR images in 26 HCA. All pathological specimens were reviewed and classified into four subgroups (steatotic or HNF 1α mutated, inflammatory, atypical or β-catenin mutated, and unspecified). Inflammatory infiltrates were scored, steatosis, and telangiectasia semiquantitatively evaluated. Results. CEUS and MRI features are well correlated: among the 16 inflammatory HCA, 7/16 presented typical imaging features: hypersignal T2, strong arterial enhancement with a centripetal filling, persistent on delayed phase. 6 HCA were classified as steatotic with typical imaging features: a drop out signal, slight arterial enhancement, vanishing on late phase. Four HCA were classified as atypical with an HCC developed in one. Five lesions displayed important steatosis (>50%) without belonging to the HNF1α group. Conclusion. In half cases, inflammatory HCA have specific imaging features well correlated with the amount of telangiectasia and inflammatory infiltrates. An HCA with important amount of steatosis noticed on chemical shift images does not always belong to the HNF1α group. PMID:22811588

Mobile Applications for Participation at the Shopping Mall: Content Analysis and Usability for Persons with Physical Disabilities and Communication or Cognitive Limitations

PubMed Central

Auger, Claudine; Leduc, Emilie; Labbé, Delphine; Guay, Cassioppée; Fillion, Brigitte; Bottari, Carolina; Swaine, Bonnie

2014-01-01

The aim of this exploratory study was to determine the important features in content and usability of existing mobile applications evaluating environmental barriers and facilitators (EBF) to participation for persons with physical disabilities presenting mild communication or cognitive limitations. A rigorous process based on a user-centered design approach led to the identification of two relevant mobile applications to evaluate the EBF. An accessibility expert, the research team as well as five users then tested the mobile applications in a shopping mall. A thematic content analysis of the research team’s and users’ comments established 10 categories of key features that adequately respond to the needs of the clientele targeted in this study. In terms of content, granularity and contextualization of the information provided were considered important. With respect to usability, relevant features were place finding, rating system, presentation of results, compatibility, user-friendliness, aesthetics, credibility of the information as well as connectivity/interactiveness. The research team and the users agreed on some aspects such as aesthetics, but had different perspectives on features such as the rating system or the connectivity/interactiveness of the application. The users proposed new features suggesting that the existing mobile applications did not correspond to all their needs. PMID:25513999

Mobile applications for participation at the shopping mall: content analysis and usability for persons with physical disabilities and communication or cognitive limitations.

PubMed

Auger, Claudine; Leduc, Emilie; Labbé, Delphine; Guay, Cassioppée; Fillion, Brigitte; Bottari, Carolina; Swaine, Bonnie

2014-12-01

The aim of this exploratory study was to determine the important features in content and usability of existing mobile applications evaluating environmental barriers and facilitators (EBF) to participation for persons with physical disabilities presenting mild communication or cognitive limitations. A rigorous process based on a user-centered design approach led to the identification of two relevant mobile applications to evaluate the EBF. An accessibility expert, the research team as well as five users then tested the mobile applications in a shopping mall. A thematic content analysis of the research team's and users' comments established 10 categories of key features that adequately respond to the needs of the clientele targeted in this study. In terms of content, granularity and contextualization of the information provided were considered important. With respect to usability, relevant features were place finding, rating system, presentation of results, compatibility, user-friendliness, aesthetics, credibility of the information as well as connectivity/interactiveness. The research team and the users agreed on some aspects such as aesthetics, but had different perspectives on features such as the rating system or the connectivity/interactiveness of the application. The users proposed new features suggesting that the existing mobile applications did not correspond to all their needs.

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness

PubMed Central

Snyder, Abraham Z.; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W.; Shen, Mark D.; Wolff, Jason J.; Botteron, Kelly N.; Dager, Stephen; Estes, Annette M.; Evans, Alan; Gerig, Guido; Hazlett, Heather C.; Paterson, Sarah J.; Schultz, Robert T.; Styner, Martin A.; Zwaigenbaum, Lonnie; Schlaggar, Bradley L.

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI. PMID:29149191

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness.

PubMed

Mitra, Anish; Snyder, Abraham Z; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W; Shen, Mark D; Wolff, Jason J; Botteron, Kelly N; Dager, Stephen; Estes, Annette M; Evans, Alan; Gerig, Guido; Hazlett, Heather C; Paterson, Sarah J; Schultz, Robert T; Styner, Martin A; Zwaigenbaum, Lonnie; Schlaggar, Bradley L; Piven, Joseph; Pruett, John R; Raichle, Marcus

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.

Expectations Do Not Alter Early Sensory Processing during Perceptual Decision-Making.

PubMed

Rungratsameetaweemana, Nuttida; Itthipuripat, Sirawaj; Salazar, Annalisa; Serences, John T

2018-06-13

Two factors play important roles in shaping perception: the allocation of selective attention to behaviorally relevant sensory features, and prior expectations about regularities in the environment. Signal detection theory proposes distinct roles of attention and expectation on decision-making such that attention modulates early sensory processing, whereas expectation influences the selection and execution of motor responses. Challenging this classic framework, recent studies suggest that expectations about sensory regularities enhance the encoding and accumulation of sensory evidence during decision-making. However, it is possible, that these findings reflect well documented attentional modulations in visual cortex. Here, we tested this framework in a group of male and female human participants by examining how expectations about stimulus features (orientation and color) and expectations about motor responses impacted electroencephalography (EEG) markers of early sensory processing and the accumulation of sensory evidence during decision-making (the early visual negative potential and the centro-parietal positive potential, respectively). We first demonstrate that these markers are sensitive to changes in the amount of sensory evidence in the display. Then we show, counter to recent findings, that neither marker is modulated by either feature or motor expectations, despite a robust effect of expectations on behavior. Instead, violating expectations about likely sensory features and motor responses impacts posterior alpha and frontal theta oscillations, signals thought to index overall processing time and cognitive conflict. These findings are inconsistent with recent theoretical accounts and suggest instead that expectations primarily influence decisions by modulating post-perceptual stages of information processing. SIGNIFICANCE STATEMENT Expectations about likely features or motor responses play an important role in shaping behavior. Classic theoretical frameworks posit that expectations modulate decision-making by biasing late stages of decision-making including the selection and execution of motor responses. In contrast, recent accounts suggest that expectations also modulate decisions by improving the quality of early sensory processing. However, these effects could instead reflect the influence of selective attention. Here we examine the effect of expectations about sensory features and motor responses on a set of electroencephalography (EEG) markers that index early sensory processing and later post-perceptual processing. Counter to recent empirical results, expectations have little effect on early sensory processing but instead modulate EEG markers of time-on-task and cognitive conflict. Copyright © 2018 the authors 0270-6474/18/385632-17$15.00/0.

Multi-resolution analysis for ear recognition using wavelet features

NASA Astrophysics Data System (ADS)

Shoaib, M.; Basit, A.; Faye, I.

2016-11-01

Security is very important and in order to avoid any physical contact, identification of human when they are moving is necessary. Ear biometric is one of the methods by which a person can be identified using surveillance cameras. Various techniques have been proposed to increase the ear based recognition systems. In this work, a feature extraction method for human ear recognition based on wavelet transforms is proposed. The proposed features are approximation coefficients and specific details of level two after applying various types of wavelet transforms. Different wavelet transforms are applied to find the suitable wavelet. Minimum Euclidean distance is used as a matching criterion. Results achieved by the proposed method are promising and can be used in real time ear recognition system.

Optical-Near-infrared Color Gradients and Merging History of Elliptical Galaxies

NASA Astrophysics Data System (ADS)

Kim, Duho; Im, Myungshin

2013-04-01

It has been suggested that merging plays an important role in the formation and the evolution of elliptical galaxies. While gas dissipation by star formation is believed to steepen metallicity and color gradients of the merger products, mixing of stars through dissipation-less merging (dry merging) is believed to flatten them. In order to understand the past merging history of elliptical galaxies, we studied the optical-near-infrared (NIR) color gradients of 204 elliptical galaxies. These galaxies are selected from the overlap region of the Sloan Digital Sky Survey (SDSS) Stripe 82 and the UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). The use of optical and NIR data (g, r, and K) provides large wavelength baselines, and breaks the age-metallicity degeneracy, allowing us to derive age and metallicity gradients. The use of the deep SDSS Stripe 82 images makes it possible for us to examine how the color/age/metallicity gradients are related to merging features. We find that the optical-NIR color and the age/metallicity gradients of elliptical galaxies with tidal features are consistent with those of relaxed ellipticals, suggesting that the two populations underwent a similar merging history on average and that mixing of stars was more or less completed before the tidal features disappeared. Elliptical galaxies with dust features have steeper color gradients than the other two types, even after masking out dust features during the analysis, which can be due to a process involving wet merging. More importantly, we find that the scatter in the color/age/metallicity gradients of the relaxed and merging feature types decreases as their luminosities (or masses) increase at M > 1011.4 M ⊙ but stays large at lower luminosities. Mean metallicity gradients appear nearly constant over the explored mass range, but a possible flattening is observed at the massive end. According to our toy model that predicts how the distribution of metallicity gradients changes as a result of major dry merging, the mean metallicity gradient should flatten by 40% and its scatter becomes smaller by 80% per a mass-doubling scale if ellipticals evolve only through major dry merger. Our result, although limited by a number statistics at the massive end, is consistent with the picture that major dry merging is an important mechanism for the evolution for ellipticals at M > 1011.4 M ⊙, but is less important at the lower mass range.

OPTICAL-NEAR-INFRARED COLOR GRADIENTS AND MERGING HISTORY OF ELLIPTICAL GALAXIES

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

Kim, Duho; Im, Myungshin

2013-04-01

It has been suggested that merging plays an important role in the formation and the evolution of elliptical galaxies. While gas dissipation by star formation is believed to steepen metallicity and color gradients of the merger products, mixing of stars through dissipation-less merging (dry merging) is believed to flatten them. In order to understand the past merging history of elliptical galaxies, we studied the optical-near-infrared (NIR) color gradients of 204 elliptical galaxies. These galaxies are selected from the overlap region of the Sloan Digital Sky Survey (SDSS) Stripe 82 and the UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Surveymore » (LAS). The use of optical and NIR data (g, r, and K) provides large wavelength baselines, and breaks the age-metallicity degeneracy, allowing us to derive age and metallicity gradients. The use of the deep SDSS Stripe 82 images makes it possible for us to examine how the color/age/metallicity gradients are related to merging features. We find that the optical-NIR color and the age/metallicity gradients of elliptical galaxies with tidal features are consistent with those of relaxed ellipticals, suggesting that the two populations underwent a similar merging history on average and that mixing of stars was more or less completed before the tidal features disappeared. Elliptical galaxies with dust features have steeper color gradients than the other two types, even after masking out dust features during the analysis, which can be due to a process involving wet merging. More importantly, we find that the scatter in the color/age/metallicity gradients of the relaxed and merging feature types decreases as their luminosities (or masses) increase at M > 10{sup 11.4} M{sub Sun} but stays large at lower luminosities. Mean metallicity gradients appear nearly constant over the explored mass range, but a possible flattening is observed at the massive end. According to our toy model that predicts how the distribution of metallicity gradients changes as a result of major dry merging, the mean metallicity gradient should flatten by 40% and its scatter becomes smaller by 80% per a mass-doubling scale if ellipticals evolve only through major dry merger. Our result, although limited by a number statistics at the massive end, is consistent with the picture that major dry merging is an important mechanism for the evolution for ellipticals at M > 10{sup 11.4} M{sub Sun }, but is less important at the lower mass range.« less

Feature integration and spatial attention: common processes for endogenous and exogenous orienting.

PubMed

Henderickx, David; Maetens, Kathleen; Soetens, Eric

2010-05-01

Briand (J Exp Psychol Hum Percept Perform 24:1243-1256, 1998) and Briand and Klein (J Exp Psychol Hum Percept Perform 13:228-241, 1987) demonstrated that spatial cueing effects are larger for detecting conjunction of features than for detecting simple features when spatial attention is oriented exogenously, and not when attention is oriented endogenously. Their results were interpreted as if only exogenous attention affects the posterior spatial attention system that performs the feature binding function attributed to spatial attention by Treisman's feature integration theory (FIT; 1980). In a series of 6 experiments, we attempted to replicate Briand's findings. Manipulations of distractor string size and symmetry of stimulus presentation left and right from fixation were implemented in Posner's cueing paradigm. The data indicate that both exogenous and endogenous cueing address the same attentional mechanism needed for feature binding. The results also limit the generalisability of Briand's proposal concerning the role of exogenous attention in feature integration. Furthermore, the importance to control the effect of unintended attentional capture in a cueing task is demonstrated.

A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation

NASA Astrophysics Data System (ADS)

Vijverberg, Koen; Ghafoorian, Mohsen; van Uden, Inge W. M.; de Leeuw, Frank-Erik; Platel, Bram; Heskes, Tom

2016-03-01

Cerebral small vessel disease (SVD) is a disorder frequently found among the old people and is associated with deterioration in cognitive performance, parkinsonism, motor and mood impairments. White matter hyperintensities (WMH) as well as lacunes, microbleeds and subcortical brain atrophy are part of the spectrum of image findings, related to SVD. Accurate segmentation of WMHs is important for prognosis and diagnosis of multiple neurological disorders such as MS and SVD. Almost all of the published (semi-)automated WMH detection models employ multiple complex hand-crafted features, which require in-depth domain knowledge. In this paper we propose to apply a single-layer network unsupervised feature learning (USFL) method to avoid hand-crafted features, but rather to automatically learn a more efficient set of features. Experimental results show that a computer aided detection system with a USFL system outperforms a hand-crafted approach. Moreover, since the two feature sets have complementary properties, a hybrid system that makes use of both hand-crafted and unsupervised learned features, shows a significant performance boost compared to each system separately, getting close to the performance of an independent human expert.

What to Build for Middle-Agers to Come? Attractive and Necessary Functions of Exercise-Promotion Mobile Phone Apps: A Cross-Sectional Study

PubMed Central

Chien, Yu-Tai; Chen, Yu-Jen; Hsiung, Hsiao-Fang; Chen, Hsiao-Jung; Hsieh, Meng-Hua; Wu, Wen-Jie

2017-01-01

Background Physical activity is important for middle-agers to maintain health both in middle age and in old age. Although thousands of exercise-promotion mobile phone apps are available for download, current literature offers little understanding regarding which design features can enhance middle-aged adults’ quality perception toward exercise-promotion apps and which factor may influence such perception. Objectives The aims of this study were to understand (1) which design features of exercise-promotion apps can enhance quality perception of middle-agers, (2) whether their needs are matched by current functions offered in app stores, and (3) whether physical activity (PA) and mobile phone self-efficacy (MPSE) influence quality perception. Methods A total of 105 middle-agers participated and filled out three scales: the International Physical Activity Questionnaire (IPAQ), the MPSE scale, and the need for design features questionnaire. The design features were developed based on the Coventry, Aberdeen, and London—Refined (CALO-RE) taxonomy. Following the Kano quality model, the need for design features questionnaire asked participants to classify design features into five categories: attractive, one-dimensional, must-be, indifferent, and reverse. The quality categorization was conducted based on a voting approach and the categorization results were compared with the findings of a prevalence study to realize whether needs match current availability. In total, 52 multinomial logistic regression models were analyzed to evaluate the effects of PA level and MPSE on quality perception of design features. Results The Kano analysis on the total sample revealed that visual demonstration of exercise instructions is the only attractive design feature, whereas the other 51 design features were perceived with indifference. Although examining quality perception by PA level, 21 features are recommended to low level, 6 features to medium level, but none to high-level PA. In contrast, high-level MPSE is recommended with 14 design features, medium level with 6 features, whereas low-level participants are recommended with 1 feature. The analysis suggests that the implementation of demanded features could be low, as the average prevalence of demanded design features is 20% (4.3/21). Surprisingly, social comparison and social support, most implemented features in current apps, were categorized into the indifferent category. The magnitude of effect is larger for MPSE because it effects quality perception of more design features than PA. Delving into the 52 regression models revealed that high MPSE more likely induces attractive or one- dimensional categorization, suggesting the importance of technological self-efficacy on eHealth care promotion. Conclusions This study is the first to propose middle-agers’ needs in relation to mobile phone exercise-promotion. In addition to the tailor-made recommendations, suggestions are offered to app designers to enhance the performance of persuasive features. An interesting finding on change of quality perception attributed to MPSE is proposed as future research. PMID:28546140

Electroencephalography Amplitude Modulation Analysis for Automated Affective Tagging of Music Video Clips

PubMed Central

Clerico, Andrea; Tiwari, Abhishek; Gupta, Rishabh; Jayaraman, Srinivasan; Falk, Tiago H.

2018-01-01

The quantity of music content is rapidly increasing and automated affective tagging of music video clips can enable the development of intelligent retrieval, music recommendation, automatic playlist generators, and music browsing interfaces tuned to the users' current desires, preferences, or affective states. To achieve this goal, the field of affective computing has emerged, in particular the development of so-called affective brain-computer interfaces, which measure the user's affective state directly from measured brain waves using non-invasive tools, such as electroencephalography (EEG). Typically, conventional features extracted from the EEG signal have been used, such as frequency subband powers and/or inter-hemispheric power asymmetry indices. More recently, the coupling between EEG and peripheral physiological signals, such as the galvanic skin response (GSR), have also been proposed. Here, we show the importance of EEG amplitude modulations and propose several new features that measure the amplitude-amplitude cross-frequency coupling per EEG electrode, as well as linear and non-linear connections between multiple electrode pairs. When tested on a publicly available dataset of music video clips tagged with subjective affective ratings, support vector classifiers trained on the proposed features were shown to outperform those trained on conventional benchmark EEG features by as much as 6, 20, 8, and 7% for arousal, valence, dominance and liking, respectively. Moreover, fusion of the proposed features with EEG-GSR coupling features showed to be particularly useful for arousal (feature-level fusion) and liking (decision-level fusion) prediction. Together, these findings show the importance of the proposed features to characterize human affective states during music clip watching. PMID:29367844

A continuous scale-space method for the automated placement of spot heights on maps

NASA Astrophysics Data System (ADS)

Rocca, Luigi; Jenny, Bernhard; Puppo, Enrico

2017-12-01

Spot heights and soundings explicitly indicate terrain elevation on cartographic maps. Cartographers have developed design principles for the manual selection, placement, labeling, and generalization of spot height locations, but these processes are work-intensive and expensive. Finding an algorithmic criterion that matches the cartographers' judgment in ranking the significance of features on a terrain is a difficult endeavor. This article proposes a method for the automated selection of spot heights locations representing natural features such as peaks, saddles and depressions. A lifespan of critical points in a continuous scale-space model is employed as the main measure of the importance of features, and an algorithm and a data structure for its computation are described. We also introduce a method for the comparison of algorithmically computed spot height locations with manually produced reference compilations. The new method is compared with two known techniques from the literature. Results show spot height locations that are closer to reference spot heights produced manually by swisstopo cartographers, compared to previous techniques. The introduced method can be applied to elevation models for the creation of topographic and bathymetric maps. It also ranks the importance of extracted spot height locations, which allows for a variation in the size of symbols and labels according to the significance of represented features. The importance ranking could also be useful for adjusting spot height density of zoomable maps in real time.

Photometric Supernova Classification with Machine Learning

NASA Astrophysics Data System (ADS)

Lochner, Michelle; McEwen, Jason D.; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.

2016-08-01

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

Evolutionary and developmental implications of asymmetric brain folding in a large primate pedigree

PubMed Central

Atkinson, Elizabeth G.; Rogers, Jeffrey; Cheverud, James M.

2016-01-01

Bilateral symmetry is a fundamental property of the vertebrate central nervous system. Local deviations from symmetry provide various types of information about the development, evolution and function of elements within the CNS, especially the cerebral hemispheres. Here, we quantify the pattern and extent of asymmetry in cortical folding within the cerebrum of Papio baboons and assess the evolutionary and developmental implications of the findings. Analyses of directional asymmetry show a population-level trend in length measurements indicating that baboons are genetically predisposed to be asymmetrical, with the right side longer than the left in the anterior cerebrum while the left side is longer than the right posteriorly. We also find a corresponding bias to display a right frontal petalia (overgrowth of the anterior pole of the cerebral cortex on the right side). By quantifying fluctuating asymmetry, we assess canalization of brain features and the susceptibility of the baboon brain to developmental perturbations. We find that features are differentially canalized depending on their ontogenetic timing. We further deduce that development of the two hemispheres is to some degree independent. This independence has important implications for the evolution of cerebral hemispheres and their separate specialization. Asymmetry is a major feature of primate brains and is characteristic of both brain structure and function. PMID:26813679

Using deep learning to quantify the beauty of outdoor places

PubMed Central

2017-01-01

Beautiful outdoor locations are protected by governments and have recently been shown to be associated with better health. But what makes an outdoor space beautiful? Does a beautiful outdoor location differ from an outdoor location that is simply natural? Here, we explore whether ratings of over 200 000 images of Great Britain from the online game Scenic-Or-Not, combined with hundreds of image features extracted using the Places Convolutional Neural Network, might help us understand what beautiful outdoor spaces are composed of. We discover that, as well as natural features such as ‘Coast’, ‘Mountain’ and ‘Canal Natural’, man-made structures such as ‘Tower’, ‘Castle’ and ‘Viaduct’ lead to places being considered more scenic. Importantly, while scenes containing ‘Trees’ tend to rate highly, places containing more bland natural green features such as ‘Grass’ and ‘Athletic Fields’ are considered less scenic. We also find that a neural network can be trained to automatically identify scenic places, and that this network highlights both natural and built locations. Our findings demonstrate how online data combined with neural networks can provide a deeper understanding of what environments we might find beautiful and offer quantitative insights for policymakers charged with design and protection of our built and natural environments. PMID:28791142

CT findings of persistent pure ground glass opacity: can we predict the invasiveness?

PubMed

Liu, Li-Heng; Liu, Ming; Wei, Ran; Jin, Er-Hu; Liu, Yu-Hui; Xu, Liang; Li, Wen-Wu; Huang, Yong

2015-01-01

To investigate whether CT findings can predict the invasiveness of persistent cancerous pure ground glass opacity (pGGO) by correlating the CT imaging features of persistent pGGO with pathological changes. Ninety five patients with persistent pGGOs were included. Three radiologists evaluated the morphologic features of these pGGOs at high resolution CT (HRCT). Binary logistic regression was used to assess the association between CT findings and histopathological classification (pre-invasive and invasive groups). Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of diameters. A total of 105 pGGOs were identified. Between pre-invasive (atypical adenomatous hyperplasia, AAH, and adenocarcinoma in situ, AIS) and invasive group (minimally invasive adenocarcinoma, MIA and invasive lung adenocarcinomas, ILA), there were significant differences in diameter, spiculation and vessel dilatation (p<0.05). No difference was found in air-bronchogram, bubble- lucency, lobulated-margin, pleural indentation or vascular convergence (p>0.05). The optimal threshold value of the diameters to predict the invasiveness of pGGO was 12.50mm. HRCT features can predict the invasiveness of persistent pGGO. The pGGO with a diameter more than 12.50mm, presences of spiculation and vessel dilatation are important factors to differentiate invasive adenocarcinoma from pre-invasive cancerous lesions.

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

Total Lipopolysaccharide from the Human Gut Microbiome Silences Toll-Like Receptor Signaling.

PubMed

d'Hennezel, Eva; Abubucker, Sahar; Murphy, Leon O; Cullen, Thomas W

2017-01-01

Cohabitation of microbial communities with the host enables the formation of a symbiotic relationship that maintains homeostasis in the gut and beyond. One prevailing model suggests that this relationship relies on the capacity of host cells and tissues to remain tolerant to the strong immune stimulation generated by the microbiota such as the activation of Toll-like receptor 4 (TLR4) pathways by lipopolysaccharide (LPS). Indeed, gut microbial LPS is thought to be one of the most potent activators of innate immune signaling and an important mediator of the microbiome's influence on host physiology. In this study, we performed computational and experimental analyses of healthy human fecal samples to examine the TLR4 signaling capacity of the gut microbiota. These analyses revealed that an immunoinhibitory activity of LPS, conserved across the members of the order Bacteroidales and derived from an underacylated structural feature, silences TLR4 signaling for the entire consortium of organisms inhabiting the human gut. Comparative analysis of metagenomic data from the Human Microbiome Project and healthy-donor samples indicates that immune silencing via LPS is a microbe-intrinsic feature in all healthy adults. These findings challenge the current belief that robust TLR4 signaling is a feature of the microbiome and demonstrate that microbiome-derived LPS has the ability to facilitate host tolerance of gut microbes. These findings have broad implications for how we model host-microbe interactions and for our understanding of microbiome-linked disease. IMPORTANCE While the ability for humans to host a complex microbial ecosystem is an essential property of life, the mechanisms allowing for immune tolerance of such a large microbial load are not completely understood and are currently the focus of intense research. This study shows that an important proinflammatory pathway that is commonly triggered by pathogenic bacteria upon interaction with the host is, in fact, actively repressed by the bacteria of the gut microbiome, supporting the idea that beneficial microbes themselves contribute to the immune tolerance in support of homeostasis. These findings are important for two reasons. First, many currently assume that proinflammatory signaling by lipopolysaccharide is a fundamental feature of the gut flora. This assumption influences greatly how host-microbiome interactions are theoretically modeled but also how they are experimentally studied, by using robust TLR signaling conditions to simulate commensals. Second, elucidation of the mechanisms that support host-microbe tolerance is key to the development of therapeutics for both intestinal and systemic inflammatory disorders.

Authentic Mars Research in the High School

NASA Astrophysics Data System (ADS)

Kortekaas, Katie; Leach, Dani

2015-01-01

As a 11th and 12th grade Astrobiology class we were charged with developing a scientific research question about the potential for life on Mars. We narrowed our big picture question to, 'Where should the next Mars rover land in order to study the volcanic and water features to find evidence of past or present extremophiles on Mars?'After a lot of searching through images on JMARS (although not extensive due to high school time constraints) we narrowed our interest to three areas of Mars we thought could be good candidates to land a rover there to do further research. We know from extremophiles on Earth that microscopic life need water and energy. It seems reasonable that Mars would be no different. We developed a research question, 'Does Kasei Valles, Dzigai Vallis and Hecate Tholus have volcanic features (lava flow, fractures, volcanoes, cryovolcanoes) and water features (layers of ice, hematite, carbonate, chaos)?'This question is important and interesting because by having a deeper understanding of whether these places have evidence of volcanic and water features, we will be able to decide where the best place to land a future rover would be. Evidence of volcanic and water features are important to help determine where to land our rover because in those areas, temperatures could have been warm and the land could be wet. In these conditions, the probability of life is higher.We individually did research through JMARS (CTX, THEMIS) in order to establish if those three areas could contain certain land features (volcanic and water features) that could possibly lead to the discovery of extremophiles. We evaluated the images to determine if the three areas have evidence of those volcanic and water features.Although we are not experts at identifying features we believe we have evidence to say that all three areas are interesting, astrobiologically, but Dzigai Vallis shows the most number of types of volcanic and water features. More importantly, through this process we as a class began to understand true authentic science and how it is performed.Thank you to Arizona State University for the curriculum and guidance.

CT of abdominal tuberculosis

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

Epstein, B.M.; Mann, J.H.

1982-11-01

Intraabdominal tuberculosis (TB) presents with a wide variety of clinical and radiologic features. Besides the reported computed tomographic (CT) finding of high-density ascites in tuberculous peritonitis, this report describes additional CT features highly suggestive of abdominal tuberculosis in eight cases: (1) irregular soft-tissue densities in the omental area; (2) low-density masses surrounded by thick solid rims; (3) a disorganized appearance of soft-tissue densities, fluid, and bowel loops forming a poorly defined mass; (4) low-density lymph nodes with a multilocular appearance after intravenous contrast administration; and (5) possibly high-density ascites. The differential diagnosis of these features include lymphoma, various forms ofmore » peritonitis, peritoneal carcinomatosis, and peritoneal mesothelioma. It is important that the CT features of intraabdominal tuberculosis be recognized in order that laparotomy be avoided and less invasive procedures (e.g., laparoscopy, biopsy, or a trial of antituberculous therapy) be instituted.« less

A proto-architecture for innate directionally selective visual maps.

PubMed

Adams, Samantha V; Harris, Chris M

2014-01-01

Self-organizing artificial neural networks are a popular tool for studying visual system development, in particular the cortical feature maps present in real systems that represent properties such as ocular dominance (OD), orientation-selectivity (OR) and direction selectivity (DS). They are also potentially useful in artificial systems, for example robotics, where the ability to extract and learn features from the environment in an unsupervised way is important. In this computational study we explore a DS map that is already latent in a simple artificial network. This latent selectivity arises purely from the cortical architecture without any explicit coding for DS and prior to any self-organising process facilitated by spontaneous activity or training. We find DS maps with local patchy regions that exhibit features similar to maps derived experimentally and from previous modeling studies. We explore the consequences of changes to the afferent and lateral connectivity to establish the key features of this proto-architecture that support DS.

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking

PubMed Central

Peel, Hayden J.; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A.

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features. PMID:29725292

Late-onset Becker muscular dystrophy: Refining the clinical features and electrophysiological findings.

PubMed

Beltran Papsdorf, Tania; Howard, James F; Chahin, Nizar

2015-11-01

The aim of this study was to characterize a unique distribution of muscle involvement in sporadic Becker muscle dystrophy (BMD). Retrospective chart review, clinical examination, electrophysiological studies, cardiac testing, and genetic testing were performed in 5 patients. Predominant weakness and atrophy of biceps brachii, hip adduction, and quadriceps muscles was noted along with calf and extensor forearm hypertrophy. Finger flexor muscles were severely weak in 3 of 5 patients, a feature that could lead to a misdiagnosis of inclusion body myositis. Creatinine kinase was only mildly elevated in most patients. Electromyography was abnormal in all patients. Muscle biopsy in 1 patient demonstrated normal immunostaining for dystrophin. We found a unique and uniform distribution of muscle involvement in 5 sporadic cases of BMD. Recognizing these features is important for differentiating it from other myopathies that may have similar features and avoids unnecessary invasive procedures such as muscle biopsy. © 2015 Wiley Periodicals, Inc.

Deep Learning for ECG Classification

NASA Astrophysics Data System (ADS)

Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

2017-10-01

The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking.

PubMed

Peel, Hayden J; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features.

Dengue encephalitis

PubMed Central

Borawake, Kapil; Prayag, Parikshit; Wagh, Atul; Dole, Swati

2011-01-01

We report a case of dengue fever with features of encephalitis. The diagnosis of dengue was confirmed by the serum antibodies to dengue and the presence of a dengue antigen in the cerebrospinal fluid. This patient had characteristic magnetic resonance imaging brain findings, mainly involving the bilateral thalami, with hemorrhage. Dengue is not primarily a neurotropic virus and encephalopathy is a common finding in Dengue. Hence various other etiological possibilities were considered before concluding this as a case of Dengue encephalitis. This case explains the importance of considering the diagnosis of dengue encephalitis in appropriate situations. PMID:22013316

A virtual microscope for academic medical education: the pate project.

PubMed

Brochhausen, Christoph; Winther, Hinrich B; Hundt, Christian; Schmitt, Volker H; Schömer, Elmar; Kirkpatrick, C James

2015-05-11

Whole-slide imaging (WSI) has become more prominent and continues to gain in importance in student teaching. Applications with different scope have been developed. Many of these applications have either technical or design shortcomings. To design a survey to determine student expectations of WSI applications for teaching histological and pathological diagnosis. To develop a new WSI application based on the findings of the survey. A total of 216 students were questioned about their experiences and expectations of WSI applications, as well as favorable and undesired features. The survey included 14 multiple choice and two essay questions. Based on the survey, we developed a new WSI application called Pate utilizing open source technologies. The survey sample included 216 students-62.0% (134) women and 36.1% (78) men. Out of 216 students, 4 (1.9%) did not disclose their gender. The best-known preexisting WSI applications included Mainzer Histo Maps (199/216, 92.1%), Histoweb Tübingen (16/216, 7.4%), and Histonet Ulm (8/216, 3.7%). Desired features for the students were latitude in the slides (190/216, 88.0%), histological (191/216, 88.4%) and pathological (186/216, 86.1%) annotations, points of interest (181/216, 83.8%), background information (146/216, 67.6%), and auxiliary informational texts (113/216, 52.3%). By contrast, a discussion forum was far less important (9/216, 4.2%) for the students. The survey revealed that the students appreciate a rich feature set, including WSI functionality, points of interest, auxiliary informational texts, and annotations. The development of Pate was significantly influenced by the findings of the survey. Although Pate currently has some issues with the Zoomify file format, it could be shown that Web technologies are capable of providing a high-performance WSI experience, as well as a rich feature set.

Manipulations of the features of standard video lottery terminal (VLT) games: effects in pathological and non-pathological gamblers.

PubMed

Loba, P; Stewart, S H; Klein, R M; Blackburn, J R

2001-01-01

The present study was conducted to identify game parameters that would reduce the risk of abuse of video lottery terminals (VLTs) by pathological gamblers, while exerting minimal effects on the behavior of non-pathological gamblers. Three manipulations of standard VLT game features were explored. Participants were exposed to: a counter which displayed a running total of money spent; a VLT spinning reels game where participants could no longer "stop" the reels by touching the screen; and sensory feature manipulations. In control conditions, participants were exposed to standard settings for either a spinning reels or a video poker game. Dependent variables were self-ratings of reactions to each set of parameters. A set of 2(3) x 2 x 2 (game manipulation [experimental condition(s) vs. control condition] x game [spinning reels vs. video poker] x gambler status [pathological vs. non-pathological]) repeated measures ANOVAs were conducted on all dependent variables. The findings suggest that the sensory manipulations (i.e., fast speed/sound or slow speed/no sound manipulations) produced the most robust reaction differences. Before advocating harm reduction policies such as lowering sensory features of VLT games to reduce potential harm to pathological gamblers, it is important to replicate findings in a more naturalistic setting, such as a real bar.

Sustainability Literacy of Older People in Retirement Villages

PubMed Central

Xia, Bo; Zuo, Jian; Skitmore, Martin; Buys, Laurie; Hu, Xin

2014-01-01

With many developed countries experiencing the aging of the population, older people play a large role in contributing to environmental problems but also to environmental solutions. The purpose of this research is to understand the awareness and behavior of current older people living in retirement villages towards sustainability development. To achieve this, a sustainability literacy survey was conducted with 65 older residents of a private retirement village located 10 Km outside the Brisbane, Australia's central business district (CBD). Most of residents recognized the importance of environment protection and would like to lead a more environmentally friendly lifestyle. In addition, the majority were willing to pay higher prices for a living environment with sustainable features. The importance of positive social communications was emphasized with most residents having established good relationships with others in the village. The findings provide an important insight into consumer perspectives regarding the sustainable features that should and can be incorporated into the village planning and development. PMID:25587448

Ecosystem features determine seagrass community response to sea otter foraging

USGS Publications Warehouse

Hessing-Lewis, Margot; Rechsteiner, Erin U.; Hughes, Brent B.; Tinker, M. Tim; Monteith, Zachary L.; Olson, Angeleen M.; Henderson, Matthew Morgan; Watson, Jane C.

2017-01-01

Comparing sea otter recovery in California (CA) and British Columbia (BC) reveals key ecosystem properties that shape top-down effects in seagrass communities. We review potential ecosystem drivers of sea otter foraging in CA and BC seagrass beds, including the role of coastline complexity and environmental stress on sea otter effects. In BC, we find greater species richness across seagrass trophic assemblages. Furthermore, Cancer spp. crabs, an important link in the seagrass trophic cascade observed in CA, are less common. Additionally, the more recent reintroduction of sea otters, more complex coastline, and reduced environmental stress in BC seagrass habitats supports the hypotheses that sea otter foraging pressure is currently reduced there. In order to manage the ecosystem features that lead to regional differences in top predator effects in seagrass communities, we review our findings, their spatial and temporal constraints, and present a social-ecological framework for future research.

An enquiry into the process of categorization of pictures and words.

PubMed

Viswanathan, Madhubalan; Childers, Terry L

2003-02-01

This paper reports a series of experiments conducted to study the categorization of pictures and words. Whereas some studies reported in the past have found a picture advantage in categorization, other studies have yielded no differences between pictures and words. This paper used an experimental paradigm designed to overcome some methodological problems to examine picture-word categorization. The results of one experiment were consistent with an advantage for pictures in categorization. To identify the source of the picture advantage in categorization, two more experiments were conducted. Findings suggest that semantic relatedness may play an important role in the categorization of both pictures and words. We explain these findings by suggesting that pictures simultaneously access both their concept and visually salient features whereas words may initially access their concept and may subsequently activate features. Therefore, pictures have an advantage in categorization by offering multiple routes to semantic processing.

Low-Dimensional Feature Representation for Instrument Identification

NASA Astrophysics Data System (ADS)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

Optimization Of Feature Weight TheVoting Feature Intervals 5 Algorithm Using Partical Swarm Optimization Algorithm

NASA Astrophysics Data System (ADS)

Hayana Hasibuan, Eka; Mawengkang, Herman; Efendi, Syahril

2017-12-01

The use of Partical Swarm Optimization Algorithm in this research is to optimize the feature weights on the Voting Feature Interval 5 algorithm so that we can find the model of using PSO algorithm with VFI 5. Optimization of feature weight on Diabetes or Dyspesia data is considered important because it is very closely related to the livelihood of many people, so if there is any inaccuracy in determining the most dominant feature weight in the data will cause death. Increased accuracy by using PSO Algorithm ie fold 1 from 92.31% to 96.15% increase accuracy of 3.8%, accuracy of fold 2 on Algorithm VFI5 of 92.52% as well as generated on PSO Algorithm means accuracy fixed, then in fold 3 increase accuracy of 85.19% Increased to 96.29% Accuracy increased by 11%. The total accuracy of all three trials increased by 14%. In general the Partical Swarm Optimization algorithm has succeeded in increasing the accuracy to several fold, therefore it can be concluded the PSO algorithm is well used in optimizing the VFI5 Classification Algorithm.

In Two Minds?--Parental Attitudes toward Physical Punishment in the UK

ERIC Educational Resources Information Center

Bunting, Lisa; Webb, Mary Anne; Healy, Julie

2010-01-01

Since the Millennium, the use of physical punishment in the home has been a widely debated topic across the UK. Reliance on public opinion has been an important feature of this debate with a variety of UK surveys showing that many find physical punishment acceptable and do not support a complete ban on smacking. Drawing on the results from a…

Comparing experts and novices in Martian surface feature change detection and identification

NASA Astrophysics Data System (ADS)

Wardlaw, Jessica; Sprinks, James; Houghton, Robert; Muller, Jan-Peter; Sidiropoulos, Panagiotis; Bamford, Steven; Marsh, Stuart

2018-02-01

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided ;expert; data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who want to use crowd-sourcing for similar scientific purposes, particularly for the supervised training of computer algorithms, and inform the scope and design of future projects.

Gender Agreement Attraction in Russian: Production and Comprehension Evidence

PubMed Central

Slioussar, Natalia; Malko, Anton

2016-01-01

Agreement attraction errors (such as the number error in the example “The key to the cabinets are rusty”) have been the object of many studies in the last 20 years. So far, almost all production experiments and all comprehension experiments looked at binary features (primarily at number in Germanic, Romance, and some other languages, in several cases at gender in Romance languages). Among other things, it was noted that both in production and in comprehension, attraction effects are much stronger for some feature combinations than for the others: they can be observed in the sentences with singular heads and plural dependent nouns (e.g.,“The key to the cabinets…”), but not in the sentences with plural heads and singular dependent nouns (e.g., “The keys to the cabinet…”). Almost all proposed explanations of this asymmetry appeal to feature markedness, but existing findings do not allow teasing different approaches to markedness apart. We report the results of four experiments (one on production and three on comprehension) studying subject-verb gender agreement in Russian, a language with three genders. Firstly, we found attraction effects both in production and in comprehension, but, unlike in the case of number agreement, they were not parallel (in production, feminine gender triggered strongest effects, while neuter triggered weakest effects, while in comprehension, masculine triggered weakest effects). Secondly, in the comprehension experiments attraction was observed for all dependent noun genders, but only for a subset of head noun genders. This goes against the traditional assumption that the features of the dependent noun are crucial for attraction, showing the features of the head are more important. We demonstrate that this approach can be extended to previous findings on attraction and that there exists other evidence for it. In total, these findings let us reconsider the question which properties of features are crucial for agreement attraction in production and in comprehension. PMID:27867365

Gender Agreement Attraction in Russian: Production and Comprehension Evidence.

PubMed

Slioussar, Natalia; Malko, Anton

2016-01-01

Agreement attraction errors (such as the number error in the example "The key to the cabinets are rusty") have been the object of many studies in the last 20 years. So far, almost all production experiments and all comprehension experiments looked at binary features (primarily at number in Germanic, Romance, and some other languages, in several cases at gender in Romance languages). Among other things, it was noted that both in production and in comprehension, attraction effects are much stronger for some feature combinations than for the others: they can be observed in the sentences with singular heads and plural dependent nouns (e.g.,"The key to the cabinets…"), but not in the sentences with plural heads and singular dependent nouns (e.g., "The keys to the cabinet…"). Almost all proposed explanations of this asymmetry appeal to feature markedness, but existing findings do not allow teasing different approaches to markedness apart. We report the results of four experiments (one on production and three on comprehension) studying subject-verb gender agreement in Russian, a language with three genders. Firstly, we found attraction effects both in production and in comprehension, but, unlike in the case of number agreement, they were not parallel (in production, feminine gender triggered strongest effects, while neuter triggered weakest effects, while in comprehension, masculine triggered weakest effects). Secondly, in the comprehension experiments attraction was observed for all dependent noun genders, but only for a subset of head noun genders. This goes against the traditional assumption that the features of the dependent noun are crucial for attraction, showing the features of the head are more important. We demonstrate that this approach can be extended to previous findings on attraction and that there exists other evidence for it. In total, these findings let us reconsider the question which properties of features are crucial for agreement attraction in production and in comprehension.

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

Buenzli, Esther; Marley, Mark S.; Apai, Daniel

The re-emergence of the 0.99 μm FeH feature in brown dwarfs of early- to mid-T spectral type has been suggested as evidence for cloud disruption where flux from deep, hot regions below the Fe cloud deck can emerge. The same mechanism could account for color changes at the L/T transition and photometric variability. We present the first observations of spectroscopic variability of brown dwarfs covering the 0.99 μm FeH feature. We observed the spatially resolved very nearby brown dwarf binary WISE J104915.57–531906.1 (Luhman 16AB), a late-L and early-T dwarf, with Hubble Space Telescope/WFC3 in the G102 grism at 0.8–1.15 μm.more » We find significant variability at all wavelengths for both brown dwarfs, with peak-to-valley amplitudes of 9.3% for Luhman 16B and 4.5% for Luhman 16A. This represents the first unambiguous detection of variability in Luhman 16A. We estimate a rotational period between 4.5 and 5.5 hr, very similar to Luhman 16B. Variability in both components complicates the interpretation of spatially unresolved observations. The probability for finding large amplitude variability in any two brown dwarfs is less than 10%. Our finding may suggest that a common but yet unknown feature of the binary is important for the occurrence of variability. For both objects, the amplitude is nearly constant at all wavelengths except in the deep K i feature below 0.84 μm. No variations are seen across the 0.99 μm FeH feature. The observations lend strong further support to cloud height variations rather than holes in the silicate clouds, but cannot fully rule out holes in the iron clouds. Here, we re-evaluate the diagnostic potential of the FeH feature as a tracer of cloud patchiness.« less

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

Buenzli, Esther; Marley, Mark S.; Apai, Dániel

The re-emergence of the 0.99 μm FeH feature in brown dwarfs of early- to mid-T spectral type has been suggested as evidence for cloud disruption where flux from deep, hot regions below the Fe cloud deck can emerge. The same mechanism could account for color changes at the L/T transition and photometric variability. We present the first observations of spectroscopic variability of brown dwarfs covering the 0.99 μm FeH feature. We observed the spatially resolved very nearby brown dwarf binary WISE J104915.57–531906.1 (Luhman 16AB), a late-L and early-T dwarf, with Hubble Space Telescope/WFC3 in the G102 grism at 0.8–1.15 μm.more » We find significant variability at all wavelengths for both brown dwarfs, with peak-to-valley amplitudes of 9.3% for Luhman 16B and 4.5% for Luhman 16A. This represents the first unambiguous detection of variability in Luhman 16A. We estimate a rotational period between 4.5 and 5.5 hr, very similar to Luhman 16B. Variability in both components complicates the interpretation of spatially unresolved observations. The probability for finding large amplitude variability in any two brown dwarfs is less than 10%. Our finding may suggest that a common but yet unknown feature of the binary is important for the occurrence of variability. For both objects, the amplitude is nearly constant at all wavelengths except in the deep K i feature below 0.84 μm. No variations are seen across the 0.99 μm FeH feature. The observations lend strong further support to cloud height variations rather than holes in the silicate clouds, but cannot fully rule out holes in the iron clouds. We re-evaluate the diagnostic potential of the FeH feature as a tracer of cloud patchiness.« less

Genome-Wide Analysis of Transposon and Retroviral Insertions Reveals Preferential Integrations in Regions of DNA Flexibility.

PubMed

Vrljicak, Pavle; Tao, Shijie; Varshney, Gaurav K; Quach, Helen Ngoc Bao; Joshi, Adita; LaFave, Matthew C; Burgess, Shawn M; Sampath, Karuna

2016-04-07

DNA transposons and retroviruses are important transgenic tools for genome engineering. An important consideration affecting the choice of transgenic vector is their insertion site preferences. Previous large-scale analyses of Ds transposon integration sites in plants were done on the basis of reporter gene expression or germ-line transmission, making it difficult to discern vertebrate integration preferences. Here, we compare over 1300 Ds transposon integration sites in zebrafish with Tol2 transposon and retroviral integration sites. Genome-wide analysis shows that Ds integration sites in the presence or absence of marker selection are remarkably similar and distributed throughout the genome. No strict motif was found, but a preference for structural features in the target DNA associated with DNA flexibility (Twist, Tilt, Rise, Roll, Shift, and Slide) was observed. Remarkably, this feature is also found in transposon and retroviral integrations in maize and mouse cells. Our findings show that structural features influence the integration of heterologous DNA in genomes, and have implications for targeted genome engineering. Copyright © 2016 Vrljicak et al.

Dynamic Balance of Excitation and Inhibition in Human and Monkey Neocortex

NASA Astrophysics Data System (ADS)

Dehghani, Nima; Peyrache, Adrien; Telenczuk, Bartosz; Le van Quyen, Michel; Halgren, Eric; Cash, Sydney S.; Hatsopoulos, Nicholas G.; Destexhe, Alain

2016-03-01

Balance of excitation and inhibition is a fundamental feature of in vivo network activity and is important for its computations. However, its presence in the neocortex of higher mammals is not well established. We investigated the dynamics of excitation and inhibition using dense multielectrode recordings in humans and monkeys. We found that in all states of the wake-sleep cycle, excitatory and inhibitory ensembles are well balanced, and co-fluctuate with slight instantaneous deviations from perfect balance, mostly in slow-wave sleep. Remarkably, these correlated fluctuations are seen for many different temporal scales. The similarity of these computational features with a network model of self-generated balanced states suggests that such balanced activity is essentially generated by recurrent activity in the local network and is not due to external inputs. Finally, we find that this balance breaks down during seizures, where the temporal correlation of excitatory and inhibitory populations is disrupted. These results show that balanced activity is a feature of normal brain activity, and break down of the balance could be an important factor to define pathological states.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

What to Build for Middle-Agers to Come? Attractive and Necessary Functions of Exercise-Promotion Mobile Phone Apps: A Cross-Sectional Study.

PubMed

Liao, Gen-Yih; Chien, Yu-Tai; Chen, Yu-Jen; Hsiung, Hsiao-Fang; Chen, Hsiao-Jung; Hsieh, Meng-Hua; Wu, Wen-Jie

2017-05-25

Physical activity is important for middle-agers to maintain health both in middle age and in old age. Although thousands of exercise-promotion mobile phone apps are available for download, current literature offers little understanding regarding which design features can enhance middle-aged adults' quality perception toward exercise-promotion apps and which factor may influence such perception. The aims of this study were to understand (1) which design features of exercise-promotion apps can enhance quality perception of middle-agers, (2) whether their needs are matched by current functions offered in app stores, and (3) whether physical activity (PA) and mobile phone self-efficacy (MPSE) influence quality perception. A total of 105 middle-agers participated and filled out three scales: the International Physical Activity Questionnaire (IPAQ), the MPSE scale, and the need for design features questionnaire. The design features were developed based on the Coventry, Aberdeen, and London-Refined (CALO-RE) taxonomy. Following the Kano quality model, the need for design features questionnaire asked participants to classify design features into five categories: attractive, one-dimensional, must-be, indifferent, and reverse. The quality categorization was conducted based on a voting approach and the categorization results were compared with the findings of a prevalence study to realize whether needs match current availability. In total, 52 multinomial logistic regression models were analyzed to evaluate the effects of PA level and MPSE on quality perception of design features. The Kano analysis on the total sample revealed that visual demonstration of exercise instructions is the only attractive design feature, whereas the other 51 design features were perceived with indifference. Although examining quality perception by PA level, 21 features are recommended to low level, 6 features to medium level, but none to high-level PA. In contrast, high-level MPSE is recommended with 14 design features, medium level with 6 features, whereas low-level participants are recommended with 1 feature. The analysis suggests that the implementation of demanded features could be low, as the average prevalence of demanded design features is 20% (4.3/21). Surprisingly, social comparison and social support, most implemented features in current apps, were categorized into the indifferent category. The magnitude of effect is larger for MPSE because it effects quality perception of more design features than PA. Delving into the 52 regression models revealed that high MPSE more likely induces attractive or one- dimensional categorization, suggesting the importance of technological self-efficacy on eHealth care promotion. This study is the first to propose middle-agers' needs in relation to mobile phone exercise-promotion. In addition to the tailor-made recommendations, suggestions are offered to app designers to enhance the performance of persuasive features. An interesting finding on change of quality perception attributed to MPSE is proposed as future research. ©Gen-Yih Liao, Yu-Tai Chien, Yu-Jen Chen, Hsiao-Fang Hsiung, Hsiao-Jung Chen, Meng-Hua Hsieh, Wen-Jie Wu. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 25.05.2017.

A novel feature extraction approach for microarray data based on multi-algorithm fusion

PubMed Central

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions. PMID:25780277

A novel feature extraction approach for microarray data based on multi-algorithm fusion.

PubMed

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions.

CROI 2018: Advances in Basic Science Understanding of HIV.

PubMed

Stevenson, Mario

2018-05-01

The conference on Retroviruses and Opportunistic Infections represents the most important venue for the dissemination of research advances in HIV and AIDS. The 25th conference, held in Boston, featured presentations that provided insight into the mechanisms of HIV-1 spread in tissues as well as new information on mechanisms of HIV-1 persistence in individuals on effective antiretroviral treatment. The ability of the conference to convey research findings for a general audience is enhanced, to a large part, by preconference workshops. These workshops feature leading researchers who aim to present cutting edge research to a general audience. These sessions rank highly in terms of education and professional value.

A biomimetic algorithm for the improved detection of microarray features

NASA Astrophysics Data System (ADS)

Nicolau, Dan V., Jr.; Nicolau, Dan V.; Maini, Philip K.

2007-02-01

One the major difficulties of microarray technology relate to the processing of large and - importantly - error-loaded images of the dots on the chip surface. Whatever the source of these errors, those obtained in the first stage of data acquisition - segmentation - are passed down to the subsequent processes, with deleterious results. As it has been demonstrated recently that biological systems have evolved algorithms that are mathematically efficient, this contribution attempts to test an algorithm that mimics a bacterial-"patented" algorithm for the search of available space and nutrients to find, "zero-in" and eventually delimitate the features existent on the microarray surface.

A quick eye to anger: An investigation of a differential effect of facial features in detecting angry and happy expressions.

PubMed

Lo, L Y; Cheng, M Y

2017-06-01

Detection of angry and happy faces is generally found to be easier and faster than that of faces expressing emotions other than anger or happiness. This can be explained by the threatening account and the feature account. Few empirical studies have explored the interaction between these two accounts which are seemingly, but not necessarily, mutually exclusive. The present studies hypothesised that prominent facial features are important in facilitating the detection process of both angry and happy expressions; yet the detection of happy faces was more facilitated by the prominent features than angry faces. Results confirmed the hypotheses and indicated that participants reacted faster to the emotional expressions with prominent features (in Study 1) and the detection of happy faces was more facilitated by the prominent feature than angry faces (in Study 2). The findings are compatible with evolutionary speculation which suggests that the angry expression is an alarming signal of potential threats to survival. Compared to the angry faces, the happy faces need more salient physical features to obtain a similar level of processing efficiency. © 2015 International Union of Psychological Science.

Anxiety or agitation in mood disorder with mixed features: A review with a focus on validity as a dimensional criterion.

PubMed

Shim, In Hee; Bae, Dong Sik; Bahk, Won-Myong

2016-08-01

The diagnostic validity of mixed features, excluding anxiety or psychomotor agitation in mood disorders, has not yet been fully examined. PubMed and relevant English-language literature (regardless of year) were searched. Keywords were mixed or mixed state or mixed features or mixed episode and anxious or anxiety or agitation and bipolar disorder or depressive disorder or mood disorder or affective disorder. Most studies on anxiety or psychomotor agitation have included a significant correlation relevant to the "with mixed features" specifier, although it is common in both poles of mood episodes regardless of the predominant polarity. There is some confusion between the characteristic of classical mixed states and the definition of the mixed features specifier with the newly added anxious distress specifier in DSM-5, specifically, whether to include anxiety and agitation as significant characteristics. This change is of concern because a large proportion of patients with mixed features are now unspecified, and this may influence treatment planning and prognosis. The findings of our review suggest that anxiety and psychomotor agitation can be core symptoms in mood episodes with mixed features and important clinical clues for prediction of treatment effects and disease course.

Spinal bone marrow necrosis with vertebral compression fracture: differentiation of BMN from AVN.

PubMed

Nix, J S; Fitzgerald, R T; Samant, R S; Harrison, M; Angtuaco, E J

2014-09-01

Bone marrow necrosis (BMN) is a rare malignancy-associated hematologic disorder characterized by necrosis of myeloid and stromal marrow elements with preservation of cortical bone. Overlap between the imaging appearances of BMN and avascular necrosis (AVN) raises the potential for diagnostic confusion. We report a case of BMN presenting with a traumatic multi-level vertebral body collapse, and finding that may potentially confound distinction between the two entities. We discuss important pathophysiologic, clinical, and radiologic differences between BMN and AVN with emphasis on features important in the differential diagnosis.

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

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

Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models tomore » curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.« less

Realistic Free-Spins Features Increase Preference for Slot Machines.

PubMed

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

Efficient feature selection using a hybrid algorithm for the task of epileptic seizure detection

NASA Astrophysics Data System (ADS)

Lai, Kee Huong; Zainuddin, Zarita; Ong, Pauline

2014-07-01

Feature selection is a very important aspect in the field of machine learning. It entails the search of an optimal subset from a very large data set with high dimensional feature space. Apart from eliminating redundant features and reducing computational cost, a good selection of feature also leads to higher prediction and classification accuracy. In this paper, an efficient feature selection technique is introduced in the task of epileptic seizure detection. The raw data are electroencephalography (EEG) signals. Using discrete wavelet transform, the biomedical signals were decomposed into several sets of wavelet coefficients. To reduce the dimension of these wavelet coefficients, a feature selection method that combines the strength of both filter and wrapper methods is proposed. Principal component analysis (PCA) is used as part of the filter method. As for wrapper method, the evolutionary harmony search (HS) algorithm is employed. This metaheuristic method aims at finding the best discriminating set of features from the original data. The obtained features were then used as input for an automated classifier, namely wavelet neural networks (WNNs). The WNNs model was trained to perform a binary classification task, that is, to determine whether a given EEG signal was normal or epileptic. For comparison purposes, different sets of features were also used as input. Simulation results showed that the WNNs that used the features chosen by the hybrid algorithm achieved the highest overall classification accuracy.

Combining various types of classifiers and features extracted from magnetic resonance imaging data in schizophrenia recognition.

PubMed

Janousova, Eva; Schwarz, Daniel; Kasparek, Tomas

2015-06-30

We investigated a combination of three classification algorithms, namely the modified maximum uncertainty linear discriminant analysis (mMLDA), the centroid method, and the average linkage, with three types of features extracted from three-dimensional T1-weighted magnetic resonance (MR) brain images, specifically MR intensities, grey matter densities, and local deformations for distinguishing 49 first episode schizophrenia male patients from 49 healthy male subjects. The feature sets were reduced using intersubject principal component analysis before classification. By combining the classifiers, we were able to obtain slightly improved results when compared with single classifiers. The best classification performance (81.6% accuracy, 75.5% sensitivity, and 87.8% specificity) was significantly better than classification by chance. We also showed that classifiers based on features calculated using more computation-intensive image preprocessing perform better; mMLDA with classification boundary calculated as weighted mean discriminative scores of the groups had improved sensitivity but similar accuracy compared to the original MLDA; reducing a number of eigenvectors during data reduction did not always lead to higher classification accuracy, since noise as well as the signal important for classification were removed. Our findings provide important information for schizophrenia research and may improve accuracy of computer-aided diagnostics of neuropsychiatric diseases. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Development of tunable high pressure CO2 laser for lidar measurements of pollutants and wind velocities, January 1976 to December 1977

NASA Technical Reports Server (NTRS)

Javan, A.

1979-01-01

A tunable multiatmospheric pulsed CO2 laser with emphasis on experimental features and supporting theoretical analyses important to differential absorption lidar and Doppler lidar measurement of pollutants and wind velocities is reported. The energy deposition and the means to produce the uniform high density plasma in the multiatmospheric medium, through UV preionization of an organic seed gas is discussed. Design features of the pulsed CO2 laser are presented. The radiative processes which are operative and prevent the laser from breaking into oscillations in a large number of modes over its broad amplification bandwidth are described. The mode competition for the transient pulsed laser oscillation in a standing wave and traveling wave ring laser configuration is discussed and contrasted with the approach to steady state oscillations. The latter findings are important to transient injection locking for production of a highly stable pulsed CO2 laser output.

Assessment of Spectral-Domain Optical Coherence Tomography Findings in Three Cases of X-Linked Juvenile Retinoschisis in the Same Family.

PubMed

Doğuizi, Sibel; Şekeroğlu, Mehmet Ali; Çolak, Salih; Anayol, Mustafa Alpaslan; Yılmazbaş, Pelin

2017-10-01

X-linked juvenile retinoschisis (XLRS) is an X-linked hereditary retinal dystrophy characterized by splitting of the neurosensory retina. On fundus examination, the macula often has a spoke wheel appearance with foveal cystic lesions, and separation of the retinal layers is typical on spectral-domain optical coherence tomography (SD-OCT). Patients with XLRS can exhibit different clinical courses, stages, and SD-OCT findings, even among members of the same family. SD-OCT is an important imaging method that allows us to achieve more detailed information about XLRS. In this study, we report three patients in the same family who have different clinical features and SD-OCT findings.

Growth Restart/Recovery Lines involving the vertebral body: a rare, incidental finding and diagnostic challenge in two patients

PubMed Central

Sajko, Sandy; Stuber, Kent; Wessely, Michelle

2011-01-01

Objective To present the phenomenon of growth restart lines and create awareness of the possible differential diagnoses. Clinical Features Two case reports outlining the presentation of growth restart lines found in the vertebrae of trampolinists. Emphasis in each case is placed on correlating the patient history with radiographic findings. Intervention and Outcome In both cases a conservative chiropractic treatment plan was initiated once the differential diagnoses could be ruled out. Conclusion Although the range of etiologies of growth restart lines is extensive, these case reports illustrate the importance of a comprehensive case history when presented with the radiographic finding of growth restart lines. PMID:22131568

Prioritizing Scientific Data for Transmission

NASA Technical Reports Server (NTRS)

Castano, Rebecca; Anderson, Robert; Estlin, Tara; DeCoste, Dennis; Gaines, Daniel; Mazzoni, Dominic; Fisher, Forest; Judd, Michele

2004-01-01

A software system has been developed for prioritizing newly acquired geological data onboard a planetary rover. The system has been designed to enable efficient use of limited communication resources by transmitting the data likely to have the most scientific value. This software operates onboard a rover by analyzing collected data, identifying potential scientific targets, and then using that information to prioritize data for transmission to Earth. Currently, the system is focused on the analysis of acquired images, although the general techniques are applicable to a wide range of data modalities. Image prioritization is performed using two main steps. In the first step, the software detects features of interest from each image. In its current application, the system is focused on visual properties of rocks. Thus, rocks are located in each image and rock properties, such as shape, texture, and albedo, are extracted from the identified rocks. In the second step, the features extracted from a group of images are used to prioritize the images using three different methods: (1) identification of key target signature (finding specific rock features the scientist has identified as important), (2) novelty detection (finding rocks we haven t seen before), and (3) representative rock sampling (finding the most average sample of each rock type). These methods use techniques such as K-means unsupervised clustering and a discrimination-based kernel classifier to rank images based on their interest level.

Evolutionary and developmental implications of asymmetric brain folding in a large primate pedigree.

PubMed

Atkinson, Elizabeth G; Rogers, Jeffrey; Cheverud, James M

2016-03-01

Bilateral symmetry is a fundamental property of the vertebrate central nervous system. Local deviations from symmetry provide various types of information about the development, evolution, and function of elements within the CNS, especially the cerebral hemispheres. Here, we quantify the pattern and extent of asymmetry in cortical folding within the cerebrum of Papio baboons and assess the evolutionary and developmental implications of the findings. Analyses of directional asymmetry show a population-level trend in length measurements indicating that baboons are genetically predisposed to be asymmetrical, with the right side longer than the left in the anterior cerebrum while the left side is longer than the right posteriorly. We also find a corresponding bias to display a right frontal petalia (overgrowth of the anterior pole of the cerebral cortex on the right side). By quantifying fluctuating asymmetry, we assess canalization of brain features and the susceptibility of the baboon brain to developmental perturbations. We find that features are differentially canalized depending on their ontogenetic timing. We further deduce that development of the two hemispheres is to some degree independent. This independence has important implications for the evolution of cerebral hemispheres and their separate specialization. Asymmetry is a major feature of primate brains and is characteristic of both brain structure and function. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

The Influence of Changes in Size and Proportion of Selected Facial Features (Eyes, Nose, Mouth) on Assessment of Similarity between Female Faces.

PubMed

Lewandowski, Zdzisław

2015-09-01

The project aimed at finding the answers to the following two questions: to what extent does a change in size, height or width of the selected facial features influence the assessment of likeness between an original female composite portrait and a modified one? And how does the sex of the person who judges the images have an impact on the perception of likeness of facial features? The first stage of the project consisted of creating the image of the averaged female faces. Then the basic facial features like eyes, nose and mouth were cut out of the averaged face and each of these features was transformed in three ways: its size was changed by reduction or enlargement, its height was modified through reduction or enlargement of the above-mentioned features and its width was altered through widening or narrowing. In each out of six feature alternation methods, intensity of modification reached up to 20% of the original size with changes every 2%. The features altered in such a way were again stuck onto the original faces and retouched. The third stage consisted of the assessment, performed by the judges of both sexes, of the extent of likeness between the averaged composite portrait (without any changes) and the modified portraits. The results indicate that there are significant differences in the assessment of likeness of the portraits with some features modified to the original ones. The images with changes in the size and height of the nose received the lowest scores on the likeness scale, which indicates that these changes were perceived by the subjects as the most important. The photos with changes in the height of lip vermillion thickness (the lip height), lip width and the height and width of eye slit, in turn, received high scores of likeness, in spite of big changes, which signifies that these modifications were perceived as less important when compared to the other features investigated.

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.

Association Rule Based Feature Extraction for Character Recognition

NASA Astrophysics Data System (ADS)

Dua, Sumeet; Singh, Harpreet

Association rules that represent isomorphisms among data have gained importance in exploratory data analysis because they can find inherent, implicit, and interesting relationships among data. They are also commonly used in data mining to extract the conditions among attribute values that occur together frequently in a dataset [1]. These rules have wide range of applications, namely in the financial and retail sectors of marketing, sales, and medicine.

Allelic and Phenotypic Heterogeneity in ABCA4 mutations

PubMed Central

Burke, Tomas R; Tsang, Stephen H

2011-01-01

Since the discovery of the ABCA4 gene as the cause of autosomal recessive Stargardt disease/fundus flavimaculatus much has been written of the phenotypic variability in ABCA4 retinopathy. In this review the authors discuss the findings seen on examination and the disease features detected using various clinical tests. Important differential diagnoses are presented and unusual presentations of ABCA4 disease highlighted. PMID:21510770

The Trouble with Boys: Social Influences and the Gender Gap in Disruptive Behavior. NBER Working Paper No. 17541

ERIC Educational Resources Information Center

Bertrand, Marianne; Pan, Jessica

2011-01-01

This paper explores the importance of the home and school environments in explaining the gender gap in disruptive behavior. We document large differences in the gender gap across key features of the home environment--boys do especially poorly in broken families. In contrast, we find little impact of the early school environment on non-cognitive…

Feature Selection and Classifier Development for Radio Frequency Device Identification

DTIC Science & Technology

2015-12-01

adds important background knowledge for this research . 41 Four leading RF-based device identification methods have been proposed: Radio...appropriate level of dimensionality. Both qualitative and quantitative DRA dimensionality assessment methods are possible. Prior RF-DNA DRA research , e.g...Employing experimental designs to find optimal algorithm settings has been seen in hyperspectral anomaly detection research , c.f. [513–520], but not

Cloud structure of the nearest brown dwarfs. II: High-amplitude variability for Luhman 16 A and B in and out of the 0.99 μm FeH feature

DOE PAGES

Buenzli, Esther; Marley, Mark S.; Apai, Daniel; ...

2015-10-20

The re-emergence of the 0.99 μm FeH feature in brown dwarfs of early- to mid-T spectral type has been suggested as evidence for cloud disruption where flux from deep, hot regions below the Fe cloud deck can emerge. The same mechanism could account for color changes at the L/T transition and photometric variability. We present the first observations of spectroscopic variability of brown dwarfs covering the 0.99 μm FeH feature. We observed the spatially resolved very nearby brown dwarf binary WISE J104915.57–531906.1 (Luhman 16AB), a late-L and early-T dwarf, with Hubble Space Telescope/WFC3 in the G102 grism at 0.8–1.15 μm.more » We find significant variability at all wavelengths for both brown dwarfs, with peak-to-valley amplitudes of 9.3% for Luhman 16B and 4.5% for Luhman 16A. This represents the first unambiguous detection of variability in Luhman 16A. We estimate a rotational period between 4.5 and 5.5 hr, very similar to Luhman 16B. Variability in both components complicates the interpretation of spatially unresolved observations. The probability for finding large amplitude variability in any two brown dwarfs is less than 10%. Our finding may suggest that a common but yet unknown feature of the binary is important for the occurrence of variability. For both objects, the amplitude is nearly constant at all wavelengths except in the deep K i feature below 0.84 μm. No variations are seen across the 0.99 μm FeH feature. The observations lend strong further support to cloud height variations rather than holes in the silicate clouds, but cannot fully rule out holes in the iron clouds. Here, we re-evaluate the diagnostic potential of the FeH feature as a tracer of cloud patchiness.« less

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Feature-based attention elicits surround suppression in feature space.

PubMed

Störmer, Viola S; Alvarez, George A

2014-09-08

It is known that focusing attention on a particular feature (e.g., the color red) facilitates the processing of all objects in the visual field containing that feature [1-7]. Here, we show that such feature-based attention not only facilitates processing but also actively inhibits processing of similar, but not identical, features globally across the visual field. We combined behavior and electrophysiological recordings of frequency-tagged potentials in human observers to measure this inhibitory surround in feature space. We found that sensory signals of an attended color (e.g., red) were enhanced, whereas sensory signals of colors similar to the target color (e.g., orange) were suppressed relative to colors more distinct from the target color (e.g., yellow). Importantly, this inhibitory effect spreads globally across the visual field, thus operating independently of location. These findings suggest that feature-based attention comprises an excitatory peak surrounded by a narrow inhibitory zone in color space to attenuate the most distracting and potentially confusable stimuli during visual perception. This selection profile is akin to what has been reported for location-based attention [8-10] and thus suggests that such center-surround mechanisms are an overarching principle of attention across different domains in the human brain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Geospatial Analytics in Retail Site Selection and Sales Prediction.

PubMed

Ting, Choo-Yee; Ho, Chiung Ching; Yee, Hui Jia; Matsah, Wan Razali

2018-03-01

Studies have shown that certain features from geography, demography, trade area, and environment can play a vital role in retail site selection, largely due to the impact they asserted on retail performance. Although the relevant features could be elicited by domain experts, determining the optimal feature set can be intractable and labor-intensive exercise. The challenges center around (1) how to determine features that are important to a particular retail business and (2) how to estimate retail sales performance given a new location? The challenges become apparent when the features vary across time. In this light, this study proposed a nonintervening approach by employing feature selection algorithms and subsequently sales prediction through similarity-based methods. The results of prediction were validated by domain experts. In this study, data sets from different sources were transformed and aggregated before an analytics data set that is ready for analysis purpose could be obtained. The data sets included data about feature location, population count, property type, education status, and monthly sales from 96 branches of a telecommunication company in Malaysia. The finding suggested that (1) optimal retail performance can only be achieved through fulfillment of specific location features together with the surrounding trade area characteristics and (2) similarity-based method can provide solution to retail sales prediction.

Ocular Features in 16 Brazilian Patients with Williams-Beuren Syndrome.

PubMed

Viana, Melissa Machado; Frasson, Maria; Galvão, Henrique; Leão, Letícia Lima; Stofanko, Martin; Gonçalves-Dornelas, Higgor; da Silva Cunha, Pricila; Burle de Aguiar, Marcos José

2015-01-01

Williams-Beuren Syndrome (WBS) is a multisystem disorder caused by the deletion of contiguous genes on chromosome 7q11.23. Ophthalmologic abnormalities and deficits in visual motor integration are important features of WBS. Here we describe our experience with Brazilian WBS patients and their ophthalmologic features. Sixteen patients with confirmed WBS went through thorough ophthalmologic examination. The most frequent ocular findings in our group of patients were stellate iris pattern (81.2%), hyperopic astigmatism (50%), hyperopia (37.5%), tortuosity of retinal vessel (37.5%) and strabismus (18.7%). This is the second report of ophthalmologic abnormalities in a group of Brazilian individuals with WBS. It is extremely valuable that specific populations are studied so that clinical diagnosis can be refined and management of patients can be driven to the most common presentations of the disease.

Distinctiveness of management in a university psychiatric hospital as a public health institution.

PubMed

Koncina, Miroslav

2008-06-01

The distinctiveness of management of a university psychiatric hospital which has the status of a public health institution is manifested in the following ways: * Distinctive features and characteristics of managing service provider organizations compared to those whose operational results involve tangible products; * Distinctive features of management which originate from its role as a regional hospital and a tertiary research and educational institution in the field of psychiatry, with special importance for the Republic of Slovenia as a whole; * Distinctive features of management that are defined by the social and legal framework of operation of public health institutions and their special social mission. This paper therefore discusses the specific theoretical and practical findings regarding management of service provider organizations from the viewpoint of their social mission and significance, as well as their legal organization, internal structure and values.

A change detection method for remote sensing image based on LBP and SURF feature

NASA Astrophysics Data System (ADS)

Hu, Lei; Yang, Hao; Li, Jin; Zhang, Yun

2018-04-01

Finding the change in multi-temporal remote sensing image is important in many the image application. Because of the infection of climate and illumination, the texture of the ground object is more stable relative to the gray in high-resolution remote sensing image. And the texture features of Local Binary Patterns (LBP) and Speeded Up Robust Features (SURF) are outstanding in extracting speed and illumination invariance. A method of change detection for matched remote sensing image pair is present, which compares the similarity by LBP and SURF to detect the change and unchanged of the block after blocking the image. And region growing is adopted to process the block edge zone. The experiment results show that the method can endure some illumination change and slight texture change of the ground object.

Administrative records and surveys as basis for statistics on international labour migration.

PubMed

Hoffmann, E

1997-08-01

"This paper discusses possible sources for statistics to be used for describing and analysing the number, structure, situation, development and impact of migrant workers. The discussion is focused on key, intrinsic features of the different sources, important for the understanding of their strengths and weaknesses, and draws the reader's attention to features which may tend to undermine the quality of statistics produced as well as ways in which the impact of such features can be evaluated and, if possible, reduced.... The paper is organized around three key groups of migrant workers: (a) Persons who are arriving in a country to work there, i.e. the inflow of foreign workers; (b) Persons who are leaving their country to find work abroad, i.e. the outflow of migrant workers; [and] (c) Stock of foreign workers in the country." (EXCERPT)

Matching CCD images to a stellar catalog using locality-sensitive hashing

NASA Astrophysics Data System (ADS)

Liu, Bo; Yu, Jia-Zong; Peng, Qing-Yu

2018-02-01

The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most widely used methods in star catalog matching. When more subgraph features are provided, the CCD images are recognized better. However, when the navigation feature database is large, the method requires more time to match the observing model. To solve this problem, this study investigates further and improves subgraph isomorphic matching algorithms. We present an algorithm based on a locality-sensitive hashing technique, which allocates quadrilateral models in the navigation feature database into different hash buckets and reduces the search range to the bucket in which the observed quadrilateral model is located. Experimental results indicate the effectivity of our method.

Feature extraction and classification algorithms for high dimensional data

NASA Technical Reports Server (NTRS)

Lee, Chulhee; Landgrebe, David

1993-01-01

Feature extraction and classification algorithms for high dimensional data are investigated. Developments with regard to sensors for Earth observation are moving in the direction of providing much higher dimensional multispectral imagery than is now possible. In analyzing such high dimensional data, processing time becomes an important factor. With large increases in dimensionality and the number of classes, processing time will increase significantly. To address this problem, a multistage classification scheme is proposed which reduces the processing time substantially by eliminating unlikely classes from further consideration at each stage. Several truncation criteria are developed and the relationship between thresholds and the error caused by the truncation is investigated. Next an approach to feature extraction for classification is proposed based directly on the decision boundaries. It is shown that all the features needed for classification can be extracted from decision boundaries. A characteristic of the proposed method arises by noting that only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is introduced. The proposed feature extraction algorithm has several desirable properties: it predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal means or equal covariances as some previous algorithms do. In addition, the decision boundary feature extraction algorithm can be used both for parametric and non-parametric classifiers. Finally, some problems encountered in analyzing high dimensional data are studied and possible solutions are proposed. First, the increased importance of the second order statistics in analyzing high dimensional data is recognized. By investigating the characteristics of high dimensional data, the reason why the second order statistics must be taken into account in high dimensional data is suggested. Recognizing the importance of the second order statistics, there is a need to represent the second order statistics. A method to visualize statistics using a color code is proposed. By representing statistics using color coding, one can easily extract and compare the first and the second statistics.

Health Care Exceptionalism? Performance and Allocation in the US Health Care Sector

PubMed Central

Chandra, Amitabh; Finkelstein, Amy; Sacarny, Adam; Syverson, Chad

2016-01-01

The conventional wisdom for the healthcare sector is that idiosyncratic features leave little scope for market forces to allocate consumers to higher performance producers. However, we find robust evidence - across several different conditions and performance measures - that higher quality hospitals have higher market shares and grow more over time. The relationship between performance and allocation is stronger among patients who have greater scope for hospital choice, suggesting that patient demand plays an important role in allocation. Our findings suggest that healthcare may have more in common with “traditional” sectors subject to market forces than often assumed. PMID:27784907

Baicalein Reduces Airway Injury in Allergen and IL-13 Induced Airway Inflammation

PubMed Central

Mabalirajan, Ulaganathan; Ahmad, Tanveer; Rehman, Rakhshinda; Leishangthem, Geeta Devi; Dinda, Amit Kumar; Agrawal, Anurag; Ghosh, Balaram; Sharma, Surendra Kumar

2013-01-01

Background Baicalein, a bioflavone present in the dry roots of Scutellaria baicalensis Georgi, is known to reduce eotaxin production in human fibroblasts. However, there are no reports of its anti-asthma activity or its effect on airway injury. Methodology/Principal Findings In a standard experimental asthma model, male Balb/c mice that were sensitized with ovalbumin (OVA), treated with baicalein (10 mg/kg, ip) or a vehicle control, either during (preventive use) or after OVA challenge (therapeutic use). In an alternate model, baicalein was administered to male Balb/c mice which were given either IL-4 or IL-13 intranasally. Features of asthma were determined by estimating airway hyperresponsiveness (AHR), histopathological changes and biochemical assays of key inflammatory molecules. Airway injury was determined with apoptotic assays, transmission electron microscopy and assessing key mitochondrial functions. Baicalein treatment reduced AHR and inflammation in both experimental models. TGF-β1, sub-epithelial fibrosis and goblet cell metaplasia, were also reduced. Furthermore, baicalein treatment significantly reduced 12/15-LOX activity, features of mitochondrial dysfunctions, and apoptosis of bronchial epithelia. Conclusion/Significance Our findings demonstrate that baicalein can attenuate important features of asthma, possibly through the reduction of airway injury and restoration of mitochondrial function. PMID:23646158

An interactive portal to empower cancer survivors: a qualitative study on user expectations.

PubMed

Kuijpers, Wilma; Groen, Wim G; Loos, Romy; Oldenburg, Hester S A; Wouters, Michel W J M; Aaronson, Neil K; van Harten, Wim H

2015-09-01

Portals are increasingly used to improve patient empowerment, but are still uncommon in oncology. In this study, we explored cancer survivors' and health professionals' expectations of possible features of an interactive portal. We conducted three focus groups with breast cancer survivors (n = 21), two with lung cancer survivors (n = 14), and four with health professionals (n = 31). Drafts of possible features of an interactive portal were presented as static screenshots: survivorship care plan (SCP), access to electronic medical record (EMR), appointments, e-consultation, online patient community, patient reported outcomes (PROs) plus feedback, telemonitoring service, online rehabilitation program, and online psychosocial self-management program. This presentation was followed by an open discussion. Focus groups were audiotaped, transcribed verbatim, and data were analyzed using content analysis. Important themes included fulfillment of information needs, communication, motivation, quality of feedback, and supervision. Cancer survivors were primarily interested in features that could fulfill their information needs: SCP, access to their EMR, and an overview of appointments. Health professionals considered PROs and telemonitoring as most useful features, as these provide relevant information about survivors' health status. We recommend to minimally include these features in an interactive portal for cancer survivors. This is the first study that evaluated the expectations of cancer survivors and health professionals concerning an interactive portal. Both groups were positive about the introduction of such a portal, although their preferences for the various features differed. These findings reflect their unique perspective and emphasize the importance of involving multiple stakeholders in the actual design process.

Who is talking in backward crosstalk? Disentangling response- from goal-conflict in dual-task performance.

PubMed

Janczyk, Markus; Pfister, Roland; Hommel, Bernhard; Kunde, Wilfried

2014-07-01

Responses in the second of two subsequently performed tasks can speed up compatible responses in the temporally preceding first task. Such backward crosstalk effects (BCEs) represent a challenge to the assumption of serial processing in stage models of human information processing, because they indicate that certain features of the second response have to be represented before the first response is emitted. Which of these features are actually relevant for BCEs is an open question, even though identifying these features is important for understanding the nature of parallel and serial response selection processes in dual-task performance. Motivated by effect-based models of action control, we show in three experiments that the BCE to a considerable degree reflects features of intended action effects, although features of the response proper (or response-associated kinesthetic feedback) also seem to play a role. These findings suggest that the codes of action effects (or action goals) can become activated simultaneously rather than serially, thereby creating BCEs. Copyright © 2014 Elsevier B.V. All rights reserved.

The Role of Book Features in Young Children's Transfer of Information from Picture Books to Real-World Contexts

PubMed Central

Strouse, Gabrielle A.; Nyhout, Angela; Ganea, Patricia A.

2018-01-01

Picture books are an important source of new language, concepts, and lessons for young children. A large body of research has documented the nature of parent-child interactions during shared book reading. A new body of research has begun to investigate the features of picture books that support children's learning and transfer of that information to the real world. In this paper, we discuss how children's symbolic development, analogical reasoning, and reasoning about fantasy may constrain their ability to take away content information from picture books. We then review the nascent body of findings that has focused on the impact of picture book features on children's learning and transfer of words and letters, science concepts, problem solutions, and morals from picture books. In each domain of learning we discuss how children's development may interact with book features to impact their learning. We conclude that children's ability to learn and transfer content from picture books can be disrupted by some book features and research should directly examine the interaction between children's developing abilities and book characteristics on children's learning. PMID:29467690

The Role of Book Features in Young Children's Transfer of Information from Picture Books to Real-World Contexts.

PubMed

Strouse, Gabrielle A; Nyhout, Angela; Ganea, Patricia A

2018-01-01

Picture books are an important source of new language, concepts, and lessons for young children. A large body of research has documented the nature of parent-child interactions during shared book reading. A new body of research has begun to investigate the features of picture books that support children's learning and transfer of that information to the real world. In this paper, we discuss how children's symbolic development, analogical reasoning, and reasoning about fantasy may constrain their ability to take away content information from picture books. We then review the nascent body of findings that has focused on the impact of picture book features on children's learning and transfer of words and letters, science concepts, problem solutions, and morals from picture books. In each domain of learning we discuss how children's development may interact with book features to impact their learning. We conclude that children's ability to learn and transfer content from picture books can be disrupted by some book features and research should directly examine the interaction between children's developing abilities and book characteristics on children's learning.

Comparison of Endoscopic and Histological Findings between Typical and Atypical Celiac Disease in Children.

PubMed

Semwal, Pooja; Gupta, Raj Kumar; Sharma, Rahul; Garg, Kapil

2018-04-01

Celiac disease is a common non-communicable disease with varied presentations. Purpose of this study was to find the duodeno-endoscopic features in celiac disease and to compare duodeno-endoscopic and histological findings between typical and atypical celiac disease in children. Hospital based observational study was conducted at Sir Padampat Mother and Child Health Institute, Jaipur from June 2015 to May 2016. Patients were selected and divided in two groups- typical and atypical celiac disease based upon the presenting symptoms. Upper gastrointestinal endoscopy and duodenal biopsy was performed for serology positive patients. Results were analysed using appropriate statistical test of significance. Out of 101 enrolled patients, 47.5% were male. Age ranged from 1 to 18 years. Study showed that 54.5% were typical and 45.5% were atypical. Patients presenting with atypical symptoms were predominantly of older age group. On endoscopy, scalloping, mosaic pattern, reduced fold height and absent fold height; and in histology, advanced Marsh stage were significantly higher in the typical group. Awareness of atypical presentations as well as duodeno-endoscopic features may have considerable practical importance for the diagnosis of celiac disease in children. Scalloping, mosaic pattern, reduced fold height and nodularity are main endoscopic markers of celiac disease in children. Endoscopic markers of duodenal mucosa may be important in early diagnosis of celiac disease, in children subjected to endoscopy for atypical presentations or indication other than suspected celiac disease.

Rigorous assessment and integration of the sequence and structure based features to predict hot spots

PubMed Central

2011-01-01

Background Systematic mutagenesis studies have shown that only a few interface residues termed hot spots contribute significantly to the binding free energy of protein-protein interactions. Therefore, hot spots prediction becomes increasingly important for well understanding the essence of proteins interactions and helping narrow down the search space for drug design. Currently many computational methods have been developed by proposing different features. However comparative assessment of these features and furthermore effective and accurate methods are still in pressing need. Results In this study, we first comprehensively collect the features to discriminate hot spots and non-hot spots and analyze their distributions. We find that hot spots have lower relASA and larger relative change in ASA, suggesting hot spots tend to be protected from bulk solvent. In addition, hot spots have more contacts including hydrogen bonds, salt bridges, and atomic contacts, which favor complexes formation. Interestingly, we find that conservation score and sequence entropy are not significantly different between hot spots and non-hot spots in Ab+ dataset (all complexes). While in Ab- dataset (antigen-antibody complexes are excluded), there are significant differences in two features between hot pots and non-hot spots. Secondly, we explore the predictive ability for each feature and the combinations of features by support vector machines (SVMs). The results indicate that sequence-based feature outperforms other combinations of features with reasonable accuracy, with a precision of 0.69, a recall of 0.68, an F1 score of 0.68, and an AUC of 0.68 on independent test set. Compared with other machine learning methods and two energy-based approaches, our approach achieves the best performance. Moreover, we demonstrate the applicability of our method to predict hot spots of two protein complexes. Conclusion Experimental results show that support vector machine classifiers are quite effective in predicting hot spots based on sequence features. Hot spots cannot be fully predicted through simple analysis based on physicochemical characteristics, but there is reason to believe that integration of features and machine learning methods can remarkably improve the predictive performance for hot spots. PMID:21798070

Histological features of localized scleroderma 'en coup de sabre': a study of 16 cases.

PubMed

Taniguchi, T; Asano, Y; Tamaki, Z; Akamata, K; Aozasa, N; Noda, S; Takahashi, T; Ichimura, Y; Toyama, T; Sugita, M; Sumida, H; Kuwano, Y; Miyazaki, M; Yanaba, K; Sato, S

2014-12-01

Early lesions of localized scleroderma are histologically characterized by perivascular lymphocytic infiltrate in the reticular dermis and swollen endothelial cells. However, there have been few information regarding histological features other than these findings in localized scleroderma. Since en coup de sabre (ECDS) is a certain subset of localized scleroderma with a relatively uniform clinical manifestation, we focused on this disease subset and evaluated its histopathological features. A total of 16 patients with ECDS were retrospectively evaluated on the basis of clinical and histological findings. Regardless of clinical manifestations, vacuolar degeneration was found in all of the ECDS patients. Importantly, keratinocyte necroses were restricted to early and active ECDS lesions. In early ECDS patients (disease duration of <3 years), moderate to severe perivascular and/or periappendageal lymphocytic infiltrate and vacuolar changes in follicular epithelium were more prominent, whereas epidermal atrophy was less frequently observed, than in late ECDS patients (disease duration of ≥6 years). Vacuolar degeneration at the dermoepidermal junction is a common histological feature in ECDS and perivascular and/or periappendageal lymphocytic infiltrate and vacuolar degeneration of follicular epithelium are characteristic especially in early ECDS, further supporting a canonical idea that the elimination of mutated epidermal cells by immune surveillance contributes to tissue damage and resultant fibrosis in localized scleroderma. © 2013 European Academy of Dermatology and Venereology.

Clinical Correlations With Lewy Body Pathology in LRRK2-Related Parkinson Disease

PubMed Central

Kalia, Lorraine V.; Lang, Anthony E.; Hazrati, Lili-Naz; Fujioka, Shinsuke; Wszolek, Zbigniew K.; Dickson, Dennis W.; Ross, Owen A.; Van Deerlin, Vivianna M.; Trojanowski, John Q.; Hurtig, Howard I.; Alcalay, Roy N.; Marder, Karen S.; Clark, Lorraine N.; Gaig, Carles; Tolosa, Eduardo; Ruiz-Martínez, Javier; Marti-Masso, Jose F.; Ferrer, Isidre; de Munain, Adolfo López; Goldman, Samuel M.; Schüle, Birgitt; Langston, J. William; Aasly, Jan O.; Giordana, Maria T.; Bonifati, Vincenzo; Puschmann, Andreas; Canesi, Margherita; Pezzoli, Gianni; De Paula, Andre Maues; Hasegawa, Kazuko; Duyckaerts, Charles; Brice, Alexis; Stoessl, A. Jon; Marras, Connie

2015-01-01

IMPORTANCE Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common cause of genetic Parkinson disease (PD) known to date. The clinical features of manifesting LRRK2 mutation carriers are generally indistinguishable from those of patients with sporadic PD. However, some PD cases associated with LRRK2 mutations lack Lewy bodies (LBs), a neuropathological hallmark of PD. We investigated whether the presence or absence of LBs correlates with different clinical features in LRRK2-related PD. OBSERVATIONS We describe genetic, clinical, and neuropathological findings of 37 cases of LRRK2-related PD including 33 published and 4 unpublished cases through October 2013. Among the different mutations, the LRRK2 p.G2019S mutation was most frequently associated with LB pathology. Nonmotor features of cognitive impairment/dementia, anxiety, and orthostatic hypotension were correlated with the presence of LBs. In contrast, a primarily motor phenotype was associated with a lack of LBs. CONCLUSIONS AND RELEVANCE To our knowledge, this is the first report of clinicopathological correlations in a series of LRRK2-related PD cases. Findings from this selected group of patients with PD demonstrated that parkinsonian motor features can occur in the absence of LBs. However, LB pathology in LRRK2-related PD may be a marker for a broader parkinsonian symptom complex including cognitive impairment. PMID:25401511

An 'inflammatory' variant of solar purpura: a simulant of leukocytoclastic vasculitis and neutrophilic dermatoses.

PubMed

Wood, Benjamin A; LeBoit, Philip E

2013-08-01

To study the clinical and pathological features of cases of apparent solar purpura, with attention to the recently described phenomenon of inflammatory changes within otherwise typical lesions. We studied 95 cases diagnosed as solar purpura and identified 10 cases (10.5%) in which significant neutrophilic inflammation was present, potentially simulating a leukocytoclastic vasculitis or neutrophilic dermatosis. An additional three cases were identified in subsequent routine practice. The clinical features, including follow-up for subsequent development of vasculitis and histological features were studied. In all cases the histological features were typical of solar purpura, with the exception of inflammatory changes, typically associated with clefting of elastotic stroma. Clinical follow-up information was available for all patients and none developed subsequent evidence of a cutaneous or systemic vasculitis or neutrophilic dermatosis. Inflammatory changes appear to be more frequent in solar purpura than is generally recognised. Awareness of this histological variation and correlation with the clinical findings and evolution is important in avoiding misdiagnosis.

Using choice-based conjoint to determine the relative importance of dental benefit plan attributes.

PubMed

Cunningham, M A; Gaeth, G J; Juang, C; Chakraborty, G

1999-05-01

The purpose of this study was to use conjoint analysis to determine the importance of specific dental benefit plan features for University of Iowa (UI) staff and to build a model to predict enrollment. From a random sample of 2000 UI staff, 40 percent responded (N = 773). The survey instrument was developed using seven attributes (five dental benefit plan features and two facility characteristics) each offered at three levels (e.g., premium = $20, $15, $10/month). Pilot testing was used to find a realistic range of plan options. Twenty-seven hypothetical dental benefit plans were developed using fractional factorial combinations of the three levels for each of the seven attributes. For all of the hypothetical plans, dental care was to be provided in the UI predoctoral dental clinic. Plan profiles were arranged four per page by combining the existing plan with three hypothetical plans, for a total of nine pages. Respondents' task was to select one plan from each set of four. A regression-like statistical model (Multinomial Logit) was used to estimate importance of each attribute and each attribute level. Relative importance (and coefficients) for each of the seven attributes are as follows: maximum annual benefit (.98), orthodontic coverage (.72), routine restorative (.70), major restorative (.67), time to complete treatment (.61), clinic hours of operation (.47), premium (.18). For each attribute, relative importance of each of three levels will also be presented. These coefficients for each level are used to predict enrollment for plans with specific combinations of the dental benefit plan features.

Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization.

PubMed

Adam, Asrul; Shapiai, Mohd Ibrahim; Tumari, Mohd Zaidi Mohd; Mohamad, Mohd Saberi; Mubin, Marizan

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model.

Problem Gambling in a Sample of Older Adult Casino Gamblers.

PubMed

van der Maas, Mark; Mann, Robert E; McCready, John; Matheson, Flora I; Turner, Nigel E; Hamilton, Hayley A; Schrans, Tracy; Ialomiteanu, Anca

2017-01-01

As older adults continue to make up a greater proportion of the Canadian population, it becomes more important to understand the implications that their leisure activities have for their physical and mental health. Gambling, in particular, is a form of leisure that is becoming more widely available and has important implications for the mental health and financial well-being of older adults. This study examines a large sample (2103) of casino-going Ontarian adults over the age of 55 and identifies those features of their gambling participation that are associated with problem gambling. Logistic regression analysis is used to analyze the data. Focusing on types of gambling participated in and motivations for visiting the casino, this study finds that several forms of gambling and motivations to gamble are associated with greater risk of problem gambling. It also finds that some motivations are associated with lower risk of problem gambling. The findings of this study have implications related to gambling availability within an aging population.

Varied Rates of Implementation of Patient-Centered Medical Home Features and Residents' Perceptions of Their Importance Based on Practice Experience.

PubMed

Eiff, M Patrice; Green, Larry A; Jones, Geoff; Devlaeminck, Alex Verdieck; Waller, Elaine; Dexter, Eve; Marino, Miguel; Carney, Patricia A

2017-03-01

Little is known about how the patient-centered medical home (PCMH) is being implemented in residency practices. We describe both the trends in implementation of PCMH features and the influence that working with PCMH features has on resident attitudes toward their importance in 14 family medicine residencies associated with the P4 Project. We assessed 24 residency continuity clinics annually between 2007-2011 on presence or absence of PCMH features. Annual resident surveys (n=690) assessed perceptions of importance of PCMH features using a 4-point scale (not at all important to very important). We used generalized estimating equations logistic regression to assess trends and ordinal-response proportional odds regression models to determine if resident ratings of importance were associated with working with those features during training. Implementation of electronic health record (EHR) features increased significantly from 2007-2011, such as email communication with patients (33% to 67%), preventive services registries (23% to 64%), chronic disease registries (63% to 82%), and population-based quality assurance (46% to 79%). Team-based care was the only process of care feature to change significantly (54% to 93%). Residents with any exposure to EHR-based features had higher odds of rating the features more important compared to those with no exposure. We observed consistently lower odds of the resident rating process of care features as more important with any exposure compared to no exposure. Residencies engaged in educational transformation were more successful in implementing EHR-based PCMH features, and exposure during training appears to positively influence resident ratings of importance, while exposure to process of care features are slower to implement with less influence on importance ratings.

Refractory Access Disorders and the Organization of Concrete and Abstract Semantics: Do they Differ?

PubMed Central

Hamilton, A. Cris; Coslett, H. Branch

2010-01-01

Patients with “refractory semantic access deficits” demonstrate several unique features that make them important sources of insight into the organization of semantic representations. Here we attempt to replicate several novel findings from single-case studies reported in the literature. Patient UM– 103 displays the cardinal features of a “refractory semantic access deficit” and showed many of the same effects of semantic relatedness reported in the literature. However, when probing concrete and abstract words, this patient revealed very different patterns of performance compared to two previously reported patients. We discuss the implications of our data for models of semantic organization of abstract and concrete words. PMID:18569737

A Phenomenological Approach to Wear Debris Analysis

DTIC Science & Technology

1996-04-01

Ferrography ; oil analysis; wear debris analysis Introduction: Wear debris analysis is an important subject in maintenance, especially condition...diagnostic ol can be traced to Ferrography developed in the early 1970’s. Westcott and Seifert [1] state e heart and soul of Ferrography , or optical debris...monitoring, as follows. The key to Ferrography or optical examination of wear debris is to find marks or features on wear debris which suggest likely

Health Selection, Migration, and HIV Infection in Malawi.

PubMed

Anglewicz, Philip; VanLandingham, Mark; Manda-Taylor, Lucinda; Kohler, Hans-Peter

2018-04-27

Despite its importance in studies of migrant health, selectivity of migrants-also known as migration health selection-has seldom been examined in sub-Saharan Africa (SSA). This neglect is problematic because several features of the context in which migration occurs in SSA-very high levels of HIV, in particular-differ from contextual features in regions that have been studied more thoroughly. To address this important gap, we use longitudinal panel data from Malawi to examine whether migrants differ from nonmigrants in pre-migration health, assessed via SF-12 measures of mental and physical health. In addition to overall health selection, we focus on three more-specific factors that may affect the relationship between migration and health: (1) whether migration health selection differs by destination (rural-rural, rural-town, and rural-urban), (2) whether HIV infection moderates the relationship between migration and health, and (3) whether circular migrants differ in pre-migration health status. We find evidence of the healthy migrant phenomenon in Malawi, where physically healthier individuals are more likely to move. This relationship varies by migration destination, with healthier rural migrants moving to urban and other rural areas. We also find interactions between HIV-infected status and health: HIV-infected women moving to cities are physically healthier than their nonmigrant counterparts.

Network Sampling and Classification:An Investigation of Network Model Representations

PubMed Central

Airoldi, Edoardo M.; Bai, Xue; Carley, Kathleen M.

2011-01-01

Methods for generating a random sample of networks with desired properties are important tools for the analysis of social, biological, and information networks. Algorithm-based approaches to sampling networks have received a great deal of attention in recent literature. Most of these algorithms are based on simple intuitions that associate the full features of connectivity patterns with specific values of only one or two network metrics. Substantive conclusions are crucially dependent on this association holding true. However, the extent to which this simple intuition holds true is not yet known. In this paper, we examine the association between the connectivity patterns that a network sampling algorithm aims to generate and the connectivity patterns of the generated networks, measured by an existing set of popular network metrics. We find that different network sampling algorithms can yield networks with similar connectivity patterns. We also find that the alternative algorithms for the same connectivity pattern can yield networks with different connectivity patterns. We argue that conclusions based on simulated network studies must focus on the full features of the connectivity patterns of a network instead of on the limited set of network metrics for a specific network type. This fact has important implications for network data analysis: for instance, implications related to the way significance is currently assessed. PMID:21666773

Exploration of the relationship between topology and designability of conformations

NASA Astrophysics Data System (ADS)

Leelananda, Sumudu P.; Towfic, Fadi; Jernigan, Robert L.; Kloczkowski, Andrzej

2011-06-01

Protein structures are evolutionarily more conserved than sequences, and sequences with very low sequence identity frequently share the same fold. This leads to the concept of protein designability. Some folds are more designable and lots of sequences can assume that fold. Elucidating the relationship between protein sequence and the three-dimensional (3D) structure that the sequence folds into is an important problem in computational structural biology. Lattice models have been utilized in numerous studies to model protein folds and predict the designability of certain folds. In this study, all possible compact conformations within a set of two-dimensional and 3D lattice spaces are explored. Complementary interaction graphs are then generated for each conformation and are described using a set of graph features. The full HP sequence space for each lattice model is generated and contact energies are calculated by threading each sequence onto all the possible conformations. Unique conformation giving minimum energy is identified for each sequence and the number of sequences folding to each conformation (designability) is obtained. Machine learning algorithms are used to predict the designability of each conformation. We find that the highly designable structures can be distinguished from other non-designable conformations based on certain graphical geometric features of the interactions. This finding confirms the fact that the topology of a conformation is an important determinant of the extent of its designability and suggests that the interactions themselves are important for determining the designability.

Chinese lexical networks: The structure, function and formation

NASA Astrophysics Data System (ADS)

Li, Jianyu; Zhou, Jie; Luo, Xiaoyue; Yang, Zhanxin

2012-11-01

In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases. To uncover the structural design principles of networks, network motif patterns are studied. It is shown that they serve as basic building blocks to form the whole phrase networks, especially triad 38 (feed forward loop) plays a more important role in forming most of the phrases and other motifs. The distinct structure may not only keep the networks stable and robust, but also be helpful for information processing. The results of the paper can give some insight into Chinese language learning and language acquisition. It strengthens the idea that learning the phrases helps to understand Chinese culture. On the other side, understanding Chinese culture and philosophy does help to learn Chinese phrases. The hub nodes in the networks show the close relationship with Chinese culture and philosophy. Learning or teaching the hub characters, hub-linking phrases and phrases which are meaning related based on motif feature should be very useful and important for Chinese learning and acquisition.

The future of primordial features with large-scale structure surveys

NASA Astrophysics Data System (ADS)

Chen, Xingang; Dvorkin, Cora; Huang, Zhiqi; Namjoo, Mohammad Hossein; Verde, Licia

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopic and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.

The future of primordial features with large-scale structure surveys

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

Chen, Xingang; Namjoo, Mohammad Hossein; Dvorkin, Cora

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopicmore » and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.« less

Detection of Clinical Depression in Adolescents’ Speech During Family Interactions

PubMed Central

Low, Lu-Shih Alex; Maddage, Namunu C.; Lech, Margaret; Sheeber, Lisa B.; Allen, Nicholas B.

2013-01-01

The properties of acoustic speech have previously been investigated as possible cues for depression in adults. However, these studies were restricted to small populations of patients and the speech recordings were made during patients’ clinical interviews or fixed-text reading sessions. Symptoms of depression often first appear during adolescence at a time when the voice is changing, in both males and females, suggesting that specific studies of these phenomena in adolescent populations are warranted. This study investigated acoustic correlates of depression in a large sample of 139 adolescents (68 clinically depressed and 71 controls). Speech recordings were made during naturalistic interactions between adolescents and their parents. Prosodic, cepstral, spectral, and glottal features, as well as features derived from the Teager energy operator (TEO), were tested within a binary classification framework. Strong gender differences in classification accuracy were observed. The TEO-based features clearly outperformed all other features and feature combinations, providing classification accuracy ranging between 81%–87% for males and 72%–79% for females. Close, but slightly less accurate, results were obtained by combining glottal features with prosodic and spectral features (67%–69% for males and 70%–75% for females). These findings indicate the importance of nonlinear mechanisms associated with the glottal flow formation as cues for clinical depression. PMID:21075715

Radiology of pancreatic neoplasms: An update

PubMed Central

de la Santa, Luis Gijón; Retortillo, José Antonio Pérez; Miguel, Ainhoa Camarero; Klein, Lea Marie

2014-01-01

Diagnostic imaging is an important tool to evaluate pancreatic neoplasms. We describe the imaging features of pancreatic malignancies and their benign mimics. Accurate detection and staging are essential for ensuring appropriate selection of patients who will benefit from surgery and for preventing unnecessary surgeries in patients with unresectable disease. Ultrasound, multidetector computed tomography with multiplanar reconstruction and magnetic resonance imaging can help to do a correct diagnosis. Radiologists should be aware of the wide variety of anatomic variants and pathologic conditions that may mimic pancreatic neoplasms. The knowledge of the most important characteristic key findings may facilitate the right diagnosis. PMID:25232458

Radiology of pancreatic neoplasms: An update.

PubMed

de la Santa, Luis Gijón; Retortillo, José Antonio Pérez; Miguel, Ainhoa Camarero; Klein, Lea Marie

2014-09-15

Diagnostic imaging is an important tool to evaluate pancreatic neoplasms. We describe the imaging features of pancreatic malignancies and their benign mimics. Accurate detection and staging are essential for ensuring appropriate selection of patients who will benefit from surgery and for preventing unnecessary surgeries in patients with unresectable disease. Ultrasound, multidetector computed tomography with multiplanar reconstruction and magnetic resonance imaging can help to do a correct diagnosis. Radiologists should be aware of the wide variety of anatomic variants and pathologic conditions that may mimic pancreatic neoplasms. The knowledge of the most important characteristic key findings may facilitate the right diagnosis.

Bone marrow failure in childhood: central pathology review of a nationwide registry.

PubMed

Ito, Masafumi

2017-01-01

Refractory cytopenia of childhood (RCC) was proposed as a provisional entity in the 2008 WHO classification of myelodysplastic syndromes (MDS). It is defined as a childhood MDS featuring persistent cytopenia without increase blasts in bone marrow (BM) or peripheral blood (PB). Because the majority of RCC cases feature hypocellularity and pancytopenia, it is quite challenging to differentiate RCC from acquired aplastic anemia (AA) and many kinds of inherited bone marrow failure syndromes (IBMFS). Diagnosis of RCC requires BM histology of characteristic features such as isolated erythroid islet with left shift, abnormal localization and micromegakaryocytes. The Japanese Society of Pediatric Hematology/Oncology has opened the central registry review system since 2009 to evaluate childhood cases of bone marrow failure (BMF). It has reviewed cytology and BM pathology of all registered BMF cases, which number more than 1,700. In the evaluation of BMF, BM pathology is important to assess the mechanism of hematopoiesis. Pathological dysplasia should be differentiated from cytological dysplasia. A central review system is important for rare diseases, such as pediatric BMF. Standardization of pathological diagnosis should be established upon consensus findings, descriptions, and diagnostic approaches. In this review, the pathology of pediatric BMF syndromes is summarized.

[Pathological features of myositis with myositis -specific autoantibodies].

PubMed

Shimizu, Jun; Mimori, Tsuneyo

2014-01-01

Myositis is a heterogeneous group of systemic autoimmune disorders characterized by inflammation of skeletal muscle. Historically, myositis has been defined using clinical features including muscle weakness, skin disease, internal organ involvement, and an association with cancer in adults. From a clinicopathologic approach, myositis has been classified into pathologically distinct subsets, polymyositis, dermatomyositis(DM), necrotizing autoimmune myositis, amyopathic DM, and non-specific myositis. Although the characteristic pathological changes are believed to be important in pathological mechanisms of each subset of myositis, in clinical practices, the percentages of the patients with typical pathological findings are usually not high. On the other hand, with the recent discovery of new myositis-specific autoantibodies (MSAs), it has been revealed that around 60% of patients with IIMs have been shown to have a anti-myositis-specific autoantibody, including anti-synthetase, anti-Mi-2, anti-MDA5, anti-TIF1 and anti-SRP antibodies. Because of striking association between unique MSAs and distinct clinical phenotypes, these antibodies are thought to be important not only for classifications of IIMs, but also as factors involved in the mechanism underlying their pathogenesis. This review reports recent progress in understanding of pathological features of myositis with MSAs.

An adaptation study of internal and external features in facial representations.

PubMed

Hills, Charlotte; Romano, Kali; Davies-Thompson, Jodie; Barton, Jason J S

2014-07-01

Prior work suggests that internal features contribute more than external features to face processing. Whether this asymmetry is also true of the mental representations of faces is not known. We used face adaptation to determine whether the internal and external features of faces contribute differently to the representation of facial identity, whether this was affected by familiarity, and whether the results differed if the features were presented in isolation or as part of a whole face. In a first experiment, subjects performed a study of identity adaptation for famous and novel faces, in which the adapting stimuli were whole faces, the internal features alone, or the external features alone. In a second experiment, the same faces were used, but the adapting internal and external features were superimposed on whole faces that were ambiguous to identity. The first experiment showed larger aftereffects for unfamiliar faces, and greater aftereffects from internal than from external features, and the latter was true for both familiar and unfamiliar faces. When internal and external features were presented in a whole-face context in the second experiment, aftereffects from either internal or external features was less than that from the whole face, and did not differ from each other. While we reproduce the greater importance of internal features when presented in isolation, we find this is equally true for familiar and unfamiliar faces. The dominant influence of internal features is reduced when integrated into a whole-face context, suggesting another facet of expert face processing. Copyright © 2014 Elsevier B.V. All rights reserved.

Graph theory applied to the analysis of motor activity in patients with schizophrenia and depression

PubMed Central

Fasmer, Erlend Eindride; Berle, Jan Øystein; Oedegaard, Ketil J.; Hauge, Erik R.

2018-01-01

Depression and schizophrenia are defined only by their clinical features, and diagnostic separation between them can be difficult. Disturbances in motor activity pattern are central features of both types of disorders. We introduce a new method to analyze time series, called the similarity graph algorithm. Time series of motor activity, obtained from actigraph registrations over 12 days in depressed and schizophrenic patients, were mapped into a graph and we then applied techniques from graph theory to characterize these time series, primarily looking for changes in complexity. The most marked finding was that depressed patients were found to be significantly different from both controls and schizophrenic patients, with evidence of less regularity of the time series, when analyzing the recordings with one hour intervals. These findings support the contention that there are important differences in control systems regulating motor behavior in patients with depression and schizophrenia. The similarity graph algorithm we have described can easily be applied to the study of other types of time series. PMID:29668743

Real-time UAV trajectory generation using feature points matching between video image sequences

NASA Astrophysics Data System (ADS)

Byun, Younggi; Song, Jeongheon; Han, Dongyeob

2017-09-01

Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system

Chinese mental illness narratives: controlling the spirit.

PubMed

Ramsay, Guy

2009-01-01

Through analysis of local level narrative themes and linguistic features and their attendant narrative 'domains' and emotive content, this study explicates the discursive forms of Chinese personal narratives about mental illness published in a psychoeducational volume in mainland China. The cultural phenomena underpinning the explicated discursive forms are considered. The study finds that the Chinese mental illness narratives emphasize the problematic nature of the illness experience for the individual concerned, as well as the importance of gaining control over the personal and social disembodiment that mental illness brings about. The language of medicine presents as a dominant linguistic feature of the texts. Narrative authors appear to respond to their illness experience by negotiating and utilizing social relationships and support structures and through active medical intercession. As such, their narratives appear deeply culturally marked despite their psychoeducational intent and institutional context of publication. The study findings bear out the call for more attention to be given to the cultural dimension when analysing illness narratives.

Graph theory applied to the analysis of motor activity in patients with schizophrenia and depression.

PubMed

Fasmer, Erlend Eindride; Fasmer, Ole Bernt; Berle, Jan Øystein; Oedegaard, Ketil J; Hauge, Erik R

2018-01-01

Depression and schizophrenia are defined only by their clinical features, and diagnostic separation between them can be difficult. Disturbances in motor activity pattern are central features of both types of disorders. We introduce a new method to analyze time series, called the similarity graph algorithm. Time series of motor activity, obtained from actigraph registrations over 12 days in depressed and schizophrenic patients, were mapped into a graph and we then applied techniques from graph theory to characterize these time series, primarily looking for changes in complexity. The most marked finding was that depressed patients were found to be significantly different from both controls and schizophrenic patients, with evidence of less regularity of the time series, when analyzing the recordings with one hour intervals. These findings support the contention that there are important differences in control systems regulating motor behavior in patients with depression and schizophrenia. The similarity graph algorithm we have described can easily be applied to the study of other types of time series.

Optimal designs for prediction studies of whiplash.

PubMed

Kamper, Steven J; Hancock, Mark J; Maher, Christopher G

2011-12-01

Commentary. To provide guidance for the design and interpretation of predictive studies of whiplash associated disorders (WAD). Numerous studies have sought to define and explain the clinical course and response to treatment of people with WAD. Design of these studies is often suboptimal, which can lead to biased findings and issues with interpreting the results. Literature review and commentary. Predictive studies can be grouped into four broad categories; studies of symptomatic course, studies that aim to identify factors that predict outcome, studies that aim to isolate variables that are causally responsible for outcome, and studies that aim to identify patients who respond best to particular treatments. Although the specific research question will determine the optimal methods, there are a number of generic features that should be incorporated into design of such studies. The aim of these features is to minimize bias, generate adequately precise prognostic estimates, and ensure generalizability of the findings. This paper provides a summary of important considerations in the design, conduct, and reporting of prediction studies in the field of whiplash.

A PLANETARY LENSING FEATURE IN CAUSTIC-CROSSING HIGH-MAGNIFICATION MICROLENSING EVENTS

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

Chung, Sun-Ju; Hwang, Kyu-Ha; Ryu, Yoon-Hyun

Current microlensing follow-up observations focus on high-magnification events because of the high efficiency of planet detection. However, central perturbations of high-magnification events caused by a planet can also be produced by a very close or a very wide binary companion, and the two kinds of central perturbations are not generally distinguished without time consuming detailed modeling (a planet-binary degeneracy). Hence, it is important to resolve the planet-binary degeneracy that occurs in high-magnification events. In this paper, we investigate caustic-crossing high-magnification events caused by a planet and a wide binary companion. From this investigation, we find that because of the differentmore » magnification excess patterns inside the central caustics induced by the planet and the binary companion, the light curves of the caustic-crossing planetary-lensing events exhibit a feature that is discriminated from those of the caustic-crossing binary-lensing events, and the feature can be used to immediately distinguish between the planetary and binary companions. The planetary-lensing feature appears in the interpeak region between the two peaks of the caustic-crossings. The structure of the interpeak region for the planetary-lensing events is smooth and convex or boxy, whereas the structure for the binary-lensing events is smooth and concave. We also investigate the effect of a finite background source star on the planetary-lensing feature in the caustic-crossing high-magnification events. From this, we find that the convex-shaped interpeak structure appears in a certain range that changes with the mass ratio of the planet to the planet-hosting star.« less

Dissociations between Featural versus Conjunction-based Texture Processing in Infancy: Analyses of Three Potential Contributing Factors.

ERIC Educational Resources Information Center

Bertin, Evelin; Bhatt, Ramesh S.

2001-01-01

Examined three possible explanations for findings that infants detect textural discrepancies based on individual features more readily than on feature conjunctions. Found that none of the proposed factors could explain 5.5-month-olds' superior processing of featural over conjunction-based textural discrepancies. Findings suggest that in infancy,…

Finding a place to connect: A qualitative study exploring the influences of the physical and social environments on spouses' opportunities to maintain relationships when visiting a partner with dementia living in long-term care.

PubMed

Førsund, Linn Hege; Ytrehus, Siri

2016-06-17

The purpose of this qualitative study was to explore how physical and social environments influence spouses' opportunities to maintain relationships when visiting a partner with dementia living in long-term care. Interviews with 15 spouses whose partners lived in long-term care facilities for persons with dementia, observations of physical environments and participant observations were conducted. The results showed how finding a place for spouses to connect in the long-term care facility was important in maintaining relationships. Access to individual rooms was an important feature that enabled connections throughout the phases of dementia, whereas common areas appeared more difficult to use because small spaces limited private interactions. Health personnel were important in sustaining spouses' abilities to maintain their relationships in long-term care facilities for persons with dementia. © The Author(s) 2016.

Microdeletions are a general feature of adult and adolescent acute lymphoblastic leukemia: Unexpected similarities with pediatric disease

PubMed Central

Paulsson, Kajsa; Cazier, Jean-Baptiste; MacDougall, Finlay; Stevens, Jane; Stasevich, Irina; Vrcelj, Nikoletta; Chaplin, Tracy; Lillington, Debra M.; Lister, T. Andrew; Young, Bryan D.

2008-01-01

We present here a genome-wide map of abnormalities found in diagnostic samples from 45 adults and adolescents with acute lymphoblastic leukemia (ALL). A 500K SNP array analysis uncovered frequent genetic abnormalities, with cryptic deletions constituting half of the detected changes, implying that microdeletions are a characteristic feature of this malignancy. Importantly, the pattern of deletions resembled that recently reported in pediatric ALL, suggesting that adult, adolescent, and childhood cases may be more similar on the genetic level than previously thought. Thus, 70% of the cases displayed deletion of one or more of the CDKN2A, PAX5, IKZF1, ETV6, RB1, and EBF1 genes. Furthermore, several genes not previously implicated in the pathogenesis of ALL were identified as possible recurrent targets of deletion. In total, the SNP array analysis identified 367 genetic abnormalities not corresponding to known copy number polymorphisms, with all but two cases (96%) displaying at least one cryptic change. The resolution level of this SNP array study is the highest used to date to investigate a malignant hematologic disorder. Our findings provide insights into the leukemogenic process and may be clinically important in adult and adolescent ALL. Most importantly, we report that microdeletions of key genes appear to be a common, characteristic feature of ALL that is shared among different clinical, morphological, and cytogenetic subgroups. PMID:18458336

Craters on Mars: Global Geometric Properties from Gridded MOLA Topography

NASA Technical Reports Server (NTRS)

Garvin, J. B.; Sakimoto, S. E. H.; Frawley, J. J.

2003-01-01

Impact craters serve as natural probes of the target properties of planetary crusts and the tremendous diversity of morphological expressions of such features on Mars attests to their importance for deciphering the history of crustal assembly, modification, and erosion. This paper summarizes the key findings associated with a five year long survey of the three-dimensional properties of approx. 6000 martian impact craters using finely gridded MOLA topography. Previous efforts have treated representative subpopulations, but this effort treats global properties from the largest survey of impact features from the perspective of their topography ever assimilated. With the Viking missions of the mid-1970 s, the most intensive and comprehensive robotic expeditions to any Deep Space location in the history of humanity were achieved, with scientifically stunning results associated with the morphology of impact craters. The relationships illustrated and suggest that martian impact features are remarkably sensitive to target properties and to the local depositional processes.

The fast detection of rare auditory feature conjunctions in the human brain as revealed by cortical gamma-band electroencephalogram.

PubMed

Ruusuvirta, T; Huotilainen, M

2005-01-01

Natural environments typically contain temporal scatters of sounds emitted from multiple sources. The sounds may often physically stand out from one another in their conjoined rather than simple features. This poses a particular challenge for the brain to detect which of these sounds are rare and, therefore, potentially important for survival. We recorded gamma-band (32-40 Hz) electroencephalographic (EEG) oscillations from the scalp of adult humans who passively listened to a repeated tone carrying frequent and rare conjunctions of its frequency and intensity. EEG oscillations that this tone induced, rather than evoked, differed in amplitude between the two conjunction types within the 56-ms analysis window from tone onset. Our finding suggests that, perhaps with the support of its non-phase-locked synchrony in the gamma band, the human brain is able to detect rare sounds as feature conjunctions very rapidly.

Identification of a motor to auditory pathway important for vocal learning

PubMed Central

Roberts, Todd F.; Hisey, Erin; Tanaka, Masashi; Kearney, Matthew; Chattree, Gaurav; Yang, Cindy F.; Shah, Nirao M.; Mooney, Richard

2017-01-01

Summary Learning to vocalize depends on the ability to adaptively modify the temporal and spectral features of vocal elements. Neurons that convey motor-related signals to the auditory system are theorized to facilitate vocal learning, but the identity and function of such neurons remain unknown. Here we identify a previously unknown neuron type in the songbird brain that transmits vocal motor signals to the auditory cortex. Genetically ablating these neurons in juveniles disrupted their ability to imitate features of an adult tutor’s song. Ablating these neurons in adults had little effect on previously learned songs, but interfered with their ability to adaptively modify the duration of vocal elements and largely prevented the degradation of song’s temporal features normally caused by deafening. These findings identify a motor to auditory circuit essential to vocal imitation and to the adaptive modification of vocal timing. PMID:28504672

48,XXYY, 48,XXXY and 49,XXXXY syndromes: not just variants of Klinefelter syndrome

PubMed Central

Tartaglia, Nicole; Ayari, Natalie; Howell, Susan; D’Epagnier, Cheryl; Zeitler, Philip

2012-01-01

Sex chromosome tetrasomy and pentasomy conditions occur in 1:18 000–1:100 000 male births. While often compared with 47,XXY/Klinefelter syndrome because of shared features including tall stature and hypergonadotropic hypogonadism, 48,XXYY, 48,XXXY and 49,XXXXY syndromes are associated with additional physical findings, congenital malformations, medical problems and psychological features. While the spectrum of cognitive abilities extends much higher than originally described, developmental delays, cognitive impairments and behavioural disorders are common and require strong treatment plans. Future research should focus on genotype–phenotype relationships and the development of evidence-based treatments. Conclusion The more complex physical, medical and psychological phenotypes of 48,XXYY, 48,XXXY and 49,XXXXY syndromes make distinction from 47,XXY important; however, all of these conditions share features of hypergonadotropic hypogonadism and the need for increased awareness, biomedical research and the development of evidence-based treatments. PMID:21342258

Principal curve detection in complicated graph images

NASA Astrophysics Data System (ADS)

Liu, Yuncai; Huang, Thomas S.

2001-09-01

Finding principal curves in an image is an important low level processing in computer vision and pattern recognition. Principal curves are those curves in an image that represent boundaries or contours of objects of interest. In general, a principal curve should be smooth with certain length constraint and allow either smooth or sharp turning. In this paper, we present a method that can efficiently detect principal curves in complicated map images. For a given feature image, obtained from edge detection of an intensity image or thinning operation of a pictorial map image, the feature image is first converted to a graph representation. In graph image domain, the operation of principal curve detection is performed to identify useful image features. The shortest path and directional deviation schemes are used in our algorithm os principal verve detection, which is proven to be very efficient working with real graph images.

Distance error correction for time-of-flight cameras

NASA Astrophysics Data System (ADS)

Fuersattel, Peter; Schaller, Christian; Maier, Andreas; Riess, Christian

2017-06-01

The measurement accuracy of time-of-flight cameras is limited due to properties of the scene and systematic errors. These errors can accumulate to multiple centimeters which may limit the applicability of these range sensors. In the past, different approaches have been proposed for improving the accuracy of these cameras. In this work, we propose a new method that improves two important aspects of the range calibration. First, we propose a new checkerboard which is augmented by a gray-level gradient. With this addition it becomes possible to capture the calibration features for intrinsic and distance calibration at the same time. The gradient strip allows to acquire a large amount of distance measurements for different surface reflectivities, which results in more meaningful training data. Second, we present multiple new features which are used as input to a random forest regressor. By using random regression forests, we circumvent the problem of finding an accurate model for the measurement error. During application, a correction value for each individual pixel is estimated with the trained forest based on a specifically tailored feature vector. With our approach the measurement error can be reduced by more than 40% for the Mesa SR4000 and by more than 30% for the Microsoft Kinect V2. In our evaluation we also investigate the impact of the individual forest parameters and illustrate the importance of the individual features.

MR imaging findings of adenomyosis: correlation with histopathologic features and diagnostic pitfalls.

PubMed

Tamai, Ken; Togashi, Kaori; Ito, Tsuyoshi; Morisawa, Nobuko; Fujiwara, Toshitaka; Koyama, Takashi

2005-01-01

Adenomyosis is a nonneoplastic condition, characterized by benign invasion of ectopic endometrium into the myometrium with hyperplasia of adjacent smooth muscle. The common symptoms include dysmenorrhea, menorrhagia, and abnormal uterine bleeding, but these do not allow diagnosis. Therefore, imaging plays an important role because establishment of the correct preoperative diagnosis is critical to avoid unnecessary intervention. Magnetic resonance (MR) imaging is a highly accurate noninvasive modality for diagnosis of adenomyosis, differentiation of adenomyosis from other gynecologic disorders, and planning of appropriate treatment. Although the typical MR imaging findings are well established, adenomyosis actually varies widely in terms of histopathologic features (adenomyosis with sparse glands), growth patterns (polypoid adenomyoma, adenomyotic cyst, and miniature uterus), responses to hormonal activity (tamoxifen, decidual changes), and responses to treatment (gonadotropin-releasing hormone agonist). The MR imaging findings of adenomyosis occasionally mimic those of uterine malignancy or ovarian cancer. Furthermore, malignancy occasionally develops in otherwise benign adenomyosis. Pitfalls in diagnosis of adenomyosis include myometrial contractions, leiomyoma, adenomatoid tumor, metastases, endometrial carcinoma, and endometrial stromal sarcoma. Knowledge of the various appearances of adenomyosis and the possible pitfalls in differential diagnosis help guide the determination of appropriate treatment options. (c) RSNA, 2005.

Characterizing populations and searching for diagnostics via elastic registration of MRI images

NASA Astrophysics Data System (ADS)

Pettey, David; Gee, James C.

2001-07-01

Given image data from two distinct populations and a family of functions, we find the scalar discriminant function which best discriminates between the populations. The goals are two-fold: first, to construct a discriminant function which can accurately and reliably classify subjects via the image data. Second, the best discriminant allows us to see which features in the images distinguish between the populations; these features can guide us to finding characteristic differences between the two groups even if these differences are not sufficient to perform classification. We apply our method to mid-sagittal MRI sections of the corpus callosum from 34 males and 52 females. While we are not certain of the ability of the derived discriminant function to perform sex classification, we find that regions in the anterior of the corpus callosum do appear to be more important for the discriminant function than other regions. This indicates there may be significant differences in the relative size of the splenium in males and females, as has been reported elsewhere. More notably, we applied previous methods which support this view on our larger data set, but found that these methods no longer show statistically significant differences between the male and female splenium.

A Virtual Microscope for Academic Medical Education: The Pate Project

PubMed Central

Hundt, Christian; Schmitt, Volker H; Schömer, Elmar; Kirkpatrick, C James

2015-01-01

Background Whole-slide imaging (WSI) has become more prominent and continues to gain in importance in student teaching. Applications with different scope have been developed. Many of these applications have either technical or design shortcomings. Objective To design a survey to determine student expectations of WSI applications for teaching histological and pathological diagnosis. To develop a new WSI application based on the findings of the survey. Methods A total of 216 students were questioned about their experiences and expectations of WSI applications, as well as favorable and undesired features. The survey included 14 multiple choice and two essay questions. Based on the survey, we developed a new WSI application called Pate utilizing open source technologies. Results The survey sample included 216 students—62.0% (134) women and 36.1% (78) men. Out of 216 students, 4 (1.9%) did not disclose their gender. The best-known preexisting WSI applications included Mainzer Histo Maps (199/216, 92.1%), Histoweb Tübingen (16/216, 7.4%), and Histonet Ulm (8/216, 3.7%). Desired features for the students were latitude in the slides (190/216, 88.0%), histological (191/216, 88.4%) and pathological (186/216, 86.1%) annotations, points of interest (181/216, 83.8%), background information (146/216, 67.6%), and auxiliary informational texts (113/216, 52.3%). By contrast, a discussion forum was far less important (9/216, 4.2%) for the students. Conclusions The survey revealed that the students appreciate a rich feature set, including WSI functionality, points of interest, auxiliary informational texts, and annotations. The development of Pate was significantly influenced by the findings of the survey. Although Pate currently has some issues with the Zoomify file format, it could be shown that Web technologies are capable of providing a high-performance WSI experience, as well as a rich feature set. PMID:25963527

Finding Kepler's Exoearths

NASA Astrophysics Data System (ADS)

Petigura, Erik; Marcy, G.

2012-05-01

With its unprecedented photometric precision and duty cycle, the Kepler mission offers the first opportunity to detect Earth analog planets. Detecting transits with depths of 0.01%, periods of 1 year, and durations of 10 hours pose a novel challenge, prompting an optimization of both the detrending of the photometry and of the transit search algorithm. We present TERRA, the Transiting Exoearth Robust Reduction Algorithm, designed specifically to find earth analogs. TERRA carefully treats systematic effects with timescales comparable to an exoearth transit and removes features that are not important from the perspective of transit detection. We demonstrate TERRA's detection power through an extensive transit injection and recovery experiment.

A simple branching model that reproduces language family and language population distributions

NASA Astrophysics Data System (ADS)

Schwämmle, Veit; de Oliveira, Paulo Murilo Castro

2009-07-01

Human history leaves fingerprints in human languages. Little is known about language evolution and its study is of great importance. Here we construct a simple stochastic model and compare its results to statistical data of real languages. The model is based on the recent finding that language changes occur independently of the population size. We find agreement with the data additionally assuming that languages may be distinguished by having at least one among a finite, small number of different features. This finite set is also used in order to define the distance between two languages, similarly to linguistics tradition since Swadesh.

Imaging of Pancreatic and Duodenal Trauma.

PubMed

Melamud, Kira; LeBedis, Christina A; Soto, Jorge A

2015-07-01

Pancreatic and duodenal injuries are rare but life-threatening occurrences, often occurring in association with other solid organ injuries. Findings of pancreatic and duodenal trauma on computed tomography and MR imaging are often nonspecific, and high levels of clinical suspicion and understanding of mechanism of injury are imperative. Familiarity with the grading schemes of pancreatic and duodenal injury is important because they help in assessing for key imaging findings that directly influence management. This article presents an overview of imaging of blunt and penetrating pancreatic and duodenal injuries, including pathophysiology, available imaging techniques, and variety of imaging features. Copyright © 2015 Elsevier Inc. All rights reserved.

Temporal resolution for the perception of features and conjunctions.

PubMed

Bodelón, Clara; Fallah, Mazyar; Reynolds, John H

2007-01-24

The visual system decomposes stimuli into their constituent features, represented by neurons with different feature selectivities. How the signals carried by these feature-selective neurons are integrated into coherent object representations is unknown. To constrain the set of possible integrative mechanisms, we quantified the temporal resolution of perception for color, orientation, and conjunctions of these two features. We find that temporal resolution is measurably higher for each feature than for their conjunction, indicating that time is required to integrate features into a perceptual whole. This finding places temporal limits on the mechanisms that could mediate this form of perceptual integration.

Radiological Findings in a case of Advance staged Mesothelioma

PubMed Central

Aziz, Fahad

2009-01-01

Chest X Ray is the initial screening test for the mesothelioma like all other the chest diseases. But computed tomography (CT) is the imaging technique of choice for charactering pleural masses. CT also gives important information regarding invasion of the chest wall and surrounding structures. Certain CT features help differentiate benign from malignant processes. This short article highlights the salient CT appearance of mesothelioma; the most common pleural tumor. PMID:22263002

Intracranial EEG fluctuates over months after implanting electrodes in human brain

NASA Astrophysics Data System (ADS)

Ung, Hoameng; Baldassano, Steven N.; Bink, Hank; Krieger, Abba M.; Williams, Shawniqua; Vitale, Flavia; Wu, Chengyuan; Freestone, Dean; Nurse, Ewan; Leyde, Kent; Davis, Kathryn A.; Cook, Mark; Litt, Brian

2017-10-01

Objective. Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. Approach. Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient’s recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. Main results. A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. Significance. These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in patients, depending upon the application, may require extended monitoring.

Peripheral hypoechoic spaces in consolidated lung: a specific diagnostic sonographic finding for necrotizing pneumonia in children.

PubMed

Chiu, Chih-Yung; Wong, Kin-Sun; Lai, Shen-Hao; Huang, Yu-Hsuan; Tsai, Ming-Han; Lin, Yu-Ching

2008-01-01

The aim of this study was to investigate the diagnostic usefulness and clinical values of the sonographic feature of peripheral hypoechoic spaces (PHES) in children with necrotizing pneumonia (NP). Between July 2002 and July 2004, 23 consecutive children with NP in whom we performed real-time chest ultrasound were enrolled into our study. Details of demographics, clinical characteristics, laboratory data, causative pathogens, complications and outcomes of these children were recorded and analyzed. PHES in ultrasonography (US) were defined as peripheral cavitations seen as hypoechoic areas in consolidated lung. The sonographic feature of PHES was correlated with the diagnosis of NP and was also used to correlate with the clinical characteristics, complications and outcomes in children with NP. Sensitivity, specificity, and positive predictive value of this sonographic finding for the diagnosis of NP were 35%, 100%, and 100%, respectively. Pneumothorax was seen more commonly in children who presented PHES in US, with a significant difference (p < 0.05). In conclusion, the sonographic feature of PHES appears to be more specific for detecting NP in childhood pneumonia. In children with pneumonia with PHES in consolidated lung, the diagnosis of NP can be suggested with confidence, and it is important to be aware of the life-threatening complication of pneumothorax to decrease morbidity.

Separation of pulsar signals from noise using supervised machine learning algorithms

NASA Astrophysics Data System (ADS)

Bethapudi, S.; Desai, S.

2018-04-01

We evaluate the performance of four different machine learning (ML) algorithms: an Artificial Neural Network Multi-Layer Perceptron (ANN MLP), Adaboost, Gradient Boosting Classifier (GBC), and XGBoost, for the separation of pulsars from radio frequency interference (RFI) and other sources of noise, using a dataset obtained from the post-processing of a pulsar search pipeline. This dataset was previously used for the cross-validation of the SPINN-based machine learning engine, obtained from the reprocessing of the HTRU-S survey data (Morello et al., 2014). We have used the Synthetic Minority Over-sampling Technique (SMOTE) to deal with high-class imbalance in the dataset. We report a variety of quality scores from all four of these algorithms on both the non-SMOTE and SMOTE datasets. For all the above ML methods, we report high accuracy and G-mean for both the non-SMOTE and SMOTE cases. We study the feature importances using Adaboost, GBC, and XGBoost and also from the minimum Redundancy Maximum Relevance approach to report algorithm-agnostic feature ranking. From these methods, we find that the signal to noise of the folded profile to be the best feature. We find that all the ML algorithms report FPRs about an order of magnitude lower than the corresponding FPRs obtained in Morello et al. (2014), for the same recall value.

Negative effects of item repetition on source memory.

PubMed

Kim, Kyungmi; Yi, Do-Joon; Raye, Carol L; Johnson, Marcia K

2012-08-01

In the present study, we explored how item repetition affects source memory for new item-feature associations (picture-location or picture-color). We presented line drawings varying numbers of times in Phase 1. In Phase 2, each drawing was presented once with a critical new feature. In Phase 3, we tested memory for the new source feature of each item from Phase 2. Experiments 1 and 2 demonstrated and replicated the negative effects of item repetition on incidental source memory. Prior item repetition also had a negative effect on source memory when different source dimensions were used in Phases 1 and 2 (Experiment 3) and when participants were explicitly instructed to learn source information in Phase 2 (Experiments 4 and 5). Importantly, when the order between Phases 1 and 2 was reversed, such that item repetition occurred after the encoding of critical item-source combinations, item repetition no longer affected source memory (Experiment 6). Overall, our findings did not support predictions based on item predifferentiation, within-dimension source interference, or general interference from multiple traces of an item. Rather, the findings were consistent with the idea that prior item repetition reduces attention to subsequent presentations of the item, decreasing the likelihood that critical item-source associations will be encoded.

Morphologic-echocardiographic correlates of Ebstein's malformation.

PubMed

Rusconi, P G; Zuberbuhler, J R; Anderson, R H; Rigby, M L

1991-07-01

The cross-sectional echocardiographic findings were analysed retrospectively in 26 patients with Ebstein's malformation in the light of studies of autopsied specimens from different patients showing this lesion. The salient anatomical feature in diagnosis is the finding of the hinge point of the septal and mural leaflets of the valve within the inlet component of the right ventricle rather than at the atrioventricular junction. The other important feature is the nature of the distal attachment of the leaflets, particularly the anterosuperior one, which can either be in focal or linear fashion. The hinge point of the septal leaflet was noted echocardiographically to be displaced in 19 patients but, significantly, the leaflet was absent in the other seven. Also significant was that the hinge point of the mural leaflet at the crux had been visualized in only 15 of the patients. The anterosuperior leaflet had a distal linear attachment in 20 of the patients, with the anteroseptal commissure becoming a keyhole in six of these through which blood passed to the functional right ventricle. The valve remained a competent structure, even though closing at the junction of atrialized and functional components of the right ventricle rather than at the atrioventricular junction. Cross-sectional echocardiography is the technique of choice with which to display the salient morphological features of Ebstein's malformation.

Characterizing Smartphone Engagement for Schizophrenia: Results of a Naturalist Mobile Health Study.

PubMed

Torous, John; Staples, Patrick; Slaters, Linda; Adams, Jared; Sandoval, Luis; Onnela, J P; Keshavan, Matcheri

2017-08-04

Despite growing interest in smartphone apps for schizophrenia, little is known about how these apps are utilized in the real world. Understanding how app users are engaging with these tools outside of the confines of traditional clinical studies offers an important information on who is most likely to use apps and what type of data they are willing to share. The Schizophrenia and Related Disorders Alliance of America, in partnership with Self Care Catalyst, has created a smartphone app for schizophrenia that is free and publically available on both Apple iTunes and Google Android Play stores. We analyzed user engagement data from this app across its medication tracking, mood tracking, and symptom tracking features from August 16 th 2015 to January 1 st 2017 using the R programming language. We included all registered app users in our analysis with reported ages less than 100. We analyzed a total of 43,451 mood, medication and symptom entries from 622 registered users, and excluded a single patient with a reported age of 114. Seventy one percent of the 622 users tried the mood-tracking feature at least once, 49% the symptom tracking feature, and 36% the medication-tracking feature. The mean number of uses of the mood feature was two, the symptom feature 10, and the medication feature 14. However, a small subset of users were very engaged with the app and the top 10 users for each feature accounted for 35% or greater of all entries for that feature. We find that user engagement follows a power law distribution for each feature, and this fit was largely invariant when stratifying for age or gender. Engagement with this app for schizophrenia was overall low, but similar to prior naturalistic studies for mental health app use in other diseases. The low rate of engagement in naturalistic settings, compared to higher rates of use in clinical studies, suggests the importance of clinical involvement as one factor in driving engagement for mental health apps. Power law relationships suggest strongly skewed user engagement, with a small subset of users accounting for the majority of substantial engagements. There is a need for further research on app engagement in schizophrenia.

[Prosody, speech input and language acquisition].

PubMed

Jungheim, M; Miller, S; Kühn, D; Ptok, M

2014-04-01

In order to acquire language, children require speech input. The prosody of the speech input plays an important role. In most cultures adults modify their code when communicating with children. Compared to normal speech this code differs especially with regard to prosody. For this review a selective literature search in PubMed and Scopus was performed. Prosodic characteristics are a key feature of spoken language. By analysing prosodic features, children gain knowledge about underlying grammatical structures. Child-directed speech (CDS) is modified in a way that meaningful sequences are highlighted acoustically so that important information can be extracted from the continuous speech flow more easily. CDS is said to enhance the representation of linguistic signs. Taking into consideration what has previously been described in the literature regarding the perception of suprasegmentals, CDS seems to be able to support language acquisition due to the correspondence of prosodic and syntactic units. However, no findings have been reported, stating that the linguistically reduced CDS could hinder first language acquisition.

Overlap between autistic and schizotypal personality traits is not accounted for by anxiety and depression.

PubMed

Mealey, Alex; Abbott, Gavin; Byrne, Linda K; McGillivray, Jane

2014-10-30

Autism spectrum and schizophrenia spectrum disorders are classified separately in the DSM-5, yet research indicates that these two disorders share overlapping features. The aim of the present study was to examine the overlap between autistic and schizotypal personality traits and whether anxiety and depression act as confounding variables in this relationship within a non-clinical population. One hundred and forty-four adults completed the Autism Spectrum Quotient and the Schizotypal Personality Questionnaire and the Depression Anxiety Stress Scales-21. A number of associations were seen between autistic and schizotypal personality traits. However, negative traits were the only schizotypal feature to uniquely predict global autistic traits, thus highlighting the importance of interpersonal qualities in the overlap of autistic and schizotypal characteristics. The inclusion of anxiety and depression did not alter relationships between autistic and schizotypal traits, indicating that anxiety and depression are not confounders of this relationship. These findings have important implications for the conceptualisation of both disorders. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Pulsatile Hormonal Signaling to Extracellular Signal-regulated Kinase

PubMed Central

Perrett, Rebecca M.; Voliotis, Margaritis; Armstrong, Stephen P.; Fowkes, Robert C.; Pope, George R.; Tsaneva-Atanasova, Krasimira; McArdle, Craig A.

2014-01-01

Gonadotropin-releasing hormone (GnRH) is secreted in brief pulses that stimulate synthesis and secretion of pituitary gonadotropin hormones and thereby mediate control of reproduction. It acts via G-protein-coupled receptors to stimulate effectors, including ERK. Information could be encoded in GnRH pulse frequency, width, amplitude, or other features of pulse shape, but the relative importance of these features is unknown. Here we examine this using automated fluorescence microscopy and mathematical modeling, focusing on ERK signaling. The simplest scenario is one in which the system is linear, and response dynamics are relatively fast (compared with the signal dynamics). In this case integrated system output (ERK activation or ERK-driven transcription) will be roughly proportional to integrated input, but we find that this is not the case. Notably, we find that relatively slow response kinetics lead to ERK activity beyond the GnRH pulse, and this reduces sensitivity to pulse width. More generally, we show that the slowing of response kinetics through the signaling cascade creates a system that is robust to pulse width. We, therefore, show how various levels of response kinetics synergize to dictate system sensitivity to different features of pulsatile hormone input. We reveal the mathematical and biochemical basis of a dynamic GnRH signaling system that is robust to changes in pulse amplitude and width but is sensitive to changes in receptor occupancy and frequency, precisely the features that are tightly regulated and exploited to exert physiological control in vivo. PMID:24482225

Learning to Detect Vandalism in Social Content Systems: A Study on Wikipedia

NASA Astrophysics Data System (ADS)

Javanmardi, Sara; McDonald, David W.; Caruana, Rich; Forouzan, Sholeh; Lopes, Cristina V.

A challenge facing user generated content systems is vandalism, i.e. edits that damage content quality. The high visibility and easy access to social networks makes them popular targets for vandals. Detecting and removing vandalism is critical for these user generated content systems. Because vandalism can take many forms, there are many different kinds of features that are potentially useful for detecting it. The complex nature of vandalism, and the large number of potential features, make vandalism detection difficult and time consuming for human editors. Machine learning techniques hold promise for developing accurate, tunable, and maintainable models that can be incorporated into vandalism detection tools. We describe a method for training classifiers for vandalism detection that yields classifiers that are more accurate on the PAN 2010 corpus than others previously developed. Because of the high turnaround in social network systems, it is important for vandalism detection tools to run in real-time. To this aim, we use feature selection to find the minimal set of features consistent with high accuracy. In addition, because some features are more costly to compute than others, we use cost-sensitive feature selection to reduce the total computational cost of executing our models. In addition to the features previously used for spam detection, we introduce new features based on user action histories. The user history features contribute significantly to classifier performance. The approach we use is general and can easily be applied to other user generated content systems.

Opening up the blackbox: an interpretable deep neural network-based classifier for cell-type specific enhancer predictions.

PubMed

Kim, Seong Gon; Theera-Ampornpunt, Nawanol; Fang, Chih-Hao; Harwani, Mrudul; Grama, Ananth; Chaterji, Somali

2016-08-01

Gene expression is mediated by specialized cis-regulatory modules (CRMs), the most prominent of which are called enhancers. Early experiments indicated that enhancers located far from the gene promoters are often responsible for mediating gene transcription. Knowing their properties, regulatory activity, and genomic targets is crucial to the functional understanding of cellular events, ranging from cellular homeostasis to differentiation. Recent genome-wide investigation of epigenomic marks has indicated that enhancer elements could be enriched for certain epigenomic marks, such as, combinatorial patterns of histone modifications. Our efforts in this paper are motivated by these recent advances in epigenomic profiling methods, which have uncovered enhancer-associated chromatin features in different cell types and organisms. Specifically, in this paper, we use recent state-of-the-art Deep Learning methods and develop a deep neural network (DNN)-based architecture, called EP-DNN, to predict the presence and types of enhancers in the human genome. It uses as features, the expression levels of the histone modifications at the peaks of the functional sites as well as in its adjacent regions. We apply EP-DNN to four different cell types: H1, IMR90, HepG2, and HeLa S3. We train EP-DNN using p300 binding sites as enhancers, and TSS and random non-DHS sites as non-enhancers. We perform EP-DNN predictions to quantify the validation rate for different levels of confidence in the predictions and also perform comparisons against two state-of-the-art computational models for enhancer predictions, DEEP-ENCODE and RFECS. We find that EP-DNN has superior accuracy and takes less time to make predictions. Next, we develop methods to make EP-DNN interpretable by computing the importance of each input feature in the classification task. This analysis indicates that the important histone modifications were distinct for different cell types, with some overlaps, e.g., H3K27ac was important in cell type H1 but less so in HeLa S3, while H3K4me1 was relatively important in all four cell types. We finally use the feature importance analysis to reduce the number of input features needed to train the DNN, thus reducing training time, which is often the computational bottleneck in the use of a DNN. In this paper, we developed EP-DNN, which has high accuracy of prediction, with validation rates above 90 % for the operational region of enhancer prediction for all four cell lines that we studied, outperforming DEEP-ENCODE and RFECS. Then, we developed a method to analyze a trained DNN and determine which histone modifications are important, and within that, which features proximal or distal to the enhancer site, are important.

Private Investment Purchase and Nursing Home Financial Health

PubMed Central

Cadigan, Rebecca Orfaly; Stevenson, David G; Caudry, Daryl J; Grabowski, David C

2015-01-01

Objective To explore the impact of nursing home acquisition by private investment firms on nursing home costs, revenue, and overall financial health. Data Sources Merged data from the Medicare Cost Reports and the Online Survey, Certification, and Reporting system for the period 1998–2010. Study Design Regression specification incorporating facility and time fixed effects. Principal Findings We found little impact on the financial health of nursing homes following purchase by private investment companies. However, our findings did suggest that private investment firms acquired nursing home chains in good financial health, possibly to derive profit from the company’s real estate holdings. Conclusions Private investment acquired facilities are an important feature of today’s nursing home sector. Although we did not observe a negative impact on the financial health of nursing homes, this development raises important issues about ownership oversight and transparency for the entire nursing home sector. PMID:25104476

Designing a Text Messaging Intervention to Improve Physical Activity Behavior Among Low-Income Latino Patients With Diabetes: A Discrete-Choice Experiment, Los Angeles, 2014-2015.

PubMed

Ramirez, Magaly; Wu, Shinyi; Beale, Elizabeth

2016-12-22

Automated text messaging can deliver self-management education to activate self-care behaviors among people with diabetes. We demonstrated how a discrete-choice experiment was used to determine the features of a text-messaging intervention that are important to urban, low-income Latino patients with diabetes and that could support improvement in their physical activity behavior. In a discrete-choice experiment from December 2014 through August 2015 we conducted a survey to elicit information on patient preferences for 5 features of a text-messaging intervention. We described 2 hypothetical interventions and in 7 pairwise comparisons asked respondents to indicate which they preferred. Respondents (n = 125) were recruited in person from a diabetes management program of a safety-net ambulatory care clinic in Los Angeles; clinicians referred patients to the research assistant after routine clinic visits. Data were analyzed by using conditional logistic regression. We found 2 intervention features that were considered by the survey respondents to be important: 1) the frequency of text messaging and 2) physical activity behavior-change education (the former being more important than the latter). Physical activity goal setting, feedback on physical activity performance, and social support were not significantly important. A discrete-choice experiment is a feasible way to elicit information on patient preferences for a text-messaging intervention designed to support behavior change. However, discrepancies may exist between patients' stated preferences and their actual behavior. Future research should validate and expand our findings.

Interactions between hyporheic flow produced by stream meanders, bars, and dunes

USGS Publications Warehouse

Stonedahl, Susa H.; Harvey, Judson W.; Packman, Aaron I.

2013-01-01

Stream channel morphology from grain-scale roughness to large meanders drives hyporheic exchange flow. In practice, it is difficult to model hyporheic flow over the wide spectrum of topographic features typically found in rivers. As a result, many studies only characterize isolated exchange processes at a single spatial scale. In this work, we simulated hyporheic flows induced by a range of geomorphic features including meanders, bars and dunes in sand bed streams. Twenty cases were examined with 5 degrees of river meandering. Each meandering river model was run initially without any small topographic features. Models were run again after superimposing only bars and then only dunes, and then run a final time after including all scales of topographic features. This allowed us to investigate the relative importance and interactions between flows induced by different scales of topography. We found that dunes typically contributed more to hyporheic exchange than bars and meanders. Furthermore, our simulations show that the volume of water exchanged and the distributions of hyporheic residence times resulting from various scales of topographic features are close to, but not linearly additive. These findings can potentially be used to develop scaling laws for hyporheic flow that can be widely applied in streams and rivers.

Mysticism and schizophrenia: A phenomenological exploration of the structure of consciousness in the schizophrenia spectrum disorders.

PubMed

Parnas, Josef; Henriksen, Mads Gram

2016-07-01

Mysticism and schizophrenia are different categories of human existence and experience. Nonetheless, they exhibit important phenomenological affinities, which, however, remain largely unaddressed. In this study, we explore structural analogies between key features of mysticism and major clinical-phenomenological aspects of the schizophrenia spectrum disorders-i.e. attitudes, the nature of experience, and the 'other', mystical or psychotic reality. Not only do these features gravitate around the issue of the basic dimensions of consciousness, they crucially seem to implicate and presuppose a specific alteration of the very structure of consciousness. This finding has bearings for the understanding of consciousness and its psychopathological distortions. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Gstruct: a system for extracting schemas from GML documents

NASA Astrophysics Data System (ADS)

Chen, Hui; Zhu, Fubao; Guan, Jihong; Zhou, Shuigeng

2008-10-01

Geography Markup Language (GML) becomes the de facto standard for geographic information representation on the internet. GML schema provides a way to define the structure, content, and semantic of GML documents. It contains useful structural information of GML documents and plays an important role in storing, querying and analyzing GML data. However, GML schema is not mandatory, and it is common that a GML document contains no schema. In this paper, we present Gstruct, a tool for GML schema extraction. Gstruct finds the features in the input GML documents, identifies geometry datatypes as well as simple datatypes, then integrates all these features and eliminates improper components to output the optimal schema. Experiments demonstrate that Gstruct is effective in extracting semantically meaningful schemas from GML documents.

A roadmap of clustering algorithms: finding a match for a biomedical application.

PubMed

Andreopoulos, Bill; An, Aijun; Wang, Xiaogang; Schroeder, Michael

2009-05-01

Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline algorithms' benefits and drawbacks as a basis for matching them to biomedical applications.

Spondyloenchondrodysplasia: a rare cause of short stature.

PubMed

Yeşiltepe-Mutlu, Gül; Ozsu, Elif; Cizmecioğlu, Filiz Mine; Alanay, Yasemin; Hatun, Sükrü

2011-01-01

Skeletal dysplasias (osteochondrodysplasias) are a group of diseases that must be included in the differential diagnosis of disproportionate short stature. History, clinical and radiologic findings and consanguinity are important features to be considered when a specific diagnosis is investigated. Spondyloenchondrodysplasia is a very rare skeletal dysplasia characterized with enchondromas in the long bones and platyspondyly. Manifestation of the disorder may include neurological involvement (spasticity, intracranial calcifications and mental retardation) and immune dysfunction. Herein, we report a 12-year-old boy who admitted to our clinic with short stature, who was born to consanguineous parents. He presented clinical (significant widening of wrists, ankles and knees) and radiologic (enchondromatous lesions in the metaphysis of long bones) features of spondyloenchondrodysplasia but did not yet have neurologic or immunologic involvement.

The role of aging in intra-item and item-context binding processes in visual working memory.

PubMed

Peterson, Dwight J; Naveh-Benjamin, Moshe

2016-11-01

Aging is accompanied by declines in both working memory and long-term episodic memory processes. Specifically, important age-related memory deficits are characterized by performance impairments exhibited by older relative to younger adults when binding distinct components into a single integrated representation, despite relatively intact memory for the individual components. While robust patterns of age-related binding deficits are prevalent in studies of long-term episodic memory, observations of such deficits in visual working memory (VWM) may depend on the specific type of binding process being examined. For instance, a number of studies indicate that processes involved in item-context binding of items to occupied spatial locations within visual working memory are impaired in older relative to younger adults. Other findings suggest that intra-item binding of visual surface features (e.g., color, shape), compared to memory for single features, within visual working memory, remains relatively intact. Here, we examined each of these binding processes in younger and older adults under both optimal conditions (i.e., no concurrent load) and concurrent load (e.g., articulatory suppression, backward counting). Experiment 1 revealed an age-related intra-item binding deficit for surface features under no concurrent load but not when articulatory suppression was required. In contrast, in Experiments 2 and 3, we observed an age-related item-context binding deficit regardless of the level of concurrent load. These findings reveal that the influence of concurrent load on distinct binding processes within VWM, potentially those supported by rehearsal, is an important factor mediating the presence or absence of age-related binding deficits within VWM. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

PubMed

Zhang, Yang; Rockett, Peter I

2009-01-01

In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

Reproducibility of radiomics for deciphering tumor phenotype with imaging

NASA Astrophysics Data System (ADS)

Zhao, Binsheng; Tan, Yongqiang; Tsai, Wei-Yann; Qi, Jing; Xie, Chuanmiao; Lu, Lin; Schwartz, Lawrence H.

2016-03-01

Radiomics (radiogenomics) characterizes tumor phenotypes based on quantitative image features derived from routine radiologic imaging to improve cancer diagnosis, prognosis, prediction and response to therapy. Although radiomic features must be reproducible to qualify as biomarkers for clinical care, little is known about how routine imaging acquisition techniques/parameters affect reproducibility. To begin to fill this knowledge gap, we assessed the reproducibility of a comprehensive, commonly-used set of radiomic features using a unique, same-day repeat computed tomography data set from lung cancer patients. Each scan was reconstructed at 6 imaging settings, varying slice thicknesses (1.25 mm, 2.5 mm and 5 mm) and reconstruction algorithms (sharp, smooth). Reproducibility was assessed using the repeat scans reconstructed at identical imaging setting (6 settings in total). In separate analyses, we explored differences in radiomic features due to different imaging parameters by assessing the agreement of these radiomic features extracted from the repeat scans reconstructed at the same slice thickness but different algorithms (3 settings in total). Our data suggest that radiomic features are reproducible over a wide range of imaging settings. However, smooth and sharp reconstruction algorithms should not be used interchangeably. These findings will raise awareness of the importance of properly setting imaging acquisition parameters in radiomics/radiogenomics research.

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection.

PubMed

Kumar Myakalwar, Ashwin; Spegazzini, Nicolas; Zhang, Chi; Kumar Anubham, Siva; Dasari, Ramachandra R; Barman, Ishan; Kumar Gundawar, Manoj

2015-08-19

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the 'curse of dimensionality' have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers -based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations.

Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization

PubMed Central

Adam, Asrul; Mohd Tumari, Mohd Zaidi; Mohamad, Mohd Saberi

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection

PubMed Central

Kumar Myakalwar, Ashwin; Spegazzini, Nicolas; Zhang, Chi; Kumar Anubham, Siva; Dasari, Ramachandra R.; Barman, Ishan; Kumar Gundawar, Manoj

2015-01-01

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the ‘curse of dimensionality’ have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers –based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations. PMID:26286630

On the structure of Bayesian network for Indonesian text document paraphrase identification

NASA Astrophysics Data System (ADS)

Prayogo, Ario Harry; Syahrul Mubarok, Mohamad; Adiwijaya

2018-03-01

Paraphrase identification is an important process within natural language processing. The idea is to automatically recognize phrases that have different forms but contain same meanings. For examples if we input query “causing fire hazard”, then the computer has to recognize this query that this query has same meaning as “the cause of fire hazard. Paraphrasing is an activity that reveals the meaning of an expression, writing, or speech using different words or forms, especially to achieve greater clarity. In this research we will focus on classifying two Indonesian sentences whether it is a paraphrase to each other or not. There are four steps in this research, first is preprocessing, second is feature extraction, third is classifier building, and the last is performance evaluation. Preprocessing consists of tokenization, non-alphanumerical removal, and stemming. After preprocessing we will conduct feature extraction in order to build new features from given dataset. There are two kinds of features in the research, syntactic features and semantic features. Syntactic features consist of normalized levenshtein distance feature, term-frequency based cosine similarity feature, and LCS (Longest Common Subsequence) feature. Semantic features consist of Wu and Palmer feature and Shortest Path Feature. We use Bayesian Networks as the method of training the classifier. Parameter estimation that we use is called MAP (Maximum A Posteriori). For structure learning of Bayesian Networks DAG (Directed Acyclic Graph), we use BDeu (Bayesian Dirichlet equivalent uniform) scoring function and for finding DAG with the best BDeu score, we use K2 algorithm. In evaluation step we perform cross-validation. The average result that we get from testing the classifier as follows: Precision 75.2%, Recall 76.5%, F1-Measure 75.8% and Accuracy 75.6%.

Titan's surface from the Cassini RADAR radiometry data during SAR mode

USGS Publications Warehouse

Paganelli, F.; Janssen, M.A.; Lopes, R.M.; Stofan, E.; Wall, S.D.; Lorenz, R.D.; Lunine, J.I.; Kirk, R.L.; Roth, L.; Elachi, C.

2008-01-01

We present initial results on the calibration and interpretation of the high-resolution radiometry data acquired during the Synthetic Aperture Radar (SAR) mode (SAR-radiometry) of the Cassini Radar Mapper during its first five flybys of Saturn's moon Titan. We construct maps of the brightness temperature at the 2-cm wavelength coincident with SAR swath imaging. A preliminary radiometry calibration shows that brightness temperature in these maps varies from 64 to 89 K. Surface features and physical properties derived from the SAR-radiometry maps and SAR imaging are strongly correlated; in general, we find that surface features with high radar reflectivity are associated with radiometrically cold regions, while surface features with low radar reflectivity correlate with radiometrically warm regions. We examined scatterplots of the normalized radar cross-section ??0 versus brightness temperature, outlining signatures that characterize various terrains and surface features. The results indicate that volume scattering is important in many areas of Titan's surface, particularly Xanadu, while other areas exhibit complex brightness temperature variations consistent with variable slopes or surface material and compositional properties. ?? 2007.

Facial Expression Influences Face Identity Recognition During the Attentional Blink

PubMed Central

2014-01-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry—suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another. PMID:25286076

Family-based risk factors for non-suicidal self-injury: Considering influences of maltreatment, adverse family-life experiences, and parent-child relational risk.

PubMed

Martin, Jodi; Bureau, Jean-François; Yurkowski, Kim; Fournier, Tania Renaud; Lafontaine, Marie-France; Cloutier, Paula

2016-06-01

The current investigation addressed the potential for unique influences of perceived childhood maltreatment, adverse family-life events, and parent-child relational trauma on the lifetime occurrence and addictive features of non-suicidal self-injury (NSSI). Participants included 957 undergraduate students (747 females; M = 20.14 years, SD = 3.88) who completed online questionnaires regarding the key variables under study. Although self-injuring youth reported more experiences with each family-based risk factor, different patterns of association were found when lifetime engagement in NSSI or its addictive features were under study. Perceived parent-child relational trauma was uniquely linked with NSSI behavior after accounting for perceived childhood maltreatment; adverse family-life events had an additional unique association. In contrast, perceived paternal maltreatment was uniquely related with NSSI's addictive features. Findings underline the importance of studying inter-related family-based risk factors of NSSI simultaneously for a comprehensive understanding of familial correlates of NSSI behavior and its underlying features. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Facial expression influences face identity recognition during the attentional blink.

PubMed

Bach, Dominik R; Schmidt-Daffy, Martin; Dolan, Raymond J

2014-12-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry-suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another.

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.

Marine Targets Classification in PolInSAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong; Ren, Lin

2014-11-01

In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then, A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

Marine Targets Classification in PolInSAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong; Ren, Lin

2014-11-01

In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then , A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

Interpersonal Factors in Understanding and Treating Posttraumatic Stress Disorder

PubMed Central

Markowitz, John C.; Milrod, Barbara; Bleiberg, Kathryn; Marshall, Randall D.

2010-01-01

Exposure to reminders of trauma underlies the theory and practice of most treatments for posttraumatic stress disorder (PTSD), yet exposure may not be the sole important treatment mechanism. Interpersonal features of PTSD influence its onset, chronicity, and possibly its treatment. The authors review interpersonal factors in PTSD, including the critical but underrecognized role of social support as both protective posttrauma and as a mechanism of recovery. They discuss interpersonal psychotherapy (IPT) as an alternative treatment for PTSD and present encouraging findings from two initial studies. Highlighting the potential importance of attachment and interpersonal relationships, the authors propose a mechanism to explain why improving relationships may ameliorate PTSD symptoms. PMID:19339847

Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN

PubMed Central

Zhu, Lianzhang; Chen, Leiming; Zhao, Dehai

2017-01-01

Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy. By comparing statistical features with deep features extracted by a Deep Belief Network (DBN), we attempt to find the best features to identify the emotion status for speech. We propose a novel classification method that combines DBN and SVM (support vector machine) instead of using only one of them. In addition, a conjugate gradient method is applied to train DBN in order to speed up the training process. Gender-dependent experiments are conducted using an emotional speech database created by the Chinese Academy of Sciences. The results show that DBN features can reflect emotion status better than artificial features, and our new classification approach achieves an accuracy of 95.8%, which is higher than using either DBN or SVM separately. Results also show that DBN can work very well for small training databases if it is properly designed. PMID:28737705

PREAL: prediction of allergenic protein by maximum Relevance Minimum Redundancy (mRMR) feature selection

PubMed Central

2013-01-01

Background Assessment of potential allergenicity of protein is necessary whenever transgenic proteins are introduced into the food chain. Bioinformatics approaches in allergen prediction have evolved appreciably in recent years to increase sophistication and performance. However, what are the critical features for protein's allergenicity have been not fully investigated yet. Results We presented a more comprehensive model in 128 features space for allergenic proteins prediction by integrating various properties of proteins, such as biochemical and physicochemical properties, sequential features and subcellular locations. The overall accuracy in the cross-validation reached 93.42% to 100% with our new method. Maximum Relevance Minimum Redundancy (mRMR) method and Incremental Feature Selection (IFS) procedure were applied to obtain which features are essential for allergenicity. Results of the performance comparisons showed the superior of our method to the existing methods used widely. More importantly, it was observed that the features of subcellular locations and amino acid composition played major roles in determining the allergenicity of proteins, particularly extracellular/cell surface and vacuole of the subcellular locations for wheat and soybean. To facilitate the allergen prediction, we implemented our computational method in a web application, which can be available at http://gmobl.sjtu.edu.cn/PREAL/index.php. Conclusions Our new approach could improve the accuracy of allergen prediction. And the findings may provide novel insights for the mechanism of allergies. PMID:24565053

Assessment of club patrons' alcohol and drug use: the use of biological markers.

PubMed

Miller, Brenda A; Byrnes, Hilary F; Branner, Amy C; Voas, Robert; Johnson, Mark B

2013-11-01

Young adulthood (ages 18-25 years) represents a time when high-risk behaviors, including alcohol and drug use, peak. Electronic music dance events (EMDEs) featured at clubs provide an ecologic niche for these high-risk behaviors. This paper examines the prevalence of alcohol and drug use among EMDE patrons. Examination of personal characteristics associated with exit levels of alcohol and drug use identifies important indicators of risk taking for prevention strategies. Data were collected anonymously during 2010-2012 from 2028 patrons as they entered and exited clubs in the San Francisco Bay area featuring EMDEs. Nearly half were aged ≤25 years. Biological measures of drug and alcohol and self-reported personal characteristics were attained. Analyses were completed in 2012. At entrance, more than one fifth of patrons were positive for drug use and one fourth arrived either impaired (blood alcohol concentration [BAC]: 0.05%-0.079%) or intoxicated (BAC: >0.08%) by alcohol. At exit, one fourth tested positive for drugs, and nearly half were impaired or intoxicated by alcohol. Individual characteristics that were important for levels of risk included prior alcohol use behaviors, sexual identity, ethnic/racial identity, and transportation to the event. Gender did not differentiate for alcohol use but fewer women used drugs. Findings confirm the importance of targeting EMDEs for prevention efforts. EMDEs attract young working adults who are engaged in heavy alcohol and/or drug use. Targeting these social settings for delivering public health prevention strategies regarding alcohol and drug use and related harm is indicated by the findings. © 2013 American Journal of Preventive Medicine.

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.

High Resolution N-Body Simulations of Terrestrial Planet Growth

NASA Astrophysics Data System (ADS)

Clark Wallace, Spencer; Quinn, Thomas R.

2018-04-01

We investigate planetesimal accretion with a direct N-body simulation of an annulus at 1 AU around a 1 M_sun star. The planetesimal ring, which initially contains N = 106 bodies is evolved through the runaway growth stage into the phase of oligarchic growth. We find that the mass distribution of planetesimals develops a bump around 1022 g shortly after the oligarchs form. This feature is absent in previous lower resolution studies. We find that this bump marks a boundary between growth modes. Below the bump mass, planetesimals are packed tightly enough together to populate first order mean motion resonances with the oligarchs. These resonances act to heat the tightly packed, low mass planetesimals, inhibiting their growth. We examine the eccentricity evolution of a dynamically hot planetary embryo embedded in an annulus of planetesimals and find that dynamical friction acts more strongly on the embryo when the planetesimals are finely resolved. This effect disappears when the annulus is made narrow enough to exclude most of the mean motion resonances. Additionally, we find that the 1022 g bump is significantly less prominent when we follow planetesimal growth with a skinny annulus.This feature, which is reminiscent of the power law break seen in the size distribution of asteroid belt objects may be an important clue for constraining the initial size of planetesimals in planet formation models.

Evidence of semantic processing impairments in behavioural variant frontotemporal dementia and Parkinson's disease.

PubMed

Cousins, Katheryn A Q; Grossman, Murray

2017-12-01

Category-specific impairments caused by brain damage can provide important insights into how semantic concepts are organized in the brain. Recent research has demonstrated that disease to sensory and motor cortices can impair perceptual feature knowledge important to the representation of semantic concepts. This evidence supports the grounded cognition theory of semantics, the view that lexical knowledge is partially grounded in perceptual experience and that sensory and motor regions support semantic representations. Less well understood, however, is how heteromodal semantic hubs work to integrate and process semantic information. Although the majority of semantic research to date has focused on how sensory cortical areas are important for the representation of semantic features, new research explores how semantic memory is affected by neurodegeneration in regions important for semantic processing. Here, we review studies that demonstrate impairments to abstract noun knowledge in behavioural variant frontotemporal degeneration (bvFTD) and to action verb knowledge in Parkinson's disease, and discuss how these deficits relate to disease of the semantic selection network. Findings demonstrate that semantic selection processes are supported by the left inferior frontal gyrus (LIFG) and basal ganglia, and that disease to these regions in bvFTD and Parkinson's disease can lead to categorical impairments for abstract nouns and action verbs, respectively.

Loop vertex expansion for higher-order interactions

NASA Astrophysics Data System (ADS)

Rivasseau, Vincent

2018-05-01

This note provides an extension of the constructive loop vertex expansion to stable interactions of arbitrarily high order, opening the way to many applications. We treat in detail the example of the (\\bar{φ } φ )^p field theory in zero dimension. We find that the important feature to extend the loop vertex expansion is not to use an intermediate field representation, but rather to force integration of exactly one particular field per vertex of the initial action.

USSR Report, Translations from Kommunist, Number 14, September 1984

DTIC Science & Technology

1985-01-15

feature films and television series, tastelessly made sculptures and canvases not only spoil the taste of millions of people, they discredit the...either heap compliments on a weak novel, play or film referring to the "importance of the subject," or take delight in the "aesthetic findings" of an...implemented to keep up employment. The Spanish government introduced a 40-hour work week, banned moonlighting and drafted plans for opening 800,000 new

Learning accurate and interpretable models based on regularized random forests regression

PubMed Central

2014-01-01

Background Many biology related research works combine data from multiple sources in an effort to understand the underlying problems. It is important to find and interpret the most important information from these sources. Thus it will be beneficial to have an effective algorithm that can simultaneously extract decision rules and select critical features for good interpretation while preserving the prediction performance. Methods In this study, we focus on regression problems for biological data where target outcomes are continuous. In general, models constructed from linear regression approaches are relatively easy to interpret. However, many practical biological applications are nonlinear in essence where we can hardly find a direct linear relationship between input and output. Nonlinear regression techniques can reveal nonlinear relationship of data, but are generally hard for human to interpret. We propose a rule based regression algorithm that uses 1-norm regularized random forests. The proposed approach simultaneously extracts a small number of rules from generated random forests and eliminates unimportant features. Results We tested the approach on some biological data sets. The proposed approach is able to construct a significantly smaller set of regression rules using a subset of attributes while achieving prediction performance comparable to that of random forests regression. Conclusion It demonstrates high potential in aiding prediction and interpretation of nonlinear relationships of the subject being studied. PMID:25350120

Discovering and visualizing indirect associations between biomedical concepts

PubMed Central

Tsuruoka, Yoshimasa; Miwa, Makoto; Hamamoto, Kaisei; Tsujii, Jun'ichi; Ananiadou, Sophia

2011-01-01

Motivation: Discovering useful associations between biomedical concepts has been one of the main goals in biomedical text-mining, and understanding their biomedical contexts is crucial in the discovery process. Hence, we need a text-mining system that helps users explore various types of (possibly hidden) associations in an easy and comprehensible manner. Results: This article describes FACTA+, a real-time text-mining system for finding and visualizing indirect associations between biomedical concepts from MEDLINE abstracts. The system can be used as a text search engine like PubMed with additional features to help users discover and visualize indirect associations between important biomedical concepts such as genes, diseases and chemical compounds. FACTA+ inherits all functionality from its predecessor, FACTA, and extends it by incorporating three new features: (i) detecting biomolecular events in text using a machine learning model, (ii) discovering hidden associations using co-occurrence statistics between concepts, and (iii) visualizing associations to improve the interpretability of the output. To the best of our knowledge, FACTA+ is the first real-time web application that offers the functionality of finding concepts involving biomolecular events and visualizing indirect associations of concepts with both their categories and importance. Availability: FACTA+ is available as a web application at http://refine1-nactem.mc.man.ac.uk/facta/, and its visualizer is available at http://refine1-nactem.mc.man.ac.uk/facta-visualizer/. Contact: tsuruoka@jaist.ac.jp PMID:21685059

Detecting spam comments on Indonesia’s Instagram posts

NASA Astrophysics Data System (ADS)

Septiandri, Ali Akbar; Wibisono, Okiriza

2017-01-01

In this paper we experimented with several feature sets for detecting spam comments in social media contents authored by Indonesian public figures. We define spam comments as comments which have promotional purposes (e.g. referring other users to products and services) and thus not related to the content to which the comments are posted. Three sets of features are evaluated for detecting spams: (1) hand-engineered features such as comment length, number of capital letters, and number of emojis, (2) keyword features such as whether the comment contains advertising words or product-related words, and (3) text features, namely, bag-of-words, TF-IDF, and fastText embeddings, each combined with latent semantic analysis. With 24,000 manually-annotated comments scraped from Instagram posts authored by more than 100 Indonesian public figures, we compared the performance of these feature sets and their combinations using 3 popular classification algorithms: Na¨ıve Bayes, SVM, and XGBoost. We find that using all three feature sets (with fastText embedding for the text features) gave the best F 1-score of 0.9601 on a holdout dataset. More interestingly, fastText embedding combined with hand-engineered features (i.e. without keyword features) yield similar F 1-score of 0.9523, and McNemar’s test failed to reject the hypothesis that the two results are not significantly different. This result is important as keyword features are largely dependent on the dataset and may not be as generalisable as the other feature sets when applied to new data. For future work, we hope to collect bigger and more diverse dataset of Indonesian spam comments, improve our model’s performance and generalisability, and publish a programming package for others to reliably detect spam comments.

A Cross-Sectional Investigation of the Importance of Park Features for Promoting Regular Physical Activity in Parks.

PubMed

Costigan, Sarah A; Veitch, Jenny; Crawford, David; Carver, Alison; Timperio, Anna

2017-11-02

Parks in the US and Australia are generally underutilised, and park visitors typically engage in low levels of physical activity (PA). Better understanding park features that may encourage visitors to be active is important. This study examined the perceived importance of park features for encouraging park-based PA and examined differences by sex, age, parental-status and participation in PA. Cross-sectional surveys were completed by local residents ( n = 2775) living near two parks (2013/2015). Demographic variables, park visitation and leisure-time PA were self-reported, respondents rated the importance of 20 park features for encouraging park-based PA in the next fortnight. Chi-square tests of independence examined differences in importance of park features for PA among sub-groups of local residents (sex, age, parental-status, PA). Park features ranked most important for park-based PA were: well maintained (96.2%), feel safe (95.4%), relaxing atmosphere (91.2%), easy to get to (91.7%), and shady trees (90.3%). All subgroups ranked 'well maintained' as most important. Natural and built environment features of parks are important for promoting adults' park-based PA, and should be considered in park (re)design.

Motivation to study dental professions in one London Dental Institute.

PubMed

Belsi, A; Asimakopoulou, K; Donaldson, N; Gallagher, J

2014-02-01

While past research has explored dental students' motivation to study, there is limited understanding in the reasons behind career choice for hygienists/therapists and dental nurses. The aim of this study was to investigate simultaneously the views of students of dentistry, hygiene/therapy and dental nursing in King's College London and explore similarities or differences in career choice. All first-year students were invited to the questionnaire survey, exploring motivation to study using a 23-item instrument. Data were analysed using SPSS v18; statistical analysis included one-way analyses of variance and factor analysis. The overall response rate to the study was 75% (n = 209). Ten out of 23 factors were considered important by more than 80% of respondents, with 'job security' (93.8%), 'desire to work with people' (88%) and 'degree leading to recognised job' (87.5%) being top three. Analysis suggested that 52% of the total variation in motivating influences was explained by four factors: 'features of the job' (26%), 'education/skills' (11%), 'public service' (8%) and 'careers-advising' (7%); at group level 'features of the job' were significantly more important for the direct entrants to dentistry (P = 0.001). The findings suggest that across groups students were motivated to study by common influences reflecting altruistic, but also pragmatic and realistic motives, while 'features of the job' were more important for the direct entrants to dentistry. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Modeling time-series count data: the unique challenges facing political communication studies.

PubMed

Fogarty, Brian J; Monogan, James E

2014-05-01

This paper demonstrates the importance of proper model specification when analyzing time-series count data in political communication studies. It is common for scholars of media and politics to investigate counts of coverage of an issue as it evolves over time. Many scholars rightly consider the issues of time dependence and dynamic causality to be the most important when crafting a model. However, to ignore the count features of the outcome variable overlooks an important feature of the data. This is particularly the case when modeling data with a low number of counts. In this paper, we argue that the Poisson autoregressive model (Brandt and Williams, 2001) accurately meets the needs of many media studies. We replicate the analyses of Flemming et al. (1997), Peake and Eshbaugh-Soha (2008), and Ura (2009) and demonstrate that models missing some of the assumptions of the Poisson autoregressive model often yield invalid inferences. We also demonstrate that the effect of any of these models can be illustrated dynamically with estimates of uncertainty through a simulation procedure. The paper concludes with implications of these findings for the practical researcher. Copyright © 2013 Elsevier Inc. All rights reserved.

Sporotrichosis: an update.

PubMed

Bonifaz, A; Vázquez-González, D

2010-10-01

Sporotrichosis is the most frequent and worldwide distributed subcutaneous mycoses. The aim of this article is to review the most recent aspects of sporotrichosis about its epidemiology, etiologic agents, mycologic characteristics, clinical features, diagnosis and treatment. The causative agents of sporotrichosis belong to five well defined species of dimorphic fungi of the called Sporothrix schenckii complex. Sporotrichosis and its etiologic agents have specific endemic areas, but it is possible to find epidemics of the disease in practically every continent, the entrance via is cutaneous due to the inoculation of the fungi into the skin after a traumatism and less frequent due to respiratory way. Clinical manifestations are widely variable, with important involvement of the skin and the superficial lymphatic system, but also with affection of the mucosa and some organs like lungs, bones and joints. Nowadays sporotrichosis is considered a true zoonosis with important changes related to the endemic areas and the ecologic features of the causative pathogens. The therapy of choice is the potassium iodide (KI), but other alternatives are itraconazole, terbinafine, thermotherapy and in severe cases amphotericin B. The importance of the recognition of the clinical manifestations of the disease in some non-endemic areas helps to challenge the diagnosis and give an accurate therapy.

Chimaeric sounds reveal dichotomies in auditory perception

PubMed Central

Smith, Zachary M.; Delgutte, Bertrand; Oxenham, Andrew J.

2008-01-01

By Fourier's theorem1, signals can be decomposed into a sum of sinusoids of different frequencies. This is especially relevant for hearing, because the inner ear performs a form of mechanical Fourier transform by mapping frequencies along the length of the cochlear partition. An alternative signal decomposition, originated by Hilbert2, is to factor a signal into the product of a slowly varying envelope and a rapidly varying fine time structure. Neurons in the auditory brainstem3–6 sensitive to these features have been found in mammalian physiological studies. To investigate the relative perceptual importance of envelope and fine structure, we synthesized stimuli that we call ‘auditory chimaeras’, which have the envelope of one sound and the fine structure of another. Here we show that the envelope is most important for speech reception, and the fine structure is most important for pitch perception and sound localization. When the two features are in conflict, the sound of speech is heard at a location determined by the fine structure, but the words are identified according to the envelope. This finding reveals a possible acoustic basis for the hypothesized ‘what’ and ‘where’ pathways in the auditory cortex7–10. PMID:11882898

The regional cerebral blood flow changes in major depressive disorder with and without psychotic features.

PubMed

Gonul, Ali Saffet; Kula, Mustafa; Bilgin, Arzu Guler; Tutus, Ahmet; Oguz, Aslan

2004-09-01

Depressive patients with psychotic features demonstrate distinct biological abnormalities in the hypothalamic-pituitary-adrenal axis (HPA), dopaminergic activity, electroencephalogram sleep profiles and measures of serotonergic function when compared to nonpsychotic depressive patients. However, very few functional neuroimaging studies were specifically designed for studying the effects of psychotic features on neuroimaging findings in depressed patients. The objective of the present study was to compare brain Single Photon Emission Tomography (SPECT) images in a group of unmedicated depressive patients with and without psychotic features. Twenty-eight patients who fully met DSM-IV criteria for major depressive disorder (MDD, 12 had psychotic features) were included in the study. They were compared with 16 control subjects matched for age, gender and education. Both psychotic and nonpsychotic depressed patients showed significantly lower regional cerebral blood flow (rCBF) values in the left and right superior frontal cortex, and left anterior cingulate cortex compared to those of controls. In comparison with depressive patients without psychotic features (DwoPF), depressive patients with psychotic features (DwPF) showed significantly lower rCBF perfusion ratios in left parietal cortex, left cerebellum but had higher rCBF perfusion ratio in the left inferior frontal cortex and caudate nucleus. The present study showed that DwPF have a different rCBF pattern compared to patients without psychotic features. Abnormalities involving inferior frontal cortex, striatum and cerebellum may play an important role in the generation of psychotic symptoms in depression.

Combined texture feature analysis of segmentation and classification of benign and malignant tumour CT slices.

PubMed

Padma, A; Sukanesh, R

2013-01-01

A computer software system is designed for the segmentation and classification of benign from malignant tumour slices in brain computed tomography (CT) images. This paper presents a method to find and select both the dominant run length and co-occurrence texture features of region of interest (ROI) of the tumour region of each slice to be segmented by Fuzzy c means clustering (FCM) and evaluate the performance of support vector machine (SVM)-based classifiers in classifying benign and malignant tumour slices. Two hundred and six tumour confirmed CT slices are considered in this study. A total of 17 texture features are extracted by a feature extraction procedure, and six features are selected using Principal Component Analysis (PCA). This study constructed the SVM-based classifier with the selected features and by comparing the segmentation results with the experienced radiologist labelled ground truth (target). Quantitative analysis between ground truth and segmented tumour is presented in terms of segmentation accuracy, segmentation error and overlap similarity measures such as the Jaccard index. The classification performance of the SVM-based classifier with the same selected features is also evaluated using a 10-fold cross-validation method. The proposed system provides some newly found texture features have an important contribution in classifying benign and malignant tumour slices efficiently and accurately with less computational time. The experimental results showed that the proposed system is able to achieve the highest segmentation and classification accuracy effectiveness as measured by jaccard index and sensitivity and specificity.

The relations between inadequate parent-child boundaries and borderline personality disorder in adolescence.

PubMed

Vanwoerden, Salome; Kalpakci, Allison; Sharp, Carla

2017-11-01

Borderline Personality Disorder (BPD) is a severe mental illness that onsets in adolescence. Research has demonstrated the central role of parent-child relationships for the development and maintenance of BPD although more research is necessary to clarify the specific dynamics that relate to BPD during adolescence. Based on preliminary research establishing the importance of parent-child boundaries for adolescent BPD, this study sought to evaluate the relations between different forms of inadequate boundaries and BPD in adolescence using a multi-method approach. To that end, 301 adolescents (65.1% female; ages 12-17) inpatients were recruited; parents and adolescents completed questionnaire- and interview-based measures of BPD features in adolescent children and a questionnaire-based measure of parent-child boundaries. Relations were found between parental guilt induction and psychological control with children's BPD features above and beyond relations with psychiatric severity and gender. Relations between parent reports of triangulation (when children are recruited to mediate parental marital conflict) and children's BPD were contingent on the level of children's perceptions of triangulation. Findings confirm previous research suggesting the relevance of inadequate parent-child boundaries to children's BPD features and have important implications for understanding the dynamics in families with adolescents with BPD, representing a relevant treatment target. Copyright © 2017 Elsevier B.V. All rights reserved.

Exploring cognitive integration of basic science and its effect on diagnostic reasoning in novices.

PubMed

Lisk, Kristina; Agur, Anne M R; Woods, Nicole N

2016-06-01

Integration of basic and clinical science knowledge is increasingly being recognized as important for practice in the health professions. The concept of 'cognitive integration' places emphasis on the value of basic science in providing critical connections to clinical signs and symptoms while accounting for the fact that clinicians may not spontaneously articulate their use of basic science knowledge in clinical reasoning. In this study we used a diagnostic justification test to explore the impact of integrated basic science instruction on novices' diagnostic reasoning process. Participants were allocated to an integrated basic science or clinical science training group. The integrated basic science group was taught the clinical features along with the underlying causal mechanisms of four musculoskeletal pathologies while the clinical science group was taught only the clinical features. Participants completed a diagnostic accuracy test immediately after initial learning, and one week later a diagnostic accuracy and justification test. The results showed that novices who learned the integrated causal mechanisms had superior diagnostic accuracy and better understanding of the relative importance of key clinical features. These findings further our understanding of cognitive integration by providing evidence of the specific changes in clinical reasoning when basic and clinical sciences are integrated during learning.

In-process and post-process measurements of drill wear for control of the drilling process

NASA Astrophysics Data System (ADS)

Liu, Tien-I.; Liu, George; Gao, Zhiyu

2011-12-01

Optical inspection was used in this research for the post-process measurements of drill wear. A precision toolmakers" microscope was used. Indirect index, cutting force, is used for in-process drill wear measurements. Using in-process measurements to estimate the drill wear for control purpose can decrease the operation cost and enhance the product quality and safety. The challenge is to correlate the in-process cutting force measurements with the post-process optical inspection of drill wear. To find the most important feature, the energy principle was used in this research. It is necessary to select only the cutting force feature which shows the highest sensitivity to drill wear. The best feature selected is the peak of torque in the drilling process. Neuro-fuzzy systems were used for correlation purposes. The Adaptive-Network-Based Fuzzy Inference System (ANFIS) can construct fuzzy rules with membership functions to generate an input-output pair. A 1x6 ANFIS architecture with product of sigmoid membership functions can in-process measure the drill wear with an error as low as 0.15%. This is extremely important for control of the drilling process. Furthermore, the measurement of drill wear was performed under different drilling conditions. This shows that ANFIS has the capability of generalization.

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

Berres, Anne Sabine

This slide presentation describes basic topological concepts, including topological spaces, homeomorphisms, homotopy, betti numbers. Scalar field topology explores finding topological features and scalar field visualization, and vector field topology explores finding topological features and vector field visualization.

Biomarkers and Imaging Findings of Anderson–Fabry Disease—What We Know Now

PubMed Central

Beirão, Idalina; Cabrita, Ana; Torres, Márcia; Silva, Fernando; Aguiar, Patrício; Laranjeira, Francisco; Gomes, Ana Marta

2017-01-01

Anderson–Fabry disease (AFD) is an X-linked lysosomal storage disorder, caused by deficiency or absence of the alpha-galactosidase A activity, with a consequent glycosphingolipid accumulation. Biomarkers and imaging findings may be useful for diagnosis, identification of an organ involvement, therapy monitoring and prognosis. The aim of this article is to review the current available literature on biomarkers and imaging findings of AFD patients. An extensive bibliographic review from PubMed, Medline and Clinical Key databases was performed by a group of experts from nephrology, neurology, genetics, cardiology and internal medicine, aiming for consensus. Lyso-GB3 is a valuable biomarker to establish the diagnosis. Proteinuria and creatinine are the most valuable to detect renal damage. Troponin I and high-sensitivity assays for cardiac troponin T can identify patients with cardiac lesions, but new techniques of cardiac imaging are essential to detect incipient damage. Specific cerebrovascular imaging findings are present in AFD patients. Techniques as metabolomics and proteomics have been developed in order to find an AFD fingerprint. Lyso-GB3 is important for evaluating the pathogenic mutations and monitoring the response to treatment. Many biomarkers can detect renal, cardiac and cerebrovascular involvement, but none of these have proved to be important to monitoring the response to treatment. Imaging features are preferred in order to find cardiac and cerebrovascular compromise in AFD patients. PMID:28933368

Jackpot Structural Features: Rollover Effect and Goal-Gradient Effect in EGM Gambling.

PubMed

Li, En; Rockloff, Matthew J; Browne, Matthew; Donaldson, Phillip

2016-06-01

Relatively little research has been undertaken on the influence of jackpot structural features on electronic gaming machine (EGM) gambling behavior. This study considered two common features of EGM jackpots: progressive (i.e., the jackpot incrementally growing in value as players make additional bets), and deterministic (i.e., a guaranteed jackpot after a fixed number of bets, which is determined in advance and at random). Their joint influences on player betting behavior and the moderating role of jackpot size were investigated in a crossed-design experiment. Using real money, players gambled on a computer simulated EGM with real jackpot prizes of either $500 (i.e., small jackpot) or $25,000 (i.e., large jackpot). The results revealed three important findings. Firstly, players placed the largest bets (20.3 % higher than the average) on large jackpot EGMs that were represented to be deterministic and non-progressive. This finding was supportive of a hypothesized 'goal-gradient effect', whereby players might have felt subjectively close to an inevitable payoff for a high-value prize. Secondly, large jackpots that were non-deterministic and progressive also promoted high bet sizes (17.8 % higher than the average), resembling the 'rollover effect' demonstrated in lottery betting, whereby players might imagine that their large bets could be later recouped through a big win. Lastly, neither the hypothesized goal-gradient effect nor the rollover effect was evident among players betting on small jackpot machines. These findings suggest that certain high-value jackpot configurations may have intensifying effects on player behavior.

Phosphaturic mesenchymal tumour mixed connective tissue variant: report of three cases with unusual histological findings.

PubMed

Shustik, David A; Ng, David Ce; Sittampalam, Kesavan

2015-01-01

Phosphaturic mesenchymal tumour mixed connective tissue variant (PMTMCT) is a rare tumour occurring in bone and soft tissue that usually behaves in a benign manner. Elaboration of biologically active substances by this tumour gives rise to a paraneoplastic syndrome known as oncogenic osteomalacia, manifesting clinically as bone pain, generalized weakness and pathological fractures. Recognition of PMTMCT and its associated syndrome is important, as resection of the tumour in most instances results in prompt resolution of symptoms. Previously reported cases of this tumour have emphasized the consistent presence of certain histological features that are considered prerequisite for making the diagnosis of PMTMCT. We describe three cases of PMTMCT, of which two first presented with progressive symptoms of osteomalacia and one remained clinically silent aside from the symptom of a palpable lump. Our cases highlight the wide-ranging histological patterns displayed by these tumours, and draw attention to certain microscopic findings that until now have been given little if any mention. Tentacular growth pattern and satellite nodules appear to be common findings in PMTMCTs, and can make complete surgical excision of these tumours challenging. The ability of this otherwise histologically benign tumour to permeate vascular spaces has to our knowledge never been described previously. One tumour lacked the characteristic calcifying matrix of PMTMCT, suggesting that in some tumours this defining feature may be focal if not entirely absent. PMTMCT shares features with and can resemble a variety of bone and soft tissue neoplasms, requiring the surgical pathologist to be familiar with this entity.

Phosphaturic mesenchymal tumour mixed connective tissue variant: report of three cases with unusual histological findings

PubMed Central

Shustik, David A; Ng, David CE; Sittampalam, Kesavan

2015-01-01

Phosphaturic mesenchymal tumour mixed connective tissue variant (PMTMCT) is a rare tumour occurring in bone and soft tissue that usually behaves in a benign manner. Elaboration of biologically active substances by this tumour gives rise to a paraneoplastic syndrome known as oncogenic osteomalacia, manifesting clinically as bone pain, generalized weakness and pathological fractures. Recognition of PMTMCT and its associated syndrome is important, as resection of the tumour in most instances results in prompt resolution of symptoms. Previously reported cases of this tumour have emphasized the consistent presence of certain histological features that are considered prerequisite for making the diagnosis of PMTMCT. We describe three cases of PMTMCT, of which two first presented with progressive symptoms of osteomalacia and one remained clinically silent aside from the symptom of a palpable lump. Our cases highlight the wide-ranging histological patterns displayed by these tumours, and draw attention to certain microscopic findings that until now have been given little if any mention. Tentacular growth pattern and satellite nodules appear to be common findings in PMTMCTs, and can make complete surgical excision of these tumours challenging. The ability of this otherwise histologically benign tumour to permeate vascular spaces has to our knowledge never been described previously. One tumour lacked the characteristic calcifying matrix of PMTMCT, suggesting that in some tumours this defining feature may be focal if not entirely absent. PMTMCT shares features with and can resemble a variety of bone and soft tissue neoplasms, requiring the surgical pathologist to be familiar with this entity. PMID:26261662

Clinical features and laboratory findings of dengue fever in German travellers: A single-centre, retrospective analysis.

PubMed

Tavakolipoor, Pulad; Schmidt-Chanasit, Jonas; Burchard, Gerd Dieter; Jordan, Sabine

2016-01-01

Dengue fever (DF) is one of the most relevant human arboviral infections worldwide and has become a frequent cause of fever in the returning traveller. This retrospective study aimed to characterize epidemiological and clinical features and laboratory findings of dengue fever in German travellers. This descriptive study analyzed medical records of patients diagnosed with DF presenting at the Section of Tropical Medicine of the University Medical Centre Hamburg-Eppendorf from 2007 to 2011. Data were collected and analyzed retrospectively. In total, data of 119 DF patients (52 female, 67 male) were included in this study. The median age of the patients was 35 (range 15-75 years). DF was most frequently acquired in South-East Asia (n = 65; 54.7%), and in particular in Thailand (n = 23; 19.7%). A considerable percentage of DF infections (n = 14; 11.8%) was imported from Africa. Patients predominantly presented with fever, headache, rash, myalgia and arthralgia but also with gastrointestinal symptoms, i.e. diarrhoea. Nine patients showed signs of minor haemorrhagic manifestations. Neurological complications occurred in 13 patients. Low platelet count, leukopenia and elevated liver enzymes were the most relevant laboratory findings. Twenty patients (17.8%) had to be hospitalized. Overall, the clinical course was mostly mild to moderate, 13 patients (10.9%) showed DF warnings signs, no fatalities occurred. DF presented as a mostly mild to moderate disease in this study cohort. Outpatient treatment was adequate for the majority of patients. Still, detailed knowledge of clinical symptoms and laboratory features is essential for appropriate triage. Copyright © 2016 Elsevier Ltd. All rights reserved.

'I love my work, but ... ': the 'best' and the 'worst' in nurse educators' working life in Finland.

PubMed

Harri, M

1996-06-01

The aim of this study was to investigate nurse educators' perceptions of the quality of their working life. Questionnaires were sent to 706 Finnish nurse educators and their spouses or other adult living with them. The results concerning the structured part of the questionnaire have been described in detail in an earlier paper (Harri 1995). This paper describes the data collected by means of semi-structured questions from 477 (68%) educators and 409 (58%) spouses) and open-ended questions (309 nurse educators and 167 spouses), analysed using content analysis. The seven categories that were identified as the best features of work were, in descending order of prevalence: students, freedom, challenges, teaching, miscellaneous, colleagues, and physical environment. Among the worst features of work, workload ranked first, followed by inadequacy of personal resources, administrative issues, changes, interpersonal relationships, miscellaneous, and physical environment. In the open-ended comments the nurse educators used 400 expressions to describe positive features of their working life, while they used 597 expressions to describe negative features. The spouses made 90 positive comments about the working life of their teacher spouse, and 425 negative comments. The importance of this kind of study was remarked on quite frequently both by nurse educators (22%) and their spouses (12%). The study provides important clues to understanding the present reality of nurse educators' working life. It is hoped that the findings of the study will help focus attention on ways of developing the quality of nurse educators' working life.

What vehicle features are considered important when buying an automobile? An examination of driver preferences by age and gender.

PubMed

Vrkljan, Brenda H; Anaby, Dana

2011-02-01

Certain vehicle features can help drivers avoid collisions and/or protect occupants in the event of a crash, and therefore, might play an important role when deciding which vehicle to purchase. The objective of this study was to examine the importance attributed to key vehicle features (including safety) that drivers consider when buying a car and its association with age and gender. A sample of 2,002 Canadian drivers aged 18 years and older completed a survey that asked them to rank the importance of eight vehicle features if they were to purchase a vehicle (storage, mileage, safety, price, comfort, performance, design, and reliability). ANOVA tests were performed to: (a) determine if there were differences in the level of importance between features and; (b) examine the effect of age and gender on the importance attributed to these features. Of the features examined, safety and reliability were the most highly rated in terms of importance, whereas design and performance had the lowest rating. Differences in safety and performance across age groups were dependent on gender. This effect was most evident in the youngest and oldest age groups. Safety and reliability were considered the most important features. Age and gender play a significant role in explaining the importance of certain features. Targeted efforts for translating safety-related information to the youngest and oldest consumers should be emphasized due to their high collision, injury, and fatality rates. Copyright © 2011 National Safety Council and Elsevier Ltd. All rights reserved.

Blur Clarified: A review and Synthesis of Blur Discrimination

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Ahumada, Albert J.

2011-01-01

Blur is an important attribute of human spatial vision, and sensitivity to blur has been the subject of considerable experimental research and theoretical modeling. Often these models have invoked specialized concepts or mechanisms, such as intrinsic blur, multiple channels, or blur estimation units. In this paper we review the several experimental studies of blur discrimination and find they are in broad empirical agreement. But contrary to previous modeling efforts, we find that the essential features of blur discrimination are fully accounted for by a visible contrast energy model (ViCE), in which two spatial patterns are distinguished when the integrated difference between their masked local contrast energy responses reaches a threshold value.

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

Lessons Learned From Trials Targeting Cytokine Pathways in Patients With Inflammatory Bowel Diseases

PubMed Central

Abraham, Clara; Dulai, Parambir S.; Vermeire, Séverine; Sandborn, William J.

2016-01-01

Insights into the pathogenesis of inflammatory bowel diseases (IBD) have provided important information for the development of therapeutics. Levels of interleukin 23 (IL23) and T-helper (Th) 17 cell pathway molecules are elevated in inflamed intestinal tissues of patients with IBD. Loss of function variants of the interleukin 23 receptor gene (IL23R) protect against IBD, and in animals, blocking IL23 reduces severity of colitis. These findings indicated that the IL23 and Th17 cell pathways might be promising targets for treatment of IBD. Clinical trials have investigated the effects of agents designed to target distinct levels of the IL23 and Th17 cell pathways, and the results are providing insights into IBD pathogenesis and additional strategies for modulating these pathways. Strategies to reduce levels of proinflammatory cytokines more broadly and increase anti-inflammatory mechanisms are also emerging for treatment of IBD. The results from trials targeting these immune system pathways have provided important lessons for future trials. Findings indicate the importance of improving approaches to integrate patient features and biomarkers of response with selection of therapeutics. PMID:27780712

Task-dependent modulation of the visual sensory thalamus assists visual-speech recognition.

PubMed

Díaz, Begoña; Blank, Helen; von Kriegstein, Katharina

2018-05-14

The cerebral cortex modulates early sensory processing via feed-back connections to sensory pathway nuclei. The functions of this top-down modulation for human behavior are poorly understood. Here, we show that top-down modulation of the visual sensory thalamus (the lateral geniculate body, LGN) is involved in visual-speech recognition. In two independent functional magnetic resonance imaging (fMRI) studies, LGN response increased when participants processed fast-varying features of articulatory movements required for visual-speech recognition, as compared to temporally more stable features required for face identification with the same stimulus material. The LGN response during the visual-speech task correlated positively with the visual-speech recognition scores across participants. In addition, the task-dependent modulation was present for speech movements and did not occur for control conditions involving non-speech biological movements. In face-to-face communication, visual speech recognition is used to enhance or even enable understanding what is said. Speech recognition is commonly explained in frameworks focusing on cerebral cortex areas. Our findings suggest that task-dependent modulation at subcortical sensory stages has an important role for communication: Together with similar findings in the auditory modality the findings imply that task-dependent modulation of the sensory thalami is a general mechanism to optimize speech recognition. Copyright © 2018. Published by Elsevier Inc.

Long-term information and distributed neural activation are relevant for the "internal features advantage" in face processing: electrophysiological and source reconstruction evidence.

PubMed

Olivares, Ela I; Saavedra, Cristina; Trujillo-Barreto, Nelson J; Iglesias, Jaime

2013-01-01

In face processing tasks, prior presentation of internal facial features, when compared with external ones, facilitates the recognition of subsequently displayed familiar faces. In a previous ERP study (Olivares & Iglesias, 2010) we found a visibly larger N400-like effect when identity mismatch familiar faces were preceded by internal features, as compared to prior presentation of external ones. In the present study we contrasted the processing of familiar and unfamiliar faces in the face-feature matching task to assess whether the so-called "internal features advantage" relies mainly on the use of stored face-identity-related information or if it might operate independently from stimulus familiarity. Our participants (N = 24) achieved better performance with internal features as primes and, significantly, with familiar faces. Importantly, ERPs elicited by identity mismatch complete faces displayed a negativity around 300-600 msec which was clearly enhanced for familiar faces primed by internal features when compared with the other experimental conditions. Source reconstruction showed incremented activity elicited by familiar stimuli in both posterior (ventral occipitotemporal) and more anterior (parahippocampal (ParaHIP) and orbitofrontal) brain regions. The activity elicited by unfamiliar stimuli was, in general, located in more posterior regions. Our findings suggest that the activation of multiple neural codes is required for optimal individuation in face-feature matching and that a cortical network related to long-term information for face-identity processing seems to support the internal feature effect. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mental simulation of routes during navigation involves adaptive temporal compression

PubMed Central

Arnold, Aiden E.G.F.; Iaria, Giuseppe; Ekstrom, Arne D.

2016-01-01

Mental simulation is a hallmark feature of human cognition, allowing features from memories to be flexibly used during prospection. While past studies demonstrate the preservation of real-world features such as size and distance during mental simulation, their temporal dynamics remains unknown. Here, we compare mental simulations to navigation of routes in a large-scale spatial environment to test the hypothesis that such simulations are temporally compressed in an adaptive manner. Our results show that simulations occurred at 2.39x the speed it took to navigate a route, increasing in compression (3.57x) for slower movement speeds. Participant self-reports of vividness and spatial coherence of simulations also correlated strongly with simulation duration, providing an important link between subjective experiences of simulated events and how spatial representations are combined during prospection. These findings suggest that simulation of spatial events involve adaptive temporal mechanisms, mediated partly by the fidelity of memories used to generate the simulation. PMID:27568586

Field migration rates of tidal meanders recapitulate fluvial morphodynamics

NASA Astrophysics Data System (ADS)

Finotello, Alvise; Lanzoni, Stefano; Ghinassi, Massimiliano; Marani, Marco; Rinaldo, Andrea; D'Alpaos, Andrea

2018-02-01

The majority of tidal channels display marked meandering features. Despite their importance in oil-reservoir formation and tidal landscape morphology, questions remain on whether tidal-meander dynamics could be understood in terms of fluvial processes and theory. Key differences suggest otherwise, like the periodic reversal of landscape-forming tidal flows and the widely accepted empirical notion that tidal meanders are stable landscape features, in stark contrast with their migrating fluvial counterparts. On the contrary, here we show that, once properly normalized, observed migration rates of tidal and fluvial meanders are remarkably similar. Key to normalization is the role of tidal channel width that responds to the strong spatial gradients of landscape-forming flow rates and tidal prisms. We find that migration dynamics of tidal meanders agree with nonlinear theories for river meander evolution. Our results challenge the conventional view of tidal channels as stable landscape features and suggest that meandering tidal channels recapitulate many fluvial counterparts owing to large gradients of tidal prisms across meander wavelengths.

Study of wavelet packet energy entropy for emotion classification in speech and glottal signals

NASA Astrophysics Data System (ADS)

He, Ling; Lech, Margaret; Zhang, Jing; Ren, Xiaomei; Deng, Lihua

2013-07-01

The automatic speech emotion recognition has important applications in human-machine communication. Majority of current research in this area is focused on finding optimal feature parameters. In recent studies, several glottal features were examined as potential cues for emotion differentiation. In this study, a new type of feature parameter is proposed, which calculates energy entropy on values within selected Wavelet Packet frequency bands. The modeling and classification tasks are conducted using the classical GMM algorithm. The experiments use two data sets: the Speech Under Simulated Emotion (SUSE) data set annotated with three different emotions (angry, neutral and soft) and Berlin Emotional Speech (BES) database annotated with seven different emotions (angry, bored, disgust, fear, happy, sad and neutral). The average classification accuracy achieved for the SUSE data (74%-76%) is significantly higher than the accuracy achieved for the BES data (51%-54%). In both cases, the accuracy was significantly higher than the respective random guessing levels (33% for SUSE and 14.3% for BES).

Well-characterized sequence features of eukaryote genomes and implications for ab initio gene prediction.

PubMed

Huang, Ying; Chen, Shi-Yi; Deng, Feilong

2016-01-01

In silico analysis of DNA sequences is an important area of computational biology in the post-genomic era. Over the past two decades, computational approaches for ab initio prediction of gene structure from genome sequence alone have largely facilitated our understanding on a variety of biological questions. Although the computational prediction of protein-coding genes has already been well-established, we are also facing challenges to robustly find the non-coding RNA genes, such as miRNA and lncRNA. Two main aspects of ab initio gene prediction include the computed values for describing sequence features and used algorithm for training the discriminant function, and by which different combinations are employed into various bioinformatic tools. Herein, we briefly review these well-characterized sequence features in eukaryote genomes and applications to ab initio gene prediction. The main purpose of this article is to provide an overview to beginners who aim to develop the related bioinformatic tools.

An approach based on wavelet analysis for feature extraction in the a-wave of the electroretinogram.

PubMed

Barraco, R; Persano Adorno, D; Brai, M

2011-12-01

Most biomedical signals are non-stationary. The knowledge of their frequency content and temporal distribution is then useful in a clinical context. The wavelet analysis is appropriate to achieve this task. The present paper uses this method to reveal hidden characteristics and anomalies of the human a-wave, an important component of the electroretinogram since it is a measure of the functional integrity of the photoreceptors. We here analyse the time-frequency features of the a-wave both in normal subjects and in patients affected by Achromatopsia, a pathology disturbing the functionality of the cones. The results indicate the presence of two or three stable frequencies that, in the pathological case, shift toward lower values and change their times of occurrence. The present findings are a first step toward a deeper understanding of the features of the a-wave and possible applications to diagnostic procedures in order to recognise incipient photoreceptoral pathologies. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Wavelet images and Chou's pseudo amino acid composition for protein classification.

PubMed

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2012-08-01

The last decade has seen an explosion in the collection of protein data. To actualize the potential offered by this wealth of data, it is important to develop machine systems capable of classifying and extracting features from proteins. Reliable machine systems for protein classification offer many benefits, including the promise of finding novel drugs and vaccines. In developing our system, we analyze and compare several feature extraction methods used in protein classification that are based on the calculation of texture descriptors starting from a wavelet representation of the protein. We then feed these texture-based representations of the protein into an Adaboost ensemble of neural network or a support vector machine classifier. In addition, we perform experiments that combine our feature extraction methods with a standard method that is based on the Chou's pseudo amino acid composition. Using several datasets, we show that our best approach outperforms standard methods. The Matlab code of the proposed protein descriptors is available at http://bias.csr.unibo.it/nanni/wave.rar .

Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

PubMed Central

2012-01-01

Background Because of the large volume of data and the intrinsic variation of data intensity observed in microarray experiments, different statistical methods have been used to systematically extract biological information and to quantify the associated uncertainty. The simplest method to identify differentially expressed genes is to evaluate the ratio of average intensities in two different conditions and consider all genes that differ by more than an arbitrary cut-off value to be differentially expressed. This filtering approach is not a statistical test and there is no associated value that can indicate the level of confidence in the designation of genes as differentially expressed or not differentially expressed. At the same time the fold change by itself provide valuable information and it is important to find unambiguous ways of using this information in expression data treatment. Results A new method of finding differentially expressed genes, called distributional fold change (DFC) test is introduced. The method is based on an analysis of the intensity distribution of all microarray probe sets mapped to a three dimensional feature space composed of average expression level, average difference of gene expression and total variance. The proposed method allows one to rank each feature based on the signal-to-noise ratio and to ascertain for each feature the confidence level and power for being differentially expressed. The performance of the new method was evaluated using the total and partial area under receiver operating curves and tested on 11 data sets from Gene Omnibus Database with independently verified differentially expressed genes and compared with the t-test and shrinkage t-test. Overall the DFC test performed the best – on average it had higher sensitivity and partial AUC and its elevation was most prominent in the low range of differentially expressed features, typical for formalin-fixed paraffin-embedded sample sets. Conclusions The distributional fold change test is an effective method for finding and ranking differentially expressed probesets on microarrays. The application of this test is advantageous to data sets using formalin-fixed paraffin-embedded samples or other systems where degradation effects diminish the applicability of correlation adjusted methods to the whole feature set. PMID:23122055

Trajectories of charged dust grains in the cometary environment

NASA Astrophysics Data System (ADS)

Horanyi, M.; Mendis, D. A.

1985-07-01

Using a simple model of the particles and fields environment of a comet, the trajectories of the smallest (micron- and submicron-sized) dust grains that are expected to be released from a cometary nucleus are calculated. It is shown that electromagnetic forces play a crucial role in the dynamics of these particles. The present calculations indicate not only the asymmetry of the sunward dust envelopes that have been suggested earlier by other authors, but they also indicate the possible existence of wavy dust features far down the tail, reminiscent of the peculiar wavy dust feature observed in the dust tail of Comet Ikeya-Seki 1965f. The importance of these findings in studying the lower end of the cometary dust mass spectrum during the forthcoming fly-by missions to Comet Halley is underscored.

Using Electroencephalography for Treatment Guidance in Major Depressive Disorder.

PubMed

Wade, Elizabeth C; Iosifescu, Dan V

2016-09-01

Given the high prevalence of treatment-resistant depression and the long delays in finding effective treatments via trial and error, valid biomarkers of treatment outcome with the ability to guide treatment selection represent one of the most important unmet needs in mood disorders. A large body of research has investigated, for this purpose, biomarkers derived from electroencephalography (EEG), using resting state EEG or evoked potentials. Most studies have focused on specific EEG features (or combinations thereof), whereas more recently machine-learning approaches have been used to define the EEG features with the best predictive abilities without a priori hypotheses. While reviewing these different approaches, we have focused on the predictor characteristics and the quality of the supporting evidence. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Cyto-histological correlation of Xp11.2 translocation/TFE3 gene fusion associated renal cell carcinoma: Report of a case with review of literature.

PubMed

Manucha, Varsha; Sessums, Mary T; Lewin, Jack; Akhtar, Israh

2018-03-01

The MiT family translocation renal cell carcinomas (RCCs) are relatively rare in comparison to the conventional RCC. The cytologic features overlap with conventional clear cell RCC and papillary RCCs, thereby making the diagnosis extremely challenging. Here, we describe a case of TFE3 translocation associated RCC in a 58-year-old patient, with emphasis on cytomorphologic features and clues toward this diagnostic entity. Correlating the cytohistologic findings and review of touch imprints revealed that presence of hyaline nodules resembling leisegang rings and psammoma bodies in cytologic smears from kidney tumors serve as an important clue in raising a suspicion for the diagnosis of MiT family translocation RCCs. © 2017 Wiley Periodicals, Inc.

Infectious mononucleosis and the spleen.

PubMed

Kinderknecht, James J

2002-04-01

Infectious mononucleosis is an extremely common problem in the athletic population. "Mono" occurs in 3% of college students. Diagnosing infectious mononucleosis requires an understanding of the clinical features such as fever, lymphadenopathy, pharyngitis, and splenomegaly, as well as laboratory findings. The time at which these clinical features and laboratory abnormalities develop is also important to understand. Splenomegaly is common, but splenic rupture is very rare. Whether an athlete may return to activity usually relates to the presence of splenomegaly and the duration of the illness. Splenic rupture has not been reported after an individual has been ill for more than 3 weeks. This article provides an overview of infectious mononucleosis. The most common complications are reviewed and the management of these problems discussed. A practical approach to determining when an athlete may return to activity is presented.

Adult Brain Tumors and Pseudotumors: Interesting (Bizarre) Cases.

PubMed

Causil, Lazaro D; Ames, Romy; Puac, Paulo; Castillo, Mauricio

2016-11-01

Some brain tumors results are interesting due to their rarity at presentation and overwhelming imaging characteristics, posing a diagnostic challenge in the eyes of any experienced neuroradiologist. This article focuses on the most important features regarding epidemiology, location, clinical presentation, histopathology, and imaging findings of cases considered "bizarre." A review of the most recent literature dealing with these unusual tumors and pseudotumors is presented, highlighting key points related to the diagnosis, treatments, outcomes, and differential diagnosis. Copyright © 2016 Elsevier Inc. All rights reserved.

Rhabdoid Meningioma of Brain - A Rare Aggressive Tumor

PubMed Central

Mondal, Sajeeb; Pradhan, Rajashree; Pal, Subrata; Chatterjee, Sharmistha; Bandyapadhyay, Arindam; Bhattacharyya, Debosmita

2017-01-01

Rhabdoid meningioma is a rare aggressive variant of meningioma, regarded as WHO Grade III type. Histologically and cytologically, it is distinctive type having abundant eosinophilic cytoplasm, cytoplasmic inclusion with eccentrically placed vesicular nuclei and prominent nucleoli. High recurrence rate and poor outcome are important features. Here, we are presenting a rare case of rhabdoid meningioma found in a recurrent meningioma of the posterior fossa in a middle-aged female. We emphasized the squash cytology and histology finding of the rare neoplasm. PMID:28900335

Noncommutative Quantum Mechanics based on Representations of Exotic Galilei Group

NASA Astrophysics Data System (ADS)

Amorim, R. G. G.; Ulhoa, S. C.

2018-02-01

Using elements of symmetry, we constructed the Noncommutative Schrödinger Equation from a representation of Exotic Galilei Group. As a consequence, we derive the Ehrenfest theorem using noncommutative coordinates. We also have showed others features of quantum mechanics in such a manifold. As an important result, we find out that a linear potential in the noncommutative Schrödinger equation is completely analogous to the ordinary case. We also worked with harmonic and anharmonic oscillators, giving corrections in the energy for each one.

Anatomy and imaging of the normal meninges.

PubMed

Patel, Neel; Kirmi, Olga

2009-12-01

The meninges are an important connective tissue envelope investing the brain. Their function is to provide a protective coating to the brain and also participate in the formation of blood-brain barrier. Understanding their anatomy is fundamental to understanding the location and spread of pathologies in relation to the layers. It also provides an insight into the characteristics of such pathologies when imaging them. This review aims to describe the anatomy of the meninges, and to demonstrate the imaging findings of specific features.

Magnetic nanoparticles: preparation, physical properties, and applications in biomedicine

PubMed Central

2012-01-01

Finally, we have addressed some relevant findings on the importance of having well-defined synthetic strategies developed for the generation of MNPs, with a focus on particle formation mechanism and recent modifications made on the preparation of monodisperse samples of relatively large quantities not only with similar physical features, but also with similar crystallochemical characteristics. Then, different methodologies for the functionalization of the prepared MNPs together with the characterization techniques are explained. Theorical views on the magnetism of nanoparticles are considered. PMID:22348683

Tracking Subtle Stereotypes of Children with Trisomy 21: From Facial-Feature-Based to Implicit Stereotyping

PubMed Central

Enea-Drapeau, Claire; Carlier, Michèle; Huguet, Pascal

2012-01-01

Background Stigmatization is one of the greatest obstacles to the successful integration of people with Trisomy 21 (T21 or Down syndrome), the most frequent genetic disorder associated with intellectual disability. Research on attitudes and stereotypes toward these people still focuses on explicit measures subjected to social-desirability biases, and neglects how variability in facial stigmata influences attitudes and stereotyping. Methodology/Principal Findings The participants were 165 adults including 55 young adult students, 55 non-student adults, and 55 professional caregivers working with intellectually disabled persons. They were faced with implicit association tests (IAT), a well-known technique whereby response latency is used to capture the relative strength with which some groups of people—here photographed faces of typically developing children and children with T21—are automatically (without conscious awareness) associated with positive versus negative attributes in memory. Each participant also rated the same photographed faces (consciously accessible evaluations). We provide the first evidence that the positive bias typically found in explicit judgments of children with T21 is smaller for those whose facial features are highly characteristic of this disorder, compared to their counterparts with less distinctive features and to typically developing children. We also show that this bias can coexist with negative evaluations at the implicit level (with large effect sizes), even among professional caregivers. Conclusion These findings support recent models of feature-based stereotyping, and more importantly show how crucial it is to go beyond explicit evaluations to estimate the true extent of stigmatization of intellectually disabled people. PMID:22496796

A tale of two timescales: Mixing, mass generation, and phase transitions in the early universe

NASA Astrophysics Data System (ADS)

Dienes, Keith R.; Kost, Jeff; Thomas, Brooks

2016-02-01

Light scalar fields such as axions and string moduli can play an important role in early-universe cosmology. However, many factors can significantly impact their late-time cosmological abundances. For example, in cases where the potentials for these fields are generated dynamically—such as during cosmological mass-generating phase transitions—the duration of the time interval required for these potentials to fully develop can have significant repercussions. Likewise, in scenarios with multiple scalars, mixing amongst the fields can also give rise to an effective timescale that modifies the resulting late-time abundances. Previous studies have focused on the effects of either the first or the second timescale in isolation. In this paper, by contrast, we examine the new features that arise from the interplay between these two timescales when both mixing and time-dependent phase transitions are introduced together. First, we find that the effects of these timescales can conspire to alter not only the total late-time abundance of the system—often by many orders of magnitude—but also its distribution across the different fields. Second, we find that these effects can produce large parametric resonances which render the energy densities of the fields highly sensitive to the degree of mixing as well as the duration of the time interval over which the phase transition unfolds. Finally, we find that these effects can even give rise to a "reoverdamping" phenomenon which causes the total energy density of the system to behave in novel ways that differ from those exhibited by pure dark matter or vacuum energy. All of these features therefore give rise to new possibilities for early-universe phenomenology and cosmological evolution. They also highlight the importance of taking into account the time dependence associated with phase transitions in cosmological settings.

Simultaneously learning DNA motif along with its position and sequence rank preferences through expectation maximization algorithm.

PubMed

Zhang, ZhiZhuo; Chang, Cheng Wei; Hugo, Willy; Cheung, Edwin; Sung, Wing-Kin

2013-03-01

Although de novo motifs can be discovered through mining over-represented sequence patterns, this approach misses some real motifs and generates many false positives. To improve accuracy, one solution is to consider some additional binding features (i.e., position preference and sequence rank preference). This information is usually required from the user. This article presents a de novo motif discovery algorithm called SEME (sampling with expectation maximization for motif elicitation), which uses pure probabilistic mixture model to model the motif's binding features and uses expectation maximization (EM) algorithms to simultaneously learn the sequence motif, position, and sequence rank preferences without asking for any prior knowledge from the user. SEME is both efficient and accurate thanks to two important techniques: the variable motif length extension and importance sampling. Using 75 large-scale synthetic datasets, 32 metazoan compendium benchmark datasets, and 164 chromatin immunoprecipitation sequencing (ChIP-Seq) libraries, we demonstrated the superior performance of SEME over existing programs in finding transcription factor (TF) binding sites. SEME is further applied to a more difficult problem of finding the co-regulated TF (coTF) motifs in 15 ChIP-Seq libraries. It identified significantly more correct coTF motifs and, at the same time, predicted coTF motifs with better matching to the known motifs. Finally, we show that the learned position and sequence rank preferences of each coTF reveals potential interaction mechanisms between the primary TF and the coTF within these sites. Some of these findings were further validated by the ChIP-Seq experiments of the coTFs. The application is available online.

Acute gastrointestinal vaso-occlusive ischemia in sickle cell disease: CT imaging features and clinical outcome.

PubMed

Gardner, Carly S; Jaffe, Tracy A

2016-03-01

The purpose of this study was to determine the incidence, specific imaging features, and outcome of gastrointestinal vaso-occlusive ischemia (GVOI) in sickle cell patients undergoing CT for acute abdominal pain. This HIPAA-compliant, IRB-approved retrospective study evaluated sickle cell patients with an abdominal pain crisis and acute gastrointestinal abnormalities on CT from 1/2006 to 1/2014. CT findings were divided into those compatible and incompatible with bowel ischemia or clinical diagnosis of GVOI. Two abdominal radiologists (1, 13 years' experience) reviewed the CTs for specific imaging features of ischemia. Clinical laboratory values (lactate, WBC) and outcome were recorded. Descriptive statistics and Wilcoxon-Mann-Whitney two-sample rank-sum test were performed. Of 217 CTs, 33 had acute gastrointestinal abnormalities: 75% (25/33) consistent with ischemia and clinical GVOI. Complications of ischemia occurred in 16% (4/25): ileus (50%), perforation (25%), and pneumatosis (25%). In uncomplicated cases, all had bowel wall thickening: segmental 52% (11/21) or diffuse 48% (10/21). The colon was commonly involved (76%, 16/21), particularly the ascending (57%, 12/21). Most abnormalities (52%, 11/21) were in the superior mesenteric artery distribution. Average lactate (4.3 ± 4.0 mmol/L, p = 0.02) and WBC count (20.1 ± 10.4, ×1000 cells/μL, p = 0.01) were significantly higher in GVOI. Overall mortality in patients with GVOI was 17% (3/18). GVOI is an important feature of the acute abdominal crisis in patients with sickle cell disease and can be seen in up to 75% of patients with abnormal bowel findings on CT. The diagnosis should be strongly considered in sickle cell patients with CT findings of diffuse or segmental bowel wall thickening, particularly involving the colon.

Pain: A content review of undergraduate pre-registration nurse education in the United Kingdom.

PubMed

Mackintosh-Franklin, Carolyn

2017-01-01

Pain is a global health issue with poor assessment and management of pain associated with serious disability and detrimental socio economic consequences. Pain is also a closely associated symptom of the three major causes of death in the developed world; Coronary Heart Disease, Stroke and Cancer. There is a significant body of work which indicates that current nursing practice has failed to address pain as a priority, resulting in poor practice and unnecessary patient suffering. Additionally nurse education appears to lack focus or emphasis on the importance of pain assessment and its management. A three step online search process was carried out across 71 Higher Education Institutes (HEIs) in the United Kingdom (UK) which deliver approved undergraduate nurse education programmes. Step one to find detailed programme documentation, step 2 to find reference to pain in the detailed documents and step 3 to find reference to pain in nursing curricula across all UK HEI websites, using Google and each HEIs site specific search tool. The word pain featured minimally in programme documents with 9 (13%) documents making reference to it, this includes 3 occurrences which were not relevant to the programme content. The word pain also featured minimally in the content of programmes/modules on the website search, with no references at all to pain in undergraduate pre-registration nursing programmes. Those references found during the website search were for continuing professional development (CPD) or Masters level programmes. In spite of the global importance of pain as a major health issue both in its own right, and as a significant symptom of leading causes of death and illness, pain appears to be a neglected area within the undergraduate nursing curriculum. Evidence suggests that improving nurse education in this area can have positive impacts on clinical practice, however without educational input the current levels of poor practice are unlikely to improve and unnecessary patient suffering will continue. Undergraduate nurse education in the UK needs to review its current approach to content and ensure that pain is appropriately and prominently featured within pre-registration nurse education. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cultural differences in the development and characteristics of depression.

PubMed

Juhasz, Gabriella; Eszlari, Nora; Pap, Dorottya; Gonda, Xenia

2012-12-01

Depression is a highly prevalent mental illness with increasing burden for the patients, their families and society as well. In spite of its increasing importance, we still do not have complete understanding either of the phenomenology or the etiopathological background of depression, and cross-country, cross-ethnic and cross-cultural differences in the prevalence and symptomatic manifestation of depression further obscure this picture. Culturally-related features of depressive illness are gaining more importance in clinical practice with the increasing migration trends worldwide. In spite of the differences replicated in multiple studies, no exhaustive explanations are offered so far. In the present paper we describe the most consistently replicated findings concerning the most important cross-national differences in the rates and characteristics of depression with a short comment on possible background factors.

Fluorescent recovery after photobleaching (FRAP) analysis of nuclear export rates identifies intrinsic features of nucleocytoplasmic transport.

PubMed

Cardarelli, Francesco; Tosti, Luca; Serresi, Michela; Beltram, Fabio; Bizzarri, Ranieri

2012-02-17

A quantitative description of carrier-mediated nuclear export in live cells is presented. To this end, we fused a prototypical leucine-rich nuclear export signal (NES) to GFP as a cargo model and expressed the fluorescent chimera in live CHO-K1 cells. By modeling FRAP data, we calculate the NES affinity for the export machinery and the maximum rate of nuclear export achievable at saturation of endogenous carriers. The measured active-export time through the Nuclear Pore Complex (NPC) is 18 ms, remarkably similar to the previously determined active-import rate. Also, our results reveal that active export/import and active export/passive diffusion fluxes are uncoupled, thus complementing previous reports on active import/passive diffusion uncoupling. These findings suggest differential gating at the NPC level.

Brainstem Correlates of Speech-in-Noise Perception in Children

PubMed Central

Anderson, Samira; Skoe, Erika; Chandrasekaran, Bharath; Zecker, Steven; Kraus, Nina

2010-01-01

Children often have difficulty understanding speech in challenging listening environments. In the absence of peripheral hearing loss, these speech perception difficulties may arise from dysfunction at more central levels in the auditory system, including subcortical structures. We examined brainstem encoding of pitch in a speech syllable in 38 school-age children. In children with poor speech-in-noise perception, we find impaired encoding of the fundamental frequency and the second harmonic, two important cues for pitch perception. Pitch, an important factor in speaker identification, aids the listener in tracking a specific voice from a background of voices. These results suggest that the robustness of subcortical neural encoding of pitch features in time-varying signals is an important factor in determining success with speech perception in noise. PMID:20708671

77 FR 66874 - Environmental Assessment and Finding of No Significant Impact

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-07

... project. Paleoliquefaction features are geologic features such as sand blows and sand dikes that formed..., groundwater, air quality) as a result of the paleoliquefaction research study. III. Finding of No Significant...

The performance of field scientists undertaking observations of early life fossils while in simulated space suit

NASA Astrophysics Data System (ADS)

Willson, D.; Rask, J. C.; George, S. C.; de Leon, P.; Bonaccorsi, R.; Blank, J.; Slocombe, J.; Silburn, K.; Steele, H.; Gargarno, M.; McKay, C. P.

2014-01-01

We conducted simulated Apollo Extravehicular Activity's (EVA) at the 3.45 Ga Australian 'Pilbara Dawn of life' (Western Australia) trail with field and non-field scientists using the University of North Dakota's NDX-1 pressurizable space suit to overview the effectiveness of scientist astronauts employing their field observation skills while looking for stromatolite fossil evidence. Off-world scientist astronauts will be faced with space suit limitations in vision, human sense perception, mobility, dexterity, the space suit fit, time limitations, and the psychological fear of death from accidents, causing physical fatigue reducing field science performance. Finding evidence of visible biosignatures for past life such as stromatolite fossils, on Mars, is a very significant discovery. Our preliminary overview trials showed that when in simulated EVAs, 25% stromatolite fossil evidence is missed with more incorrect identifications compared to ground truth surveys but providing quality characterization descriptions becomes less affected by simulated EVA limitations as the science importance of the features increases. Field scientists focused more on capturing high value characterization detail from the rock features whereas non-field scientists focused more on finding many features. We identified technologies and training to improve off-world field science performance. The data collected is also useful for NASA's "EVA performance and crew health" research program requirements but further work will be required to confirm the conclusions.

Computer-Aided Characterization and Diagnosis of Diffuse Liver Diseases Based on Ultrasound Imaging: A Review.

PubMed

Bharti, Puja; Mittal, Deepti; Ananthasivan, Rupa

2016-04-19

Diffuse liver diseases, such as hepatitis, fatty liver, and cirrhosis, are becoming a leading cause of fatality and disability all over the world. Early detection and diagnosis of these diseases is extremely important to save lives and improve effectiveness of treatment. Ultrasound imaging, a noninvasive diagnostic technique, is the most commonly used modality for examining liver abnormalities. However, the accuracy of ultrasound-based diagnosis depends highly on expertise of radiologists. Computer-aided diagnosis systems based on ultrasound imaging assist in fast diagnosis, provide a reliable "second opinion" for experts, and act as an effective tool to measure response of treatment on patients undergoing clinical trials. In this review, we first describe appearance of liver abnormalities in ultrasound images and state the practical issues encountered in characterization of diffuse liver diseases that can be addressed by software algorithms. We then discuss computer-aided diagnosis in general with features and classifiers relevant to diffuse liver diseases. In later sections of this paper, we review the published studies and describe the key findings of those studies. A concise tabular summary comparing image database, features extraction, feature selection, and classification algorithms presented in the published studies is also exhibited. Finally, we conclude with a summary of key findings and directions for further improvements in the areas of accuracy and objectiveness of computer-aided diagnosis. © The Author(s) 2016.

A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classification

NASA Astrophysics Data System (ADS)

Liu, Tao; Im, Jungho; Quackenbush, Lindi J.

2015-12-01

This study provides a novel approach to individual tree crown delineation (ITCD) using airborne Light Detection and Ranging (LiDAR) data in dense natural forests using two main steps: crown boundary refinement based on a proposed Fishing Net Dragging (FiND) method, and segment merging based on boundary classification. FiND starts with approximate tree crown boundaries derived using a traditional watershed method with Gaussian filtering and refines these boundaries using an algorithm that mimics how a fisherman drags a fishing net. Random forest machine learning is then used to classify boundary segments into two classes: boundaries between trees and boundaries between branches that belong to a single tree. Three groups of LiDAR-derived features-two from the pseudo waveform generated along with crown boundaries and one from a canopy height model (CHM)-were used in the classification. The proposed ITCD approach was tested using LiDAR data collected over a mountainous region in the Adirondack Park, NY, USA. Overall accuracy of boundary classification was 82.4%. Features derived from the CHM were generally more important in the classification than the features extracted from the pseudo waveform. A comprehensive accuracy assessment scheme for ITCD was also introduced by considering both area of crown overlap and crown centroids. Accuracy assessment using this new scheme shows the proposed ITCD achieved 74% and 78% as overall accuracy, respectively, for deciduous and mixed forest.

Determinants of Global Color-Based Selection in Human Visual Cortex.

PubMed

Bartsch, Mandy V; Boehler, Carsten N; Stoppel, Christian M; Merkel, Christian; Heinze, Hans-Jochen; Schoenfeld, Mircea A; Hopf, Jens-Max

2015-09-01

Feature attention operates in a spatially global way, with attended feature values being prioritized for selection outside the focus of attention. Accounts of global feature attention have emphasized feature competition as a determining factor. Here, we use magnetoencephalographic recordings in humans to test whether competition is critical for global feature selection to arise. Subjects performed a color/shape discrimination task in one visual field (VF), while irrelevant color probes were presented in the other unattended VF. Global effects of color attention were assessed by analyzing the response to the probe as a function of whether or not the probe's color was a target-defining color. We find that global color selection involves a sequence of modulations in extrastriate cortex, with an initial phase in higher tier areas (lateral occipital complex) followed by a later phase in lower tier retinotopic areas (V3/V4). Importantly, these modulations appeared with and without color competition in the focus of attention. Moreover, early parts of the modulation emerged for a task-relevant color not even present in the focus of attention. All modulations, however, were eliminated during simple onset-detection of the colored target. These results indicate that global color-based attention depends on target discrimination independent of feature competition in the focus of attention. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Face Alignment via Regressing Local Binary Features.

PubMed

Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian

2016-03-01

This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

NASA Astrophysics Data System (ADS)

Phinyomark, A.; Hu, H.; Phukpattaranont, P.; Limsakul, C.

2012-01-01

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier.

Arabic OCR: toward a complete system

NASA Astrophysics Data System (ADS)

El-Bialy, Ahmed M.; Kandil, Ahmed H.; Hashish, Mohamed; Yamany, Sameh M.

1999-12-01

Latin and Chinese OCR systems have been studied extensively in the literature. Yet little work was performed for Arabic character recognition. This is due to the technical challenges found in the Arabic text. Due to its cursive nature, a powerful and stable text segmentation is needed. Also; features capturing the characteristics of the rich Arabic character representation are needed to build the Arabic OCR. In this paper a novel segmentation technique which is font and size independent is introduced. This technique can segment the cursive written text line even if the line suffers from small skewness. The technique is not sensitive to the location of the centerline of the text line and can segment different font sizes and type (for different character sets) occurring on the same line. Features extraction is considered one of the most important phases of the text reading system. Ideally, the features extracted from a character image should capture the essential characteristics of this character that are independent of the font type and size. In such ideal case, the classifier stores a single prototype per character. However, it is practically challenging to find such ideal set of features. In this paper, a set of features that reflect the topological aspects of Arabia characters is proposed. These proposed features integrated with a topological matching technique introduce an Arabic text reading system that is semi Omni.

Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state.

PubMed

Yang, Yan-Li; Deng, Hong-Xia; Xing, Gui-Yang; Xia, Xiao-Luan; Li, Hai-Fang

2015-02-01

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we investigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state. Z-values in the vision-related brain regions were calculated, confirming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental findings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

Optimal faces for gender and expression: a new technique for measuring dynamic templates used in face perception.

PubMed

Poirier, Frédéric J A M; Faubert, Jocelyn

2012-06-22

Facial expressions are important for human communications. Face perception studies often measure the impact of major degradation (e.g., noise, inversion, short presentations, masking, alterations) on natural expression recognition performance. Here, we introduce a novel face perception technique using rich and undegraded stimuli. Participants modified faces to create optimal representations of given expressions. Using sliders, participants adjusted 53 face components (including 37 dynamic) including head, eye, eyebrows, mouth, and nose shape and position. Data was collected from six participants and 10 conditions (six emotions + pain + gender + neutral). Some expressions had unique features (e.g., frown for anger, upward-curved mouth for happiness), whereas others had shared features (e.g., open eyes and mouth for surprise and fear). Happiness was different from other emotions. Surprise was different from other emotions except fear. Weighted sum morphing provides acceptable stimuli for gender-neutral and dynamic stimuli. Many features were correlated, including (1) head size with internal feature sizes as related to gender, (2) internal feature scaling, and (3) eyebrow height and eye openness as related to surprise and fear. These findings demonstrate the method's validity for measuring the optimal facial expressions, which we argue is a more direct measure of their internal representations.

Premotor and non-motor features of Parkinson’s disease

PubMed Central

Goldman, Jennifer G.; Postuma, Ron

2014-01-01

Purpose of review This review highlights recent advances in premotor and non-motor features in Parkinson’s disease, focusing on these issues in the context of prodromal and early stage Parkinson’s disease. Recent findings While Parkinson’s disease patients experience a wide range of non-motor symptoms throughout the disease course, studies demonstrate that non-motor features are not solely a late manifestation. Indeed, disturbances of smell, sleep, mood, and gastrointestinal function may herald Parkinson’s disease or related synucleinopathies and precede these neurodegenerative conditions by 5 or more years. In addition, other non-motor symptoms such as cognitive impairment are now recognized in incident or de novo Parkinson’s disease cohorts. Many of these non-motor features reflect disturbances in non-dopaminergic systems and early involvement of peripheral and central nervous systems including olfactory, enteric, and brainstem neurons as in Braak’s proposed pathological staging of Parkinson’s disease. Current research focuses on identifying potential biomarkers that may detect persons at risk for Parkinson’s disease and permit early intervention with neuroprotective or disease-modifying therapeutics. Summary Recent studies provide new insights on the frequency, pathophysiology, and importance of non-motor features in Parkinson’s disease as well as the recognition that these non-motor symptoms occur in premotor, early, and later phases of Parkinson’s disease. PMID:24978368

Segmentation of photospheric magnetic elements corresponding to coronal features to understand the EUV and UV irradiance variability

NASA Astrophysics Data System (ADS)

Zender, J. J.; Kariyappa, R.; Giono, G.; Bergmann, M.; Delouille, V.; Damé, L.; Hochedez, J.-F.; Kumara, S. T.

2017-09-01

Context. The magnetic field plays a dominant role in the solar irradiance variability. Determining the contribution of various magnetic features to this variability is important in the context of heliospheric studies and Sun-Earth connection. Aims: We studied the solar irradiance variability and its association with the underlying magnetic field for a period of five years (January 2011-January 2016). We used observations from the Large Yield Radiometer (LYRA), the Sun Watcher with Active Pixel System detector and Image Processing (SWAP) on board PROBA2, the Atmospheric Imaging Assembly (AIA), and the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). Methods: The Spatial Possibilistic Clustering Algorithm (SPoCA) is applied to the extreme ultraviolet (EUV) observations obtained from the AIA to segregate coronal features by creating segmentation maps of active regions (ARs), coronal holes (CHs) and the quiet sun (QS). Further, these maps are applied to the full-disk SWAP intensity images and the full-disk (FD) HMI line-of-sight (LOS) magnetograms to isolate the SWAP coronal features and photospheric magnetic counterparts, respectively. We then computed full-disk and feature-wise averages of EUV intensity and line of sight (LOS) magnetic flux density over ARs/CHs/QS/FD. The variability in these quantities is compared with that of LYRA irradiance values. Results: Variations in the quantities resulting from the segmentation, namely the integrated intensity and the total magnetic flux density of ARs/CHs/QS/FD regions, are compared with the LYRA irradiance variations. We find that the EUV intensity over ARs/CHs/QS/FD is well correlated with the underlying magnetic field. In addition, variations in the full-disk integrated intensity and magnetic flux density values are correlated with the LYRA irradiance variations. Conclusions: Using the segmented coronal features observed in the EUV wavelengths as proxies to isolate the underlying magnetic structures is demonstrated in this study. Sophisticated feature identification and segmentation tools are important in providing more insights into the role of various magnetic features in both the short- and long-term changes in the solar irradiance. The movie associated to Fig. 2 is available at http://www.aanda.org

Individual MRI and radiographic features of knee OA in subjects with unilateral knee pain: Health ABC study

PubMed Central

Javaid, MK; Kiran, A; Guermazi, A; Kwoh, K; Zaim, S; Carbone, L; Harris, T.; McCulloch, C.E.; Arden, NK; Lane, NE; Felson, D; Nevitt, M

2012-01-01

Strong associations between radiographic features of knee OA and pain have been demonstrated in persons with unilateral knee symptoms. Our objectives were to compare radiographic with MRI features of knee OA and assess the discrimination between painful and non-painful knees in persons with unilateral symptoms. 283 individuals with unilateral knee pain aged 71 to 80 years from Health ABC, a study of weight-related diseases and mobility, had bilateral knee radiographs, read for KL grade and individual radiographic features, and 1.5T MRIs, read using WORMS. The association of structural features with pain was assessed using a within-person case/control design and conditional logistic regression. Receiver operator characteristics (ROC) were then used to test the discriminatory performance of structural features. In conditional logistic analyses, knee pain was significantly associated with both radiographic (any JSN grade >=1: OR 3.20 (1.79 – 5.71) and MRI (any cartilage defect:>=2: OR 3.67 (1.49 – 9.04)) features. However, most subjects had MR detected osteophytes, cartilage and bone marrow lesions in both knees and no individual structural feature discriminated well between painful and non-painful knees using ROC. The best performing MRI feature (synovitis/effusion) was not significantly more informative than KL grade >=2 (p=0.42). In persons with unilateral knee pain, MR and radiographic features were associated with knee pain confirming an important role in the etiology of pain. However, no single MRI or radiographic finding performed well in discriminating painful from non-painful knees. Further work is needed to examine how structural and non-structural factors influence knee pain. PMID:22736267

A self-triggered picoinjector in microfluidics

NASA Astrophysics Data System (ADS)

Yang, Yiming; Liu, Songsheng; Jia, Chunping; Mao, Hongju; Jin, Qinghui; Zhao, Jianlong; Zhou, Hongbo

2016-12-01

Droplet-based microfluidics has recently emerged as a potential platform for studies of single-cell, directed evolution, and genetic sequencing. In droplet-based microfluidics, adding reagents into drops is one of the most important functions. In this paper, we develop a new self-triggered picoinjector to add controlled volumes of reagent into droplets at kilohertz rates. In the picoinjector, the reagent injecting is triggered by the coming droplet itself, without needing a droplet detection module. Meanwhile, the dosing volume can be precisely controlled. These features make the system more practical and reliable. We expect the new picoinjector will find important applications of droplet-based microfluidics in automated biological assay, directed evolution, enzyme assay, and so on.

"Not just a dog": an attachment perspective on relationships with assistance dogs.

PubMed

Kwong, Marilyn J; Bartholomew, Kim

2011-09-01

We explored individuals' relationships with an assistance dog from an attachment-theory perspective. We used both inductive and deductive thematic methods to analyze semi-structured interviews with 25 participants who had lost an assistance dog to retirement or death. Analyses revealed attachment processes of safe haven, secure base, and separation anxiety. Although attachment dynamics were an important feature of these relationships, caregiving was equally important. When confronted with the loss of their dog, almost all participants experienced intense grief. Most grief responses were consistent with the loss of a caregiving relationship. Findings suggest that grief is a natural response to the loss of a beloved companion who fulfilled fundamental needs for attachment and caregiving.

Eating disorder features and quality of life: Does gender matter?

PubMed

Wagner, Allison F; Stefano, Emily C; Cicero, David C; Latner, Janet D; Mond, Jonathan M

2016-10-01

This study examined whether gender moderates the associations between eating disorder features and quality-of-life impairment and whether eating disorder features can explain gender differences in quality of life in a sample of undergraduate students. The SF-12 Physical and Mental Component Summary Scales were used to measure health-related quality of life (HRQoL), and the Eating Disorders Examination Questionnaire (EDE-Q) was used to quantify eating disorder behaviors and cognitions. These self-report forms were completed by undergraduate men and women (n = 709). Gender was a significant predictor of mental HRQoL, such that women in this sample reported poorer mental HRQoL than men. Eating disorder cognitions were the strongest predictor of undergraduate students' mental and physical HRQoL, while binge eating negatively predicted their physical HRQoL only. Gender was not found to moderate the associations between eating disorder features and HRQoL, and eating disorder cognitions were found to mediate the association between gender and mental HRQoL such that a proportion of the difference between undergraduate men and women's mental HRQoL was attributable to eating disorder cognitions. This study provided further evidence of the significant impact of eating disorder features, particularly eating disorder cognitions, on HRQoL. The finding that gender did not moderate the relationships between eating disorder features and HRQoL indicates the importance of investigating these features in both men and women in future research.

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

PubMed Central

Meinicke, Peter; Tech, Maike; Morgenstern, Burkhard; Merkl, Rainer

2004-01-01

Background Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. Results We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. Conclusions We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems. PMID:15511290

Biomechanical factors and physical examination findings in osteoarthritis of the knee: associations with tissue abnormalities assessed by conventional radiography and high-resolution 3.0 Tesla magnetic resonance imaging.

PubMed

Knoop, Jesper; Dekker, Joost; Klein, Jan-Paul; van der Leeden, Marike; van der Esch, Martin; Reiding, Dick; Voorneman, Ramon E; Gerritsen, Martijn; Roorda, Leo D; Steultjens, Martijn P M; Lems, Willem F

2012-10-05

We aimed to explore the associations between knee osteoarthritis (OA)-related tissue abnormalities assessed by conventional radiography (CR) and by high-resolution 3.0 Tesla magnetic resonance imaging (MRI), as well as biomechanical factors and findings from physical examination in patients with knee OA. This was an explorative cross-sectional study of 105 patients with knee OA. Index knees were imaged using CR and MRI. Multiple features from CR and MRI (cartilage, osteophytes, bone marrow lesions, effusion and synovitis) were related to biomechanical factors (quadriceps and hamstrings muscle strength, proprioceptive accuracy and varus-valgus laxity) and physical examination findings (bony tenderness, crepitus, bony enlargement and palpable warmth), using multivariable regression analyses. Quadriceps weakness was associated with cartilage integrity, effusion, synovitis (all detected by MRI) and CR-detected joint space narrowing. Knee joint laxity was associated with MRI-detected cartilage integrity, CR-detected joint space narrowing and osteophyte formation. Multiple tissue abnormalities including cartilage integrity, osteophytes and effusion, but only those detected by MRI, were found to be associated with physical examination findings such as crepitus. We observed clinically relevant findings, including a significant association between quadriceps weakness and both effusion and synovitis, detected by MRI. Inflammation was detected in over one-third of the participants, emphasizing the inflammatory component of OA and a possible important role for anti-inflammatory therapies in knee OA. In general, OA-related tissue abnormalities of the knee, even those detected by MRI, were found to be discordant with biomechanical and physical examination features.

Demands on attention and the role of response priming in visual discrimination of feature conjunctions.

PubMed

Fournier, Lisa R; Herbert, Rhonda J; Farris, Carrie

2004-10-01

This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved

Features in visual search combine linearly

PubMed Central

Pramod, R. T.; Arun, S. P.

2014-01-01

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328

Homologous prominence non-radial eruptions: A case study

NASA Astrophysics Data System (ADS)

Duchlev, P.; Koleva, K.; Madjarska, M. S.; Dechev, M.

2016-10-01

The present study provides important details on homologous eruptions of a solar prominence that occurred in active region NOAA 10904 on 2006 August 22. We report on the pre-eruptive phase of the homologous feature as well as the kinematics and the morphology of a forth from a series of prominence eruptions that is critical in defining the nature of the previous consecutive eruptions. The evolution of the overlying coronal field during homologous eruptions is discussed and a new observational criterion for homologous eruptions is provided. We find a distinctive sequence of three activation periods each of them containing pre-eruptive precursors such as a brightening and enlarging of the prominence body followed by small surge-like ejections from its southern end observed in the radio 17 GHz. We analyse a fourth eruption that clearly indicates a full reformation of the prominence after the third eruption. The fourth eruption although occurring 11 h later has an identical morphology, the same angle of propagation with respect to the radial direction, as well as similar kinematic evolution as the previous three eruptions. We find an important feature of the homologous eruptive prominence sequence that is the maximum height increase of each consecutive eruption. The present analysis establishes that all four eruptions observed in Hα are of confined type with the third eruption undergoing a thermal disappearance during its eruptive phase. We suggest that the observation of the same direction of the magnetic flux rope (MFR) ejections can be consider as an additional observational criterion for MFR homology. This observational indication for homologous eruptions is important, especially in the case of events of typical or poorly distinguishable morphology of eruptive solar phenomena.

Modelling and mapping tick dynamics using volunteered observations.

PubMed

Garcia-Martí, Irene; Zurita-Milla, Raúl; van Vliet, Arnold J H; Takken, Willem

2017-11-14

Tick populations and tick-borne infections have steadily increased since the mid-1990s posing an ever-increasing risk to public health. Yet, modelling tick dynamics remains challenging because of the lack of data and knowledge on this complex phenomenon. Here we present an approach to model and map tick dynamics using volunteered data. This approach is illustrated with 9 years of data collected by a group of trained volunteers who sampled active questing ticks (AQT) on a monthly basis and for 15 locations in the Netherlands. We aimed at finding the main environmental drivers of AQT at multiple time-scales, and to devise daily AQT maps at the national level for 2014. Tick dynamics is a complex ecological problem driven by biotic (e.g. pathogens, wildlife, humans) and abiotic (e.g. weather, landscape) factors. We enriched the volunteered AQT collection with six types of weather variables (aggregated at 11 temporal scales), three types of satellite-derived vegetation indices, land cover, and mast years. Then, we applied a feature engineering process to derive a set of 101 features to characterize the conditions that yielded a particular count of AQT on a date and location. To devise models predicting the AQT, we use a time-aware Random Forest regression method, which is suitable to find non-linear relationships in complex ecological problems, and provides an estimation of the most important features to predict the AQT. We trained a model capable of fitting AQT with reduced statistical metrics. The multi-temporal study on the feature importance indicates that variables linked to water levels in the atmosphere (i.e. evapotranspiration, relative humidity) consistently showed a higher explanatory power than previous works using temperature. As a product of this study, we are able of mapping daily tick dynamics at the national level. This study paves the way towards the design of new applications in the fields of environmental research, nature management, and public health. It also illustrates how Citizen Science initiatives produce geospatial data collections that can support scientific analysis, thus enabling the monitoring of complex environmental phenomena.

The effect of time-variant acoustical properties on orchestral instrument timbres

NASA Astrophysics Data System (ADS)

Hajda, John Michael

1999-06-01

The goal of this study was to investigate the timbre of orchestral instrument tones. Kendall (1986) showed that time-variant features are important to instrument categorization. But the relative salience of specific time-variant features to each other and to other acoustical parameters is not known. As part of a convergence strategy, a battery of experiments was conducted to assess the importance of global amplitude envelope, spectral frequencies, and spectral amplitudes. An omnibus identification experiment investigated the salience of global envelope partitions (attack, steady state, and decay). Valid partitioning models should identify important boundary conditions in the evolution of a signal; therefore, these models should be based on signal characteristics. With the use of such a model for sustained continuant tones, the steady-state segment was more salient than the attack. These findings contradicted previous research, which used questionable operational definitions for signal partitioning. For the next set of experiments, instrument tones were analyzed by phase vocoder, and stimuli were created by additive synthesis. Edits and combinations of edits controlled global amplitude envelope, spectral frequencies, and relative spectral amplitudes. Perceptual measurements were made with distance estimation, Verbal Attribute Magnitude Estimation, and similarity scaling. Results indicated that the primary acoustical attribute was the long-time-average spectral centroid. Spectral centroid is a measure of the center of energy distribution for spectral frequency components. Instruments with high values of spectral centroid (bowed strings) sound nasal while instruments with low spectral centroid (flute, clarinet) sound not nasal. The secondary acoustical attribute was spectral amplitude time variance. Predictably, time variance correlated highly with subject ratings of vibrato. The control of relative spectral amplitudes was more salient than the control of global envelope and spectral frequencies. Both amplitude phase relationships and time- variant spectral centroid were affected by the control of relative spectral amplitudes. Further experimentation is required to determine the salience of these features. The finding that instrumental vibrato is a manifestation of spectral amplitude time variance contradicts the common belief that vibrato is due to frequency (pitch) and intensity (loudness) modulation. This study suggests that vibrato is due to a periodic modulation in timbre. Future research should employ musical contexts.

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

PubMed Central

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

Biochemical recurrence after radical prostatectomy: what does it mean?

PubMed Central

Tourinho-Barbosa, Rafael; Srougi, Victor; Nunes-Silva, Igor; Baghdadi, Mohammed; Rembeyo, Gregory; Eiffel, Sophie S.; Barret, Eric; Rozet, Francois; Galiano, Marc; Cathelineau, Xavier; Sanchez-Salas, Rafael

2018-01-01

ABSTRACT Background Radical prostatectomy (RP) has been used as the main primary treatment for prostate cancer (PCa) for many years with excellent oncologic results. However, approximately 20-40% of those patients has failed to RP and presented biochemical recurrence (BCR). Prostatic specific antigen (PSA) has been the pivotal tool for recurrence diagnosis, but there is no consensus about the best PSA threshold to define BCR until this moment. The natural history of BCR after surgical procedure is highly variable, but it is important to distinguish biochemical and clinical recurrence and to find the correct timing to start multimodal treatment strategy. Also, it is important to understand the role of each clinical and pathological feature of prostate cancer in BCR, progression to metastatic disease and cancer specific mortality (CSM). Review design A simple review was made in Medline for articles written in English language about biochemical recurrence after radical prostatectomy. Objective To provide an updated assessment of BCR definition, its meaning, PCa natural history after BCR and the weight of each clinical/pathological feature and risk group classifications in BCR, metastatic disease and CSM. PMID:29039897

Relationship between craving and personality in treatment-seeking women with substance-related disorders

PubMed Central

Zilberman, Monica L; Tavares, Hermano; el-Guebaly, Nady

2003-01-01

Background Individual differences may impact susceptibility to addiction. The impact of personality features on drug craving, however, has not been studied, particularly in women. Methods Ninety-five treatment-seeking women with substance dependence, abstinent for at least 5 and no more than 21 days, were investigated regarding the correlation between personality factors and craving. Personality was assessed using the Temperament and Character Inventory (TCI), the NEO Personality Inventory Revised (NEO-PI-R), and the Barratt Impulsiveness Scale version 11 (BIS-11). Cravings were assessed through the Pennsylvania Craving Scale (PCS), and the Craving Questionnaire (CQ). Anxiety and depressive symptomatology were also recorded. Results Craving scores were positively correlated with depression and negatively correlated with number of days abstinent from substance use. Also, craving scores were positively associated with the novelty-seeking factor from the TCI and the total score on the BIS-11, and negatively associated with the conscientiousness and agreeableness facets of the NEO-PI-R. Conclusion Findings suggest that personality features, particularly impulsiveness, can be important predictors of craving in women, which has important implications for treatment planning. PMID:12525264

Heterogeneous patterns of brain atrophy in Alzheimer's disease.

PubMed

Poulakis, Konstantinos; Pereira, Joana B; Mecocci, Patrizia; Vellas, Bruno; Tsolaki, Magda; Kłoszewska, Iwona; Soininen, Hilkka; Lovestone, Simon; Simmons, Andrew; Wahlund, Lars-Olof; Westman, Eric

2018-05-01

There is increasing evidence showing that brain atrophy varies between patients with Alzheimer's disease (AD), suggesting that different anatomical patterns might exist within the same disorder. We investigated AD heterogeneity based on cortical and subcortical atrophy patterns in 299 AD subjects from 2 multicenter cohorts. Clusters of patients and important discriminative features were determined using random forest pairwise similarity, multidimensional scaling, and distance-based hierarchical clustering. We discovered 2 typical (72.2%) and 3 atypical (28.8%) subtypes with significantly different demographic, clinical, and cognitive characteristics, and different rates of cognitive decline. In contrast to previous studies, our unsupervised random forest approach based on cortical and subcortical volume measures and their linear and nonlinear interactions revealed more typical AD subtypes with important anatomically discriminative features, while the prevalence of atypical cases was lower. The hippocampal-sparing and typical AD subtypes exhibited worse clinical progression in visuospatial, memory, and executive cognitive functions. Our findings suggest there is substantial heterogeneity in AD that has an impact on how patients function and progress over time. Copyright © 2018 Elsevier Inc. All rights reserved.

Tuberculosis: finding a new potential antimycobacterium derivative in a aldehyde-arylhydrazone-oxoquinoline series.

PubMed

da C Santos, Fernanda; Castro, Helena C; Lourenço, Maria Cristina S; Abreu, Paula A; Batalha, Pedro N; Cunha, Anna C; Carvalho, Guilherme S L; Rodrigues, Carlos R; Medeiros, Cid A; Souza, Simone D; Ferreira, Vitor F; de Souza, Maria C B V

2012-10-01

Tuberculosis (TB) is a contagious disease caused by Mycobacterium tuberculosis, which remains a serious public health problem. The emergence of resistant bacterial strains has continuously increased and new treatment options are currently in need. In this work, we identified a new potential aldehyde-arylhydrazone-oxoquinoline derivative (4e) with interesting chemical structural features that may be important for designing new anti-TB agents. This 1-ethyl-N'-[(1E)-(5-nitro-2-furyl)methylene]-4-oxo-1,4-dihydroquinoline-3-carbohydrazide (4e) presented an in vitro active profile against M. tuberculosis H37Rv strain (minimum inhibitory concentration, MIC = 6.25 μg/mL) better than other acylhydrazones described in the literature (MIC = 12.5 μg/mL) and close to other antitubercular agents currently on the market. The theoretical analysis showed the importance of several structural features that together with the 5-nitro-2-furyl group generated this active compound (4e). This new compound and the analysis of its molecular properties may be useful for designing new and more efficient antibacterial drugs.

Possible effects of an early diagnosis and treatment in patients with growth hormone deficiency: the state of art.

PubMed

Stagi, Stefano; Scalini, Perla; Farello, Giovanni; Verrotti, Alberto

2017-09-16

Growth hormone deficiency (GHD) is a relatively uncommon and heterogeneous endocrine disorder presenting in childhood with short stature. However, during the neonatal period, the metabolic effects of GHD may to require prompt replacement therapy to avoid possible life-threatening complications. An increasing amount of data suggests the importance of an early diagnosis and treatment of GHD because of its auxological, metabolic, and neurodevelopmental features with respect to the patients diagnosed and treated later in life.The available results show favourable auxological outcomes for patients with GHD diagnosed and treated with r-hGH early in life compared with those from patients with GHD who do not receive this early diagnosis and treatment. Because delayed referral for GHD diagnosis and treatment is still frequent, these results highlight the need for more attention in the diagnosis and treatment of GHD.Despite these very encouraging data regarding metabolic and neurodevelopmental features, further studies are needed to better characterize these findings. Overall, the importance of early diagnosis and treatment of GHD needs to be addressed.

The cost of selective attention in category learning: Developmental differences between adults and infants

PubMed Central

Best, Catherine A.; Yim, Hyungwook; Sloutsky, Vladimir M.

2013-01-01

Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6–8 months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. PMID:23773914

Mirror movements in parkinsonism: evaluation of a new clinical sign

PubMed Central

Espay, A; Li, J; Johnston, L; Chen, R; Lang, A

2005-01-01

Background: Mirror movements (MM) are not widely appreciated in parkinsonism and no report has evaluated this clinical sign in detail. Objectives: To define the parkinsonian clinical features associated with MM in patients with early, asymmetric parkinsonism. Methods: Twenty seven patients with early Parkinson's disease were evaluated using a standardised videotaping protocol. MM were scored from blinded video assessment using a clinical scale that rates the amplitude, distribution, and proportion of mirroring in the less affected limb. Parkinsonian features were combined into axial and lateralised scores using related items of the Unified Parkinson's Disease Rating Scale. Results: MM were present in 24 of 27 patients. There was a significant linear correlation between the degree of asymmetry of motor deficits and MM on the less affected side. The effect of asymmetry was greater when the proportional rather than the absolute motor difference between sides was largest. Asymmetry in leg rigidity was the most important examination feature in the prediction of contralateral foot mirroring. Conclusions: MM are a clinical feature of the unaffected or less affected side in mild asymmetric parkinsonism. Their presence may be a useful clinical finding in early parkinsonism. PMID:16170075

Radiological features for the approach in trans-sphenoidal pituitary surgery.

PubMed

Twigg, Victoria; Carr, Simon D; Balakumar, Ramkishan; Sinha, Saurabh; Mirza, Showkat

2017-08-01

In order to perform trans-sphenoidal endoscopic pituitary surgery safely and efficiently it is important to identify anatomical and pituitary disease features on the pre-operative CT and MRI scans; thereby minimising the risk to surrounding structures and optimising outcomes. We aim to create a checklist to streamline pre-operative planning. We retrospectively reviewed pre-operative CT and MRI scans of 100 adults undergoing trans-sphenoidal endoscopic pituitary surgery. Radiological findings and their incidence included deviated nasal septum (62%), concha bullosa (32%), bony dehiscence of the carotid arteries (18%), sphenoid septation overlying the internal carotid artery (24% at the sella) and low lying CSF (32%). The mean distance of the sphenoid ostium to the skull base was 10 mm (range 2.7-17.6 mm). We also describe the 'teddy bear' sign which when present on an axial CT indicates the carotid arteries will be identifiable intra-operatively. There are significant variations in the anatomical and pituitary disease features between patients. We describe a number of features on pre-operative scans and have devised a checklist including a new 'teddy bear' sign to aid the surgeon in the anatomical assessment of patients undergoing trans-sphenoidal pituitary surgery.

The Impact of Natural Hazards such as Turbulent Wind Gusts on the Wind Energy Conversion Process

NASA Astrophysics Data System (ADS)

Wächter, M.; Hölling, M.; Milan, P.; Morales, A.; Peinke, J.

2012-12-01

Wind turbines operate in the atmospheric boundary layer, where they are exposed to wind gusts and other types of natural hazards. As the response time of wind turbines is typically in the range of seconds, they are affected by the small scale intermittent properties of the turbulent wind. We show evidence that basic features which are known for small-scale homogeneous isotropic turbulence, and in particular the well-known intermittency problem, have an important impact on the wind energy conversion process. Intermittent statistics include high probabilities of extreme events which can be related to wind gusts and other types of natural hazards. As a summarizing result we find that atmospheric turbulence imposes its intermittent features on the complete wind energy conversion process. Intermittent turbulence features are not only present in atmospheric wind, but are also dominant in the loads on the turbine, i.e. rotor torque and thrust, and in the electrical power output signal. We conclude that profound knowledge of turbulent statistics and the application of suitable numerical as well as experimental methods are necessary to grasp these unique features and quantify their effects on all stages of wind energy conversion.

Clinical and electrophysiological features of post-traumatic Guillain-Barré syndrome.

PubMed

Li, Xiaowen; Xiao, Jinting; Ding, Yanan; Xu, Jing; Li, Chuanxia; He, Yating; Zhai, Hui; Xie, Bingdi; Hao, Junwei

2017-07-27

Post-traumatic Guillain-Barré syndrome (GBS) is a rarely described potentially life-threatening cause of weakness. We sought to elucidate the clinical features and electrophysiological patterns of post-traumatic GBS as an aid to diagnosis. We retrospectively studied six patients diagnosed with post-traumatic GBS between 2014 and 2016 at Tianjin Medical University General Hospital, China. Clinical features, serum analysis, lumbar puncture results, electrophysiological examinations, and prognosis were assessed. All six patients had different degrees of muscular atrophy at nadir and in two, respiratory muscles were involved. Five also had damaged cranial nerves and four of these had serum antibodies against gangliosides. The most common electrophysiological findings were relatively normal distal latency, prominent reduction of compound muscle action potential amplitude, and absence of F-waves, which are consistent with an axonal form of GBS. It is often overlooked that GBS can be triggered by non-infectious factors such as trauma and its short-term prognosis is poor. Therefore, it is important to analyze the clinical and electrophysiological features of GBS after trauma. Here we have shown that electrophysiological evaluations are helpful for diagnosing post-traumatic GBS. Early diagnosis may support appropriate treatment to help prevent morbidity and improve prognosis.

On the probability density function and characteristic function moments of image steganalysis in the log prediction error wavelet subband

NASA Astrophysics Data System (ADS)

Bao, Zhenkun; Li, Xiaolong; Luo, Xiangyang

2017-01-01

Extracting informative statistic features is the most essential technical issue of steganalysis. Among various steganalysis methods, probability density function (PDF) and characteristic function (CF) moments are two important types of features due to the excellent ability for distinguishing the cover images from the stego ones. The two types of features are quite similar in definition. The only difference is that the PDF moments are computed in the spatial domain, while the CF moments are computed in the Fourier-transformed domain. Then, the comparison between PDF and CF moments is an interesting question of steganalysis. Several theoretical results have been derived, and CF moments are proved better than PDF moments in some cases. However, in the log prediction error wavelet subband of wavelet decomposition, some experiments show that the result is opposite and lacks a rigorous explanation. To solve this problem, a comparison result based on the rigorous proof is presented: the first-order PDF moment is proved better than the CF moment, while the second-order CF moment is better than the PDF moment. It tries to open the theoretical discussion on steganalysis and the question of finding suitable statistical features.

Goblet Cell Hyperplasia Requires High Bicarbonate Transport To Support Mucin Release.

PubMed

Gorrieri, Giulia; Scudieri, Paolo; Caci, Emanuela; Schiavon, Marco; Tomati, Valeria; Sirci, Francesco; Napolitano, Francesco; Carrella, Diego; Gianotti, Ambra; Musante, Ilaria; Favia, Maria; Casavola, Valeria; Guerra, Lorenzo; Rea, Federico; Ravazzolo, Roberto; Di Bernardo, Diego; Galietta, Luis J V

2016-10-27

Goblet cell hyperplasia, a feature of asthma and other respiratory diseases, is driven by the Th-2 cytokines IL-4 and IL-13. In human bronchial epithelial cells, we find that IL-4 induces the expression of many genes coding for ion channels and transporters, including TMEM16A, SLC26A4, SLC12A2, and ATP12A. At the functional level, we find that IL-4 enhances calcium- and cAMP-activated chloride/bicarbonate secretion, resulting in high bicarbonate concentration and alkaline pH in the fluid covering the apical surface of epithelia. Importantly, mucin release, elicited by purinergic stimulation, requires the presence of bicarbonate in the basolateral solution and is defective in cells derived from cystic fibrosis patients. In conclusion, our results suggest that Th-2 cytokines induce a profound change in expression and function in multiple ion channels and transporters that results in enhanced bicarbonate transport ability. This change is required as an important mechanism to favor release and clearance of mucus.

Goblet Cell Hyperplasia Requires High Bicarbonate Transport To Support Mucin Release

PubMed Central

Gorrieri, Giulia; Scudieri, Paolo; Caci, Emanuela; Schiavon, Marco; Tomati, Valeria; Sirci, Francesco; Napolitano, Francesco; Carrella, Diego; Gianotti, Ambra; Musante, Ilaria; Favia, Maria; Casavola, Valeria; Guerra, Lorenzo; Rea, Federico; Ravazzolo, Roberto; Di Bernardo, Diego; Galietta, Luis J. V.

2016-01-01

Goblet cell hyperplasia, a feature of asthma and other respiratory diseases, is driven by the Th-2 cytokines IL-4 and IL-13. In human bronchial epithelial cells, we find that IL-4 induces the expression of many genes coding for ion channels and transporters, including TMEM16A, SLC26A4, SLC12A2, and ATP12A. At the functional level, we find that IL-4 enhances calcium- and cAMP-activated chloride/bicarbonate secretion, resulting in high bicarbonate concentration and alkaline pH in the fluid covering the apical surface of epithelia. Importantly, mucin release, elicited by purinergic stimulation, requires the presence of bicarbonate in the basolateral solution and is defective in cells derived from cystic fibrosis patients. In conclusion, our results suggest that Th-2 cytokines induce a profound change in expression and function in multiple ion channels and transporters that results in enhanced bicarbonate transport ability. This change is required as an important mechanism to favor release and clearance of mucus. PMID:27786259

Hostility/anger as a mediator between college students' emotion regulation abilities and symptoms of depression, social anxiety, and generalized anxiety.

PubMed

Asberg, Kia

2013-01-01

Internalizing problems are common among college students and have been linked consistently to deficits in emotion regulation (ER). Also, hostility/anger (animosity toward others, phenomenological aspect of anger) is an important feature of internalizing problems, but has received limited attention as a mediator between ER and outcomes. Results (N = 160) indicated that although college students' ER abilities corresponded with all three types of internalizing symptoms, hostility/anger mediated fully the relationship for symptoms of depression and social anxiety, but not generalized anxiety (GAD). The stronger interpersonal aspect inherent in depression and social anxiety relative to GAD may in part explain findings, but findings must be viewed in lieu of limitations, which include self-report, a non-clinical sample, and a cross-sectional design. Overall, hostility/anger may be important to address in interventions and programs aimed at reducing internalizing problems, especially among those who demonstrate ER deficits and are prone to depression and social anxiety.

When to suspect a genetic syndrome.

PubMed

Solomon, Benjamin D; Muenke, Maximilian

2012-11-01

Family physicians should be able to recognize findings on physical examination and history that suggest the presence of a genetic syndrome to aid in the diagnosis and treatment of potentially affected patients, as well as subspecialty referral. General themes that can alert family physicians to the presence of genetic conditions include dysmorphic features that are evident on physical examination; multiple anomalies in one patient; unexplained neurocognitive impairment; and a family history that is suggestive of a hereditary disease. The presence of one obvious malformation should not limit the full evaluation, because additional, subtler findings will often be important in the differential diagnosis. Taking an accurate three-generation family history is invaluable when considering a genetic syndrome. Important elements include the age and sex of family members; when family members were affected by disease or when they died; the ethnic background; and if there is consanguinity. Genetic subspecialists can assist family physicians in diagnosis, suggest additional testing and referrals if warranted, help direct medical care, and provide counseling for affected patients and their families.

Regulation and competition in the Taiwanese pharmaceutical market under national health insurance.

PubMed

Liu, Ya-Ming; Yang, Yea-Huei Kao; Hsieh, Chee-Ruey

2012-05-01

This article investigates the determinants of the prices of pharmaceuticals and their impact on the demand for prescription drugs in the context of Taiwan's pharmaceutical market where medical providers earn profit directly from prescribing and dispensing drugs. Based on product-level data, we find evidence that the profit-seeking behavior of the medical providers in the prescription drug market transfers the force of competition from the unregulated wholesale market to the regulated retail market and hence market competition still plays an important role in the determination of the regulated price. We also find that the profit-seeking behavior plays a similar role to advertising in that it increases the brand loyalty and hence lowers price elasticity. An important implication of our study is that the institutional features in the pharmaceutical market matter in shaping the nature of pharmaceutical competition and the responsiveness of pharmaceutical consumption with respect to changes in price. Copyright © 2012 Elsevier B.V. All rights reserved.

An Unrecognized Rash Progressing to Lyme Carditis: Important Features and Recommendations Regarding Lyme Disease.

PubMed

Lee, Shawn; Singla, Montish

2016-01-01

We present a case report of 46-year-old man with no medical history, who complained of extreme fatigue, near-syncope, and palpitations. He initially presented in complete heart block. A transvenous pacemaker was placed in the emergency department, and he was started empirically on Ceftriaxone for Lyme disease. He was admitted and over the course of the next few days, his rhythm regressed to Mobitz type I first-degree atrioventricular block and then to normal sinus rhythm. This case report highlights some important features regarding Lyme carditis, a rare presentation of early disseminated Lyme disease (seen in a few weeks to months after the initial tick bite). In 25%-30% of patients, the characteristic targetoid rash may not be seen, a likely culprit of the disease not being detected early and progressing to disseminated disease. The most common cardiac complaint of Lyme disease is palpitations, occurring in 6.6% of patients, which may not accurately reflect progression into disseminated Lyme disease because it is a nonspecific finding. Conduction abnormality, occurring in 1.8% of patients, is a more specific finding of Borrelia invading cardiac tissue. Finally, this case report highlights a recommendation that patients with confirmed Lyme disease or those presenting with cardiac abnormalities or symptoms who have an atypical profile for a cardiac event should be screened with a 12-lead electrocardiogram, Lyme serology, and be considered for antibiotic therapy with the possibility of temporary pacing.

Moving Just Like You: Motor Interference Depends on Similar Motility of Agent and Observer

PubMed Central

Kupferberg, Aleksandra; Huber, Markus; Helfer, Bartosz; Lenz, Claus; Knoll, Alois; Glasauer, Stefan

2012-01-01

Recent findings in neuroscience suggest an overlap between brain regions involved in the execution of movement and perception of another’s movement. This so-called “action-perception coupling” is supposed to serve our ability to automatically infer the goals and intentions of others by internal simulation of their actions. A consequence of this coupling is motor interference (MI), the effect of movement observation on the trajectory of one’s own movement. Previous studies emphasized that various features of the observed agent determine the degree of MI, but could not clarify how human-like an agent has to be for its movements to elicit MI and, more importantly, what ‘human-like’ means in the context of MI. Thus, we investigated in several experiments how different aspects of appearance and motility of the observed agent influence motor interference (MI). Participants performed arm movements in horizontal and vertical directions while observing videos of a human, a humanoid robot, or an industrial robot arm with either artificial (industrial) or human-like joint configurations. Our results show that, given a human-like joint configuration, MI was elicited by observing arm movements of both humanoid and industrial robots. However, if the joint configuration of the robot did not resemble that of the human arm, MI could longer be demonstrated. Our findings present evidence for the importance of human-like joint configuration rather than other human-like features for perception-action coupling when observing inanimate agents. PMID:22761853

Search predicts and changes patience in intertemporal choice

PubMed Central

Johnson, Eric J.

2017-01-01

Intertemporal choice impacts many important outcomes, such as decisions about health, education, wealth, and the environment. However, the psychological processes underlying decisions involving outcomes at different points in time remain unclear, limiting opportunities to intervene and improve people’s patience. This research examines information-search strategies used during intertemporal choice and their impact on decisions. In experiment 1, we demonstrate that search strategies vary substantially across individuals. We subsequently identify two distinct search strategies across individuals. Comparative searchers, who compare features across options, discount future options less and are more susceptible to acceleration versus delay framing than integrative searchers, who integrate the features of an option. Experiment 2 manipulates search using an unobtrusive method to establish a causal relationship between strategy and choice, randomly assigning participants to conditions promoting either comparative or integrative search. Again, comparative search promotes greater patience than integrative search. Additionally, when participants adopt a comparative search strategy, they also exhibit greater effects of acceleration versus delay framing. Although most participants reported that the manipulation did not change their behavior, promoting comparative search decreased discounting of future rewards substantially and speeded patient choices. These findings highlight the central role that heterogeneity in psychological processes plays in shaping intertemporal choice. Importantly, these results indicate that theories that ignore variability in search strategies may be inadvertently aggregating over different subpopulations that use very different processes. The findings also inform interventions in choice architecture to increase patience and improve consumer welfare. PMID:29078303

Biologically important conformational features of DNA as interpreted by quantum mechanics and molecular mechanics computations of its simple fragments.

PubMed

Poltev, V; Anisimov, V M; Dominguez, V; Gonzalez, E; Deriabina, A; Garcia, D; Rivas, F; Polteva, N A

2018-02-01

Deciphering the mechanism of functioning of DNA as the carrier of genetic information requires identifying inherent factors determining its structure and function. Following this path, our previous DFT studies attributed the origin of unique conformational characteristics of right-handed Watson-Crick duplexes (WCDs) to the conformational profile of deoxydinucleoside monophosphates (dDMPs) serving as the minimal repeating units of DNA strand. According to those findings, the directionality of the sugar-phosphate chain and the characteristic ranges of dihedral angles of energy minima combined with the geometric differences between purines and pyrimidines determine the dependence on base sequence of the three-dimensional (3D) structure of WCDs. This work extends our computational study to complementary deoxydinucleotide-monophosphates (cdDMPs) of non-standard conformation, including those of Z-family, Hoogsteen duplexes, parallel-stranded structures, and duplexes with mispaired bases. For most of these systems, except Z-conformation, computations closely reproduce experimental data within the tolerance of characteristic limits of dihedral parameters for each conformation family. Computation of cdDMPs with Z-conformation reveals that their experimental structures do not correspond to the internal energy minimum. This finding establishes the leading role of external factors in formation of the Z-conformation. Energy minima of cdDMPs of non-Watson-Crick duplexes demonstrate different sequence-dependence features than those known for WCDs. The obtained results provide evidence that the biologically important regularities of 3D structure distinguish WCDs from duplexes having non-Watson-Crick nucleotide pairing.

How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences

PubMed Central

Dolan, Raymond J.

2016-01-01

The weight with which a specific outcome feature contributes to preference quantifies a person’s ‘taste’ for that feature. However, far from being fixed personality characteristics, tastes are plastic. They tend to align, for example, with those of others even if such conformity is not rewarded. We hypothesised that people can be uncertain about their tastes. Personal tastes are therefore uncertain beliefs. People can thus learn about them by considering evidence, such as the preferences of relevant others, and then performing Bayesian updating. If a person’s choice variability reflects uncertainty, as in random-preference models, then a signature of Bayesian updating is that the degree of taste change should correlate with that person’s choice variability. Temporal discounting coefficients are an important example of taste–for patience. These coefficients quantify impulsivity, have good psychometric properties and can change upon observing others’ choices. We examined discounting preferences in a novel, large community study of 14–24 year olds. We assessed discounting behaviour, including decision variability, before and after participants observed another person’s choices. We found good evidence for taste uncertainty and for Bayesian taste updating. First, participants displayed decision variability which was better accounted for by a random-taste than by a response-noise model. Second, apparent taste shifts were well described by a Bayesian model taking into account taste uncertainty and the relevance of social information. Our findings have important neuroscientific, clinical and developmental significance. PMID:27447491

Search predicts and changes patience in intertemporal choice.

PubMed

Reeck, Crystal; Wall, Daniel; Johnson, Eric J

2017-11-07

Intertemporal choice impacts many important outcomes, such as decisions about health, education, wealth, and the environment. However, the psychological processes underlying decisions involving outcomes at different points in time remain unclear, limiting opportunities to intervene and improve people's patience. This research examines information-search strategies used during intertemporal choice and their impact on decisions. In experiment 1, we demonstrate that search strategies vary substantially across individuals. We subsequently identify two distinct search strategies across individuals. Comparative searchers, who compare features across options, discount future options less and are more susceptible to acceleration versus delay framing than integrative searchers, who integrate the features of an option. Experiment 2 manipulates search using an unobtrusive method to establish a causal relationship between strategy and choice, randomly assigning participants to conditions promoting either comparative or integrative search. Again, comparative search promotes greater patience than integrative search. Additionally, when participants adopt a comparative search strategy, they also exhibit greater effects of acceleration versus delay framing. Although most participants reported that the manipulation did not change their behavior, promoting comparative search decreased discounting of future rewards substantially and speeded patient choices. These findings highlight the central role that heterogeneity in psychological processes plays in shaping intertemporal choice. Importantly, these results indicate that theories that ignore variability in search strategies may be inadvertently aggregating over different subpopulations that use very different processes. The findings also inform interventions in choice architecture to increase patience and improve consumer welfare. Copyright © 2017 the Author(s). Published by PNAS.

Finding meaning in art: Preferred levels of ambiguity in art appreciation

PubMed Central

Jakesch, Martina; Leder, Helmut

2011-01-01

Uncertainty is typically not desirable in everyday experiences, but uncertainty in the form of ambiguity may be a defining feature of aesthetic experiences of modern art. In this study, we examined different hypotheses concerning the quantity and quality of information appreciated in art. Artworks were shown together with auditorily presented statements. We tested whether the amount of information, the amount of matching information, or the proportion of matching to nonmatching statements apparent in a picture (levels of ambiguity) affect liking and interestingness. Only the levels of ambiguity predicted differences in the two dependent variables. These findings reveal that ambiguity is an important determinant of aesthetic appreciation and that a certain level of ambiguity is appreciable. PMID:19565431

Stomach metastasis of breast carcinoma mimicking primary gastric neoplasm on fluorodeoxy glucose-positron emission tomography-computed tomography.

PubMed

Joshi, Prathamesh; Lele, Vikram; Jain, Reetu; Khubchandani, Shaila; Sinhasan, Shraddha

2013-04-01

We present fluorodeoxy glucose positron emission tomography-computed tomography (FDG-PET/CT) findings in a case of breast carcinoma. The PET/CT findings in this case were suspicious of second primary neoplasm in the stomach. However, on endoscopic biopsy, the lesion was found to be stomach metastasis of breast carcinoma with estrogen receptor positivity. Stomach is a rare site of breast carcinoma metastasis. Our case suggests that it is difficult to distinguish a stomach metastasis of breast cancer from a primary gastric cancer on the basis of clinical and imaging features. However, this differential diagnosis must be kept in mind and it is important to make such distinction because of its implications on patient management.

Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI

NASA Astrophysics Data System (ADS)

Litjens, G. J. S.; Elliott, R.; Shih, N.; Feldman, M.; Barentsz, J. O.; Hulsbergen-van de Kaa, C. A.; Kovacs, I.; Huisman, H. J.; Madabhushi, A.

2014-03-01

Learning how to separate benign confounders from prostate cancer is important because the imaging characteristics of these confounders are poorly understood. Furthermore, the typical representations of the MRI parameters might not be enough to allow discrimination. The diagnostic uncertainty this causes leads to a lower diagnostic accuracy. In this paper a new cascaded classifier is introduced to separate prostate cancer and benign confounders on MRI in conjunction with specific computer-extracted features to distinguish each of the benign classes (benign prostatic hyperplasia (BPH), inflammation, atrophy or prostatic intra-epithelial neoplasia (PIN). In this study we tried to (1) calculate different mathematical representations of the MRI parameters which more clearly express subtle differences between different classes, (2) learn which of the MRI image features will allow to distinguish specific benign confounders from prostate cancer, and (2) find the combination of computer-extracted MRI features to best discriminate cancer from the confounding classes using a cascaded classifier. One of the most important requirements for identifying MRI signatures for adenocarcinoma, BPH, atrophy, inflammation, and PIN is accurate mapping of the location and spatial extent of the confounder and cancer categories from ex vivo histopathology to MRI. Towards this end we employed an annotated prostatectomy data set of 31 patients, all of whom underwent a multi-parametric 3 Tesla MRI prior to radical prostatectomy. The prostatectomy slides were carefully co-registered to the corresponding MRI slices using an elastic registration technique. We extracted texture features from the T2-weighted imaging, pharmacokinetic features from the dynamic contrast enhanced imaging and diffusion features from the diffusion-weighted imaging for each of the confounder classes and prostate cancer. These features were selected because they form the mainstay of clinical diagnosis. Relevant features for each of the classes were selected using maximum relevance minimum redundancy feature selection, allowing us to perform classifier independent feature selection. The selected features were then incorporated in a cascading classifier, which can focus on easier sub-tasks at each stage, leaving the more difficult classification tasks for later stages. Results show that distinct features are relevant for each of the benign classes, for example the fraction of extra-vascular, extra-cellular space in a voxel is a clear discriminator for inflammation. Furthermore, the cascaded classifier outperforms both multi-class and one-shot classifiers in overall accuracy for discriminating confounders from cancer: 0.76 versus 0.71 and 0.62.

ECG feature extraction and disease diagnosis.

PubMed

Bhyri, Channappa; Hamde, S T; Waghmare, L M

2011-01-01

An important factor to consider when using findings on electrocardiograms for clinical decision making is that the waveforms are influenced by normal physiological and technical factors as well as by pathophysiological factors. In this paper, we propose a method for the feature extraction and heart disease diagnosis using wavelet transform (WT) technique and LabVIEW (Laboratory Virtual Instrument Engineering workbench). LabVIEW signal processing tools are used to denoise the signal before applying the developed algorithm for feature extraction. First, we have developed an algorithm for R-peak detection using Haar wavelet. After 4th level decomposition of the ECG signal, the detailed coefficient is squared and the standard deviation of the squared detailed coefficient is used as the threshold for detection of R-peaks. Second, we have used daubechies (db6) wavelet for the low resolution signals. After cross checking the R-peak location in 4th level, low resolution signal of daubechies wavelet P waves and T waves are detected. Other features of diagnostic importance, mainly heart rate, R-wave width, Q-wave width, T-wave amplitude and duration, ST segment and frontal plane axis are also extracted and scoring pattern is applied for the purpose of heart disease diagnosis. In this study, detection of tachycardia, bradycardia, left ventricular hypertrophy, right ventricular hypertrophy and myocardial infarction have been considered. In this work, CSE ECG data base which contains 5000 samples recorded at a sampling frequency of 500 Hz and the ECG data base created by the S.G.G.S. Institute of Engineering and Technology, Nanded (Maharashtra) have been used.

Conversation analysis can help to distinguish between epilepsy and non-epileptic seizure disorders: a case comparison.

PubMed

Plug, Leendert; Sharrack, Basil; Reuber, Markus

2009-01-01

Factual items in patients' histories are of limited discriminating value in the differential diagnosis of epilepsy and non-epileptic seizures (NES). A number of studies using a transcript-based sociolinguistic research method inspired by Conversation Analysis (CA) suggest that it is helpful to focus on how patients talk. Previous reports communicated these findings by using particularly clear examples of diagnostically relevant interactional, linguistic and topical features from different patients. They did not discuss the sequential display of different features although this is crucially important from a conversation analytic point of view. This case comparison aims to show clinicians how the discriminating features are displayed by individual patients over the course of a clinical encounter. CA-inspired brief sequential analysis of two first 30-min doctor-patient encounters by a linguist blinded to all medical information. A gold standard diagnosis was made by the recording of a typical seizure with video-EEG. The patient with epilepsy volunteered detailed first person accounts of seizures. The NES patient exhibited resistance to focusing on individual seizure episodes and only provided a detailed seizure description after repeated prompting towards the end of the interview. Although both patients also displayed some linguistic features favouring the alternative diagnosis, the linguist's final diagnostic hypothesis matched the diagnosis made by video-EEG in both cases. This study illustrates the importance of the time point at which patients share information with the doctor. It supports the notion that close attention to how patients communicate can help in the differential diagnosis of seizures.

Newspaper Lesson Aids.

ERIC Educational Resources Information Center

Communication: Journalism Education Today (C:JET), 1986

1986-01-01

Provides photocopy-ready lesson aids on story ideas, interviewing, inverted pyramid writing style, newswriting, sports/scavenger hunt, finding feature material, identifying feature leads, feature lead selection, evaluating feature leads, compiling survey material, cutlines, headlines, paste-up rules, advertising, final semester project, newspaper…

Life events and borderline personality features: the influence of gene-environment interaction and gene-environment correlation.

PubMed

Distel, M A; Middeldorp, C M; Trull, T J; Derom, C A; Willemsen, G; Boomsma, D I

2011-04-01

Traumatic life events are generally more common in patients with borderline personality disorder (BPD) than in non-patients or patients with other personality disorders. This study investigates whether exposure to life events moderates the genetic architecture of BPD features. As the presence of genotype-environment correlation (rGE) can lead to spurious findings of genotype-environment interaction (G × E), we also test whether BPD features increase the likelihood of exposure to life events. The extent to which an individual is at risk to develop BPD was assessed with the Personality Assessment Inventory - Borderline features scale (PAI-BOR). Life events under study were a divorce/break-up, traffic accident, violent assault, sexual assault, robbery and job loss. Data were available for 5083 twins and 1285 non-twin siblings. Gene-environment interaction and correlation were assessed by using structural equation modelling (SEM) and the co-twin control design. There was evidence for both gene-environment interaction and correlation. Additive genetic influences on BPD features interacted with the exposure to sexual assault, with genetic variance being lower in exposed individuals. In individuals who had experienced a divorce/break-up, violent assault, sexual assault or job loss, environmental variance for BPD features was higher, leading to a lower heritability of BPD features in exposed individuals. Gene-environment correlation was present for some life events. The genes that influence BPD features thus also increased the likelihood of being exposed to certain life events. To our knowledge, this study is the first to test the joint effect of genetic and environmental influences and the exposure to life events on BPD features in the general population. Our results indicate the importance of both genetic vulnerability and life events.

Honeybees use the skyline in orientation.

PubMed

Towne, William F; Ritrovato, Antoinette E; Esposto, Antonina; Brown, Duncan F

2017-07-01

In view-based navigation, animals acquire views of the landscape from various locations and then compare the learned views with current views in order to orient in certain directions or move toward certain destinations. One landscape feature of great potential usefulness in view-based navigation is the skyline, the silhouette of terrestrial objects against the sky, as it is distant, relatively stable and easy to detect. The skyline has been shown to be important in the view-based navigation of ants, but no flying insect has yet been shown definitively to use the skyline in this way. Here, we show that honeybees do indeed orient using the skyline. A feeder was surrounded with an artificial replica of the natural skyline there, and the bees' departures toward the nest were recorded from above with a video camera under overcast skies (to eliminate celestial cues). When the artificial skyline was rotated, the bees' departures were rotated correspondingly, showing that the bees oriented by the artificial skyline alone. We discuss these findings in the context of the likely importance of the skyline in long-range homing in bees, the likely importance of altitude in using the skyline, the likely role of ultraviolet light in detecting the skyline, and what we know about the bees' ability to resolve skyline features. © 2017. Published by The Company of Biologists Ltd.

When viewing natural scenes, do abnormal colors impact on spatial or temporal parameters of eye movements?

PubMed

Ho-Phuoc, Tien; Guyader, Nathalie; Landragin, Frédéric; Guérin-Dugué, Anne

2012-02-03

Since Treisman's theory, it has been generally accepted that color is an elementary feature that guides eye movements when looking at natural scenes. Hence, most computational models of visual attention predict eye movements using color as an important visual feature. In this paper, using experimental data, we show that color does not affect where observers look when viewing natural scene images. Neither colors nor abnormal colors modify observers' fixation locations when compared to the same scenes in grayscale. In the same way, we did not find any significant difference between the scanpaths under grayscale, color, or abnormal color viewing conditions. However, we observed a decrease in fixation duration for color and abnormal color, and this was particularly true at the beginning of scene exploration. Finally, we found that abnormal color modifies saccade amplitude distribution.

Serial sectioning of grain microstructures under junction control: An old problem in a new guise

NASA Astrophysics Data System (ADS)

Zöllner, D.; Streitenberger, P.

2015-04-01

In the present work the importance of 3D and 4D microstructure analyses are shown. To that aim, we study polycrystalline grain microstructures obtained by grain growth under grain boundary, triple line and quadruple point control. The microstructures themselves are obtained by mesoscopic computer simulations, which enjoy a far greater control over the kinetic and thermodynamic parameters affecting grain growth than can be realized experimentally. In extensive simulation studies we find by 3D respectively 4D microstructure analyses that metrical and topological properties of the microstructures depend strongly on the microstructural feature controlling the growth kinetics. However, the differences between the growth kinetics vanish when we look at classical 2D sections of the 3D ensembles making a differentiation of the controlling grain feature near impossible.

The Nash Equilibrium Revisited: Chaos and Complexity Hidden in Simplicity

NASA Astrophysics Data System (ADS)

Fellman, Philip V.

The Nash Equilibrium is a much discussed, deceptively complex, method for the analysis of non-cooperative games (McLennan and Berg, 2005). If one reads many of the commonly available definitions the description of the Nash Equilibrium is deceptively simple in appearance. Modern research has discovered a number of new and important complex properties of the Nash Equilibrium, some of which remain as contemporary conundrums of extraordinary difficulty and complexity (Quint and Shubik, 1997). Among the recently discovered features which the Nash Equilibrium exhibits under various conditions are heteroclinic Hamiltonian dynamics, a very complex asymptotic structure in the context of two-player bi-matrix games and a number of computationally complex or computationally intractable features in other settings (Sato, Akiyama and Farmer, 2002). This paper reviews those findings and then suggests how they may inform various market prediction strategies.

Dirac State in Giant Magnetoresistive Materials

NASA Astrophysics Data System (ADS)

Wu, Y.; Jo, N. H.; Ochi, M.; Huang, L.; Mou, D.; Kong, T.; Mun, E.; Wang, L.; Lee, Y.; Bud'Ko, S. L.; Canfield, P. C.; Trivedi, N.; Arito, R.; Kaminski, A.

We use ultrahigh resolution, tunable, vacuum ultraviolet laser-based angle-resolved photoemission spectroscopy (ARPES) to study the electronic properties of materials that recently were discovered to display titanic magnetoresistance. We find that that several of these materials have Dirac-like features in their band structure. In some materials those features are ``ordinary'' Dirac cones, while in others the linear Dirac dispersion of two crossing bands forms a linear object in 3D momentum space. Our observation poses an important question about the role of Dirac dispersion in the unusually high, non-saturating magnetoresistance of these materials. Research was supported by the US DOE, Office of Basic Energy Sciences under Contract No. DE-AC02-07CH11358; Gordon and Betty Moore Foundation EPiQS Initiative (Grant No. GBMF4411); CEM, a NSF MRSEC, under Grant No. DMR-1420451.

MOTIFSIM 2.1: An Enhanced Software Platform for Detecting Similarity in Multiple DNA Motif Data Sets

PubMed Central

Huang, Chun-Hsi

2017-01-01

Abstract Finding binding site motifs plays an important role in bioinformatics as it reveals the transcription factors that control the gene expression. The development for motif finders has flourished in the past years with many tools have been introduced to the research community. Although these tools possess exceptional features for detecting motifs, they report different results for an identical data set. Hence, using multiple tools is recommended because motifs reported by several tools are likely biologically significant. However, the results from multiple tools need to be compared for obtaining common significant motifs. MOTIFSIM web tool and command-line tool were developed for this purpose. In this work, we present several technical improvements as well as additional features to further support the motif analysis in our new release MOTIFSIM 2.1. PMID:28632401

Student Buy-In to Active Learning in a College Science Course

PubMed Central

Cavanagh, Andrew J.; Aragón, Oriana R.; Chen, Xinnian; Couch, Brian; Durham, Mary; Bobrownicki, Aiyana; Hanauer, David I.; Graham, Mark J.

2016-01-01

The benefits of introducing active learning in college science courses are well established, yet more needs to be understood about student buy-in to active learning and how that process of buy-in might relate to student outcomes. We test the exposure–persuasion–identification–commitment (EPIC) process model of buy-in, here applied to student (n = 245) engagement in an undergraduate science course featuring active learning. Student buy-in to active learning was positively associated with engagement in self-regulated learning and students’ course performance. The positive associations among buy-in, self-regulated learning, and course performance suggest buy-in as a potentially important factor leading to student engagement and other student outcomes. These findings are particularly salient in course contexts featuring active learning, which encourage active student participation in the learning process. PMID:27909026

Spatially resolved dielectric constant of confined water and its connection to the non-local nature of bulk water

NASA Astrophysics Data System (ADS)

Schaaf, Christian; Gekle, Stephan

2016-08-01

We use molecular dynamics simulations to compute the spatially resolved static dielectric constant of water in cylindrical and spherical nanopores as occurring, e.g., in protein water pockets or carbon nanotubes. For this, we derive a linear-response formalism which correctly takes into account the dielectric boundary conditions in the considered geometries. We find that in cylindrical confinement, the axial component behaves similar as the local density akin to what is known near planar interfaces. The radial dielectric constant shows some oscillatory features when approaching the surface if their radius is larger than about 2 nm. Most importantly, however, the radial component exhibits pronounced oscillations at the center of the cavity. These surprising features are traced back quantitatively to the non-local dielectric nature of bulk water.

Spectral function of a hole in the t - J model

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

Liu, Z.; Manousakis, E.

1991-08-01

We give numerical solutions, on finite but large-size square lattices, of the equation for the single-hole Green's function obtained by the self-consistent approach of Schmitt-Rink {ital et} {ital al}. and Kane {ital et} {ital al}. The spectral function of the hole in a quantum antiferromagnet shows that most features describing the hole motion are in close agreement with the results of the exact diagonalization on the 4{sup 2} lattice in the region of {ital J}/{ital t}{le}0.2. Our results obtained on sufficiently large-size lattices suggest that certain important features of the spectral function survive in the thermodynamic limit while others changemore » due to finite-size effects. We find that the leading nonzero vertex correction is given by a two-loop diagram, which has a small contribution.« less

Characterizing dark matter at the LHC in Drell-Yan events

NASA Astrophysics Data System (ADS)

Capdevilla, Rodolfo M.; Delgado, Antonio; Martin, Adam; Raj, Nirmal

2018-02-01

Spectral features in LHC dileptonic events may signal radiative corrections coming from new degrees of freedom, notably dark matter and mediators. Using simplified models, and under a set of simplifying assumptions, we show how these features can reveal the fundamental properties of the dark sector, such as self-conjugation, spin and mass of dark matter, and the quantum numbers of the mediator. Distributions of both the invariant mass mℓℓ and the Collins-Soper scattering angle cos θCS are studied to pinpoint these properties. We derive constraints on the models from LHC measurements of mℓℓ and cos θCS, which are competitive with direct detection and jets+MET searches. We find that in certain scenarios the cos θCS spectrum provides the strongest bounds, underlining the importance of scattering angle measurements for nonresonant new physics.

Pathology and differential diagnosis of chronic, noninfectious gastritis.

PubMed

Polydorides, Alexandros D

2014-03-01

The histologic finding of chronic inflammation in an endoscopic mucosal biopsy of the stomach (chronic gastritis) is very common and usually reflects the presence of Helicobacter pylori infection. However, infectious organisms are not always present in biopsy material, and some cases of chronic gastritis do not result from H. pylori infection. Thus, the differential diagnosis of this finding is an important one for pathologists to keep in mind. This review presents the three most common and clinically significant causes of chronic, noninfectious gastritis, namely, autoimmune atrophic gastritis, lymphocytic gastritis, and gastric involvement in the setting of inflammatory bowel disease, especially Crohn disease. For each entity, a brief discussion of its etiology and pathogenesis, a review of the clinical and endoscopic features, and a description of the microscopic findings are presented in the context of the differential diagnosis of chronic gastritis with emphasis on helpful histopathologic hints and long-term sequelae. Copyright © 2014 Elsevier Inc. All rights reserved.

Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures

NASA Astrophysics Data System (ADS)

Peña, Isis; Viktor, Herna L.; Paquet, Eric

Clothes should fit consumers well, be aesthetically pleasing and comfortable. However, repeated studies of customers’ levels of satisfaction indicate that this is often not the case. For example, more robust males often find it difficult to find pants that are the correct length and fit their waists well. What, then, are the typical body profiles of the population? Would it be possible to identify the measurements that are of importance for different sizes and genders? Furthermore, assuming that we have access to an anthropometric database would there be a way to guide the data mining process to discover only those relevant body measurements that are of the most interest for apparel designers? This paper describes our results when addressing these questions through cluster analysis and interestingness measures-based feature selection. We explore a database containing anthropometric measurements as well as 3-D body scans, of a representative sample of the Dutch population.

'Trampoline fracture' of the proximal tibia in children: report of 3 cases and review of literature.

PubMed

Bruyeer, E; Geusens, E; Catry, F; Vanstraelen, L; Vanhoenacker, F

2012-01-01

We present three cases of fracture of the proximal tibia in young children who were jumping on a trampoline. The typical radiological findings and the underlying mechanism of trauma are discussed. The key radiological features are: a transverse hairline fracture of the upper tibia often accompanied by a buckle fracture of the lateral or medial tibial cortex, buckling of the anterior upper tibial cortex and anterior tilting of the epiphyseal plate. New types of injuries related to specific recreational activities are recognized. It is often helpful to associate a typical injury with a particular activity. Trampoline related injuries have increased dramatically over the last years. The most common lesions are fractures and ligamentous injuries, in particular a transverse fracture of the proximal tibia. However the radiological findings can be very subtle and easily overlooked. It is therefore important to be aware of the typical history and radiological findings.

Aggressive B-cell lymphomas in the update of the 4th edition of the World Health Organization classification of haematopoietic and lymphatic tissues: refinements of the classification, new entities and genetic findings.

PubMed

Ott, German

2017-09-01

The update of the 4th edition of the World Health Organization Classification of Haematopoietic and Lymphatic Tissues portends important new findings and concepts in the diagnosis, classification and biology of lymphomas. This review summarizes the basic concepts and cornerstones of the classification of aggressive B-cell lymphomas and details the major changes. Of importance, there is a new concept of High-grade B-cell lymphomas (HGBL), partly replacing the provisional entity of B-cell lymphoma, unclassifiable, with features intermediate between diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma, the so-called grey zone lymphomas. They either harbour MYC translocations together with a BCL2 and/or a BCL6 rearrangement (HGBL-Double Hit) or HGBL, not otherwise specified (NOS), lacking a double or triple hit constellation. In addition, the requirement for providing the cell-of-origin classification in the diagnostic work-up of DLBCLs, the role of MYC alterations in DLBCL subtypes, and newer findings in the specific variants/subtypes are highlighted. © 2017 John Wiley & Sons Ltd.

Pitfalls in soft tissue sarcoma imaging: chronic expanding hematomas.

PubMed

Jahed, Kiarash; Khazai, Behnaz; Umpierrez, Monica; Subhawong, Ty K; Singer, Adam D

2018-01-01

Solid or nodular enhancement is typical of soft tissue sarcomas although high grade soft tissue sarcomas and those with internal hemorrhage often appear heterogeneous with areas of nonenhancement and solid or nodular enhancement. These MRI findings often prompt an orthopedic oncology referral, a biopsy or surgery. However, not all masses with these imaging findings are malignant. We report the multimodality imaging findings of two surgically proven chronic expanding hematomas (CEH) with imaging features that mimicked sarcomas. A third case of nonenhancing CEH of the lower extremity is also presented as a comparison. It is important that in the correct clinical scenario with typical imaging findings, the differential diagnosis of a chronic expanding hematoma be included in the workup of these patients. An image-guided biopsy of nodular tissue within such masses that proves to be negative for malignancy should not necessarily be considered discordant. A correct diagnosis may prevent a morbid unnecessary surgery and may indicate the need for a conservative noninvasive follow-up with imaging.

Clinico-pathological features of kidney disease in diabetic cases.

PubMed

Furuichi, Kengo; Shimizu, Miho; Okada, Hirokazu; Narita, Ichiei; Wada, Takashi

2018-03-21

Diabetic kidney disease is the major cause of end-stage kidney disease in developed countries. However, the onset of kidney disorder and the progression pattern of kidney dysfunction and proteinuria greatly vary cases by cases. Therefore, risk classification with clinical data and pathological findings is important. Recent clinico-pathological study with kidney biopsy samples from diabetic patients revealed that pathological changes of diabetic nephropathy are characteristic and have special impacts on prognosis in each clinical stage. Moreover, comparison of the clinico-pathological findings of diabetic nephropathy with hypertensive nephrosclerosis revealed that there are few differences in their pathological findings in cases with low albuminuria and preserved estimated glomerular filtration rate (eGFR). Because it is so difficult to clearly distinguish pure kidney lesions caused by diabetes and kidney lesions due to effects other than diabetes, it is vital that these overlapped pathological findings be confirmed on kidney biopsy in cases of early stage diabetes. Further research is warranted regarding the pathogenesis of diabetic nephropathy and indication of kidney biopsy in diabetic cases.

Correlation between Clinical Features and Magnetic Resonance Imaging Findings in Lumbar Disc Prolapse.

PubMed

Thapa, S S; Lakhey, R B; Sharma, P; Pokhrel, R K

2016-05-01

Magnetic resonance imaging is routinely done for diagnosis of lumbar disc prolapse. Many abnormalities of disc are observed even in asymptomatic patient.This study was conducted tocorrelate these abnormalities observed on Magnetic resonance imaging and clinical features of lumbar disc prolapse. A This prospective analytical study includes 57 cases of lumbar disc prolapse presenting to Department of Orthopedics, Tribhuvan University Teaching Hospital from March 2011 to August 2012. All patientshad Magnetic resonance imaging of lumbar spine and the findings regarding type, level and position of lumbar disc prolapse, any neural canal or foraminal compromise was recorded. These imaging findings were then correlated with clinical signs and symptoms. Chi-square test was used to find out p-value for correlation between clinical features and Magnetic resonance imaging findings using SPSS 17.0. This study included 57 patients, with mean age 36.8 years. Of them 41(71.9%) patients had radicular leg pain along specific dermatome. Magnetic resonance imaging showed 104 lumbar disc prolapselevel. Disc prolapse at L4-L5 and L5-S1 level constituted 85.5%.Magnetic resonance imaging findings of neural foramina compromise and nerve root compression were fairly correlated withclinical findings of radicular pain and neurological deficit. Clinical features and Magnetic resonance imaging findings of lumbar discprolasehad faircorrelation, but all imaging abnormalities do not have a clinical significance.

Fluorescent Recovery after Photobleaching (FRAP) Analysis of Nuclear Export Rates Identifies Intrinsic Features of Nucleocytoplasmic Transport*

PubMed Central

Cardarelli, Francesco; Tosti, Luca; Serresi, Michela; Beltram, Fabio; Bizzarri, Ranieri

2012-01-01

A quantitative description of carrier-mediated nuclear export in live cells is presented. To this end, we fused a prototypical leucine-rich nuclear export signal (NES) to GFP as a cargo model and expressed the fluorescent chimera in live CHO-K1 cells. By modeling FRAP data, we calculate the NES affinity for the export machinery and the maximum rate of nuclear export achievable at saturation of endogenous carriers. The measured active-export time through the Nuclear Pore Complex (NPC) is 18 ms, remarkably similar to the previously determined active-import rate. Also, our results reveal that active export/import and active export/passive diffusion fluxes are uncoupled, thus complementing previous reports on active import/passive diffusion uncoupling. These findings suggest differential gating at the NPC level. PMID:22190681

Consulting communities on feedback of genetic findings in international health research: sharing sickle cell disease and carrier information in coastal Kenya

PubMed Central

2013-01-01

Background International health research in malaria-endemic settings may include screening for sickle cell disease, given the relationship between this important genetic condition and resistance to malaria, generating questions about whether and how findings should be disclosed. The literature on disclosing genetic findings in the context of research highlights the role of community consultation in understanding and balancing ethically important issues from participants’ perspectives, including social forms of benefit and harm, and the influence of access to care. To inform research practice locally, and contribute to policy more widely, this study aimed to explore the views of local residents in Kilifi County in coastal Kenya on how researchers should manage study-generated information on sickle cell disease and carrier status. Methods Between June 2010 and July 2011, we consulted 62 purposively selected Kilifi residents on how researchers should manage study-generated sickle cell disease findings. Methods drew on a series of deliberative informed small group discussions. Data were analysed thematically, using charts, to describe participants’ perceptions of the importance of disclosing findings, including reasoning, difference and underlying values. Themes were derived from the underlying research questions and from issues emerging from discussions. Data interpretation drew on relevant areas of social science and bioethics literature. Results Perceived health and social benefits generated strong support for disclosing findings on sickle cell disease, but the balance of social benefits and harms was less clear for sickle cell trait. Many forms of health and social benefits and harms of information-sharing were identified, with important underlying values related to family interests and the importance of openness. The influence of micro and macro level contextual features and prioritization of values led to marked diversity of opinion. Conclusions The approach demonstrates a high ethical importance in many malaria endemic low-to-middle income country settings of disclosing sickle cell disease findings generated during research, alongside provision of effective care and locally-informed counselling. Since these services are central to the benefits of disclosure, health researchers whose studies include screening for sickle cell disease should actively promote the development of health policy and services for this condition in situations of unmet need, including through the prior development of collaborative partnerships with government health managers and providers. Community consultation can importantly enrich ethical debate on research practice where in-depth exploration of informed views and the potential for difference are taken into account. PMID:24125465

Consulting communities on feedback of genetic findings in international health research: sharing sickle cell disease and carrier information in coastal Kenya.

PubMed

Marsh, Vicki; Kombe, Francis; Fitzpatrick, Raymond; Williams, Thomas N; Parker, Michael; Molyneux, Sassy

2013-10-14

International health research in malaria-endemic settings may include screening for sickle cell disease, given the relationship between this important genetic condition and resistance to malaria, generating questions about whether and how findings should be disclosed. The literature on disclosing genetic findings in the context of research highlights the role of community consultation in understanding and balancing ethically important issues from participants' perspectives, including social forms of benefit and harm, and the influence of access to care. To inform research practice locally, and contribute to policy more widely, this study aimed to explore the views of local residents in Kilifi County in coastal Kenya on how researchers should manage study-generated information on sickle cell disease and carrier status. Between June 2010 and July 2011, we consulted 62 purposively selected Kilifi residents on how researchers should manage study-generated sickle cell disease findings. Methods drew on a series of deliberative informed small group discussions. Data were analysed thematically, using charts, to describe participants' perceptions of the importance of disclosing findings, including reasoning, difference and underlying values. Themes were derived from the underlying research questions and from issues emerging from discussions. Data interpretation drew on relevant areas of social science and bioethics literature. Perceived health and social benefits generated strong support for disclosing findings on sickle cell disease, but the balance of social benefits and harms was less clear for sickle cell trait. Many forms of health and social benefits and harms of information-sharing were identified, with important underlying values related to family interests and the importance of openness. The influence of micro and macro level contextual features and prioritization of values led to marked diversity of opinion. The approach demonstrates a high ethical importance in many malaria endemic low-to-middle income country settings of disclosing sickle cell disease findings generated during research, alongside provision of effective care and locally-informed counselling. Since these services are central to the benefits of disclosure, health researchers whose studies include screening for sickle cell disease should actively promote the development of health policy and services for this condition in situations of unmet need, including through the prior development of collaborative partnerships with government health managers and providers. Community consultation can importantly enrich ethical debate on research practice where in-depth exploration of informed views and the potential for difference are taken into account.

Investigating the role of content knowledge, argumentation, and situational features to support genetics literacy

NASA Astrophysics Data System (ADS)

Shea, Nicole Anne

Science curriculum is often used as a means to train students as future scientists with less emphasis placed on preparing students to reason about issues they may encounter in their daily lives (Feinstein, Allen, & Jenkins, 2013; Roth & Barton, 2004). The general public is required to think scientifically to some degree throughout their life and often across a variety of issues. From an empirical standpoint, we do not have a robust understanding of what scientific knowledge the public finds useful for reasoning about socio-scientific issues in their everyday lives (Feinstein, 2011). We also know very little about how the situational features of an issue influences reasoning strategy (i.e., the use of knowledge to generate arguments). Rapid advances in science - particularly in genetics - increasingly challenge the public to reason about socio-scientific issues. This raises questions about the public's ability to participate knowledgeably in socio-scientific debates, and to provide informed consent for a variety of novel scientific procedures. This dissertation aims to answer the questions: How do individuals use their genetic content knowledge to reason about authentic issues they may encounter in their daily lives? Individuals' scientific knowledge is a critical aspect of scientific literacy, but what scientific literacy looks like in practice as individuals use their content knowledge to reason about issues comprised of different situational features is still unclear. The purpose of this dissertation is to explore what knowledge is actually used by individuals to generate and support arguments about a variety of socio-scientific issues, and how the features of those issues influences reasoning strategy. Three studies were conducted to answer questions reflecting this purpose. Findings from this dissertation provide important insights into what scientific literacy looks like in practice.

The effectiveness of celebrities in conservation marketing.

PubMed

Duthie, Elizabeth; Veríssimo, Diogo; Keane, Aidan; Knight, Andrew T

2017-01-01

Celebrities are frequently used in conservation marketing as a tool to raise awareness, generate funding and effect behaviour change. The importance of evaluating effectiveness is widely recognised in both marketing and conservation but, to date, little research into the effectiveness of celebrity endorsement as a tool for conservation marketing has been published. Using a combination of interviews and an online choice survey instrument, we investigated the extent to which a sample of UK-based conservation organisations, and other charities, evaluate their own usage of celebrity endorsement, and then carried out an experimental evaluation of a hypothetical marketing campaign. This experiment compared participants' willingness-to-engage (WTE) with, and recall of, a conservation message presented in versions of an advert featuring one of three prominent UK celebrities (David Beckham, Chris Packham or HRH Prince William) or a non-celebrity control treatment (featuring Crawford Allan, a director of TRAFFIC USA). We find that the organisations we interviewed did not routinely evaluate their marketing campaigns featuring celebrities. Furthermore, our experiment provides evidence that celebrity endorsement can produce both positive and negative effects. Participants were more willing to engage when presented with an advert featuring one of the three celebrities than the non-celebrity control, and WTE varied according to the characteristics of the celebrity and the respondent. However, celebrities were less effective at generating campaign message recall than non-celebrities. These findings suggest that celebrity endorsement should be used carefully. Further work is required to fully understand the role celebrity endorsers can play in conservation but, drawing on best practice from the field of marketing, this study introduces an approach to evaluation which could be applied more widely to improve the effectiveness of conservation marketing.

The effectiveness of celebrities in conservation marketing

PubMed Central

Veríssimo, Diogo; Keane, Aidan; Knight, Andrew T.

2017-01-01

Celebrities are frequently used in conservation marketing as a tool to raise awareness, generate funding and effect behaviour change. The importance of evaluating effectiveness is widely recognised in both marketing and conservation but, to date, little research into the effectiveness of celebrity endorsement as a tool for conservation marketing has been published. Using a combination of interviews and an online choice survey instrument, we investigated the extent to which a sample of UK-based conservation organisations, and other charities, evaluate their own usage of celebrity endorsement, and then carried out an experimental evaluation of a hypothetical marketing campaign. This experiment compared participants' willingness-to-engage (WTE) with, and recall of, a conservation message presented in versions of an advert featuring one of three prominent UK celebrities (David Beckham, Chris Packham or HRH Prince William) or a non-celebrity control treatment (featuring Crawford Allan, a director of TRAFFIC USA). We find that the organisations we interviewed did not routinely evaluate their marketing campaigns featuring celebrities. Furthermore, our experiment provides evidence that celebrity endorsement can produce both positive and negative effects. Participants were more willing to engage when presented with an advert featuring one of the three celebrities than the non-celebrity control, and WTE varied according to the characteristics of the celebrity and the respondent. However, celebrities were less effective at generating campaign message recall than non-celebrities. These findings suggest that celebrity endorsement should be used carefully. Further work is required to fully understand the role celebrity endorsers can play in conservation but, drawing on best practice from the field of marketing, this study introduces an approach to evaluation which could be applied more widely to improve the effectiveness of conservation marketing. PMID:28686595

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

Kuo, J; Su, K; Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio

Purpose: Accurate and robust photon attenuation derived from MR is essential for PET/MR and MR-based radiation treatment planning applications. Although the fuzzy C-means (FCM) algorithm has been applied for pseudo-CT generation, the input feature combination and the number of clusters have not been optimized. This study aims to optimize both for clinically practical pseudo-CT generation. Methods: Nine volunteers were recruited. A 190-second, single-acquisition UTE-mDixon with 25% (angular) sampling and 3D radial readout was performed to acquire three primitive MR features at TEs of 0.1, 1.5, and 2.8 ms: the free-induction-decay (FID), the first and the second echo images. Three derivedmore » images, Dixon-fat and Dixon-water generated by two-point Dixon water/fat separation, and R2* (1/T2*) map, were also created. To identify informative inputs for generating a pseudo-CT image volume, all 63 combinations, choosing one to six of the feature images, were used as inputs to FCM for pseudo-CT generation. Further, the number of clusters was varied from four to seven to find the optimal approach. Mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R) of different combinations were compared for feature selection. Results: Among the 63 feature combinations, the four that resulted in the best MAPD and R were further compared along with the set containing all six features. The results suggested that R2* and Dixon-water are the most informative features. Further, including FID also improved the performance of pseudo-CT generation. Consequently, the set containing FID, Dixon-water, and R2* resulted in the most accurate, robust pseudo-CT when the number of cluster equals to five (5C). The clusters were interpreted as air, fat, bone, brain, and fluid. The six-cluster Result additionally included bone marrow. Conclusion: The results suggested that FID, Dixon-water, R2* are the most important features. The findings can be used to facilitate pseudo-CT generation for unsupervised clustering. Please note that the project was completed with partial funding from the Ohio Department of Development grant TECH 11-063 and a sponsored research agreement with Philips Healthcare that is managed by Case Western Reserve University. As noted in the affiliations, some of the authors are Philips employees.« less

Histopathology of Incidental Findings in Cynomolgus Monkeys (Macaca Fascicularis) Used in Toxicity Studies

PubMed Central

Sato, Junko; Doi, Takuya; Kanno, Takeshi; Wako, Yumi; Tsuchitani, Minoru; Narama, Isao

2012-01-01

The purpose of our publication is to widely communicate pictures of spontaneous findings occurring in cynomolgus monkeys. Focal lymphoplasmacytic infiltration is commonly seen in the general organs. The frequency and severity of these lesions may be influenced by the administration of drugs with an effect on the immune system. Lymphoplasmacytic infiltration in the lamina propria of the stomach is also frequently seen in cynomolgus monkeys, and it is caused mainly by a Helicobacter pylori infection. Various degrees of brown pigments are observed in various organs, and it is possible to distinguish the material of the pigments by its morphological features and site. A focal/segmental glomerular lesion is occasionally seen in a section of the kidney, and the minimal lesion has no influence on the urinalysis. We showed the common glomerular lesions in HE-stained sections, as well as in PAM- or PAS-stained sections, for understanding the details. Young and pubertal monkeys are usually used in toxicity studies; therefore, understanding various maturation stages of the genital system is important. In particular, the female genital system needs to be understood in the morphology, because their cyclic changes are different from other laboratory animals. Thus, we present the normal features of the cyclic changes of the female genital organs. Furthermore, we provide more information on spontaneous findings in cynomolgus monkeys for exact diagnoses in toxicity studies. PMID:22481861

Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

PubMed Central

Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

2013-01-01

Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions. PMID:23422585

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties.

PubMed

Jacobs, Richard H A H; Haak, Koen V; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed-and presumably for this reason-the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities-including the aesthetic appreciation-are sufficiently universal to be predicted-with reasonable accuracy-based on the computed feature content of the textures.

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties

PubMed Central

Jacobs, Richard H. A. H.; Haak, Koen V.; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W.

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed—and presumably for this reason—the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities—including the aesthetic appreciation—are sufficiently universal to be predicted—with reasonable accuracy—based on the computed feature content of the textures. PMID:27493628

Interpreting Quasi-Thermal Effects in Ultrafast Spectroscopy of Hydrogen-Bonded Systems.

PubMed

Stingel, Ashley M; Petersen, Poul B

2018-03-15

Vibrational excitation of molecules in the condensed phase relaxes through vibrational modes of decreasing energy to ultimately generate an equilibrium state in which the energy is distributed among low-frequency modes. In ultrafast vibrational spectroscopy, changes in the vibrational features of hydrogen-bonded NH and OH stretch modes are typically observed to persist long after these high-frequency vibrations have relaxed. Due to the resemblance to the spectral changes caused by heating the sample, these features are typically described as arising from a hot ground state. However, these spectral features appear on ultrafast time scales that are much too fast to result from a true thermal state, and significant differences between the thermal difference spectrum and the induced quasi-thermal changes in ultrafast spectroscopy are often observed. Here, we examine and directly compare the thermal and quasi-thermal responses of the hydrogen-bonded homodimer of 7-azaindole with temperature-dependent FTIR spectroscopy and ultrafast mid-IR continuum spectroscopy. We find that the thermal difference spectra contain contributions from both dissociation of the hydrogen bonds and from frequency shifts due to changes in the thermal population of low-frequency modes. The transient spectra in ultrafast vibrational spectroscopy are also found to contain two contributions: initial frequency shifts over 2.3 ± 0.11 ps associated with equilibration of the initial excitation, and frequency shifts associated with the excitation of several fingerprint modes, which decay over 21.8 ± 0.11 ps, giving rise to a quasi-thermal response caused by a distribution of fingerprint modes being excited within the sample ensemble. This resembles the thermal frequency shifts due to population changes of low-frequency modes, but not the overall thermal spectrum, which is dominated by features caused by dimer dissociation. These findings provide insight into the changes in the vibrational spectrum from different origins and are important for assigning, analyzing, and comparing features in thermal and ultrafast vibrational spectroscopy of hydrogen-bonded complexes.

Differential binding of colors to objects in memory: red and yellow stick better than blue and green

PubMed Central

Kuhbandner, Christof; Spitzer, Bernhard; Lichtenfeld, Stephanie; Pekrun, Reinhard

2015-01-01

Both evolutionary considerations and recent research suggest that the color red serves as a signal indicating an object’s importance. However, until now, there is no evidence that this signaling function of red is also reflected in human memory. To examine the effect of red on memory, we conducted four experiments in which we presented objects colored in four different colors (red, green, blue, and yellow) and measured later memory for the presence of an object and for the color of an object. Across experiments, we varied the type of objects (words vs. pictures), task complexity (single objects vs. multiple objects in visual scenes), and intentionality of encoding (intentional vs. incidental learning). Memory for the presence of an object was not influenced by color. However, in all four experiments, memory for the color of an object depended on color type and was particularly high for red and yellow-colored objects and particularly low for green-colored objects, indicating that the binding of colors into object memory representations varies as a function of color type. Analyzing the observers’ confidence in their color memories revealed that color not only influenced objective memory performance but also subjective confidence. Subjective confidence judgments differentiated well between correct and incorrect color memories for red-colored objects, but poorly for green-colored objects. Our findings reveal a previously unknown color effect which may be of considerable interest for both basic color research and applied settings like eyewitness testimony in which memory for color features is relevant. Furthermore, our results indicate that feature binding in memory is not a uniform process by which any attended feature is automatically bound into unitary memory representations. Rather, memory binding seems to vary across different subtypes of features, a finding that supports recent research showing that object features are stored in memory rather independently from each other. PMID:25784892

Differential binding of colors to objects in memory: red and yellow stick better than blue and green.

PubMed

Kuhbandner, Christof; Spitzer, Bernhard; Lichtenfeld, Stephanie; Pekrun, Reinhard

2015-01-01

Both evolutionary considerations and recent research suggest that the color red serves as a signal indicating an object's importance. However, until now, there is no evidence that this signaling function of red is also reflected in human memory. To examine the effect of red on memory, we conducted four experiments in which we presented objects colored in four different colors (red, green, blue, and yellow) and measured later memory for the presence of an object and for the color of an object. Across experiments, we varied the type of objects (words vs. pictures), task complexity (single objects vs. multiple objects in visual scenes), and intentionality of encoding (intentional vs. incidental learning). Memory for the presence of an object was not influenced by color. However, in all four experiments, memory for the color of an object depended on color type and was particularly high for red and yellow-colored objects and particularly low for green-colored objects, indicating that the binding of colors into object memory representations varies as a function of color type. Analyzing the observers' confidence in their color memories revealed that color not only influenced objective memory performance but also subjective confidence. Subjective confidence judgments differentiated well between correct and incorrect color memories for red-colored objects, but poorly for green-colored objects. Our findings reveal a previously unknown color effect which may be of considerable interest for both basic color research and applied settings like eyewitness testimony in which memory for color features is relevant. Furthermore, our results indicate that feature binding in memory is not a uniform process by which any attended feature is automatically bound into unitary memory representations. Rather, memory binding seems to vary across different subtypes of features, a finding that supports recent research showing that object features are stored in memory rather independently from each other.

Dogs and intestinal parasites: a public health problem.

PubMed

Seah, S K; Hucal, G; Law, C

1975-05-17

The stools of 239 stray dogs were examined for intestinal parasites. Of the helminths found, Toxocara canis (43.5%), tapeworms (25.5%), Ascaris species (21.3%) and hookworms (12.5%) were the commonest. Of the protozoans found, Isospora species and Entamoeba coli were the most prevalent. An unusual feature of the present study was the finding of Ascaris species. The importance of the high prevalence of intestinal parasites in dogs, the close contact of humans with dogs' excreta and the possible role of this environmental pollution in the spread of human disease are discussed.

Brain and bone abnormalities of thanatophoric dwarfism.

PubMed

Miller, Elka; Blaser, Susan; Shannon, Patrick; Widjaja, Elysa

2009-01-01

The purpose of this article is to present the imaging findings of skeletal and brain abnormalities in thanatophoric dwarfism, a lethal form of dysplastic dwarfism. The bony abnormalities associated with thanatophoric dwarfism include marked shortening of the tubular bones and ribs. Abnormal temporal lobe development is a common associated feature and can be visualized as early as the second trimester. It is important to assess the brains of fetuses with suspected thanatophoric dwarfism because the presence of associated brain malformations can assist in the antenatal diagnosis of thanatophoric dwarfism.

The serial process in visual search.

PubMed

Gilden, David L; Thornton, Thomas L; Marusich, Laura R

2010-06-01

The conditions for serial search are described. A multiple target search methodology (Thornton & Gilden, 2007) is used to home in on the simplest target/distractor contrast that effectively mandates a serial scheduling of attentional resources. It is found that serial search is required when (a) targets and distractors are mirror twins, and (b) when the search elements lack the Gestalt property of intrinsic orientation. The finding is put into the context of Feature Integration Theory (Treisman & Gelade, 1980) that first identified the occasions of serial search to be important to object perception and understanding.

Reflectance confocal microscopy of cutaneous melanoma. Correlation with dermoscopy and histopathology*

PubMed Central

Rstom, Silvia Arroyo; Libório, Lorena Silva; Paschoal, Francisco Macedo

2015-01-01

In vivo Confocal Microscopy is a method for non-invasive, real-time visualization of microscopic structures and cellular details of the epidermis and dermis, which has a degree of resolution similar to that obtained with histology. We present a case of cutaneous melanoma in which diagnosis was aided by confocal microscopy examination. We also correlate the observed features with the dermoscopic and histopathological findings. Confocal microscopy proved to be an useful adjunct to dermoscopy, playing an important role as a method 'between clinical evaluation and histopathology'. PMID:26131877

Oral Manifestations and Molecular Basis of Oral Genodermatoses: A Review

PubMed Central

Shilpasree, A.S.; Chaudhary, Meenakshi

2016-01-01

Genodermatoses refers to group of inherited monogenic disorders with skin manifestations. Many of these disorders are rare and also have oral manifestations, called oral genodermatoses. This article provides a focused review of molecular basis of important genodermatoses that affects the oral cavity and also have prominent associated dermatologic features. In several conditions discussed here, the oral findings are distinct and may provide the first clue of an underlying genetic diagnosis. The article also emphasises on the prenatal diagnosis, genetic counselling and the treatment oral genodermatoses. PMID:27437377

Virally associated arthritis 2008: clinical, epidemiologic, and pathophysiologic considerations

PubMed Central

Vassilopoulos, Dimitrios; Calabrese, Leonard H

2008-01-01

Several viruses have been associated with the development of inflammatory arthritis, including the hepatitis viruses (hepatitis B virus and hepatitis C virus), HIV, the parvovirus B19, the human T-cell lymphotropic virus-I, and the alphaviruses. Here, we review the epidemiology, the pathophysiological mechanisms, the pertinent clinical and laboratory findings as well as the principles of therapy of the most common virus-associated arthritides. We believe that the knowledge of these key diagnostic and therapeutic features of virus-associated arthritides is important for the rheumatologist of the 21st century. PMID:18828883

Septin Organization and Functions in Budding Yeast

PubMed Central

Glomb, Oliver; Gronemeyer, Thomas

2016-01-01

The septins are a conserved family of GTP-binding proteins present in all eukaryotic cells except plants. They were originally discovered in the baker's yeast Saccharomyces cerevisiae that serves until today as an important model organism for septin research. In yeast, the septins assemble into a highly ordered array of filaments at the mother bud neck. The septins are regulators of spatial compartmentalization in yeast and act as key players in cytokinesis. This minireview summarizes the recent findings about structural features and cell biology of the yeast septins. PMID:27857941

[Calcifying tendinitis of the rotator cuff with focal umeral osteolysis. Imaging features].

PubMed

Mascarenhas, V V; Morais, F; Marques, H; Guerra, A; Carpinteiro, E; Gaspar, A

2015-01-01

Calcifying tendinitis occurs most commonly in the rotator cuff tendons, particularly involving the supraspinatus tendon insertion, and is often asymptomatic. Cortical erosion secondary to calcifying tendinitis has been reported in multiple locations, including in the rotator cuff tendons. The authors report two cases of symptomatic calcifying tendinitis involving the infraspinatus tendon with cortical erosion with correlative radiographic, and MR findings. The importance of considering this diagnosis when evaluating lytic lesions of the humerus and the imaging differential diagnosis of calcifying tendinitis and cortical erosion are discussed.

The Effects of Goal Relevance and Perceptual Features on Emotional Items and Associative Memory

PubMed Central

Mao, Wei B.; An, Shu; Yang, Xiao F.

2017-01-01

Showing an emotional item in a neutral background scene often leads to enhanced memory for the emotional item and impaired associative memory for background details. Meanwhile, both top–down goal relevance and bottom–up perceptual features played important roles in memory binding. We conducted two experiments and aimed to further examine the effects of goal relevance and perceptual features on emotional items and associative memory. By manipulating goal relevance (asking participants to categorize only each item image as living or non-living or to categorize each whole composite picture consisted of item image and background scene as natural scene or manufactured scene) and perceptual features (controlling visual contrast and visual familiarity) in two experiments, we found that both high goal relevance and salient perceptual features (high salience of items vs. high familiarity of items) could promote emotional item memory, but they had different effects on associative memory for emotional items and neutral backgrounds. Specifically, high goal relevance and high perceptual-salience of items could jointly impair the associative memory for emotional items and neutral backgrounds, while the effect of item familiarity on associative memory for emotional items would be modulated by goal relevance. High familiarity of items could increase associative memory for negative items and neutral backgrounds only in the low goal relevance condition. These findings suggest the effect of emotion on associative memory is not only related to attentional capture elicited by emotion, but also can be affected by goal relevance and perceptual features of stimulus. PMID:28790943

The Effects of Goal Relevance and Perceptual Features on Emotional Items and Associative Memory.

PubMed

Mao, Wei B; An, Shu; Yang, Xiao F

2017-01-01

Showing an emotional item in a neutral background scene often leads to enhanced memory for the emotional item and impaired associative memory for background details. Meanwhile, both top-down goal relevance and bottom-up perceptual features played important roles in memory binding. We conducted two experiments and aimed to further examine the effects of goal relevance and perceptual features on emotional items and associative memory. By manipulating goal relevance (asking participants to categorize only each item image as living or non-living or to categorize each whole composite picture consisted of item image and background scene as natural scene or manufactured scene) and perceptual features (controlling visual contrast and visual familiarity) in two experiments, we found that both high goal relevance and salient perceptual features (high salience of items vs. high familiarity of items) could promote emotional item memory, but they had different effects on associative memory for emotional items and neutral backgrounds. Specifically, high goal relevance and high perceptual-salience of items could jointly impair the associative memory for emotional items and neutral backgrounds, while the effect of item familiarity on associative memory for emotional items would be modulated by goal relevance. High familiarity of items could increase associative memory for negative items and neutral backgrounds only in the low goal relevance condition. These findings suggest the effect of emotion on associative memory is not only related to attentional capture elicited by emotion, but also can be affected by goal relevance and perceptual features of stimulus.

The sonographic features of malignant mediastinal lymph nodes and a proposal for an algorithmic approach for sampling during endobronchial ultrasound.

PubMed

Alici, Ibrahim Onur; Yılmaz Demirci, Nilgün; Yılmaz, Aydın; Karakaya, Jale; Özaydın, Esra

2016-09-01

There are several papers on the sonographic features of mediastinal lymph nodes affected by several diseases, but none gives the importance and clinical utility of the features. In order to find out which lymph node should be sampled in a particular nodal station during endobronchial ultrasound, we investigated the diagnostic performances of certain sonographic features and proposed an algorithmic approach. We retrospectively analyzed 1051 lymph nodes and randomly assigned them into a preliminary experimental and a secondary study group. The diagnostic performances of the sonographic features (gray scale, echogeneity, shape, size, margin, presence of necrosis, presence of calcification and absence of central hilar structure) were calculated, and an algorithm for lymph node sampling was obtained with decision tree analysis in the experimental group. Later, a modified algorithm was applied to the patients in the study group to give the accuracy. The demographic characteristics of the patients were not statistically significant between the primary and the secondary groups. All of the features were discriminative between malignant and benign diseases. The modified algorithm sensitivity, specificity, and positive and negative predictive values and diagnostic accuracy for detecting metastatic lymph nodes were 100%, 51.2%, 50.6%, 100% and 67.5%, respectively. In this retrospective analysis, the standardized sonographic classification system and the proposed algorithm performed well in choosing the node that should be sampled in a particular station during endobronchial ultrasound. © 2015 John Wiley & Sons Ltd.

Changing facial phenotype in Cohen syndrome: towards clues for an earlier diagnosis.

PubMed

El Chehadeh-Djebbar, Salima; Blair, Edward; Holder-Espinasse, Muriel; Moncla, Anne; Frances, Anne-Marie; Rio, Marlène; Debray, François-Guillaume; Rump, Patrick; Masurel-Paulet, Alice; Gigot, Nadège; Callier, Patrick; Duplomb, Laurence; Aral, Bernard; Huet, Frédéric; Thauvin-Robinet, Christel; Faivre, Laurence

2013-07-01

Cohen syndrome (CS) is a rare autosomal recessive condition caused by mutations and/or large rearrangements in the VPS13B gene. CS clinical features, including developmental delay, the typical facial gestalt, chorioretinal dystrophy (CRD) and neutropenia, are well described. CS diagnosis is generally raised after school age, when visual disturbances lead to CRD diagnosis and to VPS13B gene testing. This relatively late diagnosis precludes accurate genetic counselling. The aim of this study was to analyse the evolution of CS facial features in the early period of life, particularly before school age (6 years), to find clues for an earlier diagnosis. Photographs of 17 patients with molecularly confirmed CS were analysed, from birth to preschool age. By comparing their facial phenotype when growing, we show that there are no special facial characteristics before 1 year. However, between 2 and 6 years, CS children already share common facial features such as a short neck, a square face with micrognathia and full cheeks, a hypotonic facial appearance, epicanthic folds, long ears with an everted upper part of the auricle and/or a prominent lobe, a relatively short philtrum, a small and open mouth with downturned corners, a thick lower lip and abnormal eye shapes. These early transient facial features evolve to typical CS facial features with aging. These observations emphasize the importance of ophthalmological tests and neutrophil count in children in preschool age presenting with developmental delay, hypotonia and the facial features we described here, for an earlier CS diagnosis.

Reduced-Reference Quality Assessment Based on the Entropy of DWT Coefficients of Locally Weighted Gradient Magnitudes.

PubMed

Golestaneh, S Alireza; Karam, Lina

2016-08-24

Perceptual image quality assessment (IQA) attempts to use computational models to estimate the image quality in accordance with subjective evaluations. Reduced-reference (RR) image quality assessment (IQA) methods make use of partial information or features extracted from the reference image for estimating the quality of distorted images. Finding a balance between the number of RR features and accuracy of the estimated image quality is essential and important in IQA. In this paper we propose a training-free low-cost RRIQA method that requires a very small number of RR features (6 RR features). The proposed RRIQA algorithm is based on the discrete wavelet transform (DWT) of locally weighted gradient magnitudes.We apply human visual system's contrast sensitivity and neighborhood gradient information to weight the gradient magnitudes in a locally adaptive manner. The RR features are computed by measuring the entropy of each DWT subband, for each scale, and pooling the subband entropies along all orientations, resulting in L RR features (one average entropy per scale) for an L-level DWT. Extensive experiments performed on seven large-scale benchmark databases demonstrate that the proposed RRIQA method delivers highly competitive performance as compared to the state-of-the-art RRIQA models as well as full reference ones for both natural and texture images. The MATLAB source code of REDLOG and the evaluation results are publicly available online at https://http://lab.engineering.asu.edu/ivulab/software/redlog/.

Short-term and long-term attentional biases to frequently encountered target features.

PubMed

Sha, Li Z; Remington, Roger W; Jiang, Yuhong V

2017-07-01

It has long been known that frequently occurring targets are attended better than infrequent ones in visual search. But does this frequency-based attentional prioritization reflect momentary or durable changes in attention? Here we observed both short-term and long-term attentional biases for visual features as a function of different types of statistical associations between the targets, distractors, and features. Participants searched for a target, a line oriented horizontally or vertically among diagonal distractors, and reported its length. In one set of experiments we manipulated the target's color probability: Targets were more often in Color 1 than in Color 2. The distractors were in other colors. Participants found Color 1 targets more quickly than Color 2 targets, but this preference disappeared immediately when the target's color became random in the subsequent testing phase. In the other set of experiments, we manipulated the diagnostic values of the two colors: Color 1 was more often a target than a distractor; Color 2 was more often a distractor than a target. Participants found Color 1 targets more quickly than Color 2 targets. Importantly, and in contrast to the first set of experiments, the featural preference was sustained in the testing phase. These results suggest that short-term and long-term attentional biases are products of different statistical information. Finding a target momentarily activates its features, inducing short-term repetition priming. Long-term changes in attention, on the other hand, may rely on learning diagnostic features of the targets.

Conserved and Divergent Molecular and Anatomic Features of Human and Mouse Nephron Patterning.

PubMed

Lindström, Nils O; Tran, Tracy; Guo, Jinjin; Rutledge, Elisabeth; Parvez, Riana K; Thornton, Matthew E; Grubbs, Brendan; McMahon, Jill A; McMahon, Andrew P

2018-03-01

The nephron is the functional unit of the kidney, but the mechanism of nephron formation during human development is unclear. We conducted a detailed analysis of nephron development in humans and mice by immunolabeling, and we compared human and mouse nephron patterning to describe conserved and divergent features. We created protein localization maps that highlight the emerging patterns along the proximal-distal axis of the developing nephron and benchmark expectations for localization of functionally important transcription factors, which revealed unanticipated cellular diversity. Moreover, we identified a novel nephron subdomain marked by Wnt4 expression that we fate-mapped to the proximal mature nephron. Significant conservation was observed between human and mouse patterning. We also determined the time at which markers for mature nephron cell types first emerge-critical data for the renal organoid field. These findings have conceptual implications for the evolutionary processes driving the diversity of mammalian organ systems. Furthermore, these findings provide practical insights beyond those gained with mouse and rat models that will guide in vitro efforts to harness the developmental programs necessary to build human kidney structures. Copyright © 2018 by the American Society of Nephrology.

Familial paroxysmal nonkinesigenic dyskinesia: clinical and genetic analysis of a Taiwanese family.

PubMed

Yeh, Tu-Hsueh; Lin, Juei-Jueng; Lai, Szu-Chia; Wu-Chou, Yah-Huei; Chen, An-Chih; Yueh, Kuo-Chu; Chen, Rou-Shayn; Lu, Chin-Song

2012-12-15

Paroxysmal nonkinesigenic dyskinesia (PNKD) is a rare disorder in autosomal dominant inheritance. The clinical features and genetic findings of PNKD, rarely described in the Asians, were mostly delineated from European families. The present study characterized the clinical and genetic findings of a Taiwanese PNKD family. The clinical features of our five patients in successive three generations included onset age less than 10 years, attack duration between 3 min and 4h, and a variety of aura symptoms. The attacks were provoked not by sudden action but by emotional stress, caffeine, fatigue, heavy exercise and sleep deprivation. Sleep could abolish or diminish the attack and the attacks responded well to clonazepam. Sequencing the whole coding region of PNKD/MR-1 gene identified a heterozygous c.20 C>T (p.Ala7Val) mutation which was clearly segregated in the five affected patients. Comparing our patients with previously reported 18 families with PNKD/MR-1 mutations, the majority of the patients exhibited quite similar manifestations in attack patterns and precipitating factors. The recurrent conservative mutations in different ethnicities indicate importance in the pathogenesis of PNKD. Copyright © 2012 Elsevier B.V. All rights reserved.

Least-Squares Support Vector Machine Approach to Viral Replication Origin Prediction

PubMed Central

Cruz-Cano, Raul; Chew, David S.H.; Kwok-Pui, Choi; Ming-Ying, Leung

2010-01-01

Replication of their DNA genomes is a central step in the reproduction of many viruses. Procedures to find replication origins, which are initiation sites of the DNA replication process, are therefore of great importance for controlling the growth and spread of such viruses. Existing computational methods for viral replication origin prediction have mostly been tested within the family of herpesviruses. This paper proposes a new approach by least-squares support vector machines (LS-SVMs) and tests its performance not only on the herpes family but also on a collection of caudoviruses coming from three viral families under the order of caudovirales. The LS-SVM approach provides sensitivities and positive predictive values superior or comparable to those given by the previous methods. When suitably combined with previous methods, the LS-SVM approach further improves the prediction accuracy for the herpesvirus replication origins. Furthermore, by recursive feature elimination, the LS-SVM has also helped find the most significant features of the data sets. The results suggest that the LS-SVMs will be a highly useful addition to the set of computational tools for viral replication origin prediction and illustrate the value of optimization-based computing techniques in biomedical applications. PMID:20729987

Least-Squares Support Vector Machine Approach to Viral Replication Origin Prediction.

PubMed

Cruz-Cano, Raul; Chew, David S H; Kwok-Pui, Choi; Ming-Ying, Leung

2010-06-01

Replication of their DNA genomes is a central step in the reproduction of many viruses. Procedures to find replication origins, which are initiation sites of the DNA replication process, are therefore of great importance for controlling the growth and spread of such viruses. Existing computational methods for viral replication origin prediction have mostly been tested within the family of herpesviruses. This paper proposes a new approach by least-squares support vector machines (LS-SVMs) and tests its performance not only on the herpes family but also on a collection of caudoviruses coming from three viral families under the order of caudovirales. The LS-SVM approach provides sensitivities and positive predictive values superior or comparable to those given by the previous methods. When suitably combined with previous methods, the LS-SVM approach further improves the prediction accuracy for the herpesvirus replication origins. Furthermore, by recursive feature elimination, the LS-SVM has also helped find the most significant features of the data sets. The results suggest that the LS-SVMs will be a highly useful addition to the set of computational tools for viral replication origin prediction and illustrate the value of optimization-based computing techniques in biomedical applications.

Focal hepatic fatty infiltration in the posterior edge of the medial segment associated with aberrant gastric venous drainage: CT, US, and MR findings

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

Kawamori, Yashuiro; Matsui, Osamu; Takahashi, S.

1996-05-01

The purpose of this study is to demonstrate the relation between focal hepatic fatty infiltration and aberrant gastric venous drainage (AGVD) in the posterior edge of the medial segment (PEMS) of the liver and we present two cases of focal hepatic fatty infiltration with AGVD in the PEMS and discuss their imaging features. In both cases the focal fatty infiltration areas were hyperechoic on sonography, hypodense on CT, and hyperintense on T1-weighted MRI. Computed tomography during arterial portography (CTAP) showed nodular perfusion defects corresponding to the areas in both cases, and early enhancement of the area was observed with dynamicmore » MRI in one case. Although the findings on CTAP and dynamic MRI suggested a neoplastic nature for the lesions, focal fatty infiltration was confirmed with surgical resection in one case and with imaging follow-up in the other. Aberrant gastric venous drainage into the area was demonstrated on arteriography in both cases. The variation in blood supply caused by AGVD may play an important role in fatty metabolism in the PENIS of the liver and may influence imaging features. 9 refs., 2 figs.« less

Primary Teachers' beliefs about Scientific Creativity in the Classroom Context

NASA Astrophysics Data System (ADS)

Liu, Shu-Chiu; Lin, Huann-shyang

2014-07-01

While a number of studies have investigated people's perceptions or conceptions of creativity, there is a lack of studies looking into science teachers' views. The study aimed to explore the meanings of scientific creativity in the classroom context as perceived by a selective group of upper primary (Grades 3-6; student ages 8-12) science teachers (n = 16) in Taiwan. Using a self-report, open-ended questionnaire and follow-up interviews, the participants responded to questions as to (1) what quality, behaviours and abilities characterise a creative learner in their science classrooms, (2) what a science classroom should be like if it is to facilitate scientific creativity, and (3) whether and what particular elements of the inquiry approach are incorporated in such a classroom. The analyses revealed that the teachers captured the central features of creativity and proposed diverse ideas about how to foster creativity in school science, but seemed to overlook some aspects, such as convergent thinking, problem-finding, and linking the arts and science. These missing features are regarded as important for scientific creativity in contemporary research. The findings were discussed along with their implications for teacher education and future research.

probeBase—an online resource for rRNA-targeted oligonucleotide probes and primers: new features 2016

PubMed Central

Greuter, Daniel; Loy, Alexander; Horn, Matthias; Rattei, Thomas

2016-01-01

probeBase http://www.probebase.net is a manually maintained and curated database of rRNA-targeted oligonucleotide probes and primers. Contextual information and multiple options for evaluating in silico hybridization performance against the most recent rRNA sequence databases are provided for each oligonucleotide entry, which makes probeBase an important and frequently used resource for microbiology research and diagnostics. Here we present a major update of probeBase, which was last featured in the NAR Database Issue 2007. This update describes a complete remodeling of the database architecture and environment to accommodate computationally efficient access. Improved search functions, sequence match tools and data output now extend the opportunities for finding suitable hierarchical probe sets that target an organism or taxon at different taxonomic levels. To facilitate the identification of complementary probe sets for organisms represented by short rRNA sequence reads generated by amplicon sequencing or metagenomic analysis with next generation sequencing technologies such as Illumina and IonTorrent, we introduce a novel tool that recovers surrogate near full-length rRNA sequences for short query sequences and finds matching oligonucleotides in probeBase. PMID:26586809

A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

PubMed Central

Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953

A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.

PubMed

Sweeney, Elizabeth M; Vogelstein, Joshua T; Cuzzocreo, Jennifer L; Calabresi, Peter A; Reich, Daniel S; Crainiceanu, Ciprian M; Shinohara, Russell T

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.

Removing Shape-Preserving Transformations in Square-Root Elastic (SRE) Framework for Shape Analysis of Curves

PubMed Central

Joshi, Shantanu H.; Klassen, Eric; Srivastava, Anuj; Jermyn, Ian

2011-01-01

This paper illustrates and extends an efficient framework, called the square-root-elastic (SRE) framework, for studying shapes of closed curves, that was first introduced in [2]. This framework combines the strengths of two important ideas - elastic shape metric and path-straightening methods - for finding geodesics in shape spaces of curves. The elastic metric allows for optimal matching of features between curves while path-straightening ensures that the algorithm results in geodesic paths. This paper extends this framework by removing two important shape preserving transformations: rotations and re-parameterizations, by forming quotient spaces and constructing geodesics on these quotient spaces. These ideas are demonstrated using experiments involving 2D and 3D curves. PMID:21738385

Sudden Unexpected Death in Epilepsy: A Retrospective Autopsy Study of 112 Epileptic Patients.

PubMed

Esen Melez, İpek; Arslan, Murat Nihat; Melez, Deniz Oğuzhan; Şanli, Ahmet Necati; Koç, Sermet

2017-09-01

Sudden unexpected deaths comprise the most important and worthy investigation case profiles in both neurology and forensic medicine. Epilepsy, which is one of the neuropathological causes of sudden unexpected deaths, is an important disorder having mysterious aspects. The aim of this study is to make common the points of view between neurology and forensic medicine experts and to discuss the features of the findings together with the related clinical hypotheses, leading to the differential diagnosis of sudden unexpected death in epilepsy (SUDEP) by presenting autopsy findings and available medical data of patients who had a prior diagnosis of epilepsy. In Istanbul, the cases of 20334 autopsied patients who were referred to The Ministry of Justice Council of Forensic Medicine between 2007 and 2011 were identified from the complete forensic autopsy data of the city and were retrospectively reviewed. Patients who had a prior diagnosis of epilepsy were included. Both descriptive and inferential statistical analyses were performed through the parameters of demographical data, physical properties, incident features, macroscopic-microscopic autopsy findings, and cause of death initially for all cases and then separately for SUDEP cases. Among the 20334 patients, 112 were determined to have a prior diagnosis of epilepsy. A possible macroscopic and/or microscopic epileptic focus was present in 23 (20.5%) of these 112 cases. The cause of death was determined to be SUDEP in 40 (35.7%) cases, while it could not be determined in 28 (25%) cases. Among patients whose death cause was considered as SUDEP, the male-to-female ratio was 1.1:1, while the mean age was 31.5±13.9 years in males and 29.6±12.9 years in females. The presence of hypertrophy and myocardial scar tissue findings in the microscopic examination were significantly more frequent among patients determined to have died from cardiovascular diseases compared to patients in the SUDEP group (p=0.001 for each finding). Besides, in 40 SUDEP cases, 38 (95%) patients underwent toxicological analysis and no antiepileptic agent was detected in 21 (55.3%) of these. It can be concluded that there is equality in gender distribution among SUDEP patients, that the young adult population has a slightly increased risk for SUDEP, and that the inconsistent use of antiepileptic medicines is a greater risk factor for SUDEP than polytherapy. Besides, it is important to emphasize that all clinical and postmortem parameters together should be considered for the differential diagnosis of SUDEP, particularly with cardiovascular diseases.

Self-healing juvenile cutaneous mucinosis: cases highlighting subcutaneous/fascial involvement.

PubMed

Nagaraj, Lavanya V; Fangman, William; White, Wain L; Woosley, John T; Prose, Neil; Selim, M Angelica; Morrell, Dean S

2006-12-01

Self-healing juvenile cutaneous mucinosis is a rare disease affecting young people characterized by transient cutaneous lesions and sometimes mild inflammatory symptoms. The deep dermal and subcutaneous features of this disorder have not yet been well described. The purpose of our study was to present 3 cases of self-healing juvenile cutaneous mucinosis in which the histopathologic features caused diagnostic confusion between this disorder and proliferative fasciitis. The study includes clinical and histologic findings of 3 patients, complemented by a literature review. The histologic descriptions of nodular lesions in self-healing juvenile cutaneous mucinosis reveal features of proliferative fasciitis, including a myxoid stroma and gangliocyte-like giant cells. Self-healing juvenile cutaneous mucinosis is a rare condition and has not been frequently reported in medical literature. Our findings are based on the pathologic features of 3 patients. Our findings further elucidate the histologic features of self-healing juvenile cutaneous mucinosis and expand the differential diagnosis for entities in which gangliocyte-like giant cells are noted.

Sonographic Findings of Chondral Avulsion Fractures of the Lateral Ankle Ligaments in Children.

PubMed

Maeda, Manabu; Maeda, Nana; Takaoka, Takanori; Tanaka, Yasuhito

2017-02-01

In this series, we aimed to describe the sonographic findings of chondral avulsion fractures that develop concomitant with lateral ankle ligament injury in children. We performed stress sonography during a manual anterior drawer stress procedure of the ankle in 9 skeletally immature patients who had recently had a lateral ankle sprain. Echo videos were obtained through the course of treatment, and all videos were reviewed. We elucidated the common features of chondral avulsion fractures of the lateral ankle ligaments in the children. The features of avulsion fractures on conventional sonography included absence of a fracture with hyperechoic spots (sonographic occult fracture type), cortical discontinuity with hyperechoic spots (cortical disruption fracture type), fracture line in the cortical bone (double-line fracture type), and a step-off deformity of the cortical bone with cartilage (displaced fracture type). In contrast, the features of chondral fractures on stress sonography included abnormal motion of the chondral lesions and mobility/fluidity of hyperechoic spots along the chondral fracture site. The presence of hyperechoic spots around the chondral lesion is an important sonographic sign for diagnosing chondral fractures concomitant with ankle lateral ligament injury. Hence, we believe that stress sonography should be considered for the detection of chondral fractures concomitant with radiographically negative ankle lateral ligament injuries in skeletally immature patients with lateral ankle pain and ankle sprains, if hyperechoic spots are present in the cartilage of the distal fibula. © 2017 by the American Institute of Ultrasound in Medicine.

Unsupervised definition of the tibia-femoral joint regions of the human knee and its applications to cartilage analysis

NASA Astrophysics Data System (ADS)

Tamez-Peña, José G.; Barbu-McInnis, Monica; Totterman, Saara

2006-03-01

Abnormal MR findings including cartilage defects, cartilage denuded areas, osteophytes, and bone marrow edema (BME) are used in staging and evaluating the degree of osteoarthritis (OA) in the knee. The locations of the abnormal findings have been correlated to the degree of pain and stiffness of the joint in the same location. The definition of the anatomic region in MR images is not always an objective task, due to the lack of clear anatomical features. This uncertainty causes variance in the location of the abnormality between readers and time points. Therefore, it is important to have a reproducible system to define the anatomic regions. This works present a computerized approach to define the different anatomic knee regions. The approach is based on an algorithm that uses unique features of the femur and its spatial relation in the extended knee. The femur features are found from three dimensional segmentation maps of the knee. From the segmentation maps, the algorithm automatically divides the femur cartilage into five anatomic regions: trochlea, medial weight bearing area, lateral weight bearing area, posterior medial femoral condyle, and posterior lateral femoral condyle. Furthermore, the algorithm automatically labels the medial and lateral tibia cartilage. The unsupervised definition of the knee regions allows a reproducible way to evaluate regional OA changes. This works will present the application of this automated algorithm for the regional analysis of the cartilage tissue.

Visual Cortical Entrainment to Motion and Categorical Speech Features during Silent Lipreading

PubMed Central

O’Sullivan, Aisling E.; Crosse, Michael J.; Di Liberto, Giovanni M.; Lalor, Edmund C.

2017-01-01

Speech is a multisensory percept, comprising an auditory and visual component. While the content and processing pathways of audio speech have been well characterized, the visual component is less well understood. In this work, we expand current methodologies using system identification to introduce a framework that facilitates the study of visual speech in its natural, continuous form. Specifically, we use models based on the unheard acoustic envelope (E), the motion signal (M) and categorical visual speech features (V) to predict EEG activity during silent lipreading. Our results show that each of these models performs similarly at predicting EEG in visual regions and that respective combinations of the individual models (EV, MV, EM and EMV) provide an improved prediction of the neural activity over their constituent models. In comparing these different combinations, we find that the model incorporating all three types of features (EMV) outperforms the individual models, as well as both the EV and MV models, while it performs similarly to the EM model. Importantly, EM does not outperform EV and MV, which, considering the higher dimensionality of the V model, suggests that more data is needed to clarify this finding. Nevertheless, the performance of EMV, and comparisons of the subject performances for the three individual models, provides further evidence to suggest that visual regions are involved in both low-level processing of stimulus dynamics and categorical speech perception. This framework may prove useful for investigating modality-specific processing of visual speech under naturalistic conditions. PMID:28123363

Whatever you do, don't look at the...: Evaluating guidance by an exclusionary attentional template.

PubMed

Beck, Valerie M; Luck, Steven J; Hollingworth, Andrew

2018-04-01

People can use a target template consisting of one or more features to guide attention and gaze to matching objects in a search array. But can we also use feature information to guide attention away from known irrelevant items? Some studies found a benefit from foreknowledge of a distractor feature, whereas others found a cost. Importantly, previous work has largely relied on end-of-trial manual responses; it is unclear how feature-guided avoidance might unfold as candidate objects are inspected. In the current experiments, participants were cued with a distractor feature to avoid, then performed a visual search task while eye movements were recorded. Participants initially fixated a to-be-avoided object more frequently than predicted by chance, but they also demonstrated avoidance of cue-matching objects later in the trial. When provided more time between cue stimulus and search array, participants continued to be initially captured by a cued-color item. Furthermore, avoidance of cue-matching objects later in the trial was not contingent on initial capture by a cue-matching object. These results suggest that the conflicting findings in previous negative-cue experiments may be explained by a mixture of two independent processes: initial attentional capture by memory-matching items and later avoidance of known irrelevant items. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

How to Spot Congenital Myasthenic Syndromes Resembling the Lambert-Eaton Myasthenic Syndrome? A Brief Review of Clinical, Electrophysiological, and Genetics Features.

PubMed

Lorenzoni, Paulo José; Scola, Rosana Herminia; Kay, Claudia Suemi Kamoi; Werneck, Lineu Cesar; Horvath, Rita; Lochmüller, Hanns

2018-06-01

Congenital myasthenic syndromes (CMS) are heterogeneous genetic diseases in which neuromuscular transmission is compromised. CMS resembling the Lambert-Eaton myasthenic syndrome (CMS-LEMS) are emerging as a rare group of distinct presynaptic CMS that share the same electrophysiological features. They have low compound muscular action potential amplitude that increment after brief exercise (facilitation) or high-frequency repetitive nerve stimulation. Although clinical signs similar to LEMS can be present, the main hallmark is the electrophysiological findings, which are identical to autoimmune LEMS. CMS-LEMS occurs due to deficits in acetylcholine vesicle release caused by dysfunction of different components in its pathway. To date, the genes that have been associated with CMS-LEMS are AGRN, SYT2, MUNC13-1, VAMP1, and LAMA5. Clinicians should keep in mind these newest subtypes of CMS-LEMS to achieve the correct diagnosis and therapy. We believe that CMS-LEMS must be included as an important diagnostic clue to genetic investigation in the diagnostic algorithms to CMS. We briefly review the main features of CMS-LEMS.

Effects of moiré lattice structure on electronic properties of graphene

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

Huang, Lunan; Wu, Yun; Hershberger, M. T.

Here, we study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6√3×6√3 reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that ismore » then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.« less

Effects of moiré lattice structure on electronic properties of graphene

NASA Astrophysics Data System (ADS)

Huang, Lunan; Wu, Yun; Hershberger, M. T.; Mou, Daixiang; Schrunk, Benjamin; Tringides, Michael C.; Hupalo, Myron; Kaminski, Adam

2017-07-01

We study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6 √{3 }×6 √{3 } reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that is then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

PubMed Central

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-01

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems. PMID:28079187

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems.

PubMed

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-12

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

NASA Astrophysics Data System (ADS)

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-01

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

Neural Correlates of the Perception for Novel Objects

PubMed Central

Zhang, Hao; Liu, Jia; Zhang, Qinglin

2013-01-01

Perception of novel objects is of enormous importance in our lives. People have to perceive or understand novel objects when seeing an original painting, admiring an unconventional construction, and using an inventive device. However, very little is known about neural mechanisms underlying the perception for novel objects. Perception of novel objects relies on the integration of unusual features of novel objects in order to identify what such objects are. In the present study, functional Magnetic Resonance Imaging (MRI) was employed to investigate neural correlates of perception of novel objects. The neuroimaging data on participants engaged in novel object viewing versus ordinary object viewing revealed that perception of novel objects involves significant activation in the left precuneus (Brodmann area 7) and the right visual cortex. The results suggest that the left precuneus is associated with the integration of unusual features of novel objects, while the right visual cortex is sensitive to the detection of such features. Our findings highlight the left precuneus as a crucial component of the neural circuitry underlying perception of novel objects. PMID:23646167

Effects of moiré lattice structure on electronic properties of graphene

DOE PAGES

Huang, Lunan; Wu, Yun; Hershberger, M. T.; ...

2017-07-10

Here, we study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6√3×6√3 reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that ismore » then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.« less

Untuned Suppression Makes a Major Contribution to the Enhancement of Orientation Selectivity in Macaque V1

PubMed Central

Ringach, Dario L.; Hawken, Michael J.; Shapley, Robert M.

2011-01-01

One of the functions of the cerebral cortex is to increase the selectivity for stimulus features. Finding more about the mechanisms of increased cortical selectivity is important for understanding how the cortex works. Up to now, studies in multiple cortical areas have reported that suppressive mechanisms are involved in feature selectivity. However, the magnitude of the contribution of suppression to tuning selectivity is not yet determined. We use orientation selectivity in macaque primary visual cortex, V1, as an archetypal example of cortical feature selectivity and develop a method to estimate the magnitude of the contribution of suppression to orientation selectivity. The results show that untuned suppression, one form of cortical suppression, decreases the orthogonal-to-preferred response ratio (O/P ratio) of V1 cells from an average of 0.38 to 0.26. Untuned suppression has an especially large effect on orientation selectivity for highly selective cells (O/P < 0.2). Therefore, untuned suppression is crucial for the generation of highly orientation-selective cells in V1 cortex. PMID:22049440

Discriminant Features and Temporal Structure of Nonmanuals in American Sign Language

PubMed Central

Benitez-Quiroz, C. Fabian; Gökgöz, Kadir; Wilbur, Ronnie B.; Martinez, Aleix M.

2014-01-01

To fully define the grammar of American Sign Language (ASL), a linguistic model of its nonmanuals needs to be constructed. While significant progress has been made to understand the features defining ASL manuals, after years of research, much still needs to be done to uncover the discriminant nonmanual components. The major barrier to achieving this goal is the difficulty in correlating facial features and linguistic features, especially since these correlations may be temporally defined. For example, a facial feature (e.g., head moves down) occurring at the end of the movement of another facial feature (e.g., brows moves up), may specify a Hypothetical conditional, but only if this time relationship is maintained. In other instances, the single occurrence of a movement (e.g., brows move up) can be indicative of the same grammatical construction. In the present paper, we introduce a linguistic–computational approach to efficiently carry out this analysis. First, a linguistic model of the face is used to manually annotate a very large set of 2,347 videos of ASL nonmanuals (including tens of thousands of frames). Second, a computational approach is used to determine which features of the linguistic model are more informative of the grammatical rules under study. We used the proposed approach to study five types of sentences – Hypothetical conditionals, Yes/no questions, Wh-questions, Wh-questions postposed, and Assertions – plus their polarities – positive and negative. Our results verify several components of the standard model of ASL nonmanuals and, most importantly, identify several previously unreported features and their temporal relationship. Notably, our results uncovered a complex interaction between head position and mouth shape. These findings define some temporal structures of ASL nonmanuals not previously detected by other approaches. PMID:24516528

Bronchoalveolar carcinoma: clinical, radiologic, and pathologic factors and survival.

PubMed

Okubo, K; Mark, E J; Flieder, D; Wain, J C; Wright, C D; Moncure, A C; Grillo, H C; Mathisen, D J

1999-10-01

The principal feature of bronchoalveolar carcinoma is that it spreads along airways or aerogenously with multifocality, but many issues are unresolved. We studied 119 patients with pathologically confirmed bronchoalveolar carcinoma. Symptoms, smoking status, radiologic findings, the size of tumor, operative procedures, and complications were reviewed. We studied the pathologic features: presence or absence of aerogenous spread, patterns of growth, cell type, nuclear grade, mitosis, rate of bronchoalveolar carcinoma in adenocarcinoma, and lymphocyte infiltration. The correlation among clinical, radiologic, and pathologic findings was examined, and the factors affecting survival were analyzed. Symptomatic patients had more infiltrative radiographic features, and asymptomatic patients tended to have more mass-like features (P <.0001). Tumors with radiographically infiltrating lesions tended to have mucinous histologic features (P =.006). Tumors with mass lesions by radiograph tended to have nonmucinous and sclerosing histologic features (P =.003). Aerogenous spread was seen in 94% of specimens. The presence of a variety of cell types suggested multiple clonal origin. The overall survival in those patients undergoing resection was 69.1% at 5 years and 56.5% at 10 years. The significant factors affecting survival were radiologic presence of a mass or infiltrate, pathologic findings of the presence of sclerosis, association with a scar, the rate of bronchoalveolar carcinoma in adenocarcinoma, lymphocyte infiltration grade, nodal involvement, and status of complete resection. Mitosis or nuclear grade of tumor cells did not correlate with survival. Bronchoalveolar carcinoma showed good overall survival with appropriate surgical procedures. Certain radiologic or pathologic findings correlated with survival. These findings may enhance the ability to predict long-term survival.

TH-E-BRF-04: Characterizing the Response of Texture-Based CT Image Features for Quantification of Radiation-Induced Normal Lung Damage

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

Krafft, S; Court, L; Briere, T

2014-06-15

Purpose: Radiation induced lung damage (RILD) is an important dose-limiting toxicity for patients treated with radiation therapy. Scoring systems for RILD are subjective and limit our ability to find robust predictors of toxicity. We investigate the dose and time-related response for texture-based lung CT image features that serve as potential quantitative measures of RILD. Methods: Pre- and post-RT diagnostic imaging studies were collected for retrospective analysis of 21 patients treated with photon or proton radiotherapy for NSCLC. Total lung and selected isodose contours (0–5, 5–15, 15–25Gy, etc.) were deformably registered from the treatment planning scan to the pre-RT and availablemore » follow-up CT studies for each patient. A CT image analysis framework was utilized to extract 3698 unique texture-based features (including co-occurrence and run length matrices) for each region of interest defined by the isodose contours and the total lung volume. Linear mixed models were fit to determine the relationship between feature change (relative to pre-RT), planned dose and time post-RT. Results: Seventy-three follow-up CT scans from 21 patients (median: 3 scans/patient) were analyzed to describe CT image feature change. At the p=0.05 level, dose affected feature change in 2706 (73.1%) of the available features. Similarly, time affected feature change in 408 (11.0%) of the available features. Both dose and time were significant predictors of feature change in a total of 231 (6.2%) of the extracted image features. Conclusion: Characterizing the dose and time-related response of a large number of texture-based CT image features is the first step toward identifying objective measures of lung toxicity necessary for assessment and prediction of RILD. There is evidence that numerous features are sensitive to both the radiation dose and time after RT. Beyond characterizing feature response, further investigation is warranted to determine the utility of these features as surrogates of clinically significant lung injury.« less

A survey of stakeholder perspectives on a proposed combined exoskeleton-wheelchair technology.

PubMed

Bhatnagar, Tim; Ben Mortensen, W; Mattie, Johanne; Wolff, Jamie; Parker, Claire; Borisoff, Jaimie

2017-07-01

Exoskeleton technology has potential benefits for wheelchair users' health and mobility. However, there are practical barriers to their everyday use as a mobility device. In particular, challenges related to travelling longer distances and transitioning between using a wheelchair and exoskeleton walking may present significant deterrents to regular exoskeleton use. In an effort to remove these barriers, a combined exoskeleton-wheelchair concept ('COMBO') has been proposed, which aims to achieve the benefits of both these mobility technologies. Given the inherent importance of including user-stakeholder opinions when designing an assistive technology solution, a study was undertaken to explore the perspectives of wheelchair users and healthcare professionals on the proposed conceptual design of the COMBO. An online survey with quantitative and qualitative components was conducted with wheelchair users and healthcare professionals working directly with individuals with mobility impairments. Respondents rated whether they would use or recommend a COMBO for four potential reasons. Nine design features were rated and compared in terms of their importance. Content analysis was used to analyze data from an open-ended question regarding additional perceptions about using or recommending a COMBO. A total of 481 survey responses were analyzed, 354 from wheelchair users and 127 from healthcare professionals. Potential health benefits was the most highly rated reason for potential use or recommendation of a COMBO. Of the 9 design features, 2 had a median rating of very important: inclusion of a fall-protection mechanism, and the ability for the operator to use their hands while standing. Qualitative findings indicated that health and physical benefits, use for daily life activities, and psychosocial benefits were important considerations in whether to use or recommend the COMBO. This study captures the opinions and perspectives of two stakeholder groups for an exoskeleton-wheelchair hybrid device. It also emphasizes the importance of fall-protection, hand-use capabilities and enabling functional activities. Findings from this study can be utilized to provide insight for the refinement of the COMBO concept, as well as to guide more general mobility device research and development.

Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data.

PubMed

Becker, Natalia; Toedt, Grischa; Lichter, Peter; Benner, Axel

2011-05-09

Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net.We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone.Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution. Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (L1) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error.Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations. The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters.The penalized SVM classification algorithms as well as fixed grid and interval search for finding appropriate tuning parameters were implemented in our freely available R package 'penalizedSVM'.We conclude that the Elastic SCAD SVM is a flexible and robust tool for classification and feature selection tasks for high-dimensional data such as microarray data sets.

Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data

PubMed Central

2011-01-01

Background Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net. We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone. Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution. Results Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (L1) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error. Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations. Conclusions The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters. The penalized SVM classification algorithms as well as fixed grid and interval search for finding appropriate tuning parameters were implemented in our freely available R package 'penalizedSVM'. We conclude that the Elastic SCAD SVM is a flexible and robust tool for classification and feature selection tasks for high-dimensional data such as microarray data sets. PMID:21554689

Congenital portosystemic shunts: prenatal manifestations with postnatal confirmation and follow-up.

PubMed

Han, Byoung Hee; Park, Sung Bin; Song, Mi Jin; Lee, Kyung Sang; Lee, Young-Ho; Ko, Sun Young; Lee, Yeon Kyung

2013-01-01

The purpose of this study was to evaluate prenatal sonographic findings that could be helpful for diagnosis of congenital intrahepatic portosystemic venous shunts and the follow-up results. Six neonates with congenital shunts between the portal vein and hepatic vein were enrolled in this study. Prenatal sonography was performed in 5 cases. We categorized the cases according to a previously published classification of intrahepatic portosystemic venous shunts and retrospectively reviewed the prenatal and postnatal sonographic examinations to identify findings that might be helpful for diagnosing shunts prenatally. Follow-up sonographic examinations were done until closure of the shunts. Clinical features were also determined. According to the original reports, intrahepatic portosystemic venous shunts were diagnosed by prenatal sonography in 2 of 5 cases. In the remaining 3 cases, there were suggestive abnormal findings on retrospective review, including an abnormal intrahepatic tubular structure, a prominent hepatic vein, and congestive heart failure. Postnatal sonography showed type 2 shunts in all 6 cases. In 1 case, there were 2 type 2 lesions between two branches of the left portal vein and the middle and left hepatic veins. On follow-up sonography, 5 of the 6 congenital shunts had spontaneously closed by 11 months of age. One case was treated with coil embolization during the neonatal period. Intrauterine growth restriction was the most commonly clinical feature prenatally. Findings such as an abnormal tubular structure, a prominent hepatic vein, and congestive heart failure can be important clues for identifying congenital intrahepatic portosystemic venous shunts on prenatal sonography. The use of prenatal and postnatal sonography is feasible for detection and evaluation of these shunts.

Semaphore network encryption report

NASA Astrophysics Data System (ADS)

Johnson, Karen L.

1994-03-01

This paper documents the results of a preliminary assessment performed on the commercial off-the-shelf (COTS) Semaphore Communications Corporation (SCC) Network Security System (NSS). The Semaphore NSS is a family of products designed to address important network security concerns, such as network source address authentication and data privacy. The assessment was performed in the INFOSEC Core Integration Laboratory, and its scope was product usability focusing on interoperability and system performance in an existing operational network. Included in this paper are preliminary findings. Fundamental features and functionality of the Semaphore NSS are identified, followed by details of the assessment, including test descriptions and results. A summary of test results and future plans are also included. These findings will be useful to those investigating the use of commercially available solutions to network authentication and data privacy.

Investigation of the utility of ERTS-1 imagery for updating land use and resource data in Guatemala

NASA Technical Reports Server (NTRS)

Garcia, L. E. (Principal Investigator)

1973-01-01

The author has identified the following significant results. An intensive analysis of the imagery received has been completed and findings are reported. Conclusions are restricted by receipt of only limited amounts of cloud-free coverage of test areas. In most cases the interpretation findings were as anticipated from previous experience with multiband images. Band 7 provides promising indication of some economically important environmental communities. It also permits viewing through thin cirrus cloud layers for features of medium to high contrast. Band 4 provides information of submerged reefs and of movement of suspended sediment bodies in water areas. ERTS-1 bulk images have positional mapping accuracy adequate for representation at 1:1,000,000 scale maps. Cloud cover is a true constraint to useable satellite coverage.

Finding the top influential bloggers based on productivity and popularity features

NASA Astrophysics Data System (ADS)

Khan, Hikmat Ullah; Daud, Ali

2017-07-01

A blog acts as a platform of virtual communication to share comments or views about products, events and social issues. Like other social web activities, blogging actions spread to a large number of people. Users influence others in many ways, such as buying a product, having a particular political or social opinion or initiating new activity. Finding the top influential bloggers is an active research domain as it helps us in various fields, such as online marketing, e-commerce, product search and e-advertisements. There exist various models to find the influential bloggers, but they consider limited features using non-modular approach. This paper proposes a new model, Popularity and Productivity Model (PPM), based on a modular approach to find the top influential bloggers. It consists of popularity and productivity modules which exploit various features. We discuss the role of each proposed and existing features and evaluate the proposed model against the standard baseline models using datasets from the real-world blogs. The analysis using standard performance evaluation measures verifies that both productivity and popularity modules play a vital role to find influential bloggers in blogging community in an effective manner.

Mid-Infrared Silicate Dust Features in Seyfert 1 Spectra

NASA Astrophysics Data System (ADS)

Thompson, Grant D.; Levenson, N. A.; Sirocky, M. M.; Uddin, S.

2007-12-01

Silicate dust emission dominates the mid-infrared spectra of galaxies, and the dust produces two spectral features, at 10 and 18 μm. These features' strengths (in emission or absorption) and peak wavelengths reveal the geometry of the dust distribution, and they are sensitive to the dust composition. We examine mid-infrared spectra of 32 Seyfert 1 active galactic nuclei (AGN), observed with the Infrared Spectrograph aboard the Spitzer Space Telescope. In the spectra, we typically find the shorter-wavelength feature in emission, at an average peak wavelength of 10.0 μm, although it is known historically as the "9.7 μm" feature. In addition, peak wavelength increases with feature strength. The 10 and 18 μm feature strengths together are sensitive to the dust geometry surrounding the central heating engine. Numerical calculations of radiative transfer distinguish between clumpy and smooth distributions, and we find that the surroundings of these AGN (the obscuring "tori" of unified AGN schemes) are clumpy. Polycyclic aromatic hydrocarbon (PAH) features are associated with star formation, and we find strong PAH emission (luminosity ≥ 1042 erg/s) in only four sources, three of which show independent evidence for starbursts. We will explore the effects of luminosity on dust geometry and chemistry in a comparison sample of quasars. We acknowledge work supported by the NSF under grant number 0237291.

Asymmetrical access to color and location in visual working memory.

PubMed

Rajsic, Jason; Wilson, Daryl E

2014-10-01

Models of visual working memory (VWM) have benefitted greatly from the use of the delayed-matching paradigm. However, in this task, the ability to recall a probed feature is confounded with the ability to maintain the proper binding between the feature that is to be reported and the feature (typically location) that is used to cue a particular item for report. Given that location is typically used as a cue-feature, we used the delayed-estimation paradigm to compare memory for location to memory for color, rotating which feature was used as a cue and which was reported. Our results revealed several novel findings: 1) the likelihood of reporting a probed object's feature was superior when reporting location with a color cue than when reporting color with a location cue; 2) location report errors were composed entirely of swap errors, with little to no random location reports; and 3) both colour and location reports greatly benefitted from the presence of nonprobed items at test. This last finding suggests that it is uncertainty over the bindings between locations and colors at memory retrieval that drive swap errors, not at encoding. We interpret our findings as consistent with a representational architecture that nests remembered object features within remembered locations.

An in-silico method for identifying aggregation rate enhancer and mitigator mutations in proteins.

PubMed

Rawat, Puneet; Kumar, Sandeep; Michael Gromiha, M

2018-06-24

Newly synthesized polypeptides must pass stringent quality controls in cells to ensure appropriate folding and function. However, mutations, environmental stresses and aging can reduce efficiencies of these controls, leading to accumulation of protein aggregates, amyloid fibrils and plaques. In-vitro experiments have shown that even single amino acid substitutions can drastically enhance or mitigate protein aggregation kinetics. In this work, we have collected a dataset of 220 unique mutations in 25 proteins and classified them as enhancers or mitigators on the basis of their effect on protein aggregation rate. The data were analyzed via machine learning to identify features capable of distinguishing between aggregation rate enhancers and mitigators. Our initial Support Vector Machine (SVM) model separated such mutations with an overall accuracy of 69%. When local secondary structures at the mutation sites were considered, the accuracies further improved by 13-15%. The machine-learnt features are distinct for each secondary structure class at mutation sites. Protein stability and flexibility changes are important features for mutations in α-helices. β-strand propensity, polarity and charge become important when mutations occur in β-strands and ability to form secondary structure, helical tendency and aggregation propensity are important for mutations lying in coils. These results have been incorporated into a sequence-based algorithm (available at http://www.iitm.ac.in/bioinfo/aggrerate-disc/) capable of predicting whether a mutation will enhance or mitigate a protein's aggregation rate. This algorithm will find several applications towards understanding protein aggregation in human diseases, enable in-silico optimization of biopharmaceuticals and enzymes for improved biophysical attributes and de novo design of bio-nanomaterials. Copyright © 2018. Published by Elsevier B.V.

Skeletal idiopathic osteosclerosis helps to perform personal identification of unknown decedents: A novel contribution from anatomical variants through CT scan.

PubMed

De Angelis, D; Gibelli, D; Palazzo, E; Sconfienza, L; Obertova, Z; Cattaneo, C

2016-07-01

Personal identification consists of the comparison of ante-mortem information from a missing person with post-mortem data obtained from an unidentified corpse. Such procedure is based on the assessment of individualizing features which may help in providing a conclusive identification between ante-mortem and post-mortem material. Anatomical variants may provide important clues to correctly identify human remains. Areas of idiopathic osteosclerosis (IO), or dense bone islands (DBIs) characterized by radiopaque areas of dense, trabeculated, non-inflamed vital bone represent one of these, potentially individualizing, anatomical features. This study presents a case where the finding of DBI was crucial for a positive identification through CT-scan. A decomposed body was found in an apartment in June 2014 in advanced decomposition and no dental records were available to perform a comparison for positive identification. Genetic tests were not applicable because of the lack of relatives in a direct line. The analysis of the only ante-mortem documentation, a CT-scan to the deceased dating back to August 2009, showed the presence of three DBIs within the trabecular bone of the proximal portion of the right femur. The same bony district was removed from the corpse during the autopsy and analysed by CT-scan, which verified the presence of the same features. Forensic practitioners should therefore be aware of the great importance of anatomical bone variants, such as dense bone islands for identification purposes, and the importance of advanced radiological technique for addressing the individualizing potential of such variants. We propose that anatomical variants of the human skeleton should be considered as being "primary identification characteristics" similar to dental status, fingerprints and DNA. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Distortions of Subjective Time Perception Within and Across Senses

PubMed Central

van Wassenhove, Virginie; Buonomano, Dean V.; Shimojo, Shinsuke; Shams, Ladan

2008-01-01

Background The ability to estimate the passage of time is of fundamental importance for perceptual and cognitive processes. One experience of time is the perception of duration, which is not isomorphic to physical duration and can be distorted by a number of factors. Yet, the critical features generating these perceptual shifts in subjective duration are not understood. Methodology/Findings We used prospective duration judgments within and across sensory modalities to examine the effect of stimulus predictability and feature change on the perception of duration. First, we found robust distortions of perceived duration in auditory, visual and auditory-visual presentations despite the predictability of the feature changes in the stimuli. For example, a looming disc embedded in a series of steady discs led to time dilation, whereas a steady disc embedded in a series of looming discs led to time compression. Second, we addressed whether visual (auditory) inputs could alter the perception of duration of auditory (visual) inputs. When participants were presented with incongruent audio-visual stimuli, the perceived duration of auditory events could be shortened or lengthened by the presence of conflicting visual information; however, the perceived duration of visual events was seldom distorted by the presence of auditory information and was never perceived shorter than their actual durations. Conclusions/Significance These results support the existence of multisensory interactions in the perception of duration and, importantly, suggest that vision can modify auditory temporal perception in a pure timing task. Insofar as distortions in subjective duration can neither be accounted for by the unpredictability of an auditory, visual or auditory-visual event, we propose that it is the intrinsic features of the stimulus that critically affect subjective time distortions. PMID:18197248

Differential role of molten globule and protein folding in distinguishing unique features of botulinum neurotoxin.

PubMed

Kumar, Raj; Kukreja, Roshan V; Cai, Shuowei; Singh, Bal R

2014-06-01

Botulinum neurotoxins (BoNTs) are proteins of great interest not only because of their extreme toxicity but also paradoxically for their therapeutic applications. All the known serotypes (A-G) have varying degrees of longevity and potency inside the neuronal cell. Differential chemical modifications such as phosphorylation and ubiquitination have been suggested as possible mechanisms for their longevity, but the molecular basis of the longevity remains unclear. Since the endopeptidase domain (light chain; LC) of toxin apparently survives inside the neuronal cells for months, it is important to examine the structural features of this domain to understand its resistance to intracellular degradation. Published crystal structures (both botulinum neurotoxins and endopeptidase domain) have not provided adequate explanation for the intracellular longevity of the domain. Structural features obtained from spectroscopic analysis of LCA and LCB were similar, and a PRIME (PReImminent Molten Globule Enzyme) conformation appears to be responsible for their optimal enzymatic activity at 37°C. LCE, on the other hand, was although optimally active at 37°C, but its active conformation differed from the PRIME conformation of LCA and LCB. This study establishes and confirms our earlier finding that an optimally active conformation of these proteins in the form of PRIME exists for the most poisonous poison, botulinum neurotoxin. There are substantial variations in the structural and functional characteristics of these active molten globule related structures among the three BoNT endopeptidases examined. These differential conformations of LCs are important in understanding the fundamental structural features of proteins, and their possible connection to intracellular longevity could provide significant clues for devising new countermeasures and effective therapeutics. Copyright © 2014 Elsevier B.V. All rights reserved.

Using spectrotemporal indices to improve the fruit-tree crop classification accuracy

NASA Astrophysics Data System (ADS)

Peña, M. A.; Liao, R.; Brenning, A.

2017-06-01

This study assesses the potential of spectrotemporal indices derived from satellite image time series (SITS) to improve the classification accuracy of fruit-tree crops. Six major fruit-tree crop types in the Aconcagua Valley, Chile, were classified by applying various linear discriminant analysis (LDA) techniques on a Landsat-8 time series of nine images corresponding to the 2014-15 growing season. As features we not only used the complete spectral resolution of the SITS, but also all possible normalized difference indices (NDIs) that can be constructed from any two bands of the time series, a novel approach to derive features from SITS. Due to the high dimensionality of this "enhanced" feature set we used the lasso and ridge penalized variants of LDA (PLDA). Although classification accuracies yielded by the standard LDA applied on the full-band SITS were good (misclassification error rate, MER = 0.13), they were further improved by 23% (MER = 0.10) with ridge PLDA using the enhanced feature set. The most important bands to discriminate the crops of interest were mainly concentrated on the first two image dates of the time series, corresponding to the crops' greenup stage. Despite the high predictor weights provided by the red and near infrared bands, typically used to construct greenness spectral indices, other spectral regions were also found important for the discrimination, such as the shortwave infrared band at 2.11-2.19 μm, sensitive to foliar water changes. These findings support the usefulness of spectrotemporal indices in the context of SITS-based crop type classifications, which until now have been mainly constructed by the arithmetic combination of two bands of the same image date in order to derive greenness temporal profiles like those from the normalized difference vegetation index.

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

Lin, I.C.; Ko, S.F.; Shieh, C.S.

Ehlers-Danlos syndrome (EDS) includes a group of connective tissue disorders with abnormal collagen metabolism and a diverse clinical spectrum. We report two siblings with EDS who both presented with congenital diaphragmatic hernia (CDH). The elder sister suffered from recurrent diaphragmatic hernia twice and EDS was overlooked initially. Echocardiography as well as contrast-enhanced magnetic resonance angiography (MRA) showed dilatation of the pulmonary artery, and marked elongation and tortuosity of the aorta and its branches. A diagnosis of EDS was eventually established when these findings were coupled with the clinical features of hyperelastic skin. Her younger brother also had similar features. Thismore » report emphasizes that EDS may present as CDH in a small child which could easily be overlooked. Without appropriate surgery, diaphragmatic hernia might occur. Echocardiographic screening is recommended in patients with CDH. Contrast-enhanced MRA can be helpful in delineation of abnormally tortuous aortic great vessels that are an important clue to the early diagnosis of EDS.« less

Target templates: the precision of mental representations affects attentional guidance and decision-making in visual search.

PubMed

Hout, Michael C; Goldinger, Stephen D

2015-01-01

When people look for things in the environment, they use target templates-mental representations of the objects they are attempting to locate-to guide attention and to assess incoming visual input as potential targets. However, unlike laboratory participants, searchers in the real world rarely have perfect knowledge regarding the potential appearance of targets. In seven experiments, we examined how the precision of target templates affects the ability to conduct visual search. Specifically, we degraded template precision in two ways: 1) by contaminating searchers' templates with inaccurate features, and 2) by introducing extraneous features to the template that were unhelpful. We recorded eye movements to allow inferences regarding the relative extents to which attentional guidance and decision-making are hindered by template imprecision. Our findings support a dual-function theory of the target template and highlight the importance of examining template precision in visual search.

Flying insect detection and classification with inexpensive sensors.

PubMed

Chen, Yanping; Why, Adena; Batista, Gustavo; Mafra-Neto, Agenor; Keogh, Eamonn

2014-10-15

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect's flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.

3M syndrome: a report of four cases in two families.

PubMed

Güven, Ayla; Cebeci, Ayşe Nurcan

2011-01-01

3M syndrome is a rare entity characterized by severe growth retardation, dysmorphic features and skeletal changes as its major components. It is differentiated from other types of dwarfism by its clinical features and by the typical slender long bones and foreshortened vertebral bodies that can be visualized radiographically. 3M syndrome has an autosomal recessive mode of inheritance. An early diagnosis is important for genetic counseling. In this report, we present four children (3 males, 1 female) from two families who were aged between 4(11/12) and 10(11/12) years and had clinical findings of 3M syndrome. One of these patients had received growth hormone (GH) treatment which was discontinued due to an inadequate height gain. Physicians should be aware of this entity in the differential diagnosis of children with severe short stature and mild skeletal changes.

Functional and topological characteristics of mammalian regulatory domains

PubMed Central

Symmons, Orsolya; Uslu, Veli Vural; Tsujimura, Taro; Ruf, Sandra; Nassari, Sonya; Schwarzer, Wibke; Ettwiller, Laurence; Spitz, François

2014-01-01

Long-range regulatory interactions play an important role in shaping gene-expression programs. However, the genomic features that organize these activities are still poorly characterized. We conducted a large operational analysis to chart the distribution of gene regulatory activities along the mouse genome, using hundreds of insertions of a regulatory sensor. We found that enhancers distribute their activities along broad regions and not in a gene-centric manner, defining large regulatory domains. Remarkably, these domains correlate strongly with the recently described TADs, which partition the genome into distinct self-interacting blocks. Different features, including specific repeats and CTCF-binding sites, correlate with the transition zones separating regulatory domains, and may help to further organize promiscuously distributed regulatory influences within large domains. These findings support a model of genomic organization where TADs confine regulatory activities to specific but large regulatory domains, contributing to the establishment of specific gene expression profiles. PMID:24398455

Immigrants' Pathways to Outpatient Mental Health: Are there Differences with the Native Population?

PubMed

Gramaglia, Carla; Gambaro, Eleonora; Rossi, Annalisa; Toso, Alessandra; Feggi, Alessandro; Cattaneo, Carlo Ignazio; Castignoli, Giorgio; Mainini, Piera; Tarricone, Ilaria; Torre, Eugenio; Zeppegno, Patrizia

2016-08-01

A poor use of mental health services has been described in immigrants. We compared the sociodemographic, clinical and treatment features of immigrants and natives attending a Community Mental Health Centre (CMHC). 191 immigrants and 191 randomly selected natives applying to the Borgomanero CMHC between 1 January 2003 and 31 August 2013 were compared. Our sample consisted mainly of the so-called "economic" immigrant. Adjustment disorders and reaction to stress were the most frequent diagnoses; in most cases symptoms onset occurred after migration. Although treatment features overlapped in the two groups (duration, number of contacts), immigrants showed a higher frequency of treatment dropout. While it is necessary to improve access to mental health services for immigrants, for the "economic" immigrant it may be more important to focus on establishing a therapeutic relationship that can be experienced as reliable and trustworthy. The finding of similar pathways to access the CMHC in natives and immigrants is encouraging.

Reading the medical record. I. Analysis of physicians' ways of reading the medical record.

PubMed

Nygren, E; Henriksson, P

1992-01-01

Physicians were interviewed about their routines in everyday use of the medical record. From the interviews, we conclude that the medical record is a well functioning working instrument for the experienced physician. Using the medical record as a basis for decision making involves interpretation of format, layout and other textural features of the type-written data. Interpretation of these features provides effective guidance in the process of searching, reading and assessing the relevance of different items of information in the record. It seems that this is a skill which is an integrated part of diagnostic expertise. This skill plays an important role in decision making based on the large amount of information about a patient, which is exhibited to the reader in the medical record. This finding has implications for the design of user interfaces for reading computerized medical records.

Reexpansion pulmonary edema in children

PubMed Central

Rodrigues, Antonio Lucas L.; Lopes, Carlos Eduardo; Romaneli, Mariana Tresoldi das N.; Fraga, Andrea de Melo A.; Pereira, Ricardo Mendes; Tresoldi, Antonia Teresinha

2013-01-01

OBJECTIVE To present a case of a patient with clinical and radiological features of reexpansion pulmonary edema, a rare and potentially fatal disease. CASE DESCRIPTION An 11-year-old boy presenting fever, clinical signs and radiological features of large pleural effusion initially treated as a parapneumonic process. Due to clinical deterioration he underwent tube thoracostomy, with evacuation of 3,000 mL of fluid; he shortly presented acute respiratory insufficiency and needed mechanical ventilation. He had an atypical evolution (extubated twice with no satisfactory response). Computerized tomography findings matched those of reexpansion edema. He recovered satisfactorily after intensive care, and pleural tuberculosis was diagnosed afterwards. COMMENTS Despite its rareness in the pediatric population (only five case reports gathered), the knowledge of this pathology and its prevention is very important, due to high mortality rates. It is recommended, among other measures, slow evacuation of the pleural effusion, not removing more than 1,500 mL of fluid at once. PMID:24142327

Comparison between a Direct-Flow SPR Immunosensor for Ampicillin and a Competitive Conventional Amperometric Device: Analytical Features and Possible Applications to Real Samples

PubMed Central

Tomassetti, Mauro; Merola, Giovanni; Martini, Elisabetta; Campanella, Luigi; Sanzò, Gabriella; Favero, Gabriele; Mazzei, Franco

2017-01-01

In this research, we developed a direct-flow surface plasmon resonance (SPR) immunosensor for ampicillin to perform direct, simple, and fast measurements of this important antibiotic. In order to better evaluate the performance, it was compared with a conventional amperometric immunosensor, working with a competitive format with the aim of finding out experimental real advantages and disadvantages of two respective methods. Results showed that certain analytical features of the new SPR immunodevice, such as the lower limit of detection (LOD) value and the width of the linear range, are poorer than those of a conventional amperometric immunosensor, which adversely affects the application to samples such as natural waters. On the other hand, the SPR immunosensor was more selective to ampicillin, and measurements were more easily and quickly attained compared to those performed with the conventional competitive immunosensor. PMID:28394296

Face-space architectures: evidence for the use of independent color-based features.

PubMed

Nestor, Adrian; Plaut, David C; Behrmann, Marlene

2013-07-01

The concept of psychological face space lies at the core of many theories of face recognition and representation. To date, much of the understanding of face space has been based on principal component analysis (PCA); the structure of the psychological space is thought to reflect some important aspects of a physical face space characterized by PCA applications to face images. In the present experiments, we investigated alternative accounts of face space and found that independent component analysis provided the best fit to human judgments of face similarity and identification. Thus, our results challenge an influential approach to the study of human face space and provide evidence for the role of statistically independent features in face encoding. In addition, our findings support the use of color information in the representation of facial identity, and we thus argue for the inclusion of such information in theoretical and computational constructs of face space.

Self-assembled ultrathin nanotubes on diamond (100) surface

NASA Astrophysics Data System (ADS)

Lu, Shaohua; Wang, Yanchao; Liu, Hanyu; Miao, Mao-Sheng; Ma, Yanming

2014-04-01

Surfaces of semiconductors are crucially important for electronics, especially when the devices are reduced to the nanoscale. However, surface structures are often elusive, impeding greatly the engineering of devices. Here we develop an efficient method that can automatically explore the surface structures using structure swarm intelligence. Its application to a simple diamond (100) surface reveals an unexpected surface reconstruction featuring self-assembled carbon nanotubes arrays. Such a surface is energetically competitive with the known dimer structure under normal conditions, but it becomes more favourable under a small compressive strain or at high temperatures. The intriguing covalent bonding between neighbouring tubes creates a unique feature of carrier kinetics (that is, one dimensionality of hole states, while two dimensionality of electron states) that could lead to novel design of superior electronics. Our findings highlight that the surface plays vital roles in the fabrication of nanodevices by being a functional part of them.

Distinct lateral inhibitory circuits drive parallel processing of sensory information in the mammalian olfactory bulb

PubMed Central

Geramita, Matthew A; Burton, Shawn D; Urban, Nathan N

2016-01-01

Splitting sensory information into parallel pathways is a common strategy in sensory systems. Yet, how circuits in these parallel pathways are composed to maintain or even enhance the encoding of specific stimulus features is poorly understood. Here, we have investigated the parallel pathways formed by mitral and tufted cells of the olfactory system in mice and characterized the emergence of feature selectivity in these cell types via distinct lateral inhibitory circuits. We find differences in activity-dependent lateral inhibition between mitral and tufted cells that likely reflect newly described differences in the activation of deep and superficial granule cells. Simulations show that these circuit-level differences allow mitral and tufted cells to best discriminate odors in separate concentration ranges, indicating that segregating information about different ranges of stimulus intensity may be an important function of these parallel sensory pathways. DOI: http://dx.doi.org/10.7554/eLife.16039.001 PMID:27351103

Flexible memory retrieval in bilingual 6-month-old infants.

PubMed

Brito, Natalie; Barr, Rachel

2014-07-01

Memory flexibility is a hallmark of the human memory system. As indexed by generalization between perceptually dissimilar objects, memory flexibility develops gradually during infancy. A recent study has found a bilingual advantage in memory generalization at 18 months of age [Brito and Barr [2012] Developmental Science, 15, 812-816], and the present study examines when this advantage may first emerge. In the current study, bilingual 6-month-olds were more likely than monolinguals to generalize to a puppet that differed in two features (shape and color) than monolingual 6-month-olds. When challenged with a less complex change, two puppets that differed only in one feature--color, monolingual 6-month-olds were also able to generalize. These findings demonstrate early emerging differences in memory generalization in bilingual infants, and have important implications for our understanding of how early environmental variations shape the trajectory of memory development. © 2013 Wiley Periodicals, Inc.

Gender differences in contributions of emotion to psychopathy and antisocial personality disorder.

PubMed

Rogstad, Jill E; Rogers, Richard

2008-12-01

Traditional conceptualizations of psychopathy highlight the importance of affective features as they relate to social deviance; however, little empirical research has actually investigated specific roles of emotion and emotion processing with respect to antisocial conduct. Antisocial personality disorder (APD), prevalent in forensic populations, is commonly associated with psychopathy despite the notable omission of such core affective features in its diagnosis. In this paper, we review the empirical literature on the contribution of emotion to psychopathy and APD, highlighting in particular research on emotion processing and various facets of emotional expression, including empathy and alexithymia. Research findings are discussed on gender differences in emotional functioning and their likely effects on the assessment of psychopathy and APD. Given the known gender differences in the expressions of emotion, the article concludes with recommendations to bridge research for different offender groups, including psychopathy and APD.

An electronegativity-induced spin repulsion effect.

PubMed

Stirling, Andras; Pasquarello, Alfredo

2005-09-22

We present a spin delocalization effect in radical Si-containing systems, featuring a heteroatom of high electronegativity (such as N, O, or Cl) bonded to the unsaturated Si atom. We find that the higher the electronegativity of the heteroatom, the more the localized spin shifts away from the unsaturated Si atom and the heteroatom toward saturated Si neighbors. We demonstrate that this spin repulsion toward saturated Si atoms is induced by the electronegativity difference between the Si atom and the heteroatoms. We present a simple molecular-orbital-based mechanism which fully explains the structural and electronic effects. We contrast the present spin delocalization mechanism with the classical hyperconjugation in organic chemistry. The most important consequences of this spin redistribution are the electron-spin-resonance activity of the saturated Si neighbors and the enhanced stability of the radical centers. We predict a similar effect for Ge radicals and discuss why organic systems based on carbon do not feature such spin repulsion.

Target templates: the precision of mental representations affects attentional guidance and decision-making in visual search

PubMed Central

Hout, Michael C.; Goldinger, Stephen D.

2014-01-01

When people look for things in the environment, they use target templates—mental representations of the objects they are attempting to locate—to guide attention and to assess incoming visual input as potential targets. However, unlike laboratory participants, searchers in the real world rarely have perfect knowledge regarding the potential appearance of targets. In seven experiments, we examined how the precision of target templates affects the ability to conduct visual search. Specifically, we degraded template precision in two ways: 1) by contaminating searchers’ templates with inaccurate features, and 2) by introducing extraneous features to the template that were unhelpful. We recorded eye movements to allow inferences regarding the relative extents to which attentional guidance and decision-making are hindered by template imprecision. Our findings support a dual-function theory of the target template and highlight the importance of examining template precision in visual search. PMID:25214306

Histopathological study of the mite biting (Dermanyssus gallinae) in poultry skin

PubMed Central

Hobbenaghi, Rahim; Tavassoli, Mousa; Alimehr, Manochehr; Shokrpoor, Sara; Ghorbanzadeghan, Mohammad

2012-01-01

The red mite of poultry, Dremanyssus gallinae, is the most important hematophagous ectoparasite of poultry. In this study, pathologic changes of its biting on the poultry skin have been investigated. Thirty-two (Control = 16 and Treatment = 16) four weeks old Ross broilers (308) were infested with the mite on skin of hock joins. Samples were collected after 1, 24, 72 hours and 10 days. The skin samples were fixed in 10% buffered formalin and histological sections were prepared using routine Hematoxylin & Eosin staining method. Results showed that in all cases, except within first hour of infestation, lymphocytic infiltration was always a constant pathologic feature. Necrosis of feather's follicles was a prominent pathologic feature ensued due to vascular disturbances and resulted in loss of feather. Hyperkeratosis, parakeratosis and acanthosis were observed after 72 hours. These findings reveal that mite biting induces local epidermal hyperplasia. PMID:25610570

Histopathological study of the mite biting (Dermanyssus gallinae) in poultry skin.

PubMed

Hobbenaghi, Rahim; Tavassoli, Mousa; Alimehr, Manochehr; Shokrpoor, Sara; Ghorbanzadeghan, Mohammad

2012-01-01

The red mite of poultry, Dremanyssus gallinae, is the most important hematophagous ectoparasite of poultry. In this study, pathologic changes of its biting on the poultry skin have been investigated. Thirty-two (Control = 16 and Treatment = 16) four weeks old Ross broilers (308) were infested with the mite on skin of hock joins. Samples were collected after 1, 24, 72 hours and 10 days. The skin samples were fixed in 10% buffered formalin and histological sections were prepared using routine Hematoxylin & Eosin staining method. Results showed that in all cases, except within first hour of infestation, lymphocytic infiltration was always a constant pathologic feature. Necrosis of feather's follicles was a prominent pathologic feature ensued due to vascular disturbances and resulted in loss of feather. Hyperkeratosis, parakeratosis and acanthosis were observed after 72 hours. These findings reveal that mite biting induces local epidermal hyperplasia.

Flying Insect Detection and Classification with Inexpensive Sensors

PubMed Central

Chen, Yanping; Why, Adena; Batista, Gustavo; Mafra-Neto, Agenor; Keogh, Eamonn

2014-01-01

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered. PMID:25350921

Quality Perception of the 2012 World Indoor Athletics Championships

PubMed Central

2016-01-01

Abstract The objective of this study was to compare the views of spectators concerning the quality perception of the World Indoor Athletics Championships. The study group consisted of 568 spectators who watched the events. A measurement scale of event quality in spectator sports (SEQSS) developed by Ko et al. (2011) was used as a data collection tool in the study. In order to determine the views of the spectators concerning the quality of the Indoor Athletics Championships, the dimensions constituting the scale were compared according to the demographic features of the sample group. As a consequence, important differences in most of the dimensions of the scale were revealed with respect to the demographic data of the subjects. The most relevant finding of the study is that the dimension of “physical environment quality”, which is one of the dimensions constituting the event quality, differed significantly in all comparisons that were made according to demographic features. PMID:28031769