Sparse Zero-Sum Games as Stable Functional Feature Selection

PubMed Central

Sokolovska, Nataliya; Teytaud, Olivier; Rizkalla, Salwa; Clément, Karine; Zucker, Jean-Daniel

2015-01-01

In large-scale systems biology applications, features are structured in hidden functional categories whose predictive power is identical. Feature selection, therefore, can lead not only to a problem with a reduced dimensionality, but also reveal some knowledge on functional classes of variables. In this contribution, we propose a framework based on a sparse zero-sum game which performs a stable functional feature selection. In particular, the approach is based on feature subsets ranking by a thresholding stochastic bandit. We provide a theoretical analysis of the introduced algorithm. We illustrate by experiments on both synthetic and real complex data that the proposed method is competitive from the predictive and stability viewpoints. PMID:26325268

Features of resilience

DOE PAGES

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; ...

2017-02-20

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. As a result, the proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Features of resilience

USGS Publications Warehouse

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; Palma-Oliveira, José M.; Woods, David D.; Linkov, Igor

2017-01-01

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. The proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Analyzing key ecological functions for transboundary subbasin assessments.

Treesearch

B.G Marcot; T.A. O' Neil; J.B. Nyberg; A. MacKinnon; P.J. Paquet; D.H. Johnson

2007-01-01

We present an evaluation of the ecological roles ("key ecological functions" or KEFs) of 618 wildlife species as one facet of subbasin assessment in the Columbia River basin (CRB) of the United States and Canada. Using a wildlife-habitat relationships database (IBIS) and geographic information system, we have mapped KEFs as levels of functional redundancy (...

A more secure parallel keyed hash function based on chaotic neural network

NASA Astrophysics Data System (ADS)

Huang, Zhongquan

2011-08-01

Although various hash functions based on chaos or chaotic neural network were proposed, most of them can not work efficiently in parallel computing environment. Recently, an algorithm for parallel keyed hash function construction based on chaotic neural network was proposed [13]. However, there is a strict limitation in this scheme that its secret keys must be nonce numbers. In other words, if the keys are used more than once in this scheme, there will be some potential security flaw. In this paper, we analyze the cause of vulnerability of the original one in detail, and then propose the corresponding enhancement measures, which can remove the limitation on the secret keys. Theoretical analysis and computer simulation indicate that the modified hash function is more secure and practical than the original one. At the same time, it can keep the parallel merit and satisfy the other performance requirements of hash function, such as good statistical properties, high message and key sensitivity, and strong collision resistance, etc.

Protecting Cryptographic Keys and Functions from Malware Attacks

DTIC Science & Technology

2010-12-01

registers. modifies RSA private key signing in OpenSSL to use the technique. The resulting system has the following features: 1. No special hardware is...the above method based on OpenSSL , by exploiting the Streaming SIMD Extension (SSE) XMM registers of modern Intel and AMD x86-compatible CPU’s [22...one can store a 2048-bit exponent.1 Our prototype is based on OpenSSL 0.9.8e, the Ubuntu 6.06 Linux distribution with a 2.6.15 kernel, and SSE2 which

Audio feature extraction using probability distribution function

NASA Astrophysics Data System (ADS)

Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

2015-05-01

Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.

Identifying Key Features of Student Performance in Educational Video Games and Simulations through Cluster Analysis

ERIC Educational Resources Information Center

Kerr, Deirdre; Chung, Gregory K. W. K.

2012-01-01

The assessment cycle of "evidence-centered design" (ECD) provides a framework for treating an educational video game or simulation as an assessment. One of the main steps in the assessment cycle of ECD is the identification of the key features of student performance. While this process is relatively simple for multiple choice tests, when…

A method for data‐driven exploration to pinpoint key features in medical data and facilitate expert review

PubMed Central

Juhlin, Kristina; Norén, G. Niklas

2017-01-01

Abstract Purpose To develop a method for data‐driven exploration in pharmacovigilance and illustrate its use by identifying the key features of individual case safety reports related to medication errors. Methods We propose vigiPoint, a method that contrasts the relative frequency of covariate values in a data subset of interest to those within one or more comparators, utilizing odds ratios with adaptive statistical shrinkage. Nested analyses identify higher order patterns, and permutation analysis is employed to protect against chance findings. For illustration, a total of 164 000 adverse event reports related to medication errors were characterized and contrasted to the other 7 833 000 reports in VigiBase, the WHO global database of individual case safety reports, as of May 2013. The initial scope included 2000 features, such as patient age groups, reporter qualifications, and countries of origin. Results vigiPoint highlighted 109 key features of medication error reports. The most prominent were that the vast majority of medication error reports were from the United States (89% compared with 49% for other reports in VigiBase); that the majority of reports were sent by consumers (53% vs 17% for other reports); that pharmacists (12% vs 5.3%) and lawyers (2.9% vs 1.5%) were overrepresented; and that there were more medication error reports than expected for patients aged 2‐11 years (10% vs 5.7%), particularly in Germany (16%). Conclusions vigiPoint effectively identified key features of medication error reports in VigiBase. More generally, it reduces lead times for analysis and ensures reproducibility and transparency. An important next step is to evaluate its use in other data. PMID:28815800

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

PubMed

Ravishankar, Hariharan; Madhavan, Radhika; Mullick, Rakesh; Shetty, Teena; Marinelli, Luca; Joel, Suresh E

2016-08-01

Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity. We propose a machine-learning approach to down-select functional connectivity features associated with symptom severity in mild traumatic brain injury (mTBI). Using this approach, we identified functional regions with altered connectivity in mTBI. including the executive control, visual and precuneus networks. We compared functional connections at multiple resolutions to determine which scale would be more sensitive to changes related to patient recovery. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

Interpersonal Features and Functions of Nonsuicidal Self-Injury

ERIC Educational Resources Information Center

Muehlenkamp, Jennifer; Brausch, Amy; Quigley, Katherine; Whitlock, Janis

2013-01-01

Etiological models of nonsuicidal self-injury (NSSI) suggest interpersonal features may be important to understand this behavior, but social functions and correlates have not been extensively studied. This study addresses existing limitations by examining interpersonal correlates and functions of NSSI within a stratified random sample of 1,243…

Infants' Developing Sensitivity to Object Function: Attention to Features and Feature Correlations

ERIC Educational Resources Information Center

Baumgartner, Heidi A.; Oakes, Lisa M.

2011-01-01

When learning object function, infants must detect relations among features--for example, that squeezing is associated with squeaking or that objects with wheels roll. Previously, Perone and Oakes (2006) found 10-month-old infants were sensitive to relations between object appearances and actions, but not to relations between appearances and…

Key Generation for Fast Inversion of the Paillier Encryption Function

NASA Astrophysics Data System (ADS)

Hirano, Takato; Tanaka, Keisuke

We study fast inversion of the Paillier encryption function. Especially, we focus only on key generation, and do not modify the Paillier encryption function. We propose three key generation algorithms based on the speeding-up techniques for the RSA encryption function. By using our algorithms, the size of the private CRT exponent is half of that of Paillier-CRT. The first algorithm employs the extended Euclidean algorithm. The second algorithm employs factoring algorithms, and can construct the private CRT exponent with low Hamming weight. The third algorithm is a variant of the second one, and has some advantage such as compression of the private CRT exponent and no requirement for factoring algorithms. We also propose the settings of the parameters for these algorithms and analyze the security of the Paillier encryption function by these algorithms against known attacks. Finally, we give experimental results of our algorithms.

Mapping genomic features to functional traits through microbial whole genome sequences.

PubMed

Zhang, Wei; Zeng, Erliang; Liu, Dan; Jones, Stuart E; Emrich, Scott

2014-01-01

Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities.

PubMed

Narayanasamy, Shaman; Muller, Emilie E L; Sheik, Abdul R; Wilmes, Paul

2015-05-01

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single 'omes'. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure-function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

Key Data on Education in Europe 2009

ERIC Educational Resources Information Center

Ranguelov, Stanislav; de Coster, Isabelle; Forsthuber, Bernadette; Noorani, Sogol; Ruffio, Philippe

2009-01-01

This seventh edition of "Key Data on Education in Europe" retains its main special feature which is the combination of statistical data and qualitative information to describe the organisation and functioning of education systems in Europe. The present 2009 edition maintains the subject-based structure defined by the previous one but…

Crafting your Elevator Pitch: Key Features of an Elevator Speech to Help You Reach the Top Floor

EPA Science Inventory

You never know when you will end up talking to someone who will end up helping to shape your career. Many of these chance meetings are brief and when you only get 2-3 minutes to make your case everything that you say has to count. This presentation will cover the key features o...

From big data to rich data: The key features of athlete wheelchair mobility performance.

PubMed

van der Slikke, R M A; Berger, M A M; Bregman, D J J; Veeger, H E J

2016-10-03

Quantitative assessment of an athlete׳s individual wheelchair mobility performance is one prerequisite needed to evaluate game performance, improve wheelchair settings and optimize training routines. Inertial Measurement Unit (IMU) based methods can be used to perform such quantitative assessment, providing a large number of kinematic data. The goal of this research was to reduce that large amount of data to a set of key features best describing wheelchair mobility performance in match play and present them in meaningful way for both scientists and athletes. To test the discriminative power, wheelchair mobility characteristics of athletes with different performance levels were compared. The wheelchair kinematics of 29 (inter-)national level athletes were measured during a match using three inertial sensors mounted on the wheelchair. Principal component analysis was used to reduce 22 kinematic outcomes to a set of six outcomes regarding linear and rotational movement; speed and acceleration; average and best performance. In addition, it was explored whether groups of athletes with known performance differences based on their impairment classification also differed with respect to these key outcomes using univariate general linear models. For all six key outcomes classification showed to be a significant factor (p<0.05). We composed a set of six key kinematic outcomes that accurately describe wheelchair mobility performance in match play. The key kinematic outcomes were displayed in an easy to interpret way, usable for athletes, coaches and scientists. This standardized representation enables comparison of different wheelchair sports regarding wheelchair mobility, but also evaluation at the level of an individual athlete. By this means, the tool could enhance further development of wheelchair sports in general. Copyright © 2016 Elsevier Ltd. All rights reserved.

Turboelectric Aircraft Drive Key Performance Parameters and Functional Requirements

NASA Technical Reports Server (NTRS)

Jansen, Ralph H.; Brown, Gerald V.; Felder, James L.; Duffy, Kirsten P.

2016-01-01

The purpose of this paper is to propose specific power and efficiency as the key performance parameters for a turboelectric aircraft power system and investigate their impact on the overall aircraft. Key functional requirements are identified that impact the power system design. Breguet range equations for a base aircraft and a turboelectric aircraft are found. The benefits and costs that may result from the turboelectric system are enumerated. A break-even analysis is conducted to find the minimum allowable electric drive specific power and efficiency that can preserve the range, initial weight, operating empty weight, and payload weight of the base aircraft.

Turboelectric Aircraft Drive Key Performance Parameters and Functional Requirements

NASA Technical Reports Server (NTRS)

Jansen, Ralph; Brown, Gerald V.; Felder, James L.; Duffy, Kirsten P.

2015-01-01

The purpose of this presentation is to propose specific power and efficiency as the key performance parameters for a turboelectric aircraft power system and investigate their impact on the overall aircraft. Key functional requirements are identified that impact the power system design. Breguet range equations for a base aircraft and a turboelectric aircraft are found. The benefits and costs that may result from the turboelectric system are enumerated. A break-even analysis is conducted to find the minimum allowable electric drive specific power and efficiency that can preserve the range, initial weight, operating empty weight, and payload weight of the base aircraft.

Turboelectric Aircraft Drive Key Performance Parameters and Functional Requirements

NASA Technical Reports Server (NTRS)

Jansen, Ralph H.; Brown, Gerald V.; Felder, James L.; Duffy, Kirsten P.

2015-01-01

The purpose of this paper is to propose specific power and efficiency as the key performance parameters for a turboelectric aircraft power system and investigate their impact on the overall aircraft. Key functional requirements are identified that impact the power system design. Breguet range equations for a base aircraft and a turboelectric aircraft are found. The benefits and costs that may result from the turboelectric system are enumerated. A break-even analysis is conducted to find the minimum allowable electric drive specific power and efficiency that can preserve the range, initial weight, operating empty weight, and payload weight of the base aircraft.

Improving Latino Children's Early Language and Literacy Development: Key Features of Early Childhood Education within Family Literacy Programmes

ERIC Educational Resources Information Center

Jung, Youngok; Zuniga, Stephen; Howes, Carollee; Jeon, Hyun-Joo; Parrish, Deborah; Quick, Heather; Manship, Karen; Hauser, Alison

2016-01-01

Noting the lack of research on how early childhood education (ECE) programmes within family literacy programmes influence Latino children's early language and literacy development, this study examined key features of ECE programmes, specifically teacher-child interactions and child engagement in language and literacy activities and how these…

Cycling hypoxia: A key feature of the tumor microenvironment.

PubMed

Michiels, Carine; Tellier, Céline; Feron, Olivier

2016-08-01

A compelling body of evidence indicates that most human solid tumors contain hypoxic areas. Hypoxia is the consequence not only of the chaotic proliferation of cancer cells that places them at distance from the nearest capillary but also of the abnormal structure of the new vasculature network resulting in transient blood flow. Hence two types of hypoxia are observed in tumors: chronic and cycling (intermittent) hypoxia. Most of the current work aims at understanding the role of chronic hypoxia in tumor growth, response to treatment and metastasis. Only recently, cycling hypoxia, with spatial and temporal fluctuations in oxygen levels, has emerged as another key feature of the tumor environment that triggers different responses in comparison to chronic hypoxia. Either type of hypoxia is associated with distinct effects not only in cancer cells but also in stromal cells. In particular, cycling hypoxia has been demonstrated to favor, to a higher extent than chronic hypoxia, angiogenesis, resistance to anti-cancer treatments, intratumoral inflammation and tumor metastasis. These review details these effects as well as the signaling pathway it triggers to switch on specific transcriptomic programs. Understanding the signaling pathways through which cycling hypoxia induces these processes that support the development of an aggressive cancer could convey to the emergence of promising new cancer treatments. Copyright © 2016 Elsevier B.V. All rights reserved.

Quick Survey of Smartphone Features and Functions

PubMed Central

Fox, Brent I.; Felkey, Bill G.

2014-01-01

What do you do when you leave the house without your smartphone? Do you sleep with it beside your bed? For us, these devices are as much a part of our lives as the belts around our waists. But, how long has it been since you surveyed the market? We provide a topical update on the current features and functions of these immensely important devices. PMID:24958977

Secure image retrieval with multiple keys

NASA Astrophysics Data System (ADS)

Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

2018-03-01

This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

The Abnormal vs. Normal ECG Classification Based on Key Features and Statistical Learning

NASA Astrophysics Data System (ADS)

Dong, Jun; Tong, Jia-Fei; Liu, Xia

As cardiovascular diseases appear frequently in modern society, the medicine and health system should be adjusted to meet the new requirements. Chinese government has planned to establish basic community medical insurance system (BCMIS) before 2020, where remote medical service is one of core issues. Therefore, we have developed the "remote network hospital system" which includes data server and diagnosis terminal by the aid of wireless detector to sample ECG. To improve the efficiency of ECG processing, in this paper, abnormal vs. normal ECG classification approach based on key features and statistical learning is presented, and the results are analyzed. Large amount of normal ECG could be filtered by computer automatically and abnormal ECG is left to be diagnosed specially by physicians.

Cationic PAMAM dendrimers disrupt key platelet functions

PubMed Central

Jones, Clinton F.; Campbell, Robert A.; Franks, Zechariah; Gibson, Christopher C.; Thiagarajan, Giridhar; Vieira-de-Abreu, Adriana; Sukavaneshvar, Sivaprasad; Mohammad, S. Fazal; Li, Dean Y.; Ghandehari, Hamidreza; Weyrich, Andrew S.; Brooks, Benjamin D.; Grainger, David W.

2012-01-01

Poly(amidoamine) (PAMAM) dendrimers have been proposed for a variety of biomedical applications and are increasingly studied as model nanomaterials for such use. The dendritic structure features both modular synthetic control of molecular size and shape and presentation of multiple equivalent terminal groups. These properties make PAMAM dendrimers highly functionalizable, versatile single-molecule nanoparticles with a high degree of consistency and low polydispersity. Recent nanotoxicological studies showed that intravenous administration of amine-terminated PAMAM dendrimers to mice was lethal, causing a disseminated intravascular coagulation-like condition. To elucidate the mechanisms underlying this coagulopathy, in vitro assessments of platelet functions in contact with PAMAM dendrimers were undertaken. This study demonstrates that cationic G7 PAMAM dendrimers activate platelets and dramatically alter their morphology. These changes to platelet morphology and activation state substantially altered platelet function, including increased aggregation and adherence to surfaces. Surprisingly, dendrimer exposure also attenuated platelet-dependent thrombin generation, indicating that not all platelet functions remained intact. These findings provide additional insight into PAMAM dendrimer effects on blood components and underscore the necessity for further research on the effects and mechanisms of PAMAM-specific and general nanoparticle toxicity in blood. PMID:22497592

Protein functional features are reflected in the patterns of mRNA translation speed.

PubMed

López, Daniel; Pazos, Florencio

2015-07-09

The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.

Key Features of High-Quality Policies and Guidelines to Support Social and Emotional Learning: Recommendations and Examples for the Collaborating States Initiative (CSI)

ERIC Educational Resources Information Center

Dusenbury, Linda; Yoder, Nick

2017-01-01

The current document serves two purposes. First, it provides an overview of six key features of a high-quality, comprehensive package of policies and guidance to support student social and emotional learning (SEL). These features are based on Collaborative for Academic Social, and Emotional Learning's (CASEL's) review of the research literature on…

Work Keys USA.

ERIC Educational Resources Information Center

Work Keys USA, 1998

1998-01-01

"Work Keys" is a comprehensive program for assessing and teaching workplace skills. This serial "special issue" features 18 first-hand reports on Work Keys projects in action in states across North America. They show how the Work Keys is helping businesses and educators solve the challenge of building a world-class work force.…

Some key features in the evolution of self psychology and psychoanalysis.

PubMed

Fosshage, James L

2009-04-01

Psychoanalysis, as every science and its application, has continued to evolve over the past century, especially accelerating over the last 30 years. Self psychology has played a constitutive role in that evolution and has continued to change itself. These movements have been supported and augmented by a wide range of emergent research and theory, especially that of cognitive psychology, infant and attachment research, rapid eye movement and dream research, psychotherapy research, and neuroscience. I present schematically some of what I consider to be the key features of the evolution of self psychology and their interconnection with that of psychoanalysis at large, including the revolutionary paradigm changes, the new epistemology, listening/experiencing perspectives, from narcissism to the development of the self, the new organization model of transference, the new organization model of dreams, and the implicit and explicit dimensions of analytic work. I conclude with a focus on the radical ongoing extension of the analyst's participation in the analytic relationship, using, as an example, the co-creation of analytic love, and providing several brief clinical illustrations. The leading edge question guiding my discussion is "How does analytic change occur?"

Key Features Of Peer Support In Chronic Disease Prevention And Management.

PubMed

Fisher, Edwin B; Ballesteros, Juana; Bhushan, Nivedita; Coufal, Muchieh M; Kowitt, Sarah D; McDonough, A Manuela; Parada, Humberto; Robinette, Jennifer B; Sokol, Rebeccah L; Tang, Patrick Y; Urlaub, Diana

2015-09-01

Peer support from community health workers, promotores de salud, and others through community and health care organizations can provide social support and other assistance that enhances health. There is substantial evidence for both the effectiveness and the cost-effectiveness of peer support, as well as for its feasibility, reach, and sustainability. We discuss findings from Peers for Progress, a program of the American Academy of Family Physicians Foundation, to examine when peer support does not work, guide dissemination of peer support programs, and help integrate approaches such as e-health into peer support. Success factors for peer support programs include proactive implementation, attention to participants' emotions, and ongoing supervision. Reaching those whom conventional clinical and preventive services too often fail to reach; reaching whole populations, such as people with diabetes, rather than selected samples; and addressing behavioral health are strengths of peer support that can help achieve health care that is efficient and of high quality. Challenges for policy makers going forward include encouraging workforce development, balancing quality control with maintaining key features of peer support, and ensuring that underresourced organizations can develop and manage peer support programs. Project HOPE—The People-to-People Health Foundation, Inc.

Movement of feeder-using songbirds: the influence of urban features.

PubMed

Cox, Daniel T C; Inger, Richard; Hancock, Steven; Anderson, Karen; Gaston, Kevin J

2016-11-23

Private gardens provide vital opportunities for people to interact with nature. The most popular form of interaction is through garden bird feeding. Understanding how landscape features and seasons determine patterns of movement of feeder-using songbirds is key to maximising the well-being benefits they provide. To determine these patterns we established three networks of automated data loggers along a gradient of greenspace fragmentation. Over a 12-month period we tracked 452 tagged blue tits Cyantistes caeruleus and great tits Parus major moving between feeder pairs 9,848 times, to address two questions: (i) Do urban features within different forms, and season, influence structural (presence-absence of connections between feeders by birds) and functional (frequency of these connections) connectivity? (ii) Are there general patterns of structural and functional connectivity across forms? Vegetation cover increased connectivity in all three networks, whereas the presence of road gaps negatively affected functional but not structural connectivity. Across networks structural connectivity was lowest in the summer when birds maintain breeding territories, however patterns of functional connectivity appeared to vary with habitat fragmentation. Using empirical data this study shows how key urban features and season influence movement of feeder-using songbirds, and we provide evidence that this is related to greenspace fragmentation.

featsel: A framework for benchmarking of feature selection algorithms and cost functions

NASA Astrophysics Data System (ADS)

Reis, Marcelo S.; Estrela, Gustavo; Ferreira, Carlos Eduardo; Barrera, Junior

In this paper, we introduce featsel, a framework for benchmarking of feature selection algorithms and cost functions. This framework allows the user to deal with the search space as a Boolean lattice and has its core coded in C++ for computational efficiency purposes. Moreover, featsel includes Perl scripts to add new algorithms and/or cost functions, generate random instances, plot graphs and organize results into tables. Besides, this framework already comes with dozens of algorithms and cost functions for benchmarking experiments. We also provide illustrative examples, in which featsel outperforms the popular Weka workbench in feature selection procedures on data sets from the UCI Machine Learning Repository.

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency.

PubMed

Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C; Zhou, Changsong

2017-09-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory

PubMed Central

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding. PMID:24917833

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory.

PubMed

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding.

Key structural features of nonsteroidal ligands for binding and activation of the androgen receptor.

PubMed

Yin, Donghua; He, Yali; Perera, Minoli A; Hong, Seoung Soo; Marhefka, Craig; Stourman, Nina; Kirkovsky, Leonid; Miller, Duane D; Dalton, James T

2003-01-01

The purposes of the present studies were to examine the androgen receptor (AR) binding ability and in vitro functional activity of multiple series of nonsteroidal compounds derived from known antiandrogen pharmacophores and to investigate the structure-activity relationships (SARs) of these nonsteroidal compounds. The AR binding properties of sixty-five nonsteroidal compounds were assessed by a radioligand competitive binding assay with the use of cytosolic AR prepared from rat prostates. The AR agonist and antagonist activities of high-affinity ligands were determined by the ability of the ligand to regulate AR-mediated transcriptional activation in cultured CV-1 cells, using a cotransfection assay. Nonsteroidal compounds with diverse structural features demonstrated a wide range of binding affinity for the AR. Ten compounds, mainly from the bicalutamide-related series, showed a binding affinity superior to the structural pharmacophore from which they were derived. Several SARs regarding nonsteroidal AR binding were revealed from the binding data, including stereoisomeric conformation, steric effect, and electronic effect. The functional activity of high-affinity ligands ranged from antagonist to full agonist for the AR. Several structural features were found to be determinative of agonist and antagonist activities. The nonsteroidal AR agonists identified from the present studies provided a pool of candidates for further development of selective androgen receptor modulators (SARMs) for androgen therapy. Also, these studies uncovered or confirmed numerous important SARs governing AR binding and functional properties by nonsteroidal molecules, which would be valuable in the future structural optimization of SARMs.

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.

Functional Brain Connectivity as a New Feature for P300 Speller.

PubMed

Kabbara, Aya; Khalil, Mohamad; El-Falou, Wassim; Eid, Hassan; Hassan, Mahmoud

2016-01-01

The brain is a large-scale complex network often referred to as the "connectome". Cognitive functions and information processing are mainly based on the interactions between distant brain regions. However, most of the 'feature extraction' methods used in the context of Brain Computer Interface (BCI) ignored the possible functional relationships between different signals recorded from distinct brain areas. In this paper, the functional connectivity quantified by the phase locking value (PLV) was introduced to characterize the evoked responses (ERPs) obtained in the case of target and non-targets visual stimuli. We also tested the possibility of using the functional connectivity in the context of 'P300 speller'. The proposed approach was compared to the well-known methods proposed in the state of the art of "P300 Speller", mainly the peak picking, the area, time/frequency based features, the xDAWN spatial filtering and the stepwise linear discriminant analysis (SWLDA). The electroencephalographic (EEG) signals recorded from ten subjects were analyzed offline. The results indicated that phase synchrony offers relevant information for the classification in a P300 speller. High synchronization between the brain regions was clearly observed during target trials, although no significant synchronization was detected for a non-target trial. The results showed also that phase synchrony provides higher performance than some existing methods for letter classification in a P300 speller principally when large number of trials is available. Finally, we tested the possible combination of both approaches (classical features and phase synchrony). Our findings showed an overall improvement of the performance of the P300-speller when using Peak picking, the area and frequency based features. Similar performances were obtained compared to xDAWN and SWLDA when using large number of trials.

A step towards considering the spatial heterogeneity of urban key features in urban hydrology flood modelling

NASA Astrophysics Data System (ADS)

Leandro, J.; Schumann, A.; Pfister, A.

2016-04-01

Some of the major challenges in modelling rainfall-runoff in urbanised areas are the complex interaction between the sewer system and the overland surface, and the spatial heterogeneity of the urban key features. The former requires the sewer network and the system of surface flow paths to be solved simultaneously. The latter is still an unresolved issue because the heterogeneity of runoff formation requires high detailed information and includes a large variety of feature specific rainfall-runoff dynamics. This paper discloses a methodology for considering the variability of building types and the spatial heterogeneity of land surfaces. The former is achieved by developing a specific conceptual rainfall-runoff model and the latter by defining a fully distributed approach for infiltration processes in urban areas with limited storage capacity dependent on OpenStreetMaps (OSM). The model complexity is increased stepwise by adding components to an existing 2D overland flow model. The different steps are defined as modelling levels. The methodology is applied in a German case study. Results highlight that: (a) spatial heterogeneity of urban features has a medium to high impact on the estimated overland flood-depths, (b) the addition of multiple urban features have a higher cumulative effect due to the dynamic effects simulated by the model, (c) connecting the runoff from buildings to the sewer contributes to the non-linear effects observed on the overland flood-depths, and (d) OSM data is useful in identifying pounding areas (for which infiltration plays a decisive role) and permeable natural surface flow paths (which delay the flood propagation).

Functional mechanisms of probabilistic inference in feature- and space-based attentional systems.

PubMed

Dombert, Pascasie L; Kuhns, Anna; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2016-11-15

Humans flexibly attend to features or locations and these processes are influenced by the probability of sensory events. We combined computational modeling of response times with fMRI to compare the functional correlates of (re-)orienting, and the modulation by probabilistic inference in spatial and feature-based attention systems. Twenty-four volunteers performed two task versions with spatial or color cues. Percentage of cue validity changed unpredictably. A hierarchical Bayesian model was used to derive trial-wise estimates of probability-dependent attention, entering the fMRI analysis as parametric regressors. Attentional orienting activated a dorsal frontoparietal network in both tasks, without significant parametric modulation. Spatially invalid trials activated a bilateral frontoparietal network and the precuneus, while invalid feature trials activated the left intraparietal sulcus (IPS). Probability-dependent attention modulated activity in the precuneus, left posterior IPS, middle occipital gyrus, and right temporoparietal junction for spatial attention, and in the left anterior IPS for feature-based and spatial attention. These findings provide novel insights into the generality and specificity of the functional basis of attentional control. They suggest that probabilistic inference can distinctively affect each attentional subsystem, but that there is an overlap in the left IPS, which responds to both spatial and feature-based expectancy violations. Copyright © 2016 Elsevier Inc. All rights reserved.

Hepatic Inflammation and Fibrosis: Functional Links and Key Pathways

PubMed Central

Seki, Ekihiro; Schwabe, Robert F.

2014-01-01

Inflammation is one of the most characteristic features of chronic liver disease of viral, alcoholic, fatty and autoimmune origin. Inflammation is typically present in all disease stages, and associated with the development of fibrosis, cirrhosis and hepatocellular carcinoma. In the past decade, numerous studies have contributed to improved understanding of the links between hepatic inflammation and fibrosis. Here, we review mechanisms that link inflammation with the development of liver fibrosis, focusing on the role of inflammatory mediators in hepatic stellate cell (HSC) activation and HSC survival during fibrogenesis and fibrosis regression. We will summarize the contributions of different inflammatory cells, including hepatic macrophages, T- and B-lymphocytes, NK cells and platelets, as well as key effectors such as cytokines, chemokines, and damage-associated molecular patterns. Furthermore, we will discuss the relevance of inflammatory signaling pathways for clinical liver disease and for the development of anti-fibrogenic strategies. PMID:25066777

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency

PubMed Central

Chen, Yuhan; Wang, Shengjun

2017-01-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may

Machine fault feature extraction based on intrinsic mode functions

NASA Astrophysics Data System (ADS)

Fan, Xianfeng; Zuo, Ming J.

2008-04-01

This work employs empirical mode decomposition (EMD) to decompose raw vibration signals into intrinsic mode functions (IMFs) that represent the oscillatory modes generated by the components that make up the mechanical systems generating the vibration signals. The motivation here is to develop vibration signal analysis programs that are self-adaptive and that can detect machine faults at the earliest onset of deterioration. The change in velocity of the amplitude of some IMFs over a particular unit time will increase when the vibration is stimulated by a component fault. Therefore, the amplitude acceleration energy in the intrinsic mode functions is proposed as an indicator of the impulsive features that are often associated with mechanical component faults. The periodicity of the amplitude acceleration energy for each IMF is extracted by spectrum analysis. A spectrum amplitude index is introduced as a method to select the optimal result. A comparison study of the method proposed here and some well-established techniques for detecting machinery faults is conducted through the analysis of both gear and bearing vibration signals. The results indicate that the proposed method has superior capability to extract machine fault features from vibration signals.

Extracting intrinsic functional networks with feature-based group independent component analysis.

PubMed

Calhoun, Vince D; Allen, Elena

2013-04-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro

Summary of the key features of seven biomathematical models of human fatigue and performance.

PubMed

Mallis, Melissa M; Mejdal, Sig; Nguyen, Tammy T; Dinges, David F

2004-03-01

Biomathematical models that quantify the effects of circadian and sleep/wake processes on the regulation of alertness and performance have been developed in an effort to predict the magnitude and timing of fatigue-related responses in a variety of contexts (e.g., transmeridian travel, sustained operations, shift work). This paper summarizes key features of seven biomathematical models reviewed as part of the Fatigue and Performance Modeling Workshop held in Seattle, WA, on June 13-14, 2002. The Workshop was jointly sponsored by the National Aeronautics and Space Administration, U.S. Department of Defense, U.S. Army Medical Research and Materiel Command, Office of Naval Research, Air Force Office of Scientific Research, and U.S. Department of Transportation. An invitation was sent to developers of seven biomathematical models that were commonly cited in scientific literature and/or supported by government funding. On acceptance of the invitation to attend the Workshop, developers were asked to complete a survey of the goals, capabilities, inputs, and outputs of their biomathematical models of alertness and performance. Data from the completed surveys were summarized and juxtaposed to provide a framework for comparing features of the seven models. Survey responses revealed that models varied greatly relative to their reported goals and capabilities. While all modelers reported that circadian factors were key components of their capabilities, they differed markedly with regard to the roles of sleep and work times as input factors for prediction: four of the seven models had work time as their sole input variable(s), while the other three models relied on various aspects of sleep timing for model input. Models also differed relative to outputs: five sought to predict results from laboratory experiments, field, and operational data, while two models were developed without regard to predicting laboratory experimental results. All modelers provided published papers

Summary of the key features of seven biomathematical models of human fatigue and performance

NASA Technical Reports Server (NTRS)

Mallis, Melissa M.; Mejdal, Sig; Nguyen, Tammy T.; Dinges, David F.

2004-01-01

BACKGROUND: Biomathematical models that quantify the effects of circadian and sleep/wake processes on the regulation of alertness and performance have been developed in an effort to predict the magnitude and timing of fatigue-related responses in a variety of contexts (e.g., transmeridian travel, sustained operations, shift work). This paper summarizes key features of seven biomathematical models reviewed as part of the Fatigue and Performance Modeling Workshop held in Seattle, WA, on June 13-14, 2002. The Workshop was jointly sponsored by the National Aeronautics and Space Administration, U.S. Department of Defense, U.S. Army Medical Research and Materiel Command, Office of Naval Research, Air Force Office of Scientific Research, and U.S. Department of Transportation. METHODS: An invitation was sent to developers of seven biomathematical models that were commonly cited in scientific literature and/or supported by government funding. On acceptance of the invitation to attend the Workshop, developers were asked to complete a survey of the goals, capabilities, inputs, and outputs of their biomathematical models of alertness and performance. Data from the completed surveys were summarized and juxtaposed to provide a framework for comparing features of the seven models. RESULTS: Survey responses revealed that models varied greatly relative to their reported goals and capabilities. While all modelers reported that circadian factors were key components of their capabilities, they differed markedly with regard to the roles of sleep and work times as input factors for prediction: four of the seven models had work time as their sole input variable(s), while the other three models relied on various aspects of sleep timing for model input. Models also differed relative to outputs: five sought to predict results from laboratory experiments, field, and operational data, while two models were developed without regard to predicting laboratory experimental results. All modelers

Features of polycystic ovary syndrome (PCOS) in women with functional hypothalamic amenorrhea (FHA) may be reversible with recovery of menstrual function.

PubMed

Carmina, Enrico; Fruzzetti, Franca; Lobo, Roger A

2018-04-01

Since features of polycystic ovary syndrome (PCOS) have been found to be prevalent in women with functional hypothalamic amenorrhea (FHA), we wished to determine what happens to these features after recovery of menstrual function in FHA Design: Prospective cohort study. Twenty-eight women with FHA and 30 age-matched ovulatory controls were studied. Twenty-eight women with FHA and 30 age-matched ovulatory controls were studied. We measured serum estradiol, LH, FSH, testosterone, DHEAS, anti-Mullerian hormone (AMH), body mass index, and ovarian morphology on transvaginal ultrasound. At baseline, 12 of the 28 women (43%) had increased AMH (>4.7 ng/mL), and higher testosterone and larger ovaries compared to the other 16 women with normal AMH. One year after recovery of menstrual function, in the 12 women with increased AMH, serum AMH, testosterone and ovarian size decreased, while LH and estradiol increased. At one year, only one of the 12 women in the high AMH group developed clinical features of PCOS. In the majority of women with FHA who have PCOS-like features, these features may be due to the hypothalamic state and appear to be reversible. Few women may develop clinical PCOS after recovery.

A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity

PubMed Central

Hass, Joachim; Hertäg, Loreen; Durstewitz, Daniel

2016-01-01

The prefrontal cortex is centrally involved in a wide range of cognitive functions and their impairment in psychiatric disorders. Yet, the computational principles that govern the dynamics of prefrontal neural networks, and link their physiological, biochemical and anatomical properties to cognitive functions, are not well understood. Computational models can help to bridge the gap between these different levels of description, provided they are sufficiently constrained by experimental data and capable of predicting key properties of the intact cortex. Here, we present a detailed network model of the prefrontal cortex, based on a simple computationally efficient single neuron model (simpAdEx), with all parameters derived from in vitro electrophysiological and anatomical data. Without additional tuning, this model could be shown to quantitatively reproduce a wide range of measures from in vivo electrophysiological recordings, to a degree where simulated and experimentally observed activities were statistically indistinguishable. These measures include spike train statistics, membrane potential fluctuations, local field potentials, and the transmission of transient stimulus information across layers. We further demonstrate that model predictions are robust against moderate changes in key parameters, and that synaptic heterogeneity is a crucial ingredient to the quantitative reproduction of in vivo-like electrophysiological behavior. Thus, we have produced a physiologically highly valid, in a quantitative sense, yet computationally efficient PFC network model, which helped to identify key properties underlying spike time dynamics as observed in vivo, and can be harvested for in-depth investigation of the links between physiology and cognition. PMID:27203563

Quantum key management

DOEpatents

Hughes, Richard John; Thrasher, James Thomas; Nordholt, Jane Elizabeth

2016-11-29

Innovations for quantum key management harness quantum communications to form a cryptography system within a public key infrastructure framework. In example implementations, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a Merkle signature scheme (using Winternitz one-time digital signatures or other one-time digital signatures, and Merkle hash trees) to constitute a cryptography system. More generally, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a hash-based signature scheme. This provides a secure way to identify, authenticate, verify, and exchange secret cryptographic keys. Features of the quantum key management innovations further include secure enrollment of users with a registration authority, as well as credential checking and revocation with a certificate authority, where the registration authority and/or certificate authority can be part of the same system as a trusted authority for quantum key distribution.

Feeding difficulties, a key feature of the Drosophila NDUFS4 mitochondrial disease model

PubMed Central

Foriel, Sarah; Eidhof, Ilse

2018-01-01

ABSTRACT Mitochondrial diseases are associated with a wide variety of clinical symptoms and variable degrees of severity. Patients with such diseases generally have a poor prognosis and often an early fatal disease outcome. With an incidence of 1 in 5000 live births and no curative treatments available, relevant animal models to evaluate new therapeutic regimes for mitochondrial diseases are urgently needed. By knocking down ND-18, the unique Drosophila ortholog of NDUFS4, an accessory subunit of the NADH:ubiquinone oxidoreductase (Complex I), we developed and characterized several dNDUFS4 models that recapitulate key features of mitochondrial disease. Like in humans, the dNDUFS4 KD flies display severe feeding difficulties, an aspect of mitochondrial disorders that has so far been largely ignored in animal models. The impact of this finding, and an approach to overcome it, will be discussed in the context of interpreting disease model characterization and intervention studies. This article has an associated First Person interview with the first author of the paper. PMID:29590638

Image features dependant correlation-weighting function for efficient PRNU based source camera identification.

PubMed

Tiwari, Mayank; Gupta, Bhupendra

2018-04-01

For source camera identification (SCI), photo response non-uniformity (PRNU) has been widely used as the fingerprint of the camera. The PRNU is extracted from the image by applying a de-noising filter then taking the difference between the original image and the de-noised image. However, it is observed that intensity-based features and high-frequency details (edges and texture) of the image, effect quality of the extracted PRNU. This effects correlation calculation and creates problems in SCI. For solving this problem, we propose a weighting function based on image features. We have experimentally identified image features (intensity and high-frequency contents) effect on the estimated PRNU, and then develop a weighting function which gives higher weights to image regions which give reliable PRNU and at the same point it gives comparatively less weights to the image regions which do not give reliable PRNU. Experimental results show that the proposed weighting function is able to improve the accuracy of SCI up to a great extent. Copyright © 2018 Elsevier B.V. All rights reserved.

Pericytes of the neurovascular unit: Key functions and signaling pathways

PubMed Central

Sweeney, Melanie D.; Ayyadurai, Shiva; Zlokovic, Berislav V.

2017-01-01

Pericytes are vascular mural cells embedded in the basement membrane of blood microvessels. They extend their processes along capillaries, pre-capillary arterioles, and post-capillary venules. The central nervous system (CNS) pericytes are uniquely positioned within the neurovascular unit between endothelial cells, astrocytes, and neurons. They integrate, coordinate, and process signals from their neighboring cells to generate diverse functional responses that are critical for CNS functions in health and disease including regulation of the blood-brain barrier permeability, angiogenesis, clearance of toxic metabolites, capillary hemodynamic responses, neuroinflammation, and stem cell activity. Here, we examine the key signaling pathways between pericytes and their neighboring endothelial cells, astrocytes, and neurons that control neurovascular functions. We also review the role of pericytes in different CNS disorders including rare monogenic diseases and complex neurological disorders such as Alzheimer's disease and brain tumors. Finally, we discuss directions for future studies. PMID:27227366

Predicting materials for sustainable energy sources: The key role of density functional theory

NASA Astrophysics Data System (ADS)

Galli, Giulia

Climate change and the related need for sustainable energy sources replacing fossil fuels are pressing societal problems. The development of advanced materials is widely recognized as one of the key elements for new technologies that are required to achieve a sustainable environment and provide clean and adequate energy for our planet. We discuss the key role played by Density Functional Theory, and its implementations in high performance computer codes, in understanding, predicting and designing materials for energy applications.

Text-Based Conferencing: Features vs. Functionality

ERIC Educational Resources Information Center

Anderson, Lynn; McCarthy, Cathy

2005-01-01

This report examines three text-based conferencing products: "WowBB", "Invision Power Board", and "vBulletin". Their selection was prompted by a feature-by-feature comparison of the same products on the "WowBB" website. The comparison chart painted a misleading impression of "WowBB's" features in relation to the other two products; so the…

Biological adaptations for functional features of language in the face of cultural evolution.

PubMed

Christiansen, Morten H; Reali, Florencia; Chater, Nick

2011-04-01

Although there may be no true language universals, it is nonetheless possible to discern several family resemblance patterns across the languages of the world. Recent work on the cultural evolution of language indicates the source of these patterns is unlikely to be an innate universal grammar evolved through biological adaptations for arbitrary linguistic features. Instead, it has been suggested that the patterns of resemblance emerge because language has been shaped by the brain, with individual languages representing different but partially overlapping solutions to the same set of nonlinguistic constraints. Here, we use computational simulations to investigate whether biological adaptation for functional features of language, deriving from cognitive and communicative constraints, may nonetheless be possible alongside rapid cultural evolution. Specifically, we focus on the Baldwin effect as an evolutionary mechanism by which previously learned linguistic features might become innate through natural selection across many generations of language users. The results indicate that cultural evolution of language does not necessarily prevent functional features of language from becoming genetically fixed, thus potentially providing a particularly informative source of constraints on cross-linguistic resemblance patterns.

Bile Routing Modification Reproduces Key Features of Gastric Bypass in Rat.

PubMed

Goncalves, Daisy; Barataud, Aude; De Vadder, Filipe; Vinera, Jennifer; Zitoun, Carine; Duchampt, Adeline; Mithieux, Gilles

2015-12-01

To evaluate the role of bile routing modification on the beneficial effects of gastric bypass surgery on glucose and energy metabolism. Gastric bypass surgery (GBP) promotes early improvements in glucose and energy homeostasis in obese diabetic patients. A suggested mechanism associates a decrease in hepatic glucose production to an enhanced intestinal gluconeogenesis. Moreover, plasma bile acids are elevated after GBP and bile acids are inhibitors of gluconeogenesis. In male Sprague-Dawley rats, we performed bile diversions from the bile duct to the midjejunum or the mid-ileum to match the modified bile delivery in the gut occurring in GBP. Body weight, food intake, glucose tolerance, insulin sensitivity, and food preference were analyzed. The expression of gluconeogenesis genes was evaluated in both the liver and the intestine. Bile diversions mimicking GBP promote an increase in plasma bile acids and a marked improvement in glucose control. Bile bioavailability modification is causal because a bile acid sequestrant suppresses the beneficial effects of bile diversions on glucose control. In agreement with the inhibitory role of bile acids on gluconeogenesis, bile diversions promote a blunting in hepatic glucose production, whereas intestinal gluconeogenesis is increased in the gut segments devoid of bile. In rats fed a high-fat-high-sucrose diet, bile diversions improve glucose control and dramatically decrease food intake because of an acquired disinterest in fatty food. This study shows that bile routing modification is a key mechanistic feature in the beneficial outcomes of GBP.

A nonlinear controlling function of geological features on magmatic-hydrothermal mineralization.

PubMed

Zuo, Renguang

2016-06-03

This paper reports a nonlinear controlling function of geological features on magmatic-hydrothermal mineralization, and proposes an alternative method to measure the spatial relationships between geological features and mineral deposits using multifractal singularity theory. It was observed that the greater the proximity to geological controlling features, the greater the number of mineral deposits developed, indicating a nonlinear spatial relationship between these features and mineral deposits. This phenomenon can be quantified using the relationship between the numbers of mineral deposits N(ε) of a D-dimensional set and the scale of ε. The density of mineral deposits can be expressed as ρ(ε) = Cε(-(De-a)), where ε is the buffer width of geological controlling features, De is Euclidean dimension of space (=2 in this case), a is singularity index, and C is a constant. The expression can be rewritten as ρ = Cε(a-2). When a < 2, there is a significant spatial correlation between specific geological features and mineral deposits; lower a values indicate a more significant spatial correlation. This nonlinear relationship and the advantages of this method were illustrated using a case study from Fujian Province in China and a case study from Baguio district in Philippines.

A nonlinear controlling function of geological features on magmatic–hydrothermal mineralization

PubMed Central

Zuo, Renguang

2016-01-01

This paper reports a nonlinear controlling function of geological features on magmatic–hydrothermal mineralization, and proposes an alternative method to measure the spatial relationships between geological features and mineral deposits using multifractal singularity theory. It was observed that the greater the proximity to geological controlling features, the greater the number of mineral deposits developed, indicating a nonlinear spatial relationship between these features and mineral deposits. This phenomenon can be quantified using the relationship between the numbers of mineral deposits N(ε) of a D-dimensional set and the scale of ε. The density of mineral deposits can be expressed as ρ(ε) = Cε−(De−a), where ε is the buffer width of geological controlling features, De is Euclidean dimension of space (=2 in this case), a is singularity index, and C is a constant. The expression can be rewritten as ρ = Cεa−2. When a < 2, there is a significant spatial correlation between specific geological features and mineral deposits; lower a values indicate a more significant spatial correlation. This nonlinear relationship and the advantages of this method were illustrated using a case study from Fujian Province in China and a case study from Baguio district in Philippines. PMID:27255794

Feature-based classification of amino acid substitutions outside conserved functional protein domains.

PubMed

Gemovic, Branislava; Perovic, Vladimir; Glisic, Sanja; Veljkovic, Nevena

2013-01-01

There are more than 500 amino acid substitutions in each human genome, and bioinformatics tools irreplaceably contribute to determination of their functional effects. We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs) and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. The new algorithm is based on the informational spectrum method (ISM), a feature-based technique, and statistical analysis. Our dataset contained neutral polymorphisms and mutations associated with myeloid malignancies from epigenetic regulators ASXL1, DNMT3A, EZH2, and TET2. PolyPhen-2 and SIFT had significantly lower accuracies in predicting the effects of amino acid substitutions outside CFDs than expected, with especially low sensitivity. On the other hand, only ISM algorithm showed statistically significant classification of these sequences. It outperformed PolyPhen-2 and SIFT by 15% and 13%, respectively. These results suggest that feature-based methods, like ISM, are more suitable for the classification of amino acid substitutions outside CFDs than phylogeny-based tools.

Evaluating a variety of text-mined features for automatic protein function prediction with GOstruct.

PubMed

Funk, Christopher S; Kahanda, Indika; Ben-Hur, Asa; Verspoor, Karin M

2015-01-01

Most computational methods that predict protein function do not take advantage of the large amount of information contained in the biomedical literature. In this work we evaluate both ontology term co-mention and bag-of-words features mined from the biomedical literature and analyze their impact in the context of a structured output support vector machine model, GOstruct. We find that even simple literature based features are useful for predicting human protein function (F-max: Molecular Function =0.408, Biological Process =0.461, Cellular Component =0.608). One advantage of using literature features is their ability to offer easy verification of automated predictions. We find through manual inspection of misclassifications that some false positive predictions could be biologically valid predictions based upon support extracted from the literature. Additionally, we present a "medium-throughput" pipeline that was used to annotate a large subset of co-mentions; we suggest that this strategy could help to speed up the rate at which proteins are curated.

Multi-chaperone function modulation and association with cytoskeletal proteins are key features of the function of AIP in the pituitary gland

PubMed Central

Hernández-Ramírez, Laura C.; Morgan, Rhodri M.L.; Barry, Sayka; D’Acquisto, Fulvio; Prodromou, Chrisostomos; Korbonits, Márta

2018-01-01

Despite the well-recognized role of loss-of-function mutations of the aryl hydrocarbon receptor interacting protein gene (AIP) predisposing to pituitary adenomas, the pituitary-specific function of this tumor suppressor remains an enigma. To determine the repertoire of interacting partners for the AIP protein in somatotroph cells, wild-type and variant AIP proteins were used for pull-down/quantitative mass spectrometry experiments against lysates of rat somatotropinoma-derived cells; relevant findings were validated by co-immunoprecipitation and co-localization. Global gene expression was studied in AIP mutation positive and negative pituitary adenomas via RNA microarrays. Direct interaction with AIP was confirmed for three known and six novel partner proteins. Novel interactions with HSPA5 and HSPA9, together with known interactions with HSP90AA1, HSP90AB1 and HSPA8, indicate that the function/stability of multiple chaperone client proteins could be perturbed by a deficient AIP co-chaperone function. Interactions with TUBB, TUBB2A, NME1 and SOD1 were also identified. The AIP variants p.R304* and p.R304Q showed impaired interactions with HSPA8, HSP90AB1, NME1 and SOD1; p.R304* also displayed reduced binding to TUBB and TUBB2A, and AIP-mutated tumors showed reduced TUBB2A expression. Our findings suggest that cytoskeletal organization, cell motility/adhesion, as well as oxidative stress responses, are functions that are likely to be involved in the tumor suppressor activity of AIP. PMID:29507682

Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

PubMed

Zhou, Hang; Yang, Yang; Shen, Hong-Bin

2017-03-15

Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Childhood Ataxia: Clinical Features, Pathogenesis, Key Unanswered Questions, and Future Directions

PubMed Central

Ashley, Claire N.; Hoang, Kelly D.; Lynch, David R.; Perlman, Susan L.; Maria, Bernard L.

2013-01-01

Childhood ataxia is characterized by impaired balance and coordination primarily due to cerebellar dysfunction. Friedreich ataxia, a form of childhood ataxia, is the most common multisystem autosomal recessive disease. Most of these patients are homozygous for the GAA repeat expansion located on the first intron of the frataxin gene on chromosome 9. Mutations in the frataxin gene impair mitochondrial function, increase reactive oxygen species, and trigger redistribution of iron in the mitochondria and cytosol. Targeted therapies for Friedreich ataxia are undergoing testing. In addition, a centralized database, patient registry, and natural history study have been launched to support clinical trials in Friedreich ataxia. The 2011 Neurobiology of Disease in Children symposium, held in conjunction with the 40th annual Child Neurology Society meeting, aimed to (1) describe clinical features surrounding Friedreich ataxia, including cardiomyopathy and genetics; (2) discuss recent advances in the understanding of the pathogenesis of Friedreich ataxia and developments of clinical trials; (3) review new investigations of characteristic symptoms; (4) establish clinical and biochemical overlaps in neurodegenerative diseases and possible directions for future basic, translational, and clinical studies. PMID:22859693

Prediction of interface residue based on the features of residue interaction network.

PubMed

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

How we developed and piloted an electronic key features examination for the internal medicine clerkship based on a US national curriculum.

PubMed

Bronander, Kirk A; Lang, Valerie J; Nixon, L James; Harrell, Heather E; Kovach, Regina; Hingle, Susan; Berman, Norman

2015-01-01

Key features examinations (KFEs) have been used to assess clinical decision making in medical education, yet there are no reports of an online KFE-based on a national curriculum for the internal medicine clerkship. What we did: The authors developed and pilot tested an electronic KFE based on the US Clerkship Directors in Internal Medicine core curriculum. Teams, with expert oversight and peer review, developed key features (KFs) and cases. The exam was pilot tested at eight medical schools with 162 third and fourth year medical students, of whom 96 (59.3%) responded to a survey. While most students reported that the exam was more difficult than a multiple choice question exam, 61 (83.3%) students agreed that it reflected problems seen in clinical practice and 51 (69.9%) students reported that it more accurately assessed the ability to make clinical decisions. The development of an electronic KFs exam is a time-intensive process. A team approach offers built-in peer review and accountability. Students, although not familiar with this format in the US, recognized it as authentically assessing clinical decision-making for problems commonly seen in the clerkship.

Stress assessment based on EEG univariate features and functional connectivity measures.

PubMed

Alonso, J F; Romero, S; Ballester, M R; Antonijoan, R M; Mañanas, M A

2015-07-01

The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.

Bile Routing Modification Reproduces Key Features of Gastric Bypass in Rat

PubMed Central

Goncalves, Daisy; Barataud, Aude; De Vadder, Filipe; Vinera, Jennifer; Zitoun, Carine; Duchampt, Adeline; Mithieux, Gilles

2015-01-01

STRUCTURED ABSTRACT Objective To evaluate the role of bile routing modification on the beneficial effects of gastric bypass surgery on glucose and energy metabolism. Summary background data Gastric bypass surgery (GBP) promotes early improvements in glucose and energy homeostasis in obese diabetic patients. A suggested mechanism associates a decrease in hepatic glucose production (HGP) to an enhanced intestinal gluconeogenesis (IGN). Moreover, plasma bile acids are elevated after GBP and bile acids are inhibitors of gluconeogenesis. Methods In male Sprague-Dawley rats, we performed bile diversions from the bile duct to the mid-jejunum or the mid-ileum to match the modified bile delivery in the gut occurring in GBP. Body weight, food intake, glucose tolerance, insulin sensitivity and food preference were analyzed. The expression of gluconeogenesis genes was evaluated in both the liver and the intestine. Results Bile diversions mimicking GBP promote an increase in plasma bile acids and a marked improvement in glucose control. Bile bioavailability modification is causal since a bile acid sequestrant suppresses the beneficial effects of bile diversions on glucose control. In agreement with the inhibitory role of bile acids on gluconeogenesis, bile diversions promote a blunting in HGP, whereas IGN is increased in the gut segments devoid of bile. In rats fed a high fat-high sucrose diet, bile diversions improve glucose control and dramatically decrease food intake due to an acquired disinterest in fatty food. Conclusion This study shows that bile routing modification is a key mechanistic feature in the beneficial outcomes of GBP. PMID:25575265

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please

Single Cell Mathematical Model Successfully Replicates Key Features of GBM: Go-Or-Grow Is Not Necessary.

PubMed

Scribner, Elizabeth; Fathallah-Shaykh, Hassan M

2017-01-01

Glioblastoma (GBM) is a malignant brain tumor that continues to be associated with neurological morbidity and poor survival times. Brain invasion is a fundamental property of malignant glioma cells. The Go-or-Grow (GoG) phenotype proposes that cancer cell motility and proliferation are mutually exclusive. Here, we construct and apply a single glioma cell mathematical model that includes motility and angiogenesis and lacks the GoG phenotype. Simulations replicate key features of GBM including its multilayer structure (i.e.edema, enhancement, and necrosis), its progression patterns associated with bevacizumab treatment, and replicate the survival times of GBM treated or untreated with bevacizumab. These results suggest that the GoG phenotype is not a necessary property for the formation of the multilayer structure, recurrence patterns, and the poor survival times of patients diagnosed with GBM.

Use cases and DEMO: aligning functional features of ICT-infrastructure to business processes.

PubMed

Maij, E; Toussaint, P J; Kalshoven, M; Poerschke, M; Zwetsloot-Schonk, J H M

2002-11-12

The proper alignment of functional features of the ICT-infrastructure to business processes is a major challenge in health care organisations. This alignment takes into account that the organisational structure not only shapes the ICT-infrastructure, but that the inverse also holds. To solve the alignment problem, relevant features of the ICT-infrastructure should be derived from the organisational structure and the influence of this envisaged ICT to the work practices should be pointed out. The objective of our study was to develop a method to solve this alignment problem. In a previous study we demonstrated the appropriateness of the business process modelling methodology Dynamic Essential Modelling of Organizations (DEMO). A proven and widely used modelling language for expressing functional features is Unified Modelling Language (UML). In the context of a specific case study at the University Medical Centre Utrecht in the Netherlands we investigated if the combined use of DEMO and UML could solve the alignment problem. The study demonstrated that the DEMO models were suited as a starting point in deriving system functionality by using the use case concept of UML. Further, the case study demonstrated that in using this approach for the alignment problem, insight is gained into the mutual influence of ICT-infrastructure and organisation structure: (a) specification of independent, re-usable components-as a set of related functionalities-is realised, and (b) a helpful representation of the current and future work practice is provided for in relation to the envisaged ICT support.

Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm.

PubMed

Martinez, Emmanuel; Alvarez, Mario Moises; Trevino, Victor

2010-08-01

Biomarker discovery is a typical application from functional genomics. Due to the large number of genes studied simultaneously in microarray data, feature selection is a key step. Swarm intelligence has emerged as a solution for the feature selection problem. However, swarm intelligence settings for feature selection fail to select small features subsets. We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm. In this study, we tested our algorithm in 11 microarray datasets for brain, leukemia, lung, prostate, and others. We show that the proposed swarm intelligence algorithm successfully increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

PyEEG: an open source Python module for EEG/MEG feature extraction.

PubMed

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

PubMed Central

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction. PMID:21512582

A Novel Feature-Tracking Echocardiographic Method for the Quantitation of Regional Myocardial Function

PubMed Central

Pirat, Bahar; Khoury, Dirar S.; Hartley, Craig J.; Tiller, Les; Rao, Liyun; Schulz, Daryl G.; Nagueh, Sherif F.; Zoghbi, William A.

2012-01-01

Objectives The aim of this study was to validate a novel, angle-independent, feature-tracking method for the echocardiographic quantitation of regional function. Background A new echocardiographic method, Velocity Vector Imaging (VVI) (syngo Velocity Vector Imaging technology, Siemens Medical Solutions, Ultrasound Division, Mountain View, California), has been introduced, based on feature tracking—incorporating speckle and endocardial border tracking, that allows the quantitation of endocardial strain, strain rate (SR), and velocity. Methods Seven dogs were studied during baseline, and various interventions causing alterations in regional function: dobutamine, 5-min coronary occlusion with reperfusion up to 1 h, followed by dobutamine and esmolol infusions. Echocardiographic images were acquired from short- and long-axis views of the left ventricle. Segment-length sonomicrometry crystals were used as the reference method. Results Changes in systolic strain in ischemic segments were tracked well with VVI during the different states of regional function. There was a good correlation between circumferential and longitudinal systolic strain by VVI and sonomicrometry (r = 0.88 and r = 0.83, respectively, p < 0.001). Strain measurements in the nonischemic basal segments also demonstrated a significant correlation between the 2 methods (r = 0.65, p < 0.001). Similarly, a significant relation was observed for circumferential and longitudinal SR between the 2 methods (r = 0.94, p < 0.001 and r = 0.90, p < 0.001, respectively). The endocardial velocity relation to changes in strain by sonomicrometry was weaker owing to significant cardiac translation. Conclusions Velocity Vector Imaging, a new feature-tracking method, can accurately assess regional myocardial function at the endocardial level and is a promising clinical tool for the simultaneous quantification of regional and global myocardial function. PMID:18261685

Summary of ADTT Website Functionality and Features

NASA Technical Reports Server (NTRS)

Hawke, Veronica; Duong, Trang; Liang, Lawrence; Gage, Peter; Lawrence, Scott (Technical Monitor)

2001-01-01

This report summarizes development of the ADTT web-based design environment by the ELORET team in 2000. The Advanced Design Technology Testbed had been in development for several years, with demonstration applications restricted to aerodynamic analyses of subsonic aircraft. The key changes achieved this year were improvements in Web-based accessibility, evaluation of collaborative visualization, remote invocation of geometry updates and performance analysis, and application to aerospace system analysis. Significant effort was also devoted to post-processing of data, chiefly through comparison of similar data for alternative vehicle concepts. Such comparison is an essential requirement for designers to make informed choices between alternatives. The next section of this report provides more discussion of the goals for ADTT development. Section 3 provides screen shots from a sample session in the ADTT environment, including Login and navigation to the project of interest, data inspection, analysis execution and output evaluation. The following section provides discussion of implementation details and recommendations for future development of the software and information technologies that provide the key functionality of the ADTT system. Section 5 discusses the integration architecture for the system, which links machines running different operating systems and provides unified access to data stored in distributed locations. Security is a significant issue for this system, especially for remote access to NAS machines, so Section 6 discusses several architectural considerations with respect to security. Additional details of some aspects of ADTT development are included in Appendices.

"Key Concepts in ELT": Taking Stock

ERIC Educational Resources Information Center

Hall, Graham

2012-01-01

This article identifies patterns and trends within "Key Concepts in ELT", both since the inception of the feature in ELT Journal in 1993 and during the 17 years of the current editorship. After outlining the aims of the series, the article identifies key themes that have emerged over time, exploring the links between "Key Concepts" pieces and the…

The key-features approach to assess clinical decisions: validity evidence to date.

PubMed

Bordage, G; Page, G

2018-05-17

The key-features (KFs) approach to assessment was initially proposed during the First Cambridge Conference on Medical Education in 1984 as a more efficient and effective means of assessing clinical decision-making skills. Over three decades later, we conducted a comprehensive, systematic review of the validity evidence gathered since then. The evidence was compiled according to the Standards for Educational and Psychological Testing's five sources of validity evidence, namely, Content, Response process, Internal structure, Relations to other variables, and Consequences, to which we added two other types related to Cost-feasibility and Acceptability. Of the 457 publications that referred to the KFs approach between 1984 and October 2017, 164 are cited here; the remaining 293 were either redundant or the authors simply mentioned the KFs concept in relation to their work. While one set of articles reported meeting the validity standards, another set examined KFs test development choices and score interpretation. The accumulated validity evidence for the KFs approach since its inception supports the decision-making construct measured and its use to assess clinical decision-making skills at all levels of training and practice and with various types of exam formats. Recognizing that gathering validity evidence is an ongoing process, areas with limited evidence, such as item factor analyses or consequences of testing, are identified as well as new topics needing further clarification, such as the use of the KFs approach for formative assessment and its place within a program of assessment.

Available nitrogen is the key factor influencing soil microbial functional gene diversity in tropical rainforest.

PubMed

Cong, Jing; Liu, Xueduan; Lu, Hui; Xu, Han; Li, Yide; Deng, Ye; Li, Diqiang; Zhang, Yuguang

2015-08-20

Tropical rainforests cover over 50% of all known plant and animal species and provide a variety of key resources and ecosystem services to humans, largely mediated by metabolic activities of soil microbial communities. A deep analysis of soil microbial communities and their roles in ecological processes would improve our understanding on biogeochemical elemental cycles. However, soil microbial functional gene diversity in tropical rainforests and causative factors remain unclear. GeoChip, contained almost all of the key functional genes related to biogeochemical cycles, could be used as a specific and sensitive tool for studying microbial gene diversity and metabolic potential. In this study, soil microbial functional gene diversity in tropical rainforest was analyzed by using GeoChip technology. Gene categories detected in the tropical rainforest soils were related to different biogeochemical processes, such as carbon (C), nitrogen (N) and phosphorus (P) cycling. The relative abundance of genes related to C and P cycling detected mostly derived from the cultured bacteria. C degradation gene categories for substrates ranging from labile C to recalcitrant C were all detected, and gene abundances involved in many recalcitrant C degradation gene categories were significantly (P < 0.05) different among three sampling sites. The relative abundance of genes related to N cycling detected was significantly (P < 0.05) different, mostly derived from the uncultured bacteria. The gene categories related to ammonification had a high relative abundance. Both canonical correspondence analysis and multivariate regression tree analysis showed that soil available N was the most correlated with soil microbial functional gene structure. Overall high microbial functional gene diversity and different soil microbial metabolic potential for different biogeochemical processes were considered to exist in tropical rainforest. Soil available N could be the key factor in shaping the

Unconscious analyses of visual scenes based on feature conjunctions.

PubMed

Tachibana, Ryosuke; Noguchi, Yasuki

2015-06-01

To efficiently process a cluttered scene, the visual system analyzes statistical properties or regularities of visual elements embedded in the scene. It is controversial, however, whether those scene analyses could also work for stimuli unconsciously perceived. Here we show that our brain performs the unconscious scene analyses not only using a single featural cue (e.g., orientation) but also based on conjunctions of multiple visual features (e.g., combinations of color and orientation information). Subjects foveally viewed a stimulus array (duration: 50 ms) where 4 types of bars (red-horizontal, red-vertical, green-horizontal, and green-vertical) were intermixed. Although a conscious perception of those bars was inhibited by a subsequent mask stimulus, the brain correctly analyzed the information about color, orientation, and color-orientation conjunctions of those invisible bars. The information of those features was then used for the unconscious configuration analysis (statistical processing) of the central bars, which induced a perceptual bias and illusory feature binding in visible stimuli at peripheral locations. While statistical analyses and feature binding are normally 2 key functions of the visual system to construct coherent percepts of visual scenes, our results show that a high-level analysis combining those 2 functions is correctly performed by unconscious computations in the brain. (c) 2015 APA, all rights reserved).

Heme oxygenase: the key to renal function regulation

PubMed Central

Cao, Jian; Sacerdoti, David; Li, Xiaoying; Drummond, George

2009-01-01

Heme oxygenase (HO) plays a critical role in attenuating the production of reactive oxygen species through its ability to degrade heme in an enzymatic process that leads to the production of equimolar amounts of carbon monoxide and biliverdin/bilirubin and the release of free iron. The present review examines the beneficial role of HO-1 (inducible form of HO) that is achieved by increased expression of this enzyme in renal tissue. The influence of the HO system on renal physiology, obesity, vascular dysfunction, and blood pressure regulation is reviewed, and the clinical potential of increased levels of HO-1 protein, HO activity, and HO-derived end products of heme degradation is discussed relative to renal disease. The use of pharmacological and genetic approaches to investigate the role of the HO system in the kidney is key to the development of therapeutic approaches to prevent the adverse effects that accrue due to an impairment in renal function. PMID:19570878

PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

PubMed

Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

2014-01-01

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

Caveolae structure and function

PubMed Central

Thomas, Candice M; Smart, Eric J

2008-01-01

Abstract Studies on the structure and function of caveolae have revealed how this versatile subcellular organelle can influence numerous signalling pathways. This brief review will discuss a few of the key features of caveolae as it relates to signalling and disease processes. PMID:18315571

Dynamic features of carboxy cytoglobin distal mutants investigated by molecular dynamics simulations.

PubMed

Zhao, Cong; Du, Weihong

2016-04-01

Cytoglobin (Cgb) is a member of hemoprotein family with roles in NO metabolism, fibrosis, and tumourigenesis. Similar to other hemoproteins, Cgb structure and functions are markedly influenced by distal key residues. The sixth ligand His(81) (E7) is crucial to exogenous ligand binding, heme pocket conformation, and physiological roles of this protein. However, the effects of other key residues on heme pocket and protein biological functions are not well known. In this work, a molecular dynamics (MD) simulation study of two single mutants in CO-ligated Cgb (L46FCgbCO and L46VCgbCO) and two double mutants (L46FH81QCgbCO and L46VH81QCgbCO) was conducted to explore the effects of the key distal residues Leu(46)(B10) and His(81)(E7) on Cgb structure and functions. Results indicated that the distal mutation of B10 and E7 affected CgbCO dynamic properties on loop region fluctuation, internal cavity rearrangement, and heme motion. The distal conformation change was reflected by the distal key residues Gln(62) (CD3) and Arg(84)(E10). The hydrogen bond between heme propionates with CD3 or E10 residues were evidently influenced by B10/E7 mutation. Furthermore, heme pocket rearrangement was also observed based on the distal pocket volume and occurrence rate of inner cavities. The mutual effects of B10 and E7 residues on protein conformational rearrangement and other dynamic features were expressed in current MD studies of CgbCO and its distal mutants, suggesting their crucial role in heme pocket stabilization, ligand binding, and Cgb biological functions. The mutation of distal B10 and E7 residues affects the dynamic features of carboxy cytoglobin.

A Web-Based Data Collection Platform for Multisite Randomized Behavioral Intervention Trials: Development, Key Software Features, and Results of a User Survey.

PubMed

Modi, Riddhi A; Mugavero, Michael J; Amico, Rivet K; Keruly, Jeanne; Quinlivan, Evelyn Byrd; Crane, Heidi M; Guzman, Alfredo; Zinski, Anne; Montue, Solange; Roytburd, Katya; Church, Anna; Willig, James H

2017-06-16

Meticulous tracking of study data must begin early in the study recruitment phase and must account for regulatory compliance, minimize missing data, and provide high information integrity and/or reduction of errors. In behavioral intervention trials, participants typically complete several study procedures at different time points. Among HIV-infected patients, behavioral interventions can favorably affect health outcomes. In order to empower newly diagnosed HIV positive individuals to learn skills to enhance retention in HIV care, we developed the behavioral health intervention Integrating ENGagement and Adherence Goals upon Entry (iENGAGE) funded by the National Institute of Allergy and Infectious Diseases (NIAID), where we deployed an in-clinic behavioral health intervention in 4 urban HIV outpatient clinics in the United States. To scale our intervention strategy homogenously across sites, we developed software that would function as a behavioral sciences research platform. This manuscript aimed to: (1) describe the design and implementation of a Web-based software application to facilitate deployment of a multisite behavioral science intervention; and (2) report on results of a survey to capture end-user perspectives of the impact of this platform on the conduct of a behavioral intervention trial. In order to support the implementation of the NIAID-funded trial iENGAGE, we developed software to deploy a 4-site behavioral intervention for new clinic patients with HIV/AIDS. We integrated the study coordinator into the informatics team to participate in the software development process. Here, we report the key software features and the results of the 25-item survey to evaluate user perspectives on research and intervention activities specific to the iENGAGE trial (N=13). The key features addressed are study enrollment, participant randomization, real-time data collection, facilitation of longitudinal workflow, reporting, and reusability. We found 100% user

Mobile personal health records: an evaluation of features and functionality.

PubMed

Kharrazi, Hadi; Chisholm, Robin; VanNasdale, Dean; Thompson, Benjamin

2012-09-01

To evaluate stand-alone mobile personal health record (mPHR) applications for the three leading cellular phone platforms (iOS, BlackBerry, and Android), assessing each for content, function, security, and marketing characteristics. Nineteen stand-alone mPHR applications (8 for iOS, 5 for BlackBerry, and 6 for Android) were identified and evaluated. Main criteria used to include mPHRs were: operating standalone on a mobile platform; not requiring external connectivity; and covering a wide range of health topics. Selected mPHRs were analyzed considering product characteristics, data elements, and application features. We also reviewed additional features such as marketing tactics. Within and between the different mobile platforms attributes for the mPHR were highly variable. None of the mPHRs contained all attributes included in our evaluation. The top four mPHRs contained 13 of the 14 features omitting only the in-case-of emergency feature. Surprisingly, seven mPHRs lacked basic security measures as important as password protection. The mPHRs were relatively inexpensive: ranging from no cost to $9.99. The mPHR application cost varied in some instances based on whether it supported single or multiple users. Ten mPHRs supported multiple user profiles. Notably, eight mPHRs used scare tactics as marketing strategy. mPHR is an emerging health care technology. The majority of existing mPHR apps is limited by at least one of the attributes considered for this study; however, as the mobile market continues to expand it is likely that more comprehensive mPHRs will be developed in the near future. New advancements in mobile technology can be utilized to enhance mPHRs by long-term patient empowerment features. Marketing strategies for mPHRs should target specific subpopulations and avoid scare tactics. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Depth-time interpolation of feature trends extracted from mobile microelectrode data with kernel functions.

PubMed

Wong, Stephen; Hargreaves, Eric L; Baltuch, Gordon H; Jaggi, Jurg L; Danish, Shabbar F

2012-01-01

Microelectrode recording (MER) is necessary for precision localization of target structures such as the subthalamic nucleus during deep brain stimulation (DBS) surgery. Attempts to automate this process have produced quantitative temporal trends (feature activity vs. time) extracted from mobile MER data. Our goal was to evaluate computational methods of generating spatial profiles (feature activity vs. depth) from temporal trends that would decouple automated MER localization from the clinical procedure and enhance functional localization in DBS surgery. We evaluated two methods of interpolation (standard vs. kernel) that generated spatial profiles from temporal trends. We compared interpolated spatial profiles to true spatial profiles that were calculated with depth windows, using correlation coefficient analysis. Excellent approximation of true spatial profiles is achieved by interpolation. Kernel-interpolated spatial profiles produced superior correlation coefficient values at optimal kernel widths (r = 0.932-0.940) compared to standard interpolation (r = 0.891). The choice of kernel function and kernel width resulted in trade-offs in smoothing and resolution. Interpolation of feature activity to create spatial profiles from temporal trends is accurate and can standardize and facilitate MER functional localization of subcortical structures. The methods are computationally efficient, enhancing localization without imposing additional constraints on the MER clinical procedure during DBS surgery. Copyright © 2012 S. Karger AG, Basel.

[Specific features of digestive function development in larvae of some salmonid fish].

PubMed

Ershova, T S; Volkova, I V; Zaĭtseva, V F

2004-01-01

We studied the activities of digestive enzymes responsible for the digestion of food carbohydrate and protein components in plant-eating fish at various stages of larval development. The activities of all digestive enzymes tend to rise during larval development. Species specific features of the alimentary canal functioning have been described.

Fractographic features of glass-ceramic and zirconia-based dental restorations fractured during clinical function.

PubMed

Oilo, Marit; Hardang, Anne D; Ulsund, Amanda H; Gjerdet, Nils R

2014-06-01

Fractures during clinical function have been reported as the major concern associated with all-ceramic dental restorations. The aim of this study was to analyze the fracture features of glass-ceramic and zirconia-based restorations fractured during clinical use. Twenty-seven crowns and onlays were supplied by dentists and dental technicians with information about type of cement and time in function, if available. Fourteen lithium disilicate glass-ceramic restorations and 13 zirconia-based restorations were retrieved and analyzed. Fractographic features were examined using optical microscopy to determine crack initiation and crack propagation of the restorations. The material comprised fractured restorations from one canine, 10 incisors, four premolars, and 11 molars. One crown was not categorized because of difficulty in orientation of the fragments. The results revealed that all core and veneer fractures initiated in the cervical margin and usually from the approximal area close to the most coronally placed curvature of the margin. Three cases of occlusal chipping were found. The margin of dental all-ceramic single-tooth restorations was the area of fracture origin. The fracture features were similar for zirconia, glass-ceramic, and alumina single-tooth restorations. Design features seem to be of great importance for fracture initiation. © 2014 Eur J Oral Sci.

SIMPL Systems, or: Can We Design Cryptographic Hardware without Secret Key Information?

NASA Astrophysics Data System (ADS)

Rührmair, Ulrich

This paper discusses a new cryptographic primitive termed SIMPL system. Roughly speaking, a SIMPL system is a special type of Physical Unclonable Function (PUF) which possesses a binary description that allows its (slow) public simulation and prediction. Besides this public key like functionality, SIMPL systems have another advantage: No secret information is, or needs to be, contained in SIMPL systems in order to enable cryptographic protocols - neither in the form of a standard binary key, nor as secret information hidden in random, analog features, as it is the case for PUFs. The cryptographic security of SIMPLs instead rests on (i) a physical assumption on their unclonability, and (ii) a computational assumption regarding the complexity of simulating their output. This novel property makes SIMPL systems potentially immune against many known hardware and software attacks, including malware, side channel, invasive, or modeling attacks.

Is Early-onset in Major Depression a Predictor of Specific Clinical Features with More Impaired Social Function?

PubMed Central

Liu, Yan-Hong; Chen, Lin; Su, Yun-Ai; Fang, Yi-Ru; Srisurapanont, Manit; Hong, Jin Pyo; Hatim, Ahmad; Chua, Hong Choon; Bautista, Dianne; Si, Tian-Mei

2015-01-01

Background: Early-onset major depressive disorder (MDD) (EOD) is often particularly malignant due to its special clinical features, accompanying impaired social function, protracted recovery time, and frequent recurrence. This study aimed to observe the effects of age onset on clinical characteristics and social function in MDD patients in Asia. Methods: In total, 547 out-patients aged 18–65 years who were from 13 study sites in five Asian countries were included. These patients had MDD diagnose according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition criteria. Clinical features and social function were assessed using Symptom Checklist-90-revised (SCL-90-R) and Sheehan Disability Scale (SDS). Quality of life was assessed by a 36-item Short-form Health Survey (SF-36). Analyses were performed using a continuous or dichotomous (cut-off: 30 years) age-of-onset indicator. Results: Early-onset MDD (EOD, <30 years) was associated with longer illness (P = 0.003), unmarried status (P < 0.001), higher neuroticism (P ≤ 0.002) based on the SCL-90-R, and more limited social function and mental health (P = 0.006, P = 0.007) based on the SF-36 and SDS. The impairment of social function and clinical severity were more prominent at in-patients with younger onset ages. Special clinical features and more impaired social function and quality of life were associated with EOD, as in western studies. Conclusions: EOD often follows higher levels of neuroticism. Age of onset of MDD may be a predictor of clinical features and impaired social function, allowing earlier diagnosis and treatment. PMID:25758278

MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features.

PubMed

Xu, Juan; Li, Chuan-Xing; Li, Yong-Sheng; Lv, Jun-Ying; Ma, Ye; Shao, Ting-Ting; Xu, Liang-De; Wang, Ying-Ying; Du, Lei; Zhang, Yun-Peng; Jiang, Wei; Li, Chun-Quan; Xiao, Yun; Li, Xia

2011-02-01

Synergistic regulations among multiple microRNAs (miRNAs) are important to understand the mechanisms of complex post-transcriptional regulations in humans. Complex diseases are affected by several miRNAs rather than a single miRNA. So, it is a challenge to identify miRNA synergism and thereby further determine miRNA functions at a system-wide level and investigate disease miRNA features in the miRNA-miRNA synergistic network from a new view. Here, we constructed a miRNA-miRNA functional synergistic network (MFSN) via co-regulating functional modules that have three features: common targets of corresponding miRNA pairs, enriched in the same gene ontology category and close proximity in the protein interaction network. Predicted miRNA synergism is validated by significantly high co-expression of functional modules and significantly negative regulation to functional modules. We found that the MFSN exhibits a scale free, small world and modular architecture. Furthermore, the topological features of disease miRNAs in the MFSN are distinct from non-disease miRNAs. They have more synergism, indicating their higher complexity of functions and are the global central cores of the MFSN. In addition, miRNAs associated with the same disease are close to each other. The structure of the MFSN and the features of disease miRNAs are validated to be robust using different miRNA target data sets.

Using a Functional Simulation of Crisis Management to Test the C2 Agility Model Parameters on Key Performance Variables

DTIC Science & Technology

2013-06-01

1 18th ICCRTS Using a Functional Simulation of Crisis Management to Test the C2 Agility Model Parameters on Key Performance Variables...AND SUBTITLE Using a Functional Simulation of Crisis Management to Test the C2 Agility Model Parameters on Key Performance Variables 5a. CONTRACT...command in crisis management. C2 Agility Model Agility can be conceptualized at a number of different levels; for instance at the team

Functional group diversity is key to Southern Ocean benthic carbon pathways

PubMed Central

Sands, Chester J.

2017-01-01

High latitude benthos are globally important in terms of accumulation and storage of ocean carbon, and the feedback this is likely to have on regional warming. Understanding this ecosystem service is important but difficult because of complex taxonomic diversity, history and geography of benthic biomass. Using South Georgia as a model location (where the history and geography of benthic biology is relatively well studied) we investigated whether the composition of functional groups were critical to benthic accumulation, immobilization and burial pathway to sequestration–and also aid their study through simplification of identification. We reclassified [1], [2]) morphotype and carbon mass data to 13 functional groups, for each sample of 32 sites around the South Georgia continental shelf. We investigated the influence on carbon accumulation, immobilization and sequestration estimate by multiple factors including the compositions of functional groups. Functional groups showed high diversity within and between sites, and within and between habitat types. Carbon storage was not linked to a functional group in particular but accumulation and immobilization increased with the number of functional groups present and the presence of hard substrata. Functional groups were also important to carbon burial rate, which increased with the presence of mixed (hard and soft substrata). Functional groups showed high surrogacy for taxonomic composition and were useful for examining contrasting habitat categorization. Functional groups not only aid marine carbon storage investigation by reducing time and the need for team size and speciality, but also important to benthic carbon pathways per se. There is a distinct geography to seabed carbon storage; seabed boulder-fields are hotspots of carbon accumulation and immobilization, whilst the interface between such boulder-fields and sediments are key places for burial and sequestration. PMID:28654664

Gain-of-function mutations in beet DODA2 identify key residues for betalain pigment evolution.

PubMed

Bean, Alexander; Sunnadeniya, Rasika; Akhavan, Neda; Campbell, Annabelle; Brown, Matthew; Lloyd, Alan

2018-05-13

The key enzymatic step in betalain biosynthesis involves conversion of l-3,4-dihydroxyphenylalanine (l-DOPA) to betalamic acid. One class of enzymes capable of this is 3,4-dihydroxyphenylalanine 4,5-dioxygenase (DODA). In betalain-producing species, multiple paralogs of this gene are maintained. This study demonstrates which paralogs function in the betalain pathway and determines the residue changes required to evolve a betalain-nonfunctional DODA into a betalain-functional DODA. Functionalities of two pairs of DODAs were tested by expression in beets, Arabidopsis and yeast, and gene silencing was performed by virus-induced gene silencing. Site-directed mutagenesis identified amino acid residues essential for betalamic acid production. Beta vulgaris and Mirabilis jalapa both possess a DODA1 lineage that functions in the betalain pathway and at least one other lineage, DODA2, that does not. Site-directed mutagenesis resulted in betalain biosynthesis by a previously nonfunctional DODA, revealing key residues required for evolution of the betalain pathway. Divergent functionality of DODA paralogs, one clade involved in betalain biosynthesis but others not, is present in various Caryophyllales species. A minimum of seven amino acid residue changes conferred betalain enzymatic activity to a betalain-nonfunctional DODA paralog, providing insight into the evolution of the betalain pigment pathway in plants. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Research and Analysis on Energy Consumption Features of Civil Airports

NASA Astrophysics Data System (ADS)

Li, Bo; Zhang, Wen; Wang, Jianping; Xu, Junku; Su, Jixiang

2017-11-01

Civil aviation is an important part of China’s transportation system, and also the fastest-growing field of comprehensive transportation. Airports, as a key infrastructure of the air transportation system, are the junctions of air and ground transportation. Large airports are generally comprehensive transportation hubs that integrate various modes of transportation, serving as important functional zones of cities. Compared with other transportation hubs, airports cover a wide area, with plenty of functional sections, complex systems and strong specialization, while airport buildings represented by terminals have exhibited characteristics of large space, massive energy consumption, high requirement for safety and comfort, as well as concentrated and rapidly changing passenger flows. Through research and analysis on energy consumption features of civil airports, and analysis on energy consumption features of airports with different sizes or in different climate regions, this article has drawn conclusions therefrom.

Identifying Key Features of Effective Active Learning: The Effects of Writing and Peer Discussion

PubMed Central

Pangle, Wiline M.; Wyatt, Kevin H.; Powell, Karli N.; Sherwood, Rachel E.

2014-01-01

We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. PMID:25185230

Chromium picolinate does not improve key features of metabolic syndrome in obese nondiabetic adults.

PubMed

Iqbal, Nayyar; Cardillo, Serena; Volger, Sheri; Bloedon, LeAnne T; Anderson, Richard A; Boston, Raymond; Szapary, Philippe O

2009-04-01

The use of chromium-containing dietary supplements is widespread among patients with type 2 diabetes. Chromium's effects in patients at high risk for developing diabetes, especially those with metabolic syndrome, is unknown. The objective of this study was to determine the effects of chromium picolinate (CrPic) on glucose metabolism in patients with metabolic syndrome. A double-blind, placebo-controlled, randomized trial was conducted at a U.S. academic medical center. Sixty three patients with National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III)-defined metabolic syndrome were included. The primary end point was a change in the insulin sensitivity index derived from a frequently sampled intravenous glucose tolerance test. Prespecified secondary end points included changes in other measurements of glucose metabolism, oxidative stress, fasting serum lipids, and high sensitivity C-reactive protein. After 16 weeks of CrPic treatment, there was no significant change in insulin sensitivity index between groups (P = 0.14). However, CrPic increased acute insulin response to glucose (P 0.02). CrPic had no significant effect on other measures of glucose metabolism, body weight, serum lipids, or measures of inflammation and oxidative stress. CrPic at 1000 microg/day does not improve key features of the metabolic syndrome in obese nondiabetic patients.

The role of emotion in musical improvisation: an analysis of structural features.

PubMed

McPherson, Malinda J; Lopez-Gonzalez, Monica; Rankin, Summer K; Limb, Charles J

2014-01-01

One of the primary functions of music is to convey emotion, yet how music accomplishes this task remains unclear. For example, simple correlations between mode (major vs. minor) and emotion (happy vs. sad) do not adequately explain the enormous range, subtlety or complexity of musically induced emotions. In this study, we examined the structural features of unconstrained musical improvisations generated by jazz pianists in response to emotional cues. We hypothesized that musicians would not utilize any universal rules to convey emotions, but would instead combine heterogeneous musical elements together in order to depict positive and negative emotions. Our findings demonstrate a lack of simple correspondence between emotions and musical features of spontaneous musical improvisation. While improvisations in response to positive emotional cues were more likely to be in major keys, have faster tempos, faster key press velocities and more staccato notes when compared to negative improvisations, there was a wide distribution for each emotion with components that directly violated these primary associations. The finding that musicians often combine disparate features together in order to convey emotion during improvisation suggests that structural diversity may be an essential feature of the ability of music to express a wide range of emotion.

Identifying key features of early stressful experiences that produce stress vulnerability and resilience in primates

PubMed Central

Parker, Karen J.; Maestripieri, Dario

2010-01-01

This article examines the complex role of early stressful experiences in producing both vulnerability and resilience to later stress-related psychopathology in a variety of primate models of human development. Two types of models are reviewed: Parental Separation Models (e.g., isolate-rearing, peer-rearing, parental separations, and stress inoculation) and Maternal Behavior Models (e.g., foraging demands, variation in maternal style, and maternal abuse). Based on empirical evidence, it is argued that early life stress exposure does not increase adult vulnerability to stress-related psychopathology as a linear function, as is generally believed, but instead reflects a quadratic function. Features of early stress exposure including the type, duration, frequency, ecological validity, sensory modality, and developmental timing, within and between species, are identified to better understand how early stressful experiences alter neurobiological systems to produce such diverse developmental outcomes. This article concludes by identifying gaps in our current knowledge, providing directions for future research, and discussing the translational implications of these primate models for human development and psychopathology. PMID:20851145

Structural properties of prokaryotic promoter regions correlate with functional features.

PubMed

Meysman, Pieter; Collado-Vides, Julio; Morett, Enrique; Viola, Roberto; Engelen, Kristof; Laukens, Kris

2014-01-01

The structural properties of the DNA molecule are known to play a critical role in transcription. In this paper, the structural profiles of promoter regions were studied within the context of their diversity and their function for eleven prokaryotic species; Escherichia coli, Klebsiella pneumoniae, Salmonella Typhimurium, Pseudomonas auroginosa, Geobacter sulfurreducens Helicobacter pylori, Chlamydophila pneumoniae, Synechocystis sp., Synechoccocus elongates, Bacillus anthracis, and the archaea Sulfolobus solfataricus. The main anchor point for these promoter regions were transcription start sites identified through high-throughput experiments or collected within large curated databases. Prokaryotic promoter regions were found to be less stable and less flexible than the genomic mean across all studied species. However, direct comparison between species revealed differences in their structural profiles that can not solely be explained by the difference in genomic GC content. In addition, comparison with functional data revealed that there are patterns in the promoter structural profiles that can be linked to specific functional loci, such as sigma factor regulation or transcription factor binding. Interestingly, a novel structural element clearly visible near the transcription start site was found in genes associated with essential cellular functions and growth in several species. Our analyses reveals the great diversity in promoter structural profiles both between and within prokaryotic species. We observed relationships between structural diversity and functional features that are interesting prospects for further research to yet uncharacterized functional loci defined by DNA structural properties.

Artistic shaping of key facial features in children and adolescents.

PubMed

Sullivan, P K; Singer, D P

2001-12-01

Facial aesthetics can be enhanced by otoplasty, rhinoplasty and genioplasty. Excellent outcomes can be obtained given appropriate timing, patient selection, preoperative planning, and artistic sculpting of the region with the appropriate surgical technique. Choosing a patient with mature psychological, developmental, and anatomic features that are amenable to treatment in the pediatric population can be challenging, yet rewarding.

Key Clinical Features to Identify Girls with "CDKL5" Mutations

ERIC Educational Resources Information Center

Bahi-Buisson, Nadia; Nectoux, Juliette; Rosas-Vargas, Haydee; Milh, Mathieu; Boddaert, Nathalie; Girard, Benoit; Cances, Claude; Ville, Dorothee; Afenjar, Alexandra; Rio, Marlene; Heron, Delphine; Morel, Marie Ange N'Guyen; Arzimanoglou, Alexis; Philippe, Christophe; Jonveaux, Philippe; Chelly, Jamel; Bienvenu, Thierry

2008-01-01

Mutations in the human X-linked cyclin-dependent kinase-like 5 ("CDKL5") gene have been shown to cause infantile spasms as well as Rett syndrome (RTT)-like phenotype. To date, less than 25 different mutations have been reported. So far, there are still little data on the key clinical diagnosis criteria and on the natural history of…

[Assessment on the changing conditions of ecosystems in key ecological function zones in China].

PubMed

Huang, Lin; Cao, Wei; Wu, Dan; Gong, Guo-li; Zhao, Guo-song

2015-09-01

In this paper, the dynamics of ecosystem macrostructure, qualities and core services during 2000 and 2010 were analyzed for the key ecological function zones of China, which were classified into four types of water conservation, soil conservation, wind prevention and sand fixation, and biodiversity maintenance. In the water conservation ecological function zones, the areas of forest and grassland ecosystems were decreased whereas water bodies and wetland were increased in the past 11 years, and the water conservation volume of forest, grassland and wetland ecosystems increased by 2.9%. This region needs to reverse the decreasing trends of forest and grassland ecosystems. In the soil conservation ecological function zones, the area of farmland ecosystem was decreased, and the areas of forest, grassland, water bodies and wetland ecosystems were increased. The total amount of the soil erosion was reduced by 28.2%, however, the soil conservation amount of ecosystems increased by 38.1%. In the wind prevention and sand fixation ecological function zones, the areas of grassland, water bodies and wetland ecosystems were decreased, but forest and farmland ecosystems were increased. The unit amount of the soil. wind erosion was reduced and the sand fixation amount of ecosystems increased lightly. In this kind of region that is located in arid and semiarid areas, ecological conservation needs to reduce farmland area and give priority to the protection of the original ecological system. In the biodiversity maintenance ecological function zones, the areas of grassland and desert ecosystems were decreased and other types were increased. The human disturbances showed a weakly upward trend and needs to be reduced. The key ecological function zones should be aimed at the core services and the protecting objects, to assess quantitatively on the effectiveness of ecosystem conservation and improvement.

Erythrocytes Functional Features in the 11-YEAR Solar Cycle

NASA Astrophysics Data System (ADS)

Parshina, S. S.; Tokayeva, L. K.; Dolgova, E. M.; Afanas'yeva, T. N.; Samsonov, S. N.; Petrova, V. D.; Vodolagina, E. S.; Kaplanova, T. I.; Potapova, M. V.

There had been studied features of rheological blood failures in patients with unstable angina (UA) in periods of the high (HSA) and low solar activity (LSA) in the 23rd 11-year solar cycle. This category of patients is characterized by prethrombotic blood state, although they don't have coronary thrombosis. The research aimed to study compensatory mechanisms which block thrombosis development at the solar activity increase. There had been established that the period of the solar activity increasing in the 11-year solar cycle is characterized by an increase of a blood viscosity, comparing with the period of a low solar activity. Though, erythrocytes functional features in this case are compensatory mechanisms - erythrocyte aggregation paradoxically reduced and their deformability increases. It is probably connected with the revealed fibrinogen decrease in the period of the high solar activity. We can see that the change of a solar activity is accompanied not only by the progressing of pathologic processes, but also by an activation of adaptive changes in erythrocyte membrane so0 as to prevent thrombosis. Though, the required compensatory mechanisms were found invalid, which were shown in the decrease of an oxygen delivery to tissues, and the effectiveness decrease of the medical treatment in the period of a HSA.

An exploration of subgroups of mild cognitive impairment based on cognitive, neuropsychiatric and functional features: analysis of data from the National Alzheimer's Coordinating Center.

PubMed

Hanfelt, John J; Wuu, Joanne; Sollinger, Ann B; Greenaway, Melanie C; Lah, James J; Levey, Allan I; Goldstein, Felicia C

2011-11-01

To empirically expand the existing subtypes of mild cognitive impairment (MCI) by incorporating information on neuropsychiatric and functional features, and to assess whether cerebrovascular disease (CVD) risk factors are associated with any of these subgroups. Latent class analysis using 1,655 patients with MCI. Participants in the Uniform Data Set (UDS) from 29 National Institutes of Health-supported Alzheimer's Disease Centers. Patients with a consensus diagnosis of MCI from each center and with a Mini-Mental State Examination score of 22 or greater. UDS cognitive battery, Neuropsychiatric Inventory Questionnaire, and Functional Assessment Questionnaire administered at initial visit. Seven empirically based subgroups of MCI were identified: 1) minimally impaired (relative frequency, 12%); 2) amnestic only (16%); 3) amnestic with functional and neuropsychiatric features (16%); 4) amnestic multidomain (12%); 5) amnestic multidomain with functional and neuropsychiatric features (12%); 6) functional and neuropsychiatric features (15%); and 7) executive function and language impairments (18%). Two of these subgroups with functional and neuropsychiatric features were at least 3.8 times more likely than the minimally impaired subgroup to have a Rosen-Hachinski score of 4 or greater, an indicator of probable CVD. Findings suggest that there are several distinct phenotypes of MCI characterized by prominent cognitive features, prominent functional features, and neuropsychiatric features or a combination of all three. Subgroups with functional and neuropsychiatric features are significantly more likely to have CVD, which suggests that there may be distinct differences in disease etiology from the other phenotypes.

Effective Moment Feature Vectors for Protein Domain Structures

PubMed Central

Shi, Jian-Yu; Yiu, Siu-Ming; Zhang, Yan-Ning; Chin, Francis Yuk-Lun

2013-01-01

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100–400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity. PMID:24391828

Functioning: the third health indicator in the health system and the key indicator for rehabilitation.

PubMed

Stucki, Gerold; Bickenbach, Jerome

2017-02-01

In this methodological note on applying the ICF in rehabilitation, we introduce functioning as the third health indicator complementing the established indicators mortality and morbidity. Together, these three provide a complete set of indicators for monitoring the performance of health strategies in health systems. When applying functioning as the third health indicator across the five health strategies, it is fundamental to distinguish between biological health and lived health. For rehabilitation, functioning is the key indicator. Since we can now code mortality and morbidity data with the ICD, and functioning data with the ICF, and since given current plans to including functioning properties in the proposed ICD-11 revision, we should in the future be able to report on all three health indicators.

Semi-Local DFT Functionals with Exact-Exchange-Like Features: Beyond the AK13

NASA Astrophysics Data System (ADS)

Armiento, Rickard

The Armiento-Kümmel functional from 2013 (AK13) is a non-empirical semi-local exchange functional on generalized gradient approximation form (GGA) in Kohn-Sham (KS) density functional theory (DFT). Recent works have established that AK13 gives improved electronic-structure exchange features over other semi-local methods, with a qualitatively improved orbital description and band structure. For example, the Kohn-Sham band gap is greatly extended, as it is for exact exchange. This talk outlines recent efforts towards new exchange-correlation functionals based on, and extending, the AK13 design ideas. The aim is to improve the quantitative accuracy, the description of energetics, and to address other issues found with the original formulation. Swedish e-Science Research Centre (SeRC).

Enhancing insight in scientific problem solving by highlighting the functional features of prototypes: an fMRI study.

PubMed

Hao, Xin; Cui, Shuai; Li, Wenfu; Yang, Wenjing; Qiu, Jiang; Zhang, Qinglin

2013-10-09

Insight can be the first step toward creating a groundbreaking product. As evident in anecdotes and major inventions in history, heuristic events (heuristic prototypes) prompted inventors to acquire insight when solving problems. Bionic imitation in scientific innovation is an example of this kind of problem solving. In particular, heuristic prototypes (e.g., the lotus effect; the very high water repellence exhibited by lotus leaves) help solve insight problems (e.g., non-stick surfaces). We speculated that the biological functional feature of prototypes is a critical factor in inducing insightful scientific problem solving. In this functional magnetic resonance imaging (fMRI) study, we selected scientific innovation problems and utilized "learning prototypes-solving problems" two-phase paradigm to test the supposition. We also explored its neural mechanisms. Functional MRI data showed that the activation of the middle temporal gyrus (MTG, BA 37) and the middle occipital gyrus (MOG, BA 19) were associated with the highlighted functional feature condition. fMRI data also indicated that the MTG (BA 37) could be responsible for the semantic processing of functional features and for the formation of novel associations based on related functions. In addition, the MOG (BA 19) could be involved in the visual imagery of formation and application of function association between the heuristic prototype and problem. Our findings suggest that both semantic processing and visual imagery could be crucial components underlying scientific problem solving. © 2013 Elsevier B.V. All rights reserved.

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

PubMed

Cui, Zaixu; Gong, Gaolang

2018-06-02

Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accuracies. However, the effects of the ML regression algorithm and sample size on individualized behavioral/cognitive prediction performance have not been comprehensively assessed. To address this issue, the present study included six commonly used ML regression algorithms: ordinary least squares (OLS) regression, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic-net regression, linear support vector regression (LSVR), and relevance vector regression (RVR), to perform specific behavioral/cognitive predictions based on different sample sizes. Specifically, the publicly available resting-state functional MRI (rs-fMRI) dataset from the Human Connectome Project (HCP) was used, and whole-brain resting-state functional connectivity (rsFC) or rsFC strength (rsFCS) were extracted as prediction features. Twenty-five sample sizes (ranged from 20 to 700) were studied by sub-sampling from the entire HCP cohort. The analyses showed that rsFC-based LASSO regression performed remarkably worse than the other algorithms, and rsFCS-based OLS regression performed markedly worse than the other algorithms. Regardless of the algorithm and feature type, both the prediction accuracy and its stability exponentially increased with increasing sample size. The specific patterns of the observed algorithm and sample size effects were well replicated in the prediction using re-testing fMRI data, data processed by different imaging preprocessing schemes, and different behavioral/cognitive scores, thus indicating excellent robustness/generalization of the effects. The current findings provide critical insight into how the selected ML regression algorithm and sample size influence individualized predictions of

Key Features of the Intragraft Microenvironment that Determine Long-Term Survival Following Transplantation

PubMed Central

Bruneau, Sarah; Woda, Craig Bryan; Daly, Kevin Patrick; Boneschansker, Leonard; Jain, Namrata Gargee; Kochupurakkal, Nora; Contreras, Alan Gabriel; Seto, Tatsuichiro; Briscoe, David Michael

2012-01-01

In this review, we discuss how changes in the intragraft microenvironment serve to promote or sustain the development of chronic allograft rejection. We propose two key elements within the microenvironment that contribute to the rejection process. The first is endothelial cell proliferation and angiogenesis that serve to create abnormal microvascular blood flow patterns as well as local tissue hypoxia, and precedes endothelial-to-mesenchymal transition. The second is the overexpression of local cytokines and growth factors that serve to sustain inflammation and, in turn, function to promote a leukocyte-induced angiogenesis reaction. Central to both events is overexpression of vascular endothelial growth factor (VEGF), which is both pro-inflammatory and pro-angiogenic, and thus drives progression of the chronic rejection microenvironment. In our discussion, we focus on how inflammation results in angiogenesis and how leukocyte-induced angiogenesis is pathological. We also discuss how VEGF is a master control factor that fosters the development of the chronic rejection microenvironment. Overall, this review provides insight into the intragraft microenvironment as an important paradigm for future direction in the field. PMID:22566935

Generic decoding of seen and imagined objects using hierarchical visual features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-05-22

Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a set of features rendered invariant through hierarchical processing. We show that visual features, including those derived from a deep convolutional neural network, can be predicted from fMRI patterns, and that greater accuracy is achieved for low-/high-level features with lower-/higher-level visual areas, respectively. Predicted features are used to identify seen/imagined object categories (extending beyond decoder training) from a set of computed features for numerous object images. Furthermore, decoding of imagined objects reveals progressive recruitment of higher-to-lower visual representations. Our results demonstrate a homology between human and machine vision and its utility for brain-based information retrieval.

Transverse beam splitting made operational: Key features of the multiturn extraction at the CERN Proton Synchrotron

NASA Astrophysics Data System (ADS)

Huschauer, A.; Blas, A.; Borburgh, J.; Damjanovic, S.; Gilardoni, S.; Giovannozzi, M.; Hourican, M.; Kahle, K.; Le Godec, G.; Michels, O.; Sterbini, G.; Hernalsteens, C.

2017-06-01

Following a successful commissioning period, the multiturn extraction (MTE) at the CERN Proton Synchrotron (PS) has been applied for the fixed-target physics programme at the Super Proton Synchrotron (SPS) since September 2015. This exceptional extraction technique was proposed to replace the long-serving continuous transfer (CT) extraction, which has the drawback of inducing high activation in the ring. MTE exploits the principles of nonlinear beam dynamics to perform loss-free beam splitting in the horizontal phase space. Over multiple turns, the resulting beamlets are then transferred to the downstream accelerator. The operational deployment of MTE was rendered possible by the full understanding and mitigation of different hardware limitations and by redesigning the extraction trajectories and nonlinear optics, which was required due to the installation of a dummy septum to reduce the activation of the magnetic extraction septum. This paper focuses on these key features including the use of the transverse damper and the septum shadowing, which allowed a transition from the MTE study to a mature operational extraction scheme.

Designing for adaptation to novelty and change: functional information, emergent feature graphics, and higher-level control.

PubMed

Hajdukiewicz, John R; Vicente, Kim J

2002-01-01

Ecological interface design (EID) is a theoretical framework that aims to support worker adaptation to change and novelty in complex systems. Previous evaluations of EID have emphasized representativeness to enhance generalizability of results to operational settings. The research presented here is complementary, emphasizing experimental control to enhance theory building. Two experiments were conducted to test the impact of functional information and emergent feature graphics on adaptation to novelty and change in a thermal-hydraulic process control microworld. Presenting functional information in an interface using emergent features encouraged experienced participants to become perceptually coupled to the interface and thereby to exhibit higher-level control and more successful adaptation to unanticipated events. The absence of functional information or of emergent features generally led to lower-level control and less success at adaptation, the exception being a minority of participants who compensated by relying on analytical reasoning. These findings may have practical implications for shaping coordination in complex systems and fundamental implications for the development of a general unified theory of coordination for the technical, human, and social sciences. Actual or potential applications of this research include the design of human-computer interfaces that improve safety in complex sociotechnical systems.

Chromium Picolinate Does Not Improve Key Features of Metabolic Syndrome in Obese Nondiabetic Adults

PubMed Central

Iqbal, Nayyar; Cardillo, Serena; Volger, Sheri; Bloedon, LeAnne T.; Anderson, Richard A.; Boston, Raymond

2009-01-01

Abstract Background The use of chromium-containing dietary supplements is widespread among patients with type 2 diabetes. Chromium's effects in patients at high risk for developing diabetes, especially those with metabolic syndrome, is unknown. The objective of this study was to determine the effects of chromium picolinate (CrPic) on glucose metabolism in patients with metabolic syndrome. Method A double-blind, placebo-controlled, randomized trial was conducted at a U.S. academic medical center. Sixty three patients with National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III)-defined metabolic syndrome were included. The primary end point was a change in the insulin sensitivity index derived from a frequently sampled intravenous glucose tolerance test. Prespecified secondary end points included changes in other measurements of glucose metabolism, oxidative stress, fasting serum lipids, and high sensitivity C-reactive protein. Results After 16 weeks of CrPic treatment, there was no significant change in insulin sensitivity index between groups (P = 0.14). However, CrPic increased acute insulin response to glucose (P = 0.02). CrPic had no significant effect on other measures of glucose metabolism, body weight, serum lipids, or measures of inflammation and oxidative stress. Conclusion CrPic at 1000 μg/day does not improve key features of the metabolic syndrome in obese nondiabetic patients. PMID:19422140

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior

PubMed Central

Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-01-01

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information. PMID:29513219

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.

PubMed

Groen, Iris Ia; Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-03-07

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information.

Identifying key radiogenomic associations between DCE-MRI and micro-RNA expressions for breast cancer

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Kim, Renaid

2017-03-01

Understanding the key radiogenomic associations for breast cancer between DCE-MRI and micro-RNA expressions is the foundation for the discovery of radiomic features as biomarkers for assessing tumor progression and prognosis. We conducted a study to analyze the radiogenomic associations for breast cancer using the TCGA-TCIA data set. The core idea that tumor etiology is a function of the behavior of miRNAs is used to build the regression models. The associations based on regression are analyzed for three study outcomes: diagnosis, prognosis, and treatment. The diagnosis group consists of miRNAs associated with clinicopathologic features of breast cancer and significant aberration of expression in breast cancer patients. The prognosis group consists of miRNAs which are closely associated with tumor suppression and regulation of cell proliferation and differentiation. The treatment group consists of miRNAs that contribute significantly to the regulation of metastasis thereby having the potential to be part of therapeutic mechanisms. As a first step, important miRNA expressions were identified and their ability to classify the clinical phenotypes based on the study outcomes was evaluated using the area under the ROC curve (AUC) as a figure-of-merit. The key mapping between the selected miRNAs and radiomic features were determined using least absolute shrinkage and selection operator (LASSO) regression analysis within a two-loop leave-one-out cross-validation strategy. These key associations indicated a number of radiomic features from DCE-MRI to be potential biomarkers for the three study outcomes.

Home and Community Environmental Features, Activity Performance, and Community Participation among Older Adults with Functional Limitations

PubMed Central

Yang, Hsiang-Yu; Sanford, Jon A.

2012-01-01

This paper describes relationships among home and community environmental features, activity performance in the home, and community participation potential to support aging in place. A subset of data on older adults with functional limitations (N = 122), sixty three (63) with mobility and 59 with other limitations, were utilized in this study from a larger project's subject pool. Results showed significant and positive correlations between environmental barriers, activity dependence and difficulty at home, and less community participation in the mobility limitation group. While kitchen and bathroom features were most limiting to home performance, bathtub or shower was the only home feature, and destination social environment was the only community feature, that explained community participation. Compared to environmental features, home performance explained much more community participation. Study results provide detailed information about environmental features as well as types of home activities that can be prioritized as interventions for aging in place. PMID:22162808

Functional characterization of neotropical snakes peripheral blood leukocytes subsets: Linking flow cytometry cell features, microscopy images and serum corticosterone levels.

PubMed

de Carvalho, Marcelo Pires Nogueira; Queiroz-Hazarbassanov, Nicolle Gilda Teixeira; de Oliveira Massoco, Cristina; Sant'Anna, Sávio Stefanini; Lourenço, Mariana Mathias; Levin, Gabriel; Sogayar, Mari Cleide; Grego, Kathleen Fernandes; Catão-Dias, José Luiz

2017-09-01

Reptiles are the unique ectothermic amniotes, providing the key link between ectothermic anamniotes fish and amphibians, and endothermic birds and mammals; becoming an important group to study with the aim of providing significant knowledge into the evolutionary history of vertebrate immunity. Classification systems for reptiles' leukocytes have been described by their appearance rather than function, being still inconsistent. With the advent of modern techniques and the establishment of analytical protocols for snakes' blood by flow cytometry, we bring a qualitative and quantitative assessment of innate activities presented by snakes' peripheral blood leukocytes, thereby linking flow cytometric features with fluorescent and light microscopy images. Moreover, since corticosterone is an important immunomodulator in reptiles, hormone levels of all blood samples were measured. We provide novel and additional information which should contribute to better understanding of the development of the immune system of reptiles and vertebrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Role of Emotion in Musical Improvisation: An Analysis of Structural Features

PubMed Central

McPherson, Malinda J.; Lopez-Gonzalez, Monica; Rankin, Summer K.; Limb, Charles J.

2014-01-01

One of the primary functions of music is to convey emotion, yet how music accomplishes this task remains unclear. For example, simple correlations between mode (major vs. minor) and emotion (happy vs. sad) do not adequately explain the enormous range, subtlety or complexity of musically induced emotions. In this study, we examined the structural features of unconstrained musical improvisations generated by jazz pianists in response to emotional cues. We hypothesized that musicians would not utilize any universal rules to convey emotions, but would instead combine heterogeneous musical elements together in order to depict positive and negative emotions. Our findings demonstrate a lack of simple correspondence between emotions and musical features of spontaneous musical improvisation. While improvisations in response to positive emotional cues were more likely to be in major keys, have faster tempos, faster key press velocities and more staccato notes when compared to negative improvisations, there was a wide distribution for each emotion with components that directly violated these primary associations. The finding that musicians often combine disparate features together in order to convey emotion during improvisation suggests that structural diversity may be an essential feature of the ability of music to express a wide range of emotion. PMID:25144200

Functional and Genomic Features of Human Genes Mutated in Neuropsychiatric Disorders.

PubMed

Forero, Diego A; Prada, Carlos F; Perry, George

2016-01-01

In recent years, a large number of studies around the world have led to the identification of causal genes for hereditary types of common and rare neurological and psychiatric disorders. To explore the functional and genomic features of known human genes mutated in neuropsychiatric disorders. A systematic search was used to develop a comprehensive catalog of genes mutated in neuropsychiatric disorders (NPD). Functional enrichment and protein-protein interaction analyses were carried out. A false discovery rate approach was used for correction for multiple testing. We found several functional categories that are enriched among NPD genes, such as gene ontologies, protein domains, tissue expression, signaling pathways and regulation by brain-expressed miRNAs and transcription factors. Sixty six of those NPD genes are known to be druggable. Several topographic parameters of protein-protein interaction networks and the degree of conservation between orthologous genes were identified as significant among NPD genes. These results represent one of the first analyses of enrichment of functional categories of genes known to harbor mutations for NPD. These findings could be useful for a future creation of computational tools for prioritization of novel candidate genes for NPD.

Functional and Genomic Features of Human Genes Mutated in Neuropsychiatric Disorders

PubMed Central

Forero, Diego A.; Prada, Carlos F.; Perry, George

2016-01-01

Background: In recent years, a large number of studies around the world have led to the identification of causal genes for hereditary types of common and rare neurological and psychiatric disorders. Objective: To explore the functional and genomic features of known human genes mutated in neuropsychiatric disorders. Methods: A systematic search was used to develop a comprehensive catalog of genes mutated in neuropsychiatric disorders (NPD). Functional enrichment and protein-protein interaction analyses were carried out. A false discovery rate approach was used for correction for multiple testing. Results: We found several functional categories that are enriched among NPD genes, such as gene ontologies, protein domains, tissue expression, signaling pathways and regulation by brain-expressed miRNAs and transcription factors. Sixty six of those NPD genes are known to be druggable. Several topographic parameters of protein-protein interaction networks and the degree of conservation between orthologous genes were identified as significant among NPD genes. Conclusion: These results represent one of the first analyses of enrichment of functional categories of genes known to harbor mutations for NPD. These findings could be useful for a future creation of computational tools for prioritization of novel candidate genes for NPD. PMID:27990183

Key Features of Academic Detailing: Development of an Expert Consensus Using the Delphi Method.

PubMed

Yeh, James S; Van Hoof, Thomas J; Fischer, Michael A

2016-02-01

Academic detailing is an outreach education technique that combines the direct social marketing traditionally used by pharmaceutical representatives with unbiased content summarizing the best evidence for a given clinical issue. Academic detailing is conducted with clinicians to encourage evidence-based practice in order to improve the quality of care and patient outcomes. The adoption of academic detailing has increased substantially since the original studies in the 1980s. However, the lack of standard agreement on its implementation makes the evaluation of academic detailing outcomes challenging. To identify consensus on the key elements of academic detailing among a group of experts with varying experiences in academic detailing. This study is based on an online survey of 20 experts with experience in academic detailing. We used the Delphi process, an iterative and systematic method of developing consensus within a group. We conducted 3 rounds of online surveys, which addressed 72 individual items derived from a previous literature review of 5 features of academic detailing, including (1) content, (2) communication process, (3) clinicians targeted, (4) change agents delivering intervention, and (5) context for intervention. Nonrespondents were removed from later rounds of the surveys. For most questions, a 4-point ordinal scale was used for responses. We defined consensus agreement as 70% of respondents for a single rating category or 80% for dichotomized ratings. The overall survey response rate was 95% (54 of 57 surveys) and nearly 92% consensus agreement on the survey items (66 of 72 items) by the end of the Delphi exercise. The experts' responses suggested that (1) focused clinician education offering support for clinical decision-making is a key component of academic detailing, (2) detailing messages need to be tailored and provide feasible strategies and solutions to challenging cases, and (3) academic detailers need to develop specific skill sets

Key Features of Academic Detailing: Development of an Expert Consensus Using the Delphi Method

PubMed Central

Yeh, James S.; Van Hoof, Thomas J.; Fischer, Michael A.

2016-01-01

Background Academic detailing is an outreach education technique that combines the direct social marketing traditionally used by pharmaceutical representatives with unbiased content summarizing the best evidence for a given clinical issue. Academic detailing is conducted with clinicians to encourage evidence-based practice in order to improve the quality of care and patient outcomes. The adoption of academic detailing has increased substantially since the original studies in the 1980s. However, the lack of standard agreement on its implementation makes the evaluation of academic detailing outcomes challenging. Objective To identify consensus on the key elements of academic detailing among a group of experts with varying experiences in academic detailing. Methods This study is based on an online survey of 20 experts with experience in academic detailing. We used the Delphi process, an iterative and systematic method of developing consensus within a group. We conducted 3 rounds of online surveys, which addressed 72 individual items derived from a previous literature review of 5 features of academic detailing, including (1) content, (2) communication process, (3) clinicians targeted, (4) change agents delivering intervention, and (5) context for intervention. Nonrespondents were removed from later rounds of the surveys. For most questions, a 4-point ordinal scale was used for responses. We defined consensus agreement as 70% of respondents for a single rating category or 80% for dichotomized ratings. Results The overall survey response rate was 95% (54 of 57 surveys) and nearly 92% consensus agreement on the survey items (66 of 72 items) by the end of the Delphi exercise. The experts' responses suggested that (1) focused clinician education offering support for clinical decision-making is a key component of academic detailing, (2) detailing messages need to be tailored and provide feasible strategies and solutions to challenging cases, and (3) academic detailers need

Mapping feature-sensitivity and attentional modulation in human auditory cortex with functional magnetic resonance imaging

PubMed Central

Paltoglou, Aspasia E; Sumner, Christian J; Hall, Deborah A

2011-01-01

Feature-specific enhancement refers to the process by which selectively attending to a particular stimulus feature specifically increases the response in the same region of the brain that codes that stimulus property. Whereas there are many demonstrations of this mechanism in the visual system, the evidence is less clear in the auditory system. The present functional magnetic resonance imaging (fMRI) study examined this process for two complex sound features, namely frequency modulation (FM) and spatial motion. The experimental design enabled us to investigate whether selectively attending to FM and spatial motion enhanced activity in those auditory cortical areas that were sensitive to the two features. To control for attentional effort, the difficulty of the target-detection tasks was matched as closely as possible within listeners. Locations of FM-related and motion-related activation were broadly compatible with previous research. The results also confirmed a general enhancement across the auditory cortex when either feature was being attended to, as compared with passive listening. The feature-specific effects of selective attention revealed the novel finding of enhancement for the nonspatial (FM) feature, but not for the spatial (motion) feature. However, attention to spatial features also recruited several areas outside the auditory cortex. Further analyses led us to conclude that feature-specific effects of selective attention are not statistically robust, and appear to be sensitive to the choice of fMRI experimental design and localizer contrast. PMID:21447093

Hippocampal Sleep Features: Relations to Human Memory Function

PubMed Central

Ferrara, Michele; Moroni, Fabio; De Gennaro, Luigi; Nobili, Lino

2012-01-01

The recent spread of intracranial electroencephalographic (EEG) recording techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific patterns of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, non-REM sleep) in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples) that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate

Predicting Key Events in the Popularity Evolution of Online Information.

PubMed

Hu, Ying; Hu, Changjun; Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

Creating Concepts from Converging Features in Human Cortex

PubMed Central

Coutanche, Marc N.; Thompson-Schill, Sharon L.

2015-01-01

To make sense of the world around us, our brain must remember the overlapping features of millions of objects. Crucially, it must also represent each object's unique feature-convergence. Some theories propose that an integration area (or “convergence zone”) binds together separate features. We report an investigation of our knowledge of objects' features and identity, and the link between them. We used functional magnetic resonance imaging to record neural activity, as humans attempted to detect a cued fruit or vegetable in visual noise. Crucially, we analyzed brain activity before a fruit or vegetable was present, allowing us to interrogate top-down activity. We found that pattern-classification algorithms could be used to decode the detection target's identity in the left anterior temporal lobe (ATL), its shape in lateral occipital cortex, and its color in right V4. A novel decoding-dependency analysis revealed that identity information in left ATL was specifically predicted by the temporal convergence of shape and color codes in early visual regions. People with stronger feature-and-identity dependencies had more similar top-down and bottom-up activity patterns. These results fulfill three key requirements for a neural convergence zone: a convergence result (object identity), ingredients (color and shape), and the link between them. PMID:24692512

The crystal structure of mammalian inositol 1,3,4,5,6-pentakisphosphate 2-kinase reveals a new zinc-binding site and key features for protein function

PubMed Central

Franco-Echevarría, Elsa; Sanz-Aparicio, Julia; Brearley, Charles A.; González-Rubio, Juana M.; González, Beatriz

2017-01-01

Inositol 1,3,4,5,6-pentakisphosphate 2-kinases (IP5 2-Ks) are part of a family of enzymes in charge of synthesizing inositol hexakisphosphate (IP6) in eukaryotic cells. This protein and its product IP6 present many roles in cells, participating in mRNA export, embryonic development, and apoptosis. We reported previously that the full-length IP5 2-K from Arabidopsis thaliana is a zinc metallo-enzyme, including two separated lobes (the N- and C-lobes). We have also shown conformational changes in IP5 2-K and have identified the residues involved in substrate recognition and catalysis. However, the specific features of mammalian IP5 2-Ks remain unknown. To this end, we report here the first structure for a murine IP5 2-K in complex with ATP/IP5 or IP6. Our structural findings indicated that the general folding in N- and C-lobes is conserved with A. thaliana IP5 2-K. A helical scaffold in the C-lobe constitutes the inositol phosphate-binding site, which, along with the participation of the N-lobe, endows high specificity to this protein. However, we also noted large structural differences between the orthologues from these two eukaryotic kingdoms. These differences include a novel zinc-binding site and regions unique to the mammalian IP5 2-K, as an unexpected basic patch on the protein surface. In conclusion, our findings have uncovered distinct features of a mammalian IP5 2-K and set the stage for investigations into protein-protein or protein-RNA interactions important for IP5 2-K function and activity. PMID:28450399

Features of CRISPR-Cas Regulation Key to Highly Efficient and Temporally-Specific crRNA Production.

PubMed

Rodic, Andjela; Blagojevic, Bojana; Djordjevic, Magdalena; Severinov, Konstantin; Djordjevic, Marko

2017-01-01

Bacterial immune systems, such as CRISPR-Cas or restriction-modification (R-M) systems, affect bacterial pathogenicity and antibiotic resistance by modulating horizontal gene flow. A model system for CRISPR-Cas regulation, the Type I-E system from Escherichia coli , is silent under standard laboratory conditions and experimentally observing the dynamics of CRISPR-Cas activation is challenging. Two characteristic features of CRISPR-Cas regulation in E. coli are cooperative transcription repression of cas gene and CRISPR array promoters, and fast non-specific degradation of full length CRISPR transcripts (pre-crRNA). In this work, we use computational modeling to understand how these features affect the system expression dynamics. Signaling which leads to CRISPR-Cas activation is currently unknown, so to bypass this step, we here propose a conceptual setup for cas expression activation, where cas genes are put under transcription control typical for a restriction-modification (R-M) system and then introduced into a cell. Known transcription regulation of an R-M system is used as a proxy for currently unknown CRISPR-Cas transcription control, as both systems are characterized by high cooperativity, which is likely related to similar dynamical constraints of their function. We find that the two characteristic CRISPR-Cas control features are responsible for its temporally-specific dynamical response, so that the system makes a steep (switch-like) transition from OFF to ON state with a time-delay controlled by pre-crRNA degradation rate. We furthermore find that cooperative transcription regulation qualitatively leads to a cross-over to a regime where, at higher pre-crRNA processing rates, crRNA generation approaches the limit of an infinitely abrupt system induction. We propose that these dynamical properties are associated with rapid expression of CRISPR-Cas components and efficient protection of bacterial cells against foreign DNA. In terms of synthetic applications

Terrain feature recognition for synthetic aperture radar (SAR) imagery employing spatial attributes of targets

NASA Astrophysics Data System (ADS)

Iisaka, Joji; Sakurai-Amano, Takako

1994-08-01

This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.

Lactic acid fermentation as a tool to enhance the functional features of Echinacea spp

PubMed Central

2013-01-01

Background Extracts and products (roots and/or aerial parts) from Echinacea ssp. represent a profitable market sector for herbal medicines thanks to different functional features. Alkamides and polyacetylenes, phenols like caffeic acid and its derivatives, polysaccharides and glycoproteins are the main bioactive compounds of Echinacea spp. This study aimed at investigating the capacity of selected lactic acid bacteria to enhance the antimicrobial, antioxidant and immune-modulatory features of E. purpurea with the prospect of its application as functional food, dietary supplement or pharmaceutical preparation. Results Echinacea purpurea suspension (5%, wt/vol) in distilled water, containing 0.4% (wt/vol) yeast extract, was fermented with Lactobacillus plantarum POM1, 1MR20 or C2, previously selected from plant materials. Chemically acidified suspension, without bacterial inoculum, was used as the control to investigate functional features. Echinacea suspension fermented with Lb. plantarum C2 exhibited a marked antimicrobial activity towards Gram-positive and -negative bacteria. Compared to control, the water-soluble extract from Echinacea suspension fermented with Lactobacillus plantarum 1MR20 showed twice time higher radical scavenging activity on DPPH. Almost the same was found for the inhibition of oleic acid peroxidation. The methanol extract from Echinacea suspension had inherent antioxidant features but the activity of extract from the sample fermented with strain 1MR20 was the highest. The antioxidant activities were confirmed on Balb 3T3 mouse fibroblasts. Lactobacillus plantarum C2 and 1MR20 were used in association to ferment Echinacea suspension, and the water-soluble extract was subjected to ultra-filtration and purification through RP-FPLC. The antioxidant activity was distributed in a large number of fractions and proportional to the peptide concentration. The antimicrobial activity was detected only in one fraction, further subjected to nano

Quantum key distribution without the wavefunction

NASA Astrophysics Data System (ADS)

Niestegge, Gerd

A well-known feature of quantum mechanics is the secure exchange of secret bit strings which can then be used as keys to encrypt messages transmitted over any classical communication channel. It is demonstrated that this quantum key distribution allows a much more general and abstract access than commonly thought. The results include some generalizations of the Hilbert space version of quantum key distribution, but are based upon a general nonclassical extension of conditional probability. A special state-independent conditional probability is identified as origin of the superior security of quantum key distribution; this is a purely algebraic property of the quantum logic and represents the transition probability between the outcomes of two consecutive quantum measurements.

Predicting Key Events in the Popularity Evolution of Online Information

PubMed Central

Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the “burst”, “peak”, and “fade” key events together as a representative summary of popularity evolution. We propose a novel prediction task—predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify “burst”, “peak”, and “fade” in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution. PMID:28046121

Quantum Hash function and its application to privacy amplification in quantum key distribution, pseudo-random number generation and image encryption

NASA Astrophysics Data System (ADS)

Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min

2016-01-01

Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information.

Quantum Hash function and its application to privacy amplification in quantum key distribution, pseudo-random number generation and image encryption

PubMed Central

Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min

2016-01-01

Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information. PMID:26823196

Quantum Hash function and its application to privacy amplification in quantum key distribution, pseudo-random number generation and image encryption.

PubMed

Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min

2016-01-29

Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information.

Quantum key distribution network for multiple applications

NASA Astrophysics Data System (ADS)

Tajima, A.; Kondoh, T.; Ochi, T.; Fujiwara, M.; Yoshino, K.; Iizuka, H.; Sakamoto, T.; Tomita, A.; Shimamura, E.; Asami, S.; Sasaki, M.

2017-09-01

The fundamental architecture and functions of secure key management in a quantum key distribution (QKD) network with enhanced universal interfaces for smooth key sharing between arbitrary two nodes and enabling multiple secure communication applications are proposed. The proposed architecture consists of three layers: a quantum layer, key management layer and key supply layer. We explain the functions of each layer, the key formats in each layer and the key lifecycle for enabling a practical QKD network. A quantum key distribution-advanced encryption standard (QKD-AES) hybrid system and an encrypted smartphone system were developed as secure communication applications on our QKD network. The validity and usefulness of these systems were demonstrated on the Tokyo QKD Network testbed.

Strong nonadditivity as a key structure-activity relationship feature: distinguishing structural changes from assay artifacts.

PubMed

Kramer, Christian; Fuchs, Julian E; Liedl, Klaus R

2015-03-23

Nonadditivity in protein-ligand affinity data represents highly instructive structure-activity relationship (SAR) features that indicate structural changes and have the potential to guide rational drug design. At the same time, nonadditivity is a challenge for both basic SAR analysis as well as many ligand-based data analysis techniques such as Free-Wilson Analysis and Matched Molecular Pair analysis, since linear substituent contribution models inherently assume additivity and thus do not work in such cases. While structural causes for nonadditivity have been analyzed anecdotally, no systematic approaches to interpret and use nonadditivity prospectively have been developed yet. In this contribution, we lay the statistical framework for systematic analysis of nonadditivity in a SAR series. First, we develop a general metric to quantify nonadditivity. Then, we demonstrate the non-negligible impact of experimental uncertainty that creates apparent nonadditivity, and we introduce techniques to handle experimental uncertainty. Finally, we analyze public SAR data sets for strong nonadditivity and use recourse to the original publications and available X-ray structures to find structural explanations for the nonadditivity observed. We find that all cases of strong nonadditivity (ΔΔpKi and ΔΔpIC50 > 2.0 log units) with sufficient structural information to generate reasonable hypothesis involve changes in binding mode. With the appropriate statistical basis, nonadditivity analysis offers a variety of new attempts for various areas in computer-aided drug design, including the validation of scoring functions and free energy perturbation approaches, binding pocket classification, and novel features in SAR analysis tools.

Function Follows Form: Activation of Shape and Function Features during Object Identification

ERIC Educational Resources Information Center

Yee, Eiling; Huffstetler, Stacy; Thompson-Schill, Sharon L.

2011-01-01

Most theories of semantic memory characterize knowledge of a given object as comprising a set of semantic features. But how does conceptual activation of these features proceed during object identification? We present the results of a pair of experiments that demonstrate that object recognition is a dynamically unfolding process in which function…

Assessing Motor Skills as a Differentiating Feature between High Functioning Autism and Asperger's Disorder

ERIC Educational Resources Information Center

Cid, Maria R.

2011-01-01

The purpose of this research was to investigate if motor skills could be used as a differentiating feature between Asperger's Disorder (AD) and High Functioning (HFA) in children under the age of 9 years, 0 months, in order to provide additional information regarding the usefulness and validity of distinguishing these two disorders. There is…

Influence of contrast morphogenetic features of urban constructed soils on the functioning of Moscow green lawn urban ecosystems: analysis based on the field model experiment

NASA Astrophysics Data System (ADS)

Epikhina, Anna; Vizirskaya, Mariya; Mazirov, Ilya; Vasenev, Vyacheslav; Vasenev, Ivan; Valentini, Riccardo

2014-05-01

Green lawns are the key element of the urban environment. They occupy a considerable part of the city area and locate in different urban functional zones. Urban constructed soils under green lawns have a unique spatial variability in chemical and morphogenetic features. So far, there is lack of information on the influence of morphogenetic features of urban soils on the functioning of the green lawn ecosystems especially in Moscow - the biggest megalopolis in Europe. Urban lawns perform a number of principal functions including both aesthetic and environmental. The role of the green lawn ecosystems in global carbon cycle is one of their main environmental functions. It is traditionally assessed through carbon stocks and fluxes in the basic ecosystem components. So far, such a data for the urban lawn ecosystems of the Moscow megapolis is lacking. In addition to environmental functions, green lawns perform an important ornamental role, which is also a critical criterion of their optimal functioning. Considering the variability of driving factors, influencing green lawns in urban environment, we carry out the model experiment in order to analyze "pure" effect of soil morphogenetic features. The current study aimed to analyze the influence of contrast morphogenetic features of urban constructed soils on the environmental and aesthetic functions of lawn ecosystems in Moscow megapolis basing in the model experiment. We carry out the model experiment located at the experimental field of the Russian State Agrarian University. Special transparent containers developed for the experiment, provided an option to observe soil morphogenetic features dynamics, including the depth and material of the organic transformation. At the same soil body inside the containers was united with the outside environment through the system of holes in the bottom and walls. The set of urban constructed soils includ four contrast types of the top soil (turf (T), turf-sand (TSa), turf-soil (TSo) and

Development of fluorescent probes based on protection-deprotection of the key functional groups for biological imaging.

PubMed

Tang, Yonghe; Lee, Dayoung; Wang, Jiaoliang; Li, Guanhan; Yu, Jinghua; Lin, Weiying; Yoon, Juyoung

2015-08-07

Recently, the strategy of protection-deprotection of functional groups has been widely employed to design fluorescent probes, as the protection-deprotection of functional groups often induces a marked change in electronic properties. Significant advances have been made in the development of analyte-responsive fluorescent probes based on the protection-deprotection strategy. In this tutorial review, we highlight the representative examples of small-molecule based fluorescent probes for bioimaging, which are operated via the protection-deprotection of key functional groups such as aldehyde, hydroxyl, and amino functional groups reported from 2010 to 2014. The discussion includes the general protection-deprotection methods for aldehyde, hydroxyl, or amino groups, as well as the design strategies, sensing mechanisms, and deprotection modes of the representative fluorescent imaging probes applied to bio-imaging.

Identifying key features of effective active learning: the effects of writing and peer discussion.

PubMed

Linton, Debra L; Pangle, Wiline M; Wyatt, Kevin H; Powell, Karli N; Sherwood, Rachel E

2014-01-01

We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. © 2014 D. L. Linton et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Long-term assessment of facial features and functions needing more attention in treatment of Treacher Collins syndrome.

PubMed

Plomp, Raul G; Versnel, Sarah L; van Lieshout, Manouk J S; Poublon, Rene M L; Mathijssen, Irene M J

2013-08-01

This study aimed to determine which facial features and functions need more attention during surgical treatment of Treacher Collins syndrome (TCS) in the long term. A cross-sectional cohort study was conducted to compare 23 TCS patients with 206 controls (all≥18 years) regarding satisfaction with their face. The adjusted Body Cathexis Scale was used to determine satisfaction with the appearance of the different facial features and functions. Desire for further treatment of these items was questioned. For each patient an overview was made of all facial operations performed, the affected facial features and the objective severity of the facial deformities. Patients were least satisfied with the appearance of the ears, facial profile and eyelids and with the functions hearing and nasal patency (P<0.001). Residual deformity of the reconstructed facial areas remained a problem in mainly the orbital area. The desire for further treatment and dissatisfaction was high in the operated patients, predominantly for eyelid reconstructions. Another significant wish was for improvement of hearing. In patients with TCS, functional deficits of the face are shown to be as important as the facial appearance. Particularly nasal patency and hearing are frequently impaired and require routine screening and treatment from intake onwards. Furthermore, correction of ear deformities and midface hypoplasia should be offered and performed more frequently. Residual deformity and dissatisfaction remains a problem, especially in reconstructed eyelids. II. Copyright © 2013 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets.

PubMed

Yoo, Kwangsun; Rosenberg, Monica D; Hsu, Wei-Ting; Zhang, Sheng; Li, Chiang-Shan R; Scheinost, Dustin; Constable, R Todd; Chun, Marvin M

2018-02-15

Connectome-based predictive modeling (CPM; Finn et al., 2015; Shen et al., 2017) was recently developed to predict individual differences in traits and behaviors, including fluid intelligence (Finn et al., 2015) and sustained attention (Rosenberg et al., 2016a), from functional brain connectivity (FC) measured with fMRI. Here, using the CPM framework, we compared the predictive power of three different measures of FC (Pearson's correlation, accordance, and discordance) and two different prediction algorithms (linear and partial least square [PLS] regression) for attention function. Accordance and discordance are recently proposed FC measures that respectively track in-phase synchronization and out-of-phase anti-correlation (Meskaldji et al., 2015). We defined connectome-based models using task-based or resting-state FC data, and tested the effects of (1) functional connectivity measure and (2) feature-selection/prediction algorithm on individualized attention predictions. Models were internally validated in a training dataset using leave-one-subject-out cross-validation, and externally validated with three independent datasets. The training dataset included fMRI data collected while participants performed a sustained attention task and rested (N = 25; Rosenberg et al., 2016a). The validation datasets included: 1) data collected during performance of a stop-signal task and at rest (N = 83, including 19 participants who were administered methylphenidate prior to scanning; Farr et al., 2014a; Rosenberg et al., 2016b), 2) data collected during Attention Network Task performance and rest (N = 41, Rosenberg et al., in press), and 3) resting-state data and ADHD symptom severity from the ADHD-200 Consortium (N = 113; Rosenberg et al., 2016a). Models defined using all combinations of functional connectivity measure (Pearson's correlation, accordance, and discordance) and prediction algorithm (linear and PLS regression) predicted attentional abilities, with

Flexible feature interface for multimedia sources

DOEpatents

Coffland, Douglas R [Livermore, CA

2009-06-09

A flexible feature interface for multimedia sources system that includes a single interface for the addition of features and functions to multimedia sources and for accessing those features and functions from remote hosts. The interface utilizes the export statement: export "C" D11Export void FunctionName(int argc, char ** argv,char * result, SecureSession *ctrl) or the binary equivalent of the export statement.

Simple 2.5 GHz time-bin quantum key distribution

NASA Astrophysics Data System (ADS)

Boaron, Alberto; Korzh, Boris; Houlmann, Raphael; Boso, Gianluca; Rusca, Davide; Gray, Stuart; Li, Ming-Jun; Nolan, Daniel; Martin, Anthony; Zbinden, Hugo

2018-04-01

We present a 2.5 GHz quantum key distribution setup with the emphasis on a simple experimental realization. It features a three-state time-bin protocol based on a pulsed diode laser and a single intensity modulator. Implementing an efficient one-decoy scheme and finite-key analysis, we achieve record breaking secret key rates of 1.5 kbps over 200 km of standard optical fibers.

ClinicalKey: a point-of-care search engine.

PubMed

Vardell, Emily

2013-01-01

ClinicalKey is a new point-of-care resource for health care professionals. Through controlled vocabulary, ClinicalKey offers a cross section of resources on diseases and procedures, from journals to e-books and practice guidelines to patient education. A sample search was conducted to demonstrate the features of the database, and a comparison with similar tools is presented.

Visual perceptual training reconfigures post-task resting-state functional connectivity with a feature-representation region.

PubMed

Sarabi, Mitra Taghizadeh; Aoki, Ryuta; Tsumura, Kaho; Keerativittayayut, Ruedeerat; Jimura, Koji; Nakahara, Kiyoshi

2018-01-01

The neural mechanisms underlying visual perceptual learning (VPL) have typically been studied by examining changes in task-related brain activation after training. However, the relationship between post-task "offline" processes and VPL remains unclear. The present study examined this question by obtaining resting-state functional magnetic resonance imaging (fMRI) scans of human brains before and after a task-fMRI session involving visual perceptual training. During the task-fMRI session, participants performed a motion coherence discrimination task in which they judged the direction of moving dots with a coherence level that varied between trials (20, 40, and 80%). We found that stimulus-induced activation increased with motion coherence in the middle temporal cortex (MT+), a feature-specific region representing visual motion. On the other hand, stimulus-induced activation decreased with motion coherence in the dorsal anterior cingulate cortex (dACC) and bilateral insula, regions involved in decision making under perceptual ambiguity. Moreover, by comparing pre-task and post-task rest periods, we revealed that resting-state functional connectivity (rs-FC) with the MT+ was significantly increased after training in widespread cortical regions including the bilateral sensorimotor and temporal cortices. In contrast, rs-FC with the MT+ was significantly decreased in subcortical regions including the thalamus and putamen. Importantly, the training-induced change in rs-FC was observed only with the MT+, but not with the dACC or insula. Thus, our findings suggest that perceptual training induces plastic changes in offline functional connectivity specifically in brain regions representing the trained visual feature, emphasising the distinct roles of feature-representation regions and decision-related regions in VPL.

Basic features of the pion valence-quark distribution function

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

Chang, Lei; Mezrag, Cédric; Moutarde, Hervé

2014-10-07

The impulse-approximation expression used hitherto to define the pion's valence-quark distribution function is flawed because it omits contributions from the gluons which bind quarks into the pion. A corrected leading-order expression produces the model-independent result that quarks dressed via the rainbow–ladder truncation, or any practical analogue, carry all the pion's light-front momentum at a characteristic hadronic scale. Corrections to the leading contribution may be divided into two classes, responsible for shifting dressed-quark momentum into glue and sea-quarks. Working with available empirical information, we use an algebraic model to express the principal impact of both classes of corrections. This enables amore » realistic comparison with experiment that allows us to highlight the basic features of the pion's measurable valence-quark distribution, q π(x); namely, at a characteristic hadronic scale, q π(x)~(1-x) 2 for x≳0.85; and the valence-quarks carry approximately two-thirds of the pion's light-front momentum.« less

MRIVIEW: An interactive computational tool for investigation of brain structure and function

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

Ranken, D.; George, J.

MRIVIEW is a software system which uses image processing and visualization to provide neuroscience researchers with an integrated environment for combining functional and anatomical information. Key features of the software include semi-automated segmentation of volumetric head data and an interactive coordinate reconciliation method which utilizes surface visualization. The current system is a precursor to a computational brain atlas. We describe features this atlas will incorporate, including methods under development for visualizing brain functional data obtained from several different research modalities.

Parrots as key multilinkers in ecosystem structure and functioning.

PubMed

Blanco, Guillermo; Hiraldo, Fernando; Rojas, Abraham; Dénes, Francisco V; Tella, José L

2015-09-01

Mutually enhancing organisms can become reciprocal determinants of their distribution, abundance, and demography and thus influence ecosystem structure and dynamics. In addition to the prevailing view of parrots (Psittaciformes) as plant antagonists, we assessed whether they can act as plant mutualists in the dry tropical forest of the Bolivian inter-Andean valleys, an ecosystem particularly poor in vertebrate frugivores other than parrots (nine species). We hypothesised that if interactions between parrots and their food plants evolved as primarily or facultatively mutualistic, selection should have acted to maximize the strength of their interactions by increasing the amount and variety of resources and services involved in particular pairwise and community-wide interaction contexts. Food plants showed different growth habits across a wide phylogenetic spectrum, implying that parrots behave as super-generalists exploiting resources differing in phenology, type, biomass, and rewards from a high diversity of plants (113 species from 38 families). Through their feeding activities, parrots provided multiple services acting as genetic linkers, seed facilitators for secondary dispersers, and plant protectors, and therefore can be considered key mutualists with a pervasive impact on plant assemblages. The number of complementary and redundant mutualistic functions provided by parrots to each plant species was positively related to the number of different kinds of food extracted from them. These mutually enhancing interactions were reflected in species-level properties (e.g., biomass or dominance) of both partners, as a likely consequence of the temporal convergence of eco-(co)evolutionary dynamics shaping the ongoing structure and organization of the ecosystem. A full assessment of the, thus far largely overlooked, parrot-plant mutualisms and other ecological linkages could change the current perception of the role of parrots in the structure, organization, and

Enhancing Critical Infrastructure and Key Resources (CIKR) Level-0 Physical Process Security Using Field Device Distinct Native Attribute Features

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

Lopez, Juan; Liefer, Nathan C.; Busho, Colin R.

Here, the need for improved Critical Infrastructure and Key Resource (CIKR) security is unquestioned and there has been minimal emphasis on Level-0 (PHY Process) improvements. Wired Signal Distinct Native Attribute (WS-DNA) Fingerprinting is investigated here as a non-intrusive PHY-based security augmentation to support an envisioned layered security strategy. Results are based on experimental response collections from Highway Addressable Remote Transducer (HART) Differential Pressure Transmitter (DPT) devices from three manufacturers (Yokogawa, Honeywell, Endress+Hauer) installed in an automated process control system. Device discrimination is assessed using Time Domain (TD) and Slope-Based FSK (SB-FSK) fingerprints input to Multiple Discriminant Analysis, Maximum Likelihood (MDA/ML)more » and Random Forest (RndF) classifiers. For 12 different classes (two devices per manufacturer at two distinct set points), both classifiers performed reliably and achieved an arbitrary performance benchmark of average cross-class percent correct of %C > 90%. The least challenging cross-manufacturer results included near-perfect %C ≈ 100%, while the more challenging like-model (serial number) discrimination results included 90%< %C < 100%, with TD Fingerprinting marginally outperforming SB-FSK Fingerprinting; SB-FSK benefits from having less stringent response alignment and registration requirements. The RndF classifier was most beneficial and enabled reliable selection of dimensionally reduced fingerprint subsets that minimize data storage and computational requirements. The RndF selected feature sets contained 15% of the full-dimensional feature sets and only suffered a worst case %CΔ = 3% to 4% performance degradation.« less

Salient features of the ciliated organ of asymmetry

PubMed Central

Amack, Jeffrey D.

2014-01-01

Many internal organs develop distinct left and right sides that are essential for their functions. In several vertebrate embryos, motile cilia generate an asymmetric fluid flow that plays an important role in establishing left-right (LR) signaling cascades. These ‘LR cilia’ are found in the ventral node and posterior notochordal plate in mammals, the gastrocoel roof plate in amphibians and Kupffer’s vesicle in teleost fish. I consider these transient ciliated structures as the ‘organ of asymmetry’ that directs LR patterning of the developing embryo. Variations in size and morphology of the organ of asymmetry in different vertebrate species have raised questions regarding the fundamental features that are required for LR determination. Here, I review current models for how LR asymmetry is established in vertebrates, discuss the cellular architecture of the ciliated organ of asymmetry and then propose key features of this organ that are critical for orienting the LR body axis. PMID:24481178

The functional characterization and comparison of two single CRD containing C-type lectins with novel and typical key motifs from Portunus trituberculatus.

PubMed

Huang, Mengmeng; Mu, Changkao; Wu, Yuehong; Ye, Fei; Wang, Dan; Sun, Cong; Lv, Zhengbing; Han, Bingnan; Wang, Chunlin; Xu, Xue-Wei

2017-11-01

C-type lectins are a superfamily of Ca 2+ -dependent carbohydrate-recognition proteins, which play crucial roles in innate immunity including nonself-recognition and pathogen elimination. In the present study, two single-CRD containing C-type lectins were identified from swimming crab Portunus trituberculatus (designated as PtCTL-2 and PtCTL-3). The open reading frame (ORF) of PtCTL-2 encoded polypeptides of 485 amino acids with a signal peptide and a single carbohydrate-recognition domain (CRD), while PtCTL-3's ORF encoded polypeptides of 241 amino acids with a coiled-coil region and a single-CRD. The key motifs determining carbohydrate binding specificity in PtCTL-2 and PtCTL-3 were EPR (Glu-Pro-Arg) and QPD (Gln-Pro-Asp). EPR is a motif being identified for the first time, whereas QPD is a typical motif in C-type lectins. Different PAMPs binding features of the two recombinant proteins - PtCTL-2 (rPtCTL-2) and PtCTL-3 (rPtCTL-3) have been observed in our experiments. rPtCTL-2 could bind three pathogen-associated molecular patterns (PAMPs) with relatively high affinity, including glucan, lipopolysaccharide (LPS) and peptidoglycan (PGN), while rPtCTL-3 could barely bind any of them. However, rPtCTL-2 could bind seven kinds of microbes and rPtCTL-3 could bind six kinds in microbe binding assay. Moreover, rPtCTL-2 and rPtCTL-3 exhibited similar agglutination activity against Gram-positive bacteria, Gram-negative bacteria and fungi in agglutination assay. All these results illustrated that PtCTL-2 and PtCTL-3 could function as important pattern-recognition receptors (PRR) with broad nonself-recognition spectrum involved in immune defense against invaders. In addition, the results of carbohydrate binding specificity showed that PtCTL-2 with novel key motif had broad carbohydrate binding specificity, while PtCTL-3 with typical key motif possessed different carbohydrate binding specificity from the classical binding rule. Furthermore, PtCTL-2 and PtCTL-3 could also

25 CFR 502.14 - Key employee.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 2 2010-04-01 2010-04-01 false Key employee. 502.14 Section 502.14 Indians NATIONAL....14 Key employee. Key employee means: (a) A person who performs one or more of the following functions... gaming operation. (d) Any other person designated by the tribe as a key employee. [57 FR 12392, Apr. 9...

A computational analysis of the three isoforms of glutamate dehydrogenase reveals structural features of the isoform EC 1.4.1.4 supporting a key role in ammonium assimilation by plants

PubMed Central

Jaspard, Emmanuel

2006-01-01

Background There are three isoforms of glutamate dehydrogenase. The isoform EC 1.4.1.4 (GDH4) catalyses glutamate synthesis from 2-oxoglutarate and ammonium, using NAD(P)H. Ammonium assimilation is critical for plant growth. Although GDH4 from animals and prokaryotes are well characterized, there are few data concerning plant GDH4, even from those whose genomes are well annotated. Results A large set of the three GDH isoforms was built resulting in 116 non-redundant full polypeptide sequences. A computational analysis was made to gain more information concerning the structure – function relationship of GDH4 from plants (Eukaryota, Viridiplantae). The tested plant GDH4 sequences were the two ones known to date, those of Chlorella sorokiniana. This analysis revealed several structural features specific of plant GDH4: (i) the lack of a structure called "antenna"; (ii) the NAD(P)-binding motif GAGNVA; and (iii) a second putative coenzyme-binding motif GVLTGKG together with four residues involved in the binding of the reduced form of NADP. Conclusion A number of structural features specific of plant GDH4 have been found. The results reinforce the probable key role of GDH4 in ammonium assimilation by plants. Reviewers This article was reviewed by Tina Bakolitsa (nominated by Eugene Koonin), Martin Jambon (nominated by Laura Landweber), Sandor Pangor and Franck Eisenhaber. PMID:17173671

High Precision Prediction of Functional Sites in Protein Structures

PubMed Central

Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

2014-01-01

We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

The Plant Peptidome: An Expanding Repertoire of Structural Features and Biological Functions[OPEN

PubMed Central

Tavormina, Patrizia; De Coninck, Barbara; Nikonorova, Natalia; De Smet, Ive; Cammue, Bruno P.A.

2015-01-01

Peptides fulfill a plethora of functions in plant growth, development, and stress responses. They act as key components of cell-to-cell communication, interfere with signaling and response pathways, or display antimicrobial activity. Strikingly, both the diversity and amount of plant peptides have been largely underestimated. Most characterized plant peptides to date acting as small signaling peptides or antimicrobial peptides are derived from nonfunctional precursor proteins. However, evidence is emerging on peptides derived from a functional protein, directly translated from small open reading frames (without the involvement of a precursor) or even encoded by primary transcripts of microRNAs. These novel types of peptides further add to the complexity of the plant peptidome, even though their number is still limited and functional characterization as well as translational evidence are often controversial. Here, we provide a comprehensive overview of the reported types of plant peptides, including their described functional and structural properties. We propose a novel, unifying peptide classification system to emphasize the enormous diversity in peptide synthesis and consequent complexity of the still expanding knowledge on the plant peptidome. PMID:26276833

Visualizing chemical functionality in plant cell walls.

PubMed

Zeng, Yining; Himmel, Michael E; Ding, Shi-You

2017-01-01

Understanding plant cell wall cross-linking chemistry and polymeric architecture is key to the efficient utilization of biomass in all prospects from rational genetic modification to downstream chemical and biological conversion to produce fuels and value chemicals. In fact, the bulk properties of cell wall recalcitrance are collectively determined by its chemical features over a wide range of length scales from tissue, cellular to polymeric architectures. Microscopic visualization of cell walls from the nanometer to the micrometer scale offers an in situ approach to study their chemical functionality considering its spatial and chemical complexity, particularly the capabilities of characterizing biomass non-destructively and in real-time during conversion processes. Microscopic characterization has revealed heterogeneity in the distribution of chemical features, which would otherwise be hidden in bulk analysis. Key microscopic features include cell wall type, wall layering, and wall composition-especially cellulose and lignin distributions. Microscopic tools, such as atomic force microscopy, stimulated Raman scattering microscopy, and fluorescence microscopy, have been applied to investigations of cell wall structure and chemistry from the native wall to wall treated by thermal chemical pretreatment and enzymatic hydrolysis. While advancing our current understanding of plant cell wall recalcitrance and deconstruction, microscopic tools with improved spatial resolution will steadily enhance our fundamental understanding of cell wall function.

Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features.

PubMed

Youji Feng; Lixin Fan; Yihong Wu

2016-01-01

The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key

Functional Detachment of Totalitarian Nazi Architecture

NASA Astrophysics Data System (ADS)

Antoszczyszyn, Marek

2017-10-01

The paper describes the systematization process of architectural styles in use during Nazi period in Germany between 1933-45. In the results of the research some regularity about strict concern between function & styling has been observed. Using comparison & case study as well as analytical methods there were pointed out characteristic features of more than 500 objects’ architectural appearance that helped to specify their styling & group them into architectural trends. Ultimately the paper proves that the found trends of architectural styling could be collected by functional detachment key. This observation explains easy to recognize even nowadays traceability - so characteristic to Nazi German architecture. Facing today pluralism in architecture, the findings could be a helpful key in the organization of spatial architectural identification process.

Tensor-driven extraction of developmental features from varying paediatric EEG datasets.

PubMed

Kinney-Lang, Eli; Spyrou, Loukianos; Ebied, Ahmed; Chin, Richard Fm; Escudero, Javier

2018-05-21

Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usability of such technologies. Taking advantage of the multi-dimensional structure of EEG data through tensor analysis may offer a framework for extracting relevant developmental features of paediatric datasets. A proof of concept is demonstrated through identifying latent developmental features in resting-state EEG. Approach. Three paediatric datasets (n = 50, 17, 44) were analyzed using a two-step constrained parallel factor (PARAFAC) tensor decomposition. Subject age was used as a proxy measure of development. Classification used support vector machines (SVM) to test if PARAFAC identified features could predict subject age. The results were cross-validated within each dataset. Classification analysis was complemented by visualization of the high-dimensional feature structures using t-distributed Stochastic Neighbour Embedding (t-SNE) maps. Main Results. Development-related features were successfully identified for the developmental conditions of each dataset. SVM classification showed the identified features could accurately predict subject at a significant level above chance for both healthy and impaired populations. t-SNE maps revealed suitable tensor factorization was key in extracting the developmental features. Significance. The described methods are a promising tool for identifying latent developmental features occurring throughout childhood EEG. © 2018 IOP Publishing Ltd.

Ocean feature recognition using genetic algorithms with fuzzy fitness functions (GA/F3)

NASA Technical Reports Server (NTRS)

Ankenbrandt, C. A.; Buckles, B. P.; Petry, F. E.; Lybanon, M.

1990-01-01

A model for genetic algorithms with semantic nets is derived for which the relationships between concepts is depicted as a semantic net. An organism represents the manner in which objects in a scene are attached to concepts in the net. Predicates between object pairs are continuous valued truth functions in the form of an inverse exponential function (e sub beta lxl). 1:n relationships are combined via the fuzzy OR (Max (...)). Finally, predicates between pairs of concepts are resolved by taking the average of the combined predicate values of the objects attached to the concept at the tail of the arc representing the predicate in the semantic net. The method is illustrated by applying it to the identification of oceanic features in the North Atlantic.

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Key Microbiota Identification Using Functional Gene Analysis during Pepper (Piper nigrum L.) Peeling.

PubMed

Zhang, Jiachao; Hu, Qisong; Xu, Chuanbiao; Liu, Sixin; Li, Congfa

2016-01-01

Pepper pericarp microbiota plays an important role in the pepper peeling process for the production of white pepper. We collected pepper samples at different peeling time points from Hainan Province, China, and used a metagenomic approach to identify changes in the pericarp microbiota based on functional gene analysis. UniFrac distance-based principal coordinates analysis revealed significant changes in the pericarp microbiota structure during peeling, which were attributed to increases in bacteria from the genera Selenomonas and Prevotella. We identified 28 core operational taxonomic units at each time point, mainly belonging to Selenomonas, Prevotella, Megasphaera, Anaerovibrio, and Clostridium genera. The results were confirmed by quantitative polymerase chain reaction. At the functional level, we observed significant increases in microbial features related to acetyl xylan esterase and pectinesterase for pericarp degradation during peeling. These findings offer a new insight into biodegradation for pepper peeling and will promote the development of the white pepper industry.

Key Microbiota Identification Using Functional Gene Analysis during Pepper (Piper nigrum L.) Peeling

PubMed Central

Xu, Chuanbiao; Liu, Sixin; Li, Congfa

2016-01-01

Pepper pericarp microbiota plays an important role in the pepper peeling process for the production of white pepper. We collected pepper samples at different peeling time points from Hainan Province, China, and used a metagenomic approach to identify changes in the pericarp microbiota based on functional gene analysis. UniFrac distance-based principal coordinates analysis revealed significant changes in the pericarp microbiota structure during peeling, which were attributed to increases in bacteria from the genera Selenomonas and Prevotella. We identified 28 core operational taxonomic units at each time point, mainly belonging to Selenomonas, Prevotella, Megasphaera, Anaerovibrio, and Clostridium genera. The results were confirmed by quantitative polymerase chain reaction. At the functional level, we observed significant increases in microbial features related to acetyl xylan esterase and pectinesterase for pericarp degradation during peeling. These findings offer a new insight into biodegradation for pepper peeling and will promote the development of the white pepper industry. PMID:27768750

A feature illustration and application of azimuthal P receiver function patterns

NASA Astrophysics Data System (ADS)

Eckhardt, C.; Rabbel, W.

2009-12-01

Based on a synthetic catalog of thirty azimuthal patterns of P receiver functions for crustal structures down to thirty km depth we have summarized and illustrated the most important azimuthal features. We have constructed five model classes encompassing (an-)isotropic horizontal and dipping layers. The model classes were initialized by in situ observations of three deep reflection seismic profiles (DEKORP) of varying high reflective zones and a spiral shaped foliation scheme of an upper crustal bore hole out of the German Continental Deep Drilling Program (KTB). Up to fourteen azimuthal features were extracted out of the synthetic patterns and could be grouped into an already known fundamental part, a multiple part and into an extension part. Each feature was rated by a specific grade A, B, C to inform about the type of its initialization ((an-) isotropy and/or layer dipping). We have evaluated the fourteen features on the synthetic patterns to apply a hierarchical classification. From the classification of the model objects we found that nearly eighty percent of the models are well explained by the fundamental part. The hierarchical order of the model objects can be used as a template to screen real observed azimuthal patterns to find a starting model for a forward modeling or an inversion procedure. For one station of the German Regional Seismic Network (GRSN) we have evaluated the features and screened them through the template. A forward simulation of the azimuthal pattern, using the modified first found model explanation out of the hierarchical order for station MOX, leads to a good coincidence between the real and the simulated pattern. The final 1D model could be divided into an upper crustal part (8 km deep) with an axis of symmetry tilt of 55° and 20°NW trend (direction of axis tilt) and a lower crustal part (24 km thickness) with an axis of symmetry of increasing tilt from 55° to 85° and a trend orientation of 20°SE. For the simulation we have

Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity

PubMed Central

Mooney, Catherine; Haslam, Niall J.; Pollastri, Gianluca; Shields, Denis C.

2012-01-01

The conventional wisdom is that certain classes of bioactive peptides have specific structural features that endow their particular functions. Accordingly, predictions of bioactivity have focused on particular subgroups, such as antimicrobial peptides. We hypothesized that bioactive peptides may share more general features, and assessed this by contrasting the predictive power of existing antimicrobial predictors as well as a novel general predictor, PeptideRanker, across different classes of peptides. We observed that existing antimicrobial predictors had reasonable predictive power to identify peptides of certain other classes i.e. toxin and venom peptides. We trained two general predictors of peptide bioactivity, one focused on short peptides (4–20 amino acids) and one focused on long peptides ( amino acids). These general predictors had performance that was typically as good as, or better than, that of specific predictors. We noted some striking differences in the features of short peptide and long peptide predictions, in particular, high scoring short peptides favour phenylalanine. This is consistent with the hypothesis that short and long peptides have different functional constraints, perhaps reflecting the difficulty for typical short peptides in supporting independent tertiary structure. We conclude that there are general shared features of bioactive peptides across different functional classes, indicating that computational prediction may accelerate the discovery of novel bioactive peptides and aid in the improved design of existing peptides, across many functional classes. An implementation of the predictive method, PeptideRanker, may be used to identify among a set of peptides those that may be more likely to be bioactive. PMID:23056189

Functional source separation and hand cortical representation for a brain–computer interface feature extraction

PubMed Central

Tecchio, Franca; Porcaro, Camillo; Barbati, Giulia; Zappasodi, Filippo

2007-01-01

A brain–computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI features – spatial and time-frequency properties – are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This

Key Features of the Deployed NPP/NPOESS Ground System

NASA Astrophysics Data System (ADS)

Heckmann, G.; Grant, K. D.; Mulligan, J. E.

2010-12-01

The National Oceanic & Atmospheric Administration (NOAA), Department of Defense (DoD), and National Aeronautics & Space Administration (NASA) are jointly acquiring the next-generation weather/environmental satellite system; the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NPOESS replaces the current NOAA Polar-orbiting Operational Environmental Satellites (POES) and DoD Defense Meteorological Satellite Program (DMSP). NPOESS satellites carry sensors to collect meteorological, oceanographic, climatological, and solar-geophysical data of the earth, atmosphere, and space. The ground data processing segment is the Interface Data Processing Segment (IDPS), developed by Raytheon Intelligence & Information Systems (IIS). The IDPS processes NPOESS Preparatory Project (NPP)/NPOESS satellite data to provide environmental data products/records (EDRs) to NOAA and DoD processing centers operated by the US government. The IDPS will process EDRs beginning with NPP and continuing through the lifetime of the NPOESS system. The command & telemetry segment is the Command, Control & Communications Segment (C3S), also developed by Raytheon IIS. C3S is responsible for managing the overall NPP/NPOESS missions from control & status of the space and ground assets to ensuring delivery of timely, high quality data from the Space Segment to IDPS for processing. In addition, the C3S provides the globally-distributed ground assets needed to collect and transport mission, telemetry, and command data between the satellites and processing locations. The C3S provides all functions required for day-to-day satellite commanding & state-of-health monitoring, and delivery of Stored Mission Data to each Central IDP for data products development and transfer to system subscribers. The C3S also monitors and reports system-wide health & status and data communications with external systems and between the segments. The C3S & IDPS segments were delivered & transitioned to

The key actors maintaining elders in functional autonomy in Bobo-Dioulasso (Burkina Faso)

PubMed Central

2014-01-01

Background Globally, a significant increase in functional disability among the elderly is expected in the near future. It is therefore vital to begin considering how Sub-Saharan Africa countries can best start building or strengthening the care and support system for that target population. Study objectives are: 1) identify the key actors of the social system who maintain elders in functional autonomy at home in Bobo-Dioulasso (Burkina Faso) and 2) to describe the functional status of older people living at home. Methods We conducted a longitudinal descriptive study among the elderly aged 60 and above (351). Their functional status was evaluated using the Functional Autonomy Measurement System (SMAF). Data analysis was done using the statistical software package STATA (SE11). Results In Bobo-Dioulasso, 68% of seniors have good functional capacity or a slight incapacity and 32% have moderate to severe incapacities. Older people die before (3%) or during (14%) moderate to severe disabilities. This would mean that the quality of medical and/or social care is not good for maintaining functional autonomy of older people with moderate to severe disabilities. Two main groups of people contribute to maintain elders in functional autonomy: the elderly themselves and their family. Community, private or public structures for maintaining elders in functional autonomy are non-existent. The social system for maintaining elders in functional autonomy is incomplete and failing. In case of functional handicap at home, the elders die. But stakeholders are not conscious of this situation; they believe that this system is good for maintaining elders in functional autonomy. Conclusion It is likely that the absence of formal care and support structure likely shortens the lifespan of severely disabled older people. Stakeholders have not yet looked at this possibility. The stakeholders should seriously think about: 1) how to establish the third level of actors who can fulfill the needs to

Bag-of-features based medical image retrieval via multiple assignment and visual words weighting.

PubMed

Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

2011-11-01

Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights.

[Standardization of the terms for Chinese herbal functions based on functional targeting].

PubMed

Xiao, Bin; Tao, Ou; Gu, Hao; Wang, Yun; Qiao, Yan-Jiang

2011-03-01

Functional analysis concisely summarizes and concentrates on the therapeutic characteristics and features of Chinese herbal medicine. Standardization of the terms for Chinese herbal functions not only plays a key role in modern research and development of Chinese herbal medicine, but also has far-reaching clinical applications. In this paper, a new method for standardizing the terms for Chinese herbal function was proposed. Firstly, functional targets were collected. Secondly, the pathological conditions and the mode of action of every functional target were determined by analyzing the references. Thirdly, the relationships between the pathological condition and the mode of action were determined based on Chinese medicine theory and data. This three-step approach allows for standardization of the terms for Chinese herbal functions. Promoting the standardization of Chinese medicine terms will benefit the overall clinical application of Chinese herbal medicine.

Novel Basic Protein, PfN23, Functions as Key Macromolecule during Nacre Formation*

PubMed Central

Fang, Dong; Pan, Cong; Lin, Huijuan; Lin, Ya; Zhang, Guiyou; Wang, Hongzhong; He, Maoxian; Xie, Liping; Zhang, Rongqing

2012-01-01

The fine microstructure of nacre (mother of pearl) illustrates the beauty of nature. Proteins found in nacre were believed to be “natural hands” that control nacre formation. In the classical view of nacre formation, nucleation of the main minerals, calcium carbonate, is induced on and by the acidic proteins in nacre. However, the basic proteins were not expected to be components of nacre. Here, we reported that a novel basic protein, PfN23, was a key accelerator in the control over crystal growth in nacre. The expression profile, in situ immunostaining, and in vitro immunodetection assays showed that PfN23 was localized within calcium carbonate crystals in the nacre. Knocking down the expression of PfN23 in adults via double-stranded RNA injection led to a disordered nacre surface in adults. Blocking the translation of PfN23 in embryos using morpholino oligomers led to the arrest of larval development. The in vitro crystallization assay showed that PfN23 increases the rate of calcium carbonate deposition and induced the formation of aragonite crystals with characteristics close to nacre. In addition, we constructed the peptides and truncations of different regions of this protein and found that the positively charged C-terminal region was a key region for the function of PfN23 Taken together, the basic protein PfN23 may be a key accelerator in the control of crystal growth in nacre. This provides a valuable balance to the classic view that acidic proteins control calcium carbonate deposition in nacre. PMID:22416139

PredictProtein—an open resource for online prediction of protein structural and functional features

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

Information verification cryptosystem using one-time keys based on double random phase encoding and public-key cryptography

NASA Astrophysics Data System (ADS)

Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

2016-08-01

A novel image encryption system based on double random phase encoding (DRPE) and RSA public-key algorithm is proposed. The main characteristic of the system is that each encryption process produces a new decryption key (even for the same plaintext), thus the encryption system conforms to the feature of the one-time pad (OTP) cryptography. The other characteristic of the system is the use of fingerprint key. Only with the rightful authorization will the true decryption be obtained, otherwise the decryption will result in noisy images. So the proposed system can be used to determine whether the ciphertext is falsified by attackers. In addition, the system conforms to the basic agreement of asymmetric cryptosystem (ACS) due to the combination with the RSA public-key algorithm. The simulation results show that the encryption scheme has high robustness against the existing attacks.

Conserved and Divergent Features of Human and Mouse Kidney Organogenesis.

PubMed

Lindström, Nils O; McMahon, Jill A; Guo, Jinjin; Tran, Tracy; Guo, Qiuyu; Rutledge, Elisabeth; Parvez, Riana K; Saribekyan, Gohar; Schuler, Robert E; Liao, Christopher; Kim, Albert D; Abdelhalim, Ahmed; Ruffins, Seth W; Thornton, Matthew E; Basking, Laurence; Grubbs, Brendan; Kesselman, Carl; McMahon, Andrew P

2018-03-01

Human kidney function is underpinned by approximately 1,000,000 nephrons, although the number varies substantially, and low nephron number is linked to disease. Human kidney development initiates around 4 weeks of gestation and ends around 34-37 weeks of gestation. Over this period, a reiterative inductive process establishes the nephron complement. Studies have provided insightful anatomic descriptions of human kidney development, but the limited histologic views are not readily accessible to a broad audience. In this first paper in a series providing comprehensive insight into human kidney formation, we examined human kidney development in 135 anonymously donated human kidney specimens. We documented kidney development at a macroscopic and cellular level through histologic analysis, RNA in situ hybridization, immunofluorescence studies, and transcriptional profiling, contrasting human development (4-23 weeks) with mouse development at selected stages (embryonic day 15.5 and postnatal day 2). The high-resolution histologic interactive atlas of human kidney organogenesis generated can be viewed at the GUDMAP database (www.gudmap.org) together with three-dimensional reconstructions of key components of the data herein. At the anatomic level, human and mouse kidney development differ in timing, scale, and global features such as lobe formation and progenitor niche organization. The data also highlight differences in molecular and cellular features, including the expression and cellular distribution of anchor gene markers used to identify key cell types in mouse kidney studies. These data will facilitate and inform in vitro efforts to generate human kidney structures and comparative functional analyses across mammalian species. Copyright © 2018 by the American Society of Nephrology.

Semantic image segmentation with fused CNN features

NASA Astrophysics Data System (ADS)

Geng, Hui-qiang; Zhang, Hua; Xue, Yan-bing; Zhou, Mian; Xu, Guang-ping; Gao, Zan

2017-09-01

Semantic image segmentation is a task to predict a category label for every image pixel. The key challenge of it is to design a strong feature representation. In this paper, we fuse the hierarchical convolutional neural network (CNN) features and the region-based features as the feature representation. The hierarchical features contain more global information, while the region-based features contain more local information. The combination of these two kinds of features significantly enhances the feature representation. Then the fused features are used to train a softmax classifier to produce per-pixel label assignment probability. And a fully connected conditional random field (CRF) is used as a post-processing method to improve the labeling consistency. We conduct experiments on SIFT flow dataset. The pixel accuracy and class accuracy are 84.4% and 34.86%, respectively.

Enantioselective Total Syntheses of FR901464 and Spliceostatin A and Evaluation of Splicing Activity of Key Derivatives

PubMed Central

2015-01-01

FR901464 (1) and spliceostatin A (2) are potent inhibitors of spliceosomes. These compounds have shown remarkable anticancer activity against multiple human cancer cell lines. Herein, we describe efficient, enantioselective syntheses of FR901464, spliceostatin A, six corresponding diastereomers and an evaluation of their splicing activity. Syntheses of spliceostatin A and FR901464 were carried out in the longest linear sequence of 9 and 10 steps, respectively. To construct the highly functionalized tetrahydropyran A-ring, we utilized CBS reduction, Achmatowicz rearrangement, Michael addition, and reductive amination as key steps. The remarkable diastereoselectivity of the Michael addition was specifically demonstrated with different substrates under various reaction conditions. The side chain B was prepared from an optically active alcohol, followed by acetylation and hydrogenation over Lindlar’s catalyst. The other densely functionalized tetrahydropyran C-ring was derived from readily available (R)-isopropylidene glyceraldehyde through a route featuring 1,2-addition, cyclic ketalization, and regioselective epoxidation. These fragments were coupled together at a late stage through amidation and cross-metathesis in a convergent manner. Six key diastereomers were then synthesized to probe the importance of specific stereochemical features of FR901464 and spliceostatin A, with respect to their in vitro splicing activity. PMID:24873648

Key Considerations of Community, Scalability, Supportability, Security, and Functionality in Selecting Open-Source Software in California Universities as Perceived by Technology Leaders

ERIC Educational Resources Information Center

Britton, Todd Alan

2014-01-01

Purpose: The purpose of this study was to examine the key considerations of community, scalability, supportability, security, and functionality for selecting open-source software in California universities as perceived by technology leaders. Methods: After a review of the cogent literature, the key conceptual framework categories were identified…

Levels of personality functioning and their association with clinical features and interpersonal functioning in patients with personality disorders.

PubMed

Lowyck, Benedicte; Luyten, Patrick; Verhaest, Yannic; Vandeneede, Bart; Vermote, Rudi

2013-06-01

Recently, the DSM-5 Personality and Personality Disorders Work Group has proposed a multiple level approach toward the classification and diagnosis of personality disorders (PDs), with the first level entailing a rating of impairments in levels of personality functioning. Although a number of measures that assess levels of personality functioning have been validated, given its prominent status in the DSM-5 proposal and contemporary theories of personality pathology, the Work Group has called for more research in this area (e.g., Bender, Morey, & Skodol, 2011). In response to this call, this study investigates the relationship between two major, well-validated dimensional measures of levels of personality functioning, that is, the Differentiation-Relatedness Scale (DR-S; Diamond, Blatt, Stayner, & Kaslow, 1991), as scored on the Object Relations Inventory (ORI; Blatt, Wein, Chevron, & Quinlan, 1979), and the Inventory of Personality Organization (IPO; Lenzenweger, Clarkin, Kernberg, & Foelsch, 2001), a self-report instrument, and their relationship with different measures of clinical and interpersonal functioning in 70 patients with a PD. First, results showed that higher levels of differentiation and relatedness of descriptions of self and significant others, and of the self in particular, were negatively related to indices of personality functioning as assessed by the IPO. Lower levels of personality functioning, as measured with both the DR-S and the IPO, were positively related to severity of depression, symptomatic distress, self-harm, and interpersonal problems. Finally, results showed that the DR-S and the IPO independently predicted clinical features and interpersonal functioning. Hence, this study lends further support for the concurrent and predictive validity of the DR-S and the IPO in assessing levels of personality functioning. However, more research concerning the validity of these measures in assessing levels of personality functioning is needed

Psychoemotional features of a doubtful disorder: functional dyspepsia.

PubMed

Dragoş, D; Ionescu, O; Micuţ, R; Ojog, D G; Tănăsescu, M D

2012-09-15

To delineate the psychological profile of individuals prone to FD-like symptoms (FDLS). A triple questionnaire of 614 items (including psychological and medical ones) was given to 10192 respondents, the results were analyzed by means of Cronbach alpha, and Chi square test, together with an ad-hoc designed method that implied ranking and outliers detecting. FDLS appears to be an accompanying feature of many (if not most) human emotions and are more frequent in anxious, timid, pessimistic, discontent, irascible, tense, success-doubting, unexpected-dreading individuals, bothered by persistent thoughts and tormented by the professional requirements and the lack of time. A higher degree of specificity might have: chiefly fear of failure, susceptibility, and tension, secondarily emotivity, fear of unpredictable events, sense of insufficient time, preoccupation with authority factors, and tendency to endure unacceptable situations, and also faulty patience and lack of punctuality. Rumination appears to be the psychological tendency most strongly associated with FD. Nocturnal epigastric pain seems to indicate a submissive nature but a rather responsibilities-free childhood, while early satiety is associated with inclination to work and responsibility and preoccupation with self-image. The superposition of FD symptoms with biliary and esophageal symptoms cast a doubt over the distinctness and even the materiality of the various functional digestive disorders.

Experimental quantum key distribution with finite-key security analysis for noisy channels.

PubMed

Bacco, Davide; Canale, Matteo; Laurenti, Nicola; Vallone, Giuseppe; Villoresi, Paolo

2013-01-01

In quantum key distribution implementations, each session is typically chosen long enough so that the secret key rate approaches its asymptotic limit. However, this choice may be constrained by the physical scenario, as in the perspective use with satellites, where the passage of one terminal over the other is restricted to a few minutes. Here we demonstrate experimentally the extraction of secure keys leveraging an optimal design of the prepare-and-measure scheme, according to recent finite-key theoretical tight bounds. The experiment is performed in different channel conditions, and assuming two distinct attack models: individual attacks or general quantum attacks. The request on the number of exchanged qubits is then obtained as a function of the key size and of the ambient quantum bit error rate. The results indicate that viable conditions for effective symmetric, and even one-time-pad, cryptography are achievable.

Biomaterial design for specific cellular interactions: Role of surface functionalization and geometric features

NASA Astrophysics Data System (ADS)

Kolhar, Poornima

The areas of drug delivery and tissue engineering have experienced extraordinary growth in recent years with the application of engineering principles and their potential to support and improve the field of medicine. The tremendous progress in nanotechnology and biotechnology has lead to this explosion of research and development in biomedical applications. Biomaterials can now be engineered at a nanoscale and their specific interactions with the biological tissues can be modulated. Various design parameters are being established and researched for design of drug-delivery carriers and scaffolds to be implanted into humans. Nanoparticles made from versatile biomaterial can deliver both small-molecule drugs and various classes of bio-macromolecules, such as proteins and oligonucleotides. Similarly in the field of tissue engineering, current approaches emphasize nanoscale control of cell behavior by mimicking the natural extracellular matrix (ECM) unlike, traditional scaffolds. Drug delivery and tissue engineering are closely connected fields and both of these applications require materials with exceptional physical, chemical, biological, and biomechanical properties to provide superior therapy. In the current study the surface functionalization and the geometric features of the biomaterials has been explored. In particular, a synthetic surface for culture of human embryonic stem cells has been developed, demonstrating the importance of surface functionalization in maintaining the pluripotency of hESCs. In the second study, the geometric features of the drug delivery carriers are investigated and the polymeric nanoneedles mediated cellular permeabilization and direct cytoplasmic delivery is reported. In the third study, the combined effect of surface functionalization and geometric modification of carriers for vascular targeting is enunciated. These studies illustrate how the biomaterials can be designed to achieve various cellular behaviors and control the

Fluid flows and forces in development: functions, features and biophysical principles

PubMed Central

Freund, Jonathan B.; Goetz, Jacky G.; Hill, Kent L.; Vermot, Julien

2012-01-01

Throughout morphogenesis, cells experience intracellular tensile and contractile forces on microscopic scales. Cells also experience extracellular forces, such as static forces mediated by the extracellular matrix and forces resulting from microscopic fluid flow. Although the biological ramifications of static forces have received much attention, little is known about the roles of fluid flows and forces during embryogenesis. Here, we focus on the microfluidic forces generated by cilia-driven fluid flow and heart-driven hemodynamics, as well as on the signaling pathways involved in flow sensing. We discuss recent studies that describe the functions and the biomechanical features of these fluid flows. These insights suggest that biological flow determines many aspects of cell behavior and identity through a specific set of physical stimuli and signaling pathways. PMID:22395739

Towards benchmarking citizen observatories: Features and functioning of online amateur weather networks.

PubMed

Gharesifard, Mohammad; Wehn, Uta; van der Zaag, Pieter

2017-05-15

Crowd-sourced environmental observations are increasingly being considered as having the potential to enhance the spatial and temporal resolution of current data streams from terrestrial and areal sensors. The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public and has resulted in the formation of various online environmental citizen observatory networks. Online amateur weather networks are a particular example of such ICT-mediated observatories that are rooted in one of the oldest and most widely practiced citizen science activities, namely amateur weather observation. The objective of this paper is to introduce a conceptual framework that enables a systematic review of the features and functioning of these expanding networks. This is done by considering distinct dimensions, namely the geographic scope and types of participants, the network's establishment mechanism, revenue stream(s), existing communication paradigm, efforts required by data sharers, support offered by platform providers, and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run the networks, and their sustainability. This framework is then utilized to perform a critical review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) there are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks; (2) the revenue stream(s) of online amateur weather networks is one of the least discussed but arguably most important dimensions that is crucial for the sustainability of these networks; and (3) all of the networks included in this study have one or more explicit modes of bi-directional communication, however, this is limited to

Feature Masking in Computer Game Promotes Visual Imagery

ERIC Educational Resources Information Center

Smith, Glenn Gordon; Morey, Jim; Tjoe, Edwin

2007-01-01

Can learning of mental imagery skills for visualizing shapes be accelerated with feature masking? Chemistry, physics fine arts, military tactics, and laparoscopic surgery often depend on mentally visualizing shapes in their absence. Does working with "spatial feature-masks" (skeletal shapes, missing key identifying portions) encourage people to…

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

PubMed Central

Shi, Xiao-He; Hu, Le-Le; Kong, Xiangyin; Cai, Yu-Dong; Chou, Kuo-Chen

2010-01-01

Background Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance Our results indicate that the network prediction system thus established is quite promising and encouraging. PMID:20300175

Social Cognition and Executive Functions As Key Factors for Effective Pedagogy in Higher Education.

PubMed

Correia, Rut; Navarrete, Gorka

2017-01-01

Higher education (HE) faces the challenge of responding to an increasing diversity. In this context, more attention is being paid to teachers and teaching skills positively related to students learning. Beyond the knowledges identified as key components of an effective teacher, teachers also need to be capable of unraveling what their students think and believe, and how they accommodate the new information. More importantly, teachers need to be able to adapt their own teaching to their audience's needs. In learners, social cognition (SC) has been related to a better receptivity to the different teacher-student interactions. Since these interactions are bidirectional, SC could also help to explain teachers' receptiveness to the information available in feedback situations. However, little is known about how SC is related to teacher development, and therefore teaching effectiveness, in HE. In addition, executive functions (EFs), closely related to SC, could play a key role in the ability to self-regulate their own teaching to better answering their students emerging needs. Although there is wide evidence regarding the association of EFs to performance in high demanding settings, as far as we know, there are no studies exploring the relationship between teachers' EFs and teaching effectiveness in HE. Establishing a positive association between teaching effectiveness and these socio-cognitive functions could be a promising first step in designing professional development programs that promote HE academics' ability to understand and care about students thoughts and emotions, to eventually adapt their teaching to their students needs for a better learning.

Parallel Key Frame Extraction for Surveillance Video Service in a Smart City.

PubMed

Zheng, Ran; Yao, Chuanwei; Jin, Hai; Zhu, Lei; Zhang, Qin; Deng, Wei

2015-01-01

Surveillance video service (SVS) is one of the most important services provided in a smart city. It is very important for the utilization of SVS to provide design efficient surveillance video analysis techniques. Key frame extraction is a simple yet effective technique to achieve this goal. In surveillance video applications, key frames are typically used to summarize important video content. It is very important and essential to extract key frames accurately and efficiently. A novel approach is proposed to extract key frames from traffic surveillance videos based on GPU (graphics processing units) to ensure high efficiency and accuracy. For the determination of key frames, motion is a more salient feature in presenting actions or events, especially in surveillance videos. The motion feature is extracted in GPU to reduce running time. It is also smoothed to reduce noise, and the frames with local maxima of motion information are selected as the final key frames. The experimental results show that this approach can extract key frames more accurately and efficiently compared with several other methods.

Effect of Processing and Storage on RBC function in vivo

PubMed Central

Doctor, Allan; Spinella, Phil

2012-01-01

Red Blood Cell (RBC) transfusion is indicated to improve oxygen delivery to tissue, and for no other purpose. We have come to appreciate that donor RBCs are fundamentally altered during processing and storage, in a fashion that both impairs oxygen transport efficacy and introduces additional risk by perturbing both immune and coagulation systems. The protean biophysical and physiologic changes in RBC function arising from storage are termed the ‘storage lesion’; many have been understood for some time; for example, we know that the oxygen affinity of stored blood rises during the storage period1 and that intracellular allosteric regulators, notably 2,3-bisphosphoglyceric acid (DPG) and ATP, are depleted during storage. Our appreciation of other storage lesion features has emerged with improved understanding of coagulation, immune and vascular signaling systems. Herein we review key features of the ‘storage lesion’. Additionally, we call particular attention to the newly appreciated role of RBCs in regulating linkage between regional blood flow and regional O2 consumption by regulating the bioavailability of key vasoactive mediators in plasma, as well as discuss how processing and storage disturbs this key signaling function and impairs transfusion efficacy. PMID:22818545

Visualizing chemical functionality in plant cell walls

DOE PAGES

Zeng, Yining; Himmel, Michael E.; Ding, Shi-You

2017-11-30

Understanding plant cell wall cross-linking chemistry and polymeric architecture is key to the efficient utilization of biomass in all prospects from rational genetic modification to downstream chemical and biological conversion to produce fuels and value chemicals. In fact, the bulk properties of cell wall recalcitrance are collectively determined by its chemical features over a wide range of length scales from tissue, cellular to polymeric architectures. Microscopic visualization of cell walls from the nanometer to the micrometer scale offers an in situ approach to study their chemical functionality considering its spatial and chemical complexity, particularly the capabilities of characterizing biomass non-destructivelymore » and in real-time during conversion processes. Microscopic characterization has revealed heterogeneity in the distribution of chemical features, which would otherwise be hidden in bulk analysis. Key microscopic features include cell wall type, wall layering, and wall composition - especially cellulose and lignin distributions. Microscopic tools, such as atomic force microscopy, stimulated Raman scattering microscopy, and fluorescence microscopy, have been applied to investigations of cell wall structure and chemistry from the native wall to wall treated by thermal chemical pretreatment and enzymatic hydrolysis. While advancing our current understanding of plant cell wall recalcitrance and deconstruction, microscopic tools with improved spatial resolution will steadily enhance our fundamental understanding of cell wall function.« less

Visualizing chemical functionality in plant cell walls

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

Zeng, Yining; Himmel, Michael E.; Ding, Shi-You

Understanding plant cell wall cross-linking chemistry and polymeric architecture is key to the efficient utilization of biomass in all prospects from rational genetic modification to downstream chemical and biological conversion to produce fuels and value chemicals. In fact, the bulk properties of cell wall recalcitrance are collectively determined by its chemical features over a wide range of length scales from tissue, cellular to polymeric architectures. Microscopic visualization of cell walls from the nanometer to the micrometer scale offers an in situ approach to study their chemical functionality considering its spatial and chemical complexity, particularly the capabilities of characterizing biomass non-destructivelymore » and in real-time during conversion processes. Microscopic characterization has revealed heterogeneity in the distribution of chemical features, which would otherwise be hidden in bulk analysis. Key microscopic features include cell wall type, wall layering, and wall composition - especially cellulose and lignin distributions. Microscopic tools, such as atomic force microscopy, stimulated Raman scattering microscopy, and fluorescence microscopy, have been applied to investigations of cell wall structure and chemistry from the native wall to wall treated by thermal chemical pretreatment and enzymatic hydrolysis. While advancing our current understanding of plant cell wall recalcitrance and deconstruction, microscopic tools with improved spatial resolution will steadily enhance our fundamental understanding of cell wall function.« less

A fast image matching algorithm based on key points

NASA Astrophysics Data System (ADS)

Wang, Huilin; Wang, Ying; An, Ru; Yan, Peng

2014-05-01

Image matching is a very important technique in image processing. It has been widely used for object recognition and tracking, image retrieval, three-dimensional vision, change detection, aircraft position estimation, and multi-image registration. Based on the requirements of matching algorithm for craft navigation, such as speed, accuracy and adaptability, a fast key point image matching method is investigated and developed. The main research tasks includes: (1) Developing an improved celerity key point detection approach using self-adapting threshold of Features from Accelerated Segment Test (FAST). A method of calculating self-adapting threshold was introduced for images with different contrast. Hessian matrix was adopted to eliminate insecure edge points in order to obtain key points with higher stability. This approach in detecting key points has characteristics of small amount of computation, high positioning accuracy and strong anti-noise ability; (2) PCA-SIFT is utilized to describe key point. 128 dimensional vector are formed based on the SIFT method for the key points extracted. A low dimensional feature space was established by eigenvectors of all the key points, and each eigenvector was projected onto the feature space to form a low dimensional eigenvector. These key points were re-described by dimension-reduced eigenvectors. After reducing the dimension by the PCA, the descriptor was reduced to 20 dimensions from the original 128. This method can reduce dimensions of searching approximately near neighbors thereby increasing overall speed; (3) Distance ratio between the nearest neighbour and second nearest neighbour searching is regarded as the measurement criterion for initial matching points from which the original point pairs matched are obtained. Based on the analysis of the common methods (e.g. RANSAC (random sample consensus) and Hough transform cluster) used for elimination false matching point pairs, a heuristic local geometric restriction

High-Precision Registration of Point Clouds Based on Sphere Feature Constraints.

PubMed

Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter

2016-12-30

Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.

High-Precision Registration of Point Clouds Based on Sphere Feature Constraints

PubMed Central

Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter

2016-01-01

Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method. PMID:28042846

Identification of Key Functional Residues in the Active Site of Human β1,4-Galactosyltransferase 7

PubMed Central

Talhaoui, Ibtissam; Bui, Catherine; Oriol, Rafael; Mulliert, Guillermo; Gulberti, Sandrine; Netter, Patrick; Coughtrie, Michael W. H.; Ouzzine, Mohamed; Fournel-Gigleux, Sylvie

2010-01-01

Glycosaminoglycans (GAGs) play a central role in many pathophysiological events, and exogenous xyloside substrates of β1,4-galactosyltransferase 7 (β4GalT7), a major enzyme of GAG biosynthesis, have interesting biomedical applications. To predict functional peptide regions important for substrate binding and activity of human β4GalT7, we conducted a phylogenetic analysis of the β1,4-galactosyltransferase family and generated a molecular model using the x-ray structure of Drosophila β4GalT7-UDP as template. Two evolutionary conserved motifs, 163DVD165 and 221FWGWGREDDE230, are central in the organization of the enzyme active site. This model was challenged by systematic engineering of point mutations, combined with in vitro and ex vivo functional assays. Investigation of the kinetic properties of purified recombinant wild-type β4GalT7 and selected mutants identified Trp224 as a key residue governing both donor and acceptor substrate binding. Our results also suggested the involvement of the canonical carboxylate residue Asp228 acting as general base in the reaction catalyzed by human β4GalT7. Importantly, ex vivo functional tests demonstrated that regulation of GAG synthesis is highly responsive to modification of these key active site amino acids. Interestingly, engineering mutants at position 224 allowed us to modify the affinity and to modulate the specificity of human β4GalT7 toward UDP-sugars and xyloside acceptors. Furthermore, the W224H mutant was able to sustain decorin GAG chain substitution but not GAG synthesis from exogenously added xyloside. Altogether, this study provides novel insight into human β4GalT7 active site functional domains, allowing manipulation of this enzyme critical for the regulation of GAG synthesis. A better understanding of the mechanism underlying GAG assembly paves the way toward GAG-based therapeutics. PMID:20843813

Structural and functional features of a developmentally regulated lipopolysaccharide-binding protein.

PubMed

Krasity, Benjamin C; Troll, Joshua V; Lehnert, Erik M; Hackett, Kathleen T; Dillard, Joseph P; Apicella, Michael A; Goldman, William E; Weiss, Jerrold P; McFall-Ngai, Margaret J

2015-10-13

Mammalian lipopolysaccharide (LPS) binding proteins (LBPs) occur mainly in extracellular fluids and promote LPS delivery to specific host cell receptors. The function of LBPs has been studied principally in the context of host defense; the possible role of LBPs in nonpathogenic host-microbe interactions has not been well characterized. Using the Euprymna scolopes-Vibrio fischeri model, we analyzed the structure and function of an LBP family protein, E. scolopes LBP1 (EsLBP1), and provide evidence for its role in triggering a symbiont-induced host developmental program. Previous studies showed that, during initial host colonization, the LPS of V. fischeri synergizes with peptidoglycan (PGN) monomer to induce morphogenesis of epithelial tissues of the host animal. Computationally modeled EsLBP1 shares some but not all structural features of mammalian LBPs that are thought important for LPS binding. Similar to human LBP, recombinant EsLBP1 expressed in insect cells bound V. fischeri LPS and Neisseria meningitidis lipooligosaccharide (LOS) with nanomolar or greater affinity but bound Francisella tularensis LPS only weakly and did not bind PGN monomer. Unlike human LBP, EsLBP1 did not bind N. meningitidis LOS:CD14 complexes. The eslbp1 transcript was upregulated ~22-fold by V. fischeri at 24 h postinoculation. Surprisingly, this upregulation was not induced by exposure to LPS but, rather, to the PGN monomer alone. Hybridization chain reaction-fluorescent in situ hybridization (HCR-FISH) and immunocytochemistry (ICC) localized eslbp1 transcript and protein in crypt epithelia, where V. fischeri induces morphogenesis. The data presented here provide a window into the evolution of LBPs and the scope of their roles in animal symbioses. Mammalian lipopolysaccharide (LPS)-binding protein (LBP) is implicated in conveying LPS to host cells and potentiating its signaling activity. In certain disease states, such as obesity, the overproduction of this protein has been a

Cockayne syndrome: Clinical features, model systems and pathways

PubMed Central

Karikkineth, Ajoy C.; Scheibye-Knudsen, Morten; Fivenson, Elayne; Croteau, Deborah L.; Bohr, Vilhelm A.

2016-01-01

Cockayne syndrome (CS) is a disorder characterized by a variety of clinical features including cachectic dwarfism, severe neurological manifestations including microcephaly and cognitive deficits, pigmentary retinopathy, cataracts, sensorineural deafness, and ambulatory and feeding difficulties, leading to death by 12 years of age on average. It is an autosomal recessive disorder, with a prevalence of approximately 2.5 per million. There are several phenotypes (1, 2 and 3) and complementation groups (CSA and CSB), and overlaps with xeroderma pigmentosum (XP). It has been considered a progeria, and many of the clinical features resemble accelerated aging. As such, the study of CS affords an opportunity to better understand the underlying mechanisms of aging. The molecular basis of CS has traditionally been considered to be due to defects in transcription and transcription-coupled nucleotide excision repair (TC-NER). However, recent work suggests that defects in base excision DNA repair and mitochondrial functions may also play key roles. This opens up the possibility of molecular interventions in CS, and by extrapolation, possibly in aging. PMID:27507608

Feature inference with uncertain categorization: Re-assessing Anderson's rational model.

PubMed

Konovalova, Elizaveta; Le Mens, Gaël

2017-09-18

A key function of categories is to help predictions about unobserved features of objects. At the same time, humans are often in situations where the categories of the objects they perceive are uncertain. In an influential paper, Anderson (Psychological Review, 98(3), 409-429, 1991) proposed a rational model for feature inferences with uncertain categorization. A crucial feature of this model is the conditional independence assumption-it assumes that the within category feature correlation is zero. In prior research, this model has been found to provide a poor fit to participants' inferences. This evidence is restricted to task environments inconsistent with the conditional independence assumption. Currently available evidence thus provides little information about how this model would fit participants' inferences in a setting with conditional independence. In four experiments based on a novel paradigm and one experiment based on an existing paradigm, we assess the performance of Anderson's model under conditional independence. We find that this model predicts participants' inferences better than competing models. One model assumes that inferences are based on just the most likely category. The second model is insensitive to categories but sensitive to overall feature correlation. The performance of Anderson's model is evidence that inferences were influenced not only by the more likely category but also by the other candidate category. Our findings suggest that a version of Anderson's model which relaxes the conditional independence assumption will likely perform well in environments characterized by within-category feature correlation.

A novel feature extraction scheme with ensemble coding for protein-protein interaction prediction.

PubMed

Du, Xiuquan; Cheng, Jiaxing; Zheng, Tingting; Duan, Zheng; Qian, Fulan

2014-07-18

Protein-protein interactions (PPIs) play key roles in most cellular processes, such as cell metabolism, immune response, endocrine function, DNA replication, and transcription regulation. PPI prediction is one of the most challenging problems in functional genomics. Although PPI data have been increasing because of the development of high-throughput technologies and computational methods, many problems are still far from being solved. In this study, a novel predictor was designed by using the Random Forest (RF) algorithm with the ensemble coding (EC) method. To reduce computational time, a feature selection method (DX) was adopted to rank the features and search the optimal feature combination. The DXEC method integrates many features and physicochemical/biochemical properties to predict PPIs. On the Gold Yeast dataset, the DXEC method achieves 67.2% overall precision, 80.74% recall, and 70.67% accuracy. On the Silver Yeast dataset, the DXEC method achieves 76.93% precision, 77.98% recall, and 77.27% accuracy. On the human dataset, the prediction accuracy reaches 80% for the DXEC-RF method. We extended the experiment to a bigger and more realistic dataset that maintains 50% recall on the Yeast All dataset and 80% recall on the Human All dataset. These results show that the DXEC method is suitable for performing PPI prediction. The prediction service of the DXEC-RF classifier is available at http://ailab.ahu.edu.cn:8087/ DXECPPI/index.jsp.

Handwriting: Feature Correlation Analysis for Biometric Hashes

NASA Astrophysics Data System (ADS)

Vielhauer, Claus; Steinmetz, Ralf

2004-12-01

In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation), the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.

Simple Math is Enough: Two Examples of Inferring Functional Associations from Genomic Data

NASA Technical Reports Server (NTRS)

Liang, Shoudan

2003-01-01

Non-random features in the genomic data are usually biologically meaningful. The key is to choose the feature well. Having a p-value based score prioritizes the findings. If two proteins share a unusually large number of common interaction partners, they tend to be involved in the same biological process. We used this finding to predict the functions of 81 un-annotated proteins in yeast.

Simple dynamical models capturing the key features of the Central Pacific El Niño.

PubMed

Chen, Nan; Majda, Andrew J

2016-10-18

The Central Pacific El Niño (CP El Niño) has been frequently observed in recent decades. The phenomenon is characterized by an anomalous warm sea surface temperature (SST) confined to the central Pacific and has different teleconnections from the traditional El Niño. Here, simple models are developed and shown to capture the key mechanisms of the CP El Niño. The starting model involves coupled atmosphere-ocean processes that are deterministic, linear, and stable. Then, systematic strategies are developed for incorporating several major mechanisms of the CP El Niño into the coupled system. First, simple nonlinear zonal advection with no ad hoc parameterization of the background SST gradient is introduced that creates coupled nonlinear advective modes of the SST. Secondly, due to the recent multidecadal strengthening of the easterly trade wind, a stochastic parameterization of the wind bursts including a mean easterly trade wind anomaly is coupled to the simple atmosphere-ocean processes. Effective stochastic noise in the wind burst model facilitates the intermittent occurrence of the CP El Niño with realistic amplitude and duration. In addition to the anomalous warm SST in the central Pacific, other major features of the CP El Niño such as the rising branch of the anomalous Walker circulation being shifted to the central Pacific and the eastern Pacific cooling with a shallow thermocline are all captured by this simple coupled model. Importantly, the coupled model succeeds in simulating a series of CP El Niño that lasts for 5 y, which resembles the two CP El Niño episodes during 1990-1995 and 2002-2006.

Human olfactory consciousness and cognition: its unusual features may not result from unusual functions but from limited neocortical processing resources

PubMed Central

Stevenson, Richard J.; Attuquayefio, Tuki

2013-01-01

Human and animal olfactory perception is shaped both by functional demands and by various environmental constraints seemingly peculiar to chemical stimuli. These demands and constraints may have generated a sensory system that is cognitively distinct from the major senses. In this article we identify these various functional demands and constraints, and examine whether they can be used to account for olfaction's unique cognitive features on a case-by-case basis. We then use this as grounds to argue that specific conscious processes do have functional value, a finding that naturally emerges when a comparative approach to consciousness across the senses is adopted. More generally, we conclude that certain peculiar features of olfactory cognition may owe more to limited neocortical processing resources, than they do to the challenges faced by perceiving chemical stimuli. PMID:24198808

Electrostatics of DNA-Functionalized Nanoparticles

NASA Astrophysics Data System (ADS)

Hoffmann, Kyle; Krishnamoorthy, Kurinji; Kewalramani, Sumit; Bedzyk, Michael; Olvera de La Cruz, Monica

DNA-functionalized nanoparticles have applications in directed self-assembly and targeted cellular delivery of therapeutic proteins. In order to design specific systems, it is necessary to understand their self-assembly properties, of which the long-range electrostatic interactions are a critical component. We iteratively solved equations derived from classical density functional theory in order to predict the distribution of ions around DNA-functionalized Cg Catalase. We then compared estimates of the resonant intensity to those from SAXS measurements to estimate key features of DNA-functionalized proteins, such as the size of the region linking the protein and DNA and the extension of the single-stranded DNA. Using classical density functional theory and coarse-grained simulations, we are able to predict and understand these fundamental properties in order to rationally design new biomaterials.

Risk management of key issues of FPSO

NASA Astrophysics Data System (ADS)

Sun, Liping; Sun, Hai

2012-12-01

Risk analysis of key systems have become a growing topic late of because of the development of offshore structures. Equipment failures of offloading system and fire accidents were analyzed based on the floating production, storage and offloading (FPSO) features. Fault tree analysis (FTA), and failure modes and effects analysis (FMEA) methods were examined based on information already researched on modules of relex reliability studio (RRS). Equipment failures were also analyzed qualitatively by establishing a fault tree and Boolean structure function based on the shortage of failure cases, statistical data, and risk control measures examined. Failure modes of fire accident were classified according to the different areas of fire occurrences during the FMEA process, using risk priority number (RPN) methods to evaluate their severity rank. The qualitative analysis of FTA gave the basic insight of forming the failure modes of FPSO offloading, and the fire FMEA gave the priorities and suggested processes. The research has practical importance for the security analysis problems of FPSO.

Experience improves feature extraction in Drosophila.

PubMed

Peng, Yueqing; Xi, Wang; Zhang, Wei; Zhang, Ke; Guo, Aike

2007-05-09

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

Experimental demonstration of subcarrier multiplexed quantum key distribution system.

PubMed

Mora, José; Ruiz-Alba, Antonio; Amaya, Waldimar; Martínez, Alfonso; García-Muñoz, Víctor; Calvo, David; Capmany, José

2012-06-01

We provide, to our knowledge, the first experimental demonstration of the feasibility of sending several parallel keys by exploiting the technique of subcarrier multiplexing (SCM) widely employed in microwave photonics. This approach brings several advantages such as high spectral efficiency compatible with the actual secure key rates, the sharing of the optical fainted pulse by all the quantum multiplexed channels reducing the system complexity, and the possibility of upgrading with wavelength division multiplexing in a two-tier scheme, to increase the number of parallel keys. Two independent quantum SCM channels featuring a sifted key rate of 10 Kb/s/channel over a link with quantum bit error rate <2% is reported.

Methamphetamine functions as a positive and negative drug feature in a Pavlovian appetitive discrimination task.

PubMed

Reichel, Carmela M; Wilkinson, Jamie L; Bevins, Rick A

2007-12-01

This research determined the ability of methamphetamine to serve as a positive or negative feature, and assessed the ability of bupropion, cocaine, and naloxone to substitute for the methamphetamine features. Rats received methamphetamine (0.5 mg/kg, intraperitoneally) or saline 15 min before a conditioning session. For the feature positive (FP) group, offset of 15-s cue lights was followed by access to sucrose on methamphetamine sessions; sucrose was withheld during saline sessions. For the feature negative (FN) group, the light offset was followed by sucrose on saline sessions; sucrose was withheld during methamphetamine sessions. During acquisition, the FP group had higher responding on methamphetamine sessions than on saline sessions. For the FN group, responding was higher on saline sessions than on methamphetamine sessions. Conditioned responding was sensitive to methamphetamine dose. For the FP group, bupropion and cocaine fully and partially substituted for methamphetamine, respectively. In contrast, both drugs fully substituted for methamphetamine in the FN group. Naloxone did not substitute in either set of rats. FP-trained rats were more sensitive to the locomotor stimulating effects of the test drugs than FN-trained rats. This research demonstrates that the pharmacological effects of methamphetamine function as a FP or FN in this Pavlovian discrimination task and that training history can affect conditioned responding and locomotor effects evoked by a drug.

Topological numbering of features on a mesh

NASA Technical Reports Server (NTRS)

Atallah, Mikhail J.; Hambrusch, Susanne E.; Tewinkel, Lynn E.

1988-01-01

Assume a nxn binary image is given containing horizontally convex features; i.e., for each feature, each of its row's pixels form an interval on that row. The problem of assigning topological numbers to such features is considered; i.e., assign a number to every feature f so that all features to the left of f have a smaller number assigned to them. This problem arises in solutions to the stereo matching problem. A parallel algorithm to solve the topological numbering problem in O(n) time on an nxn mesh of processors is presented. The key idea of the solution is to create a tree from which the topological numbers can be obtained even though the tree does not uniquely represent the to the left of relationship of the features.

The Main Features and the Key Challenges of the Education System in Taiwan

ERIC Educational Resources Information Center

Chien, Chiu-Kuei Chang; Lin, Lung-Chi; Chen, Chun-Fu

2013-01-01

Taiwan has undergone radical innovation of its educational system in the wake of political liberalization and democratization, with a request for a change in the idea which diverts from "de-centralization" to "individualization." The reforms have led to two main features of pluralism and generalization of education in our…

Which ante mortem clinical features predict progressive supranuclear palsy pathology?

PubMed

Respondek, Gesine; Kurz, Carolin; Arzberger, Thomas; Compta, Yaroslau; Englund, Elisabet; Ferguson, Leslie W; Gelpi, Ellen; Giese, Armin; Irwin, David J; Meissner, Wassilios G; Nilsson, Christer; Pantelyat, Alexander; Rajput, Alex; van Swieten, John C; Troakes, Claire; Josephs, Keith A; Lang, Anthony E; Mollenhauer, Brit; Müller, Ulrich; Whitwell, Jennifer L; Antonini, Angelo; Bhatia, Kailash P; Bordelon, Yvette; Corvol, Jean-Christophe; Colosimo, Carlo; Dodel, Richard; Grossman, Murray; Kassubek, Jan; Krismer, Florian; Levin, Johannes; Lorenzl, Stefan; Morris, Huw; Nestor, Peter; Oertel, Wolfgang H; Rabinovici, Gil D; Rowe, James B; van Eimeren, Thilo; Wenning, Gregor K; Boxer, Adam; Golbe, Lawrence I; Litvan, Irene; Stamelou, Maria; Höglinger, Günter U

2017-07-01

Progressive supranuclear palsy (PSP) is a neuropathologically defined disease presenting with a broad spectrum of clinical phenotypes. To identify clinical features and investigations that predict or exclude PSP pathology during life, aiming at an optimization of the clinical diagnostic criteria for PSP. We performed a systematic review of the literature published since 1996 to identify clinical features and investigations that may predict or exclude PSP pathology. We then extracted standardized data from clinical charts of patients with pathologically diagnosed PSP and relevant disease controls and calculated the sensitivity, specificity, and positive predictive value of key clinical features for PSP in this cohort. Of 4166 articles identified by the database inquiry, 269 met predefined standards. The literature review identified clinical features predictive of PSP, including features of the following 4 functional domains: ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. No biomarker or genetic feature was found reliably validated to predict definite PSP. High-quality original natural history data were available from 206 patients with pathologically diagnosed PSP and from 231 pathologically diagnosed disease controls (54 corticobasal degeneration, 51 multiple system atrophy with predominant parkinsonism, 53 Parkinson's disease, 73 behavioral variant frontotemporal dementia). We identified clinical features that predicted PSP pathology, including phenotypes other than Richardson's syndrome, with varying sensitivity and specificity. Our results highlight the clinical variability of PSP and the high prevalence of phenotypes other than Richardson's syndrome. The features of variant phenotypes with high specificity and sensitivity should serve to optimize clinical diagnosis of PSP. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Challenges for semilocal density functionals with asymptotically nonvanishing potentials

NASA Astrophysics Data System (ADS)

Aschebrock, Thilo; Armiento, Rickard; Kümmel, Stephan

2017-08-01

The Becke-Johnson model potential [A. D. Becke and E. R. Johnson, J. Chem. Phys. 124, 221101 (2006), 10.1063/1.2213970] and the potential of the AK13 functional [R. Armiento and S. Kümmel, Phys. Rev. Lett. 111, 036402 (2013), 10.1103/PhysRevLett.111.036402] have been shown to mimic features of the exact Kohn-Sham exchange potential, such as step structures that are associated with shell closings and particle-number changes. A key element in the construction of these functionals is that the potential has a limiting value far outside a finite system that is a system-dependent constant rather than zero. We discuss a set of anomalous features in these functionals that are closely connected to the nonvanishing asymptotic potential. The findings constitute a formidable challenge for the future development of semilocal functionals based on the concept of a nonvanishing asymptotic constant.

Photo interpretation key to Michigan land cover/use

NASA Technical Reports Server (NTRS)

Enslin, W. R.; Hudson, W. D.; Lusch, D. P.

1983-01-01

A set of photo interpretation keys is presented to provide a structured approach to the identification of land cover/use categories as specified in the Michigan Resource Inventory Act. The designated categories are urban and; built up lands; agricultural lands; forest land; nonforested land; water bodies; wetlands; and barren land. The keys were developed for use with medium scale (1:20,000 to 1:24,000) color infrared aerial photography. Although each key is generalized in that it relies only upon the most distinguishing photo characteristics in separating the various land cover/use categories, additional interpretation characteristics, distinguishing features and background material are given.

[Organization, functioning and expectations of organizations representing patients. Survey of key informants].

PubMed

García-Sempere, Aníbal; Artells, Juan José

2005-01-01

To explore patient organizations and their scope in terms of patient and user participation in decisions affecting their health. Semi-structured questionnaire survey of key informants from 21 patient organizations. Most of the patient organizations were regional or national private organizations. Their main objectives include improving quality of life and representing the interests of patients and their families, developing information triage and dissemination activities, and providing additional services not offered by the public health service. The main methods of communicating with members were electronic mail, open meetings and forums. Most patient organizations considered health professionals to be the most important group of stakeholders. The sources of funding most frequently quoted were membership fees, public grants and contributions from the pharmaceutical industry. The most important factor for enhancing patient co-responsibility was considered to be involving patients in health care as a way to improve the quality of the heath services. The proposed future scenario that received the most support was the creation of a legal forum in which the patient's voice could be heard and demonstrably taken into account. Patient organizations can play an important role in providing patients and health professionals with information, promoting self care and improving the effectiveness of health care. These features require visible commitment by the health authorities to facilitate opportunities for patient decisions and choice within the system.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

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

2016-01-13

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

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

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

2016-01-01

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features. PMID:26759193

Evaluation of features to support safety and quality in general practice clinical software

PubMed Central

2011-01-01

Background Electronic prescribing is now the norm in many countries. We wished to find out if clinical software systems used by general practitioners in Australia include features (functional capabilities and other characteristics) that facilitate improved patient safety and care, with a focus on quality use of medicines. Methods Seven clinical software systems used in general practice were evaluated. Fifty software features that were previously rated as likely to have a high impact on safety and/or quality of care in general practice were tested and are reported here. Results The range of results for the implementation of 50 features across the 7 clinical software systems was as follows: 17-31 features (34-62%) were fully implemented, 9-13 (18-26%) partially implemented, and 9-20 (18-40%) not implemented. Key findings included: Access to evidence based drug and therapeutic information was limited. Decision support for prescribing was available but varied markedly between systems. During prescribing there was potential for medicine mis-selection in some systems, and linking a medicine with its indication was optional. The definition of 'current medicines' versus 'past medicines' was not always clear. There were limited resources for patients, and some medicines lists for patients were suboptimal. Results were provided to the software vendors, who were keen to improve their systems. Conclusions The clinical systems tested lack some of the features expected to support patient safety and quality of care. Standards and certification for clinical software would ensure that safety features are present and that there is a minimum level of clinical functionality that clinicians could expect to find in any system.

Bit-Oriented Quantum Public-Key Cryptosystem Based on Bell States

NASA Astrophysics Data System (ADS)

Wu, WanQing; Cai, QingYu; Zhang, HuanGuo; Liang, XiaoYan

2018-02-01

Quantum public key encryption system provides information confidentiality using quantum mechanics. This paper presents a quantum public key cryptosystem (Q P K C) based on the Bell states. By H o l e v o's theorem, the presented scheme provides the security of the secret key using one-wayness during the QPKC. While the QPKC scheme is information theoretic security under chosen plaintext attack (C P A). Finally some important features of presented QPKC scheme can be compared with other QPKC scheme.

Bit-Oriented Quantum Public-Key Cryptosystem Based on Bell States

NASA Astrophysics Data System (ADS)

Wu, WanQing; Cai, QingYu; Zhang, HuanGuo; Liang, XiaoYan

2018-06-01

Quantum public key encryption system provides information confidentiality using quantum mechanics. This paper presents a quantum public key cryptosystem ( Q P K C) based on the Bell states. By H o l e v o' s theorem, the presented scheme provides the security of the secret key using one-wayness during the QPKC. While the QPKC scheme is information theoretic security under chosen plaintext attack ( C P A). Finally some important features of presented QPKC scheme can be compared with other QPKC scheme.

Confirming the key role of Ar+ ion bombardment in the growth feature of nanostructured carbon materials by PECVD

NASA Astrophysics Data System (ADS)

Liu, Yulin; Lin, Jinghuang; Jia, Henan; Chen, Shulin; Qi, Junlei; Qu, Chaoqun; Cao, Jian; Feng, Jicai; Fei, Weidong

2017-11-01

In order to confirm the key role of Ar+ ion bombardment in the growth feature of nanostructured carbon materials (NCMs), here we report a novel strategy to create different Ar+ ion states in situ in plasma enhanced chemical vapor deposition (PECVD) by separating catalyst film from the substrate. Different bombardment environments on either side of the catalyst film were created simultaneously to achieve multi-layered structural NCMs. Results showed that Ar+ ion bombardment is crucial and complex for the growth of NCMs. Firstly, Ar+ ion bombardment has both positive and negative effects on carbon nanotubes (CNTs). On one hand, Ar+ ions can break up the graphic structure of CNTs and suppress thin CNT nucleation and growth. On the other hand, Ar+ ion bombardment can remove redundant carbon layers on the surface of large catalyst particles which is essential for thick CNTs. As a result, the diameter of the CNTs depends on the Ar+ ion state. As for vertically oriented few-layer graphene (VFG), Ar+ ions are essential and can even convert the CNTs into VFG. Therefore, by combining with the catalyst separation method, specific or multi-layered structural NCMs can be obtained by PECVD only by changing the intensity of Ar+ ion bombardment, and these special NCMs are promising in many fields.

Confirming the key role of Ar+ ion bombardment in the growth feature of nanostructured carbon materials by PECVD.

PubMed

Liu, Yulin; Lin, Jinghuang; Jia, Henan; Chen, Shulin; Qi, Junlei; Qu, Chaoqun; Cao, Jian; Feng, Jicai; Fei, Weidong

2017-11-24

In order to confirm the key role of Ar + ion bombardment in the growth feature of nanostructured carbon materials (NCMs), here we report a novel strategy to create different Ar + ion states in situ in plasma enhanced chemical vapor deposition (PECVD) by separating catalyst film from the substrate. Different bombardment environments on either side of the catalyst film were created simultaneously to achieve multi-layered structural NCMs. Results showed that Ar + ion bombardment is crucial and complex for the growth of NCMs. Firstly, Ar + ion bombardment has both positive and negative effects on carbon nanotubes (CNTs). On one hand, Ar + ions can break up the graphic structure of CNTs and suppress thin CNT nucleation and growth. On the other hand, Ar + ion bombardment can remove redundant carbon layers on the surface of large catalyst particles which is essential for thick CNTs. As a result, the diameter of the CNTs depends on the Ar + ion state. As for vertically oriented few-layer graphene (VFG), Ar + ions are essential and can even convert the CNTs into VFG. Therefore, by combining with the catalyst separation method, specific or multi-layered structural NCMs can be obtained by PECVD only by changing the intensity of Ar + ion bombardment, and these special NCMs are promising in many fields.

Key attributes of ecological production functions

EPA Science Inventory

Ecological production functions (EPFs) link ecosystems, stressors, and management actions to ecosystem service (ES) production. Though essential for improving environmental management, relatively little attention has been directed toward the characteristics of EPFs. EPFs may be d...

Discovering semantic features in the literature: a foundation for building functional associations

PubMed Central

Chagoyen, Monica; Carmona-Saez, Pedro; Shatkay, Hagit; Carazo, Jose M; Pascual-Montano, Alberto

2006-01-01

Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. Results We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. Conclusion The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental

Diagnosing and improving functioning in interdisciplinary health care teams.

PubMed

Blackmore, Gail; Persaud, D David

2012-01-01

Interdisciplinary teams play a key role in the delivery of health care. Team functioning can positively or negatively impact the effective and efficient delivery of health care services as well as the personal well-being of group members. Additionally, teams must be able and willing to work together to achieve team goals within a climate that reflects commitment to team goals, accountability, respect, and trust. Not surprisingly, dysfunctional team functioning can limit the success of interdisciplinary health care teams. The first step in improving dysfunctional team function is to conduct an analysis based on criteria necessary for team success, and this article provides meaningful criteria for doing such an analysis. These are the following: a common team goal, the ability and willingness to work together to achieve team goals, decision making, communication, and team member relationships. High-functioning interdisciplinary teams must exhibit features of good team function in all key domains. If a team functions well in some domains and needs to improve in others, targeted strategies are described that can be used to improve team functioning.

Functional neuroimaging and presenting psychiatric features in frontotemporal dementia

PubMed Central

Mendez, M F; McMurtray, A; Chen, A K; Shapira, J S; Mishkin, F; Miller, B L

2006-01-01

Background Frontotemporal dementia (FTD) is a behavioural syndrome caused by degeneration of the frontal and anterior temporal lobes. Behavioural disturbances include psychiatric features. Whether patients with FTD present with psychiatric features varies with the initial neuroanatomical variability of FTD. Objective To identify presenting psychiatric changes not part of diagnostic criteria of FTD and contrast them with the degree of hemispheric asymmetry and frontal and temporal hypoperfusion on single photon emission computed tomography (SPECT) imaging. Methods 74 patients who met consensus criteria for FTD were evaluated at a two year follow up. All had brain SPECT on initial presentation. Results of an FTD psychiatric checklist were contrasted with ratings of regional hypoperfusion. Results The regions of predominant hypoperfusion did not correlate with differences on FTD demographic variables but were associated with presenting psychiatric features. Dysthymia and anxiety were associated with right temporal hypoperfusion. “Moria” or frivolous behaviour also occurred with temporal lobe changes, especially on the right. The only significant frontal lobe feature was the presence of a peculiar physical bearing in association with right frontal hypoperfusion. Conclusions Patients with FTD may present with psychiatric changes distinct from the behavioural diagnostic criteria for this disorder. Early temporal involvement is associated with frivolous behaviour and right temporal involvement is associated with emotional disturbances. In contrast, those with right frontal disease may present with alterations in non‐verbal behaviour. PMID:16043457

Identification of key regulators for the migration and invasion of rheumatoid synoviocytes through a systems approach

PubMed Central

You, Sungyong; Yoo, Seung-Ah; Choi, Susanna; Kim, Ji-Young; Park, Su-Jung; Ji, Jong Dae; Kim, Tae-Hwan; Kim, Ki-Jo; Cho, Chul-Soo; Hwang, Daehee; Kim, Wan-Uk

2014-01-01

Rheumatoid synoviocytes, which consist of fibroblast-like synoviocytes (FLSs) and synovial macrophages (SMs), are crucial for the progression of rheumatoid arthritis (RA). Particularly, FLSs of RA patients (RA-FLSs) exhibit invasive characteristics reminiscent of cancer cells, destroying cartilage and bone. RA-FLSs and SMs originate differently from mesenchymal and myeloid cells, respectively, but share many pathologic functions. However, the molecular signatures and biological networks representing the distinct and shared features of the two cell types are unknown. We performed global transcriptome profiling of FLSs and SMs obtained from RA and osteoarthritis patients. By comparing the transcriptomes, we identified distinct molecular signatures and cellular processes defining invasiveness of RA-FLSs and proinflammatory properties of RA-SMs, respectively. Interestingly, under the interleukin-1β (IL-1β)–stimulated condition, the RA-FLSs newly acquired proinflammatory signature dominant in RA-SMs without losing invasive properties. We next reconstructed a network model that delineates the shared, RA-FLS–dominant (invasive), and RA-SM–dominant (inflammatory) processes. From the network model, we selected 13 genes, including periostin, osteoblast-specific factor (POSTN) and twist basic helix–loop–helix transcription factor 1 (TWIST1), as key regulator candidates responsible for FLS invasiveness. Of note, POSTN and TWIST1 expressions were elevated in independent RA-FLSs and further instigated by IL-1β. Functional assays demonstrated the requirement of POSTN and TWIST1 for migration and invasion of RA-FLSs stimulated with IL-1β. Together, our systems approach to rheumatoid synovitis provides a basis for identifying key regulators responsible for pathological features of RA-FLSs and -SMs, demonstrating how a certain type of cells acquires functional redundancy under chronic inflammatory conditions. PMID:24374632

Suppression effects in feature-based attention

PubMed Central

Wang, Yixue; Miller, James; Liu, Taosheng

2015-01-01

Attending to a feature enhances visual processing of that feature, but it is less clear what occurs to unattended features. Single-unit recording studies in middle temporal (MT) have shown that neuronal modulation is a monotonic function of the difference between the attended and neuron's preferred direction. Such a relationship should predict a monotonic suppressive effect in psychophysical performance. However, past research on suppressive effects of feature-based attention has remained inconclusive. We investigated the suppressive effect for motion direction, orientation, and color in three experiments. We asked participants to detect a weak signal among noise and provided a partially valid feature cue to manipulate attention. We measured performance as a function of the offset between the cued and signal feature. We also included neutral trials where no feature cues were presented to provide a baseline measure of performance. Across three experiments, we consistently observed enhancement effects when the target feature and cued feature coincided and suppression effects when the target feature deviated from the cued feature. The exact profile of suppression was different across feature dimensions: Whereas the profile for direction exhibited a “rebound” effect, the profiles for orientation and color were monotonic. These results demonstrate that unattended features are suppressed during feature-based attention, but the exact suppression profile depends on the specific feature. Overall, the results are largely consistent with neurophysiological data and support the feature-similarity gain model of attention. PMID:26067533

Thumb-loops up for catalysis: a structure/function investigation of a functional loop movement in a GH11 xylanase

PubMed Central

Paës, Gabriel; Cortés, Juan; Siméon, Thierry; O'Donohue, Michael J.; Tran, Vinh

2012-01-01

Dynamics is a key feature of enzyme catalysis. Unfortunately, current experimental and computational techniques do not yet provide a comprehensive understanding and description of functional macromolecular motions. In this work, we have extended a novel computational technique, which combines molecular modeling methods and robotics algorithms, to investigate functional motions of protein loops. This new approach has been applied to study the functional importance of the so-called thumb-loop in the glycoside hydrolase family 11 xylanase from Thermobacillus xylanilyticus (Tx-xyl). The results obtained provide new insight into the role of the loop in the glycosylation/deglycosylation catalytic cycle, and underline the key importance of the nature of the residue located at the tip of the thumb-loop. The effect of mutations predicted in silico has been validated by in vitro site-directed mutagenesis experiments. Overall, we propose a comprehensive model of Tx-xyl catalysis in terms of substrate and product dynamics by identifying the action of the thumb-loop motion during catalysis. PMID:24688637

Configuration interaction of hydropathic waves enables ubiquitin functionality

NASA Astrophysics Data System (ADS)

Allan, Douglas C.; Phillips, J. C.

2018-02-01

Ubiquitin, discovered less than 50 years ago, tags thousands of diseased proteins for destruction. It is small (only 76 amino acids), and is found unchanged in mammals, birds, fish and even worms. Key features of its functionality are identified here using critical point thermodynamic scaling theory. These include Fano interference between first- and second-order elements of correlated long-range globular surface shape transitions. Comparison with its closest relative, 76 amino acid Nedd8, shows that the latter lacks these features. A cracked elastic network model is proposed for the common target shared by many diseased proteins.

iFeature: a python package and web server for features extraction and selection from protein and peptide sequences.

PubMed

Chen, Zhen; Zhao, Pei; Li, Fuyi; Leier, André; Marquez-Lago, Tatiana T; Wang, Yanan; Webb, Geoffrey I; Smith, A Ian; Daly, Roger J; Chou, Kuo-Chen; Song, Jiangning

2018-03-08

Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional, expression and interaction profiles of proteins and peptides as well as DNAs/RNAs. Here, we present iFeature, a versatile Python-based toolkit for generating various numerical feature representation schemes for both protein and peptide sequences. iFeature is capable of calculating and extracting a comprehensive spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. It also allows users to extract specific amino acid properties from the AAindex database. Furthermore, iFeature integrates 12 different types of commonly used feature clustering, selection, and dimensionality reduction algorithms, greatly facilitating training, analysis, and benchmarking of machine-learning models. The functionality of iFeature is made freely available via an online web server and a stand-alone toolkit. http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/. jiangning.song@monash.edu; kcchou@gordonlifescience.org; roger.daly@monash.edu. Supplementary data are available at Bioinformatics online.

Key Features of Intertidal Food Webs That Support Migratory Shorebirds

PubMed Central

Saint-Béat, Blanche; Dupuy, Christine; Bocher, Pierrick; Chalumeau, Julien; De Crignis, Margot; Fontaine, Camille; Guizien, Katell; Lavaud, Johann; Lefebvre, Sébastien; Montanié, Hélène; Mouget, Jean-Luc; Orvain, Francis; Pascal, Pierre-Yves; Quaintenne, Gwenaël; Radenac, Gilles; Richard, Pierre; Robin, Frédéric; Vézina, Alain F.; Niquil, Nathalie

2013-01-01

The migratory shorebirds of the East Atlantic flyway land in huge numbers during a migratory stopover or wintering on the French Atlantic coast. The Brouage bare mudflat (Marennes-Oléron Bay, NE Atlantic) is one of the major stopover sites in France. The particular structure and function of a food web affects the efficiency of carbon transfer. The structure and functioning of the Brouage food web is crucial for the conservation of species landing within this area because it provides sufficient food, which allows shorebirds to reach the north of Europe where they nest. The aim of this study was to describe and understand which food web characteristics support nutritional needs of birds. Two food-web models were constructed, based on in situ measurements that were made in February 2008 (the presence of birds) and July 2008 (absence of birds). To complete the models, allometric relationships and additional data from the literature were used. The missing flow values of the food web models were estimated by Monte Carlo Markov Chain – Linear Inverse Modelling. The flow solutions obtained were used to calculate the ecological network analysis indices, which estimate the emergent properties of the functioning of a food-web. The total activities of the Brouage ecosystem in February and July are significantly different. The specialisation of the trophic links within the ecosystem does not appear to differ between the two models. In spite of a large export of carbon from the primary producer and detritus in winter, the higher recycling leads to a similar retention of carbon for the two seasons. It can be concluded that in February, the higher activity of the ecosystem coupled with a higher cycling and a mean internal organization, ensure the sufficient feeding of the migratory shorebirds. PMID:24204666

Key features of intertidal food webs that support migratory shorebirds.

PubMed

Saint-Béat, Blanche; Dupuy, Christine; Bocher, Pierrick; Chalumeau, Julien; De Crignis, Margot; Fontaine, Camille; Guizien, Katell; Lavaud, Johann; Lefebvre, Sébastien; Montanié, Hélène; Mouget, Jean-Luc; Orvain, Francis; Pascal, Pierre-Yves; Quaintenne, Gwenaël; Radenac, Gilles; Richard, Pierre; Robin, Frédéric; Vézina, Alain F; Niquil, Nathalie

2013-01-01

The migratory shorebirds of the East Atlantic flyway land in huge numbers during a migratory stopover or wintering on the French Atlantic coast. The Brouage bare mudflat (Marennes-Oléron Bay, NE Atlantic) is one of the major stopover sites in France. The particular structure and function of a food web affects the efficiency of carbon transfer. The structure and functioning of the Brouage food web is crucial for the conservation of species landing within this area because it provides sufficient food, which allows shorebirds to reach the north of Europe where they nest. The aim of this study was to describe and understand which food web characteristics support nutritional needs of birds. Two food-web models were constructed, based on in situ measurements that were made in February 2008 (the presence of birds) and July 2008 (absence of birds). To complete the models, allometric relationships and additional data from the literature were used. The missing flow values of the food web models were estimated by Monte Carlo Markov Chain--Linear Inverse Modelling. The flow solutions obtained were used to calculate the ecological network analysis indices, which estimate the emergent properties of the functioning of a food-web. The total activities of the Brouage ecosystem in February and July are significantly different. The specialisation of the trophic links within the ecosystem does not appear to differ between the two models. In spite of a large export of carbon from the primary producer and detritus in winter, the higher recycling leads to a similar retention of carbon for the two seasons. It can be concluded that in February, the higher activity of the ecosystem coupled with a higher cycling and a mean internal organization, ensure the sufficient feeding of the migratory shorebirds.

Functional equivalency inferred from "authoritative sources" in networks of homologous proteins.

PubMed

Natarajan, Shreedhar; Jakobsson, Eric

2009-06-12

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods.

Transient and Big Are Key Features of an Invertebrate T-type Channel (LCav3) from the Central Nervous System of Lymnaea stagnalis*

PubMed Central

Senatore, Adriano; Spafford, J. David

2010-01-01

Here we describe features of the first non-mammalian T-type calcium channel (LCav3) expressed in vitro. This molluscan channel possesses combined biophysical properties that are reminiscent of all mammalian T-type channels. It exhibits T-type features such as “transient” kinetics, but the “tiny” label, usually associated with Ba2+ conductance, is hard to reconcile with the “bigness” of this channel in many respects. LCav3 is 25% larger than any voltage-gated ion channel expressed to date. It codes for a massive, 322-kDa protein that conducts large macroscopic currents in vitro. LCav3 is also the most abundant Ca2+ channel transcript in the snail nervous system. A window current at typical resting potentials appears to be at least as large as that reported for mammalian channels. This distant gene provides a unique perspective to analyze the structural, functional, drug binding, and evolutionary aspects of T-type channels. PMID:20056611

A giant sediment trap in the Florida keys

USGS Publications Warehouse

Shinn, E.A.; Reich, C.D.; Locker, S.D.; Hine, A.C.

1996-01-01

Aerial photography, high-resolution seismic profiling, coring and jet probing have revealed a large sediment-filled sinkhole in the Key Largo National Marine Sanctuary off Key Largo, Florida. The 600-m-diameter feature straddles coral reef and carbonate-sand facies and contains >55 m of marine lime sand and aragonite mud. Bulk 14C age determinations of mud from a 30- m sediment core indicate infilling rates exceeding 20 m/ka between 3 and 5.6 ka. The total thickness and nature of the sediment near the base of the sinkhole are not known.

Cities and health: history, approaches, and key questions.

PubMed

Vlahov, David; Gibble, Emily; Freudenberg, Nicholas; Galea, Sandro

2004-12-01

The majority of the world's population will live in cities in the next few years, and the pace of urbanization worldwide will continue to accelerate over the coming decades. Such a dramatic demographic shift can be expected to have an impact on population health. Although there has been historic interest in how city living is associated with health, this interest has waxed and waned and a cogent framework has yet to evolve that encompasses key issues in urban health. In this article, the authors discuss three alternate approaches to the study of urban health today; these include considering urban health from the perspective of a presumed urban health penalty, from an urban sprawl perspective, and more comprehensively, considering how urban living conditions may be associated with health. The authors also propose three key questions that may help guide the study and practice of urban health in coming decades. These include considering what specific features of cities are causally related to health, the extent to which these features are unique to a particular city or are different between cities, and ultimately, to what extent these features of cities are modifiable in order to allow interventions that can improve the health of urban populations.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

Cascade detection for the extraction of localized sequence features; specificity results for HIV-1 protease and structure-function results for the Schellman loop.

PubMed

Newell, Nicholas E

2011-12-15

The extraction of the set of features most relevant to function from classified biological sequence sets is still a challenging problem. A central issue is the determination of expected counts for higher order features so that artifact features may be screened. Cascade detection (CD), a new algorithm for the extraction of localized features from sequence sets, is introduced. CD is a natural extension of the proportional modeling techniques used in contingency table analysis into the domain of feature detection. The algorithm is successfully tested on synthetic data and then applied to feature detection problems from two different domains to demonstrate its broad utility. An analysis of HIV-1 protease specificity reveals patterns of strong first-order features that group hydrophobic residues by side chain geometry and exhibit substantial symmetry about the cleavage site. Higher order results suggest that favorable cooperativity is weak by comparison and broadly distributed, but indicate possible synergies between negative charge and hydrophobicity in the substrate. Structure-function results for the Schellman loop, a helix-capping motif in proteins, contain strong first-order features and also show statistically significant cooperativities that provide new insights into the design of the motif. These include a new 'hydrophobic staple' and multiple amphipathic and electrostatic pair features. CD should prove useful not only for sequence analysis, but also for the detection of multifactor synergies in cross-classified data from clinical studies or other sources. Windows XP/7 application and data files available at: https://sites.google.com/site/cascadedetect/home. nacnewell@comcast.net Supplementary information is available at Bioinformatics online.

Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.

Automated secured cost effective key refreshing technique to enhance WiMAX privacy key management

NASA Astrophysics Data System (ADS)

Sridevi, B.; Sivaranjani, S.; Rajaram, S.

2013-01-01

In all walks of life the way of communication is transformed by the rapid growth of wireless communication and its pervasive use. A wireless network which is fixed and richer in bandwidth is specified as IEEE 802.16, promoted and launched by an industrial forum is termed as Worldwide Interoperability for Microwave Access (WiMAX). This technology enables seamless delivery of wireless broadband service for fixed and/or mobile users. The obscurity is the long delay which occurs during the handoff management in every network. Mobile WiMAX employs an authenticated key management protocol as a part of handoff management in which the Base Station (BS) controls the distribution of keying material to the Mobile Station (MS). The protocol employed is Privacy Key Management Version 2- Extensible Authentication Protocol (PKMV2-EAP) which is responsible for the normal and periodical authorization of MSs, reauthorization as well as key refreshing. Authorization key (AK) and Traffic Encryption key (TEK) plays a vital role in key exchange. When the lifetime of key expires, MS has to request for a new key to BS which in turn leads to repetition of authorization, authentication as well as key exchange. To avoid service interruption during reauthorization , two active keys are transmitted at the same time by BS to MS. The consequences of existing work are hefty amount of bandwidth utilization, time consumption and large storage. It is also endured by Man in the Middle attack and Impersonation due to lack of security in key exchange. This paper designs an automatic mutual refreshing of keys to minimize bandwidth utilization, key storage and time consumption by proposing Previous key and Iteration based Key Refreshing Function (PKIBKRF). By integrating PKIBKRF in key generation, the simulation results indicate that 21.8% of the bandwidth and storage of keys are reduced and PKMV2 mutual authentication time is reduced by 66.67%. The proposed work is simulated with Qualnet model and

Lexical Processing in Individuals with High-Functioning Autism and Asperger's Disorder

ERIC Educational Resources Information Center

Speirs, Samantha; Yelland, Greg; Rinehart, Nicole; Tonge, Bruce

2011-01-01

The presence or absence of clinically delayed language development prior to 3 years of age is a key, but contentious, clinical feature distinguishing autism from Asperger's disorder. The aim of this study was to examine language processing in children with high-functioning autism (HFA) and Asperger's disorder (AD) using a task which taps lexical…

Loss of Mitochondrial Function Impairs Lysosomes.

PubMed

Demers-Lamarche, Julie; Guillebaud, Gérald; Tlili, Mouna; Todkar, Kiran; Bélanger, Noémie; Grondin, Martine; Nguyen, Angela P; Michel, Jennifer; Germain, Marc

2016-05-06

Alterations in mitochondrial function, as observed in neurodegenerative diseases, lead to disrupted energy metabolism and production of damaging reactive oxygen species. Here, we demonstrate that mitochondrial dysfunction also disrupts the structure and function of lysosomes, the main degradation and recycling organelle. Specifically, inhibition of mitochondrial function, following deletion of the mitochondrial protein AIF, OPA1, or PINK1, as well as chemical inhibition of the electron transport chain, impaired lysosomal activity and caused the appearance of large lysosomal vacuoles. Importantly, our results show that lysosomal impairment is dependent on reactive oxygen species. Given that alterations in both mitochondrial function and lysosomal activity are key features of neurodegenerative diseases, this work provides important insights into the etiology of neurodegenerative diseases. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Cellular and Molecular Characterization of Human Cardiac Stem Cells Reveals Key Features Essential for Their Function and Safety

PubMed Central

Vahdat, Sadaf; Mousavi, Seyed Ahmad; Omrani, Gholamreza; Gholampour, Maziar; Sotoodehnejadnematalahi, Fattah; Ghazizadeh, Zaniar; Gharechahi, Javad

2015-01-01

Cell therapy of heart diseases is emerging as one of the most promising known treatments in recent years. Transplantation of cardiac stem cells (CSCs) may be one of the best strategies to cure adult or pediatric heart diseases. As these patient-derived stem cells need to be isolated from small heart biopsies, it is important to select the best isolation method and CSC subpopulation with the best cardiogenic functionality. We employed three different protocols including c-KIT+ cell sorting, clonogenic expansion, and explants culture to isolate c-KIT+ cells, clonogenic expansion-derived cells (CEDCs), and cardiosphere-derived cells (CDCs), respectively. Evaluation of isolated CSC characteristics in vitro and after rat myocardial infarction (MI) model transplantation revealed that although c-KIT+ and CDCs had higher MI regenerative potential, CEDCs had more commitment into cardiomyocytes and needed lower passages that were essential to reach a definite cell count. Furthermore, genome-wide expression analysis showed that subsequent passages caused changes in characteristics of cells, downregulation of cell cycle-related genes, and upregulation of differentiation and carcinogenic genes, which might lead to senescence, commitment, and possible tumorigenicity of the cells. Because of different properties of CSC subpopulations, we suggest that appropriate CSCs subpopulation should be chosen based on their experimental or clinical use. PMID:25867933

Do word-problem features differentially affect problem difficulty as a function of students' mathematics difficulty with and without reading difficulty?

PubMed

Powell, Sarah R; Fuchs, Lynn S; Fuchs, Douglas; Cirino, Paul T; Fletcher, Jack M

2009-01-01

This study examined whether and, if so, how word-problem features differentially affect problem difficulty as a function of mathematics difficulty (MD) status: no MD (n = 109), MD only (n = 109), or MD in combination with reading difficulties (MDRD; n = 109). The problem features were problem type (total, difference, or change) and position of missing information in the number sentence representing the word problem (first, second, or third position). Students were assessed on 14 word problems near the beginning of third grade. Consistent with the hypothesis that mathematical cognition differs as a function of MD subtype, problem type affected problem difficulty differentially for MDRD versus MD-only students; however, the position of missing information in word problems did not. Implications for MD subtyping and for instruction are discussed.

Functional Equivalency Inferred from “Authoritative Sources” in Networks of Homologous Proteins

PubMed Central

Natarajan, Shreedhar; Jakobsson, Eric

2009-01-01

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods. PMID:19521530

Psychoemotional Features of a Doubtful Disorder: Functional Dyspepsia

PubMed Central

Dragos, D; Ionescu, O; Micut, R; Ojog, DG; Tanasescu, MD

2012-01-01

Objective. To delineate the psychological profile of individuals prone to FD-like symptoms (FDLS). Method. A triple questionnaire of 614 items (including psychological and medical ones) was given to 10192 respondents, the results were analyzed by means of Cronbach alpha, and Chi square test, together with an ad-hoc designed method that implied ranking and outliers detecting. Results and conclusions. FDLS appears to be an accompanying feature of many (if not most) human emotions and are more frequent in anxious, timid, pessimistic, discontent, irascible, tense, success-doubting, unexpected-dreading individuals, bothered by persistent thoughts and tormented by the professional requirements and the lack of time. A higher degree of specificity might have: chiefly fear of failure, susceptibility, and tension, secondarily emotivity, fear of unpredictable events, sense of insufficient time, preoccupation with authority factors, and tendency to endure unacceptable situations, and also faulty patience and lack of punctuality. Rumination appears to be the psychological tendency most strongly associated with FD. Nocturnal epigastric pain seems to indicate a submissive nature but a rather responsibilities-free childhood, while early satiety is associated with inclination to work and responsibility and preoccupation with self-image. The superposition of FD symptoms with biliary and esophageal symptoms cast a doubt over the distinctness and even the materiality of the various functional digestive disorders. Abbreviations: ChiSq = chi-square; CrA = Cronbach alpha; OdRa = odds ratio; OdRaCL = OdRa confidence limits; E = exponential (for the sake of legibility we have used the exponential notation throughout this article; i.e. 4E-28 = 4×10-28); ErrProb = probability of error; SS = statistically significant; SD = standard deviation; a / m = the calculations were done by taking into account the average/ maximal score; P / M = psychological / medical category; PaMm / PmMa / PmMm / Pa

Semi-Supervised Geographical Feature Detection

NASA Astrophysics Data System (ADS)

Yu, H.; Yu, L.; Kuo, K. S.

2016-12-01

Extraction and tracking geographical features is a fundamental requirement in many geoscience fields. However, this operation has become an increasingly challenging task for domain scientists when tackling a large amount of geoscience data. Although domain scientists may have a relatively clear definition of features, it is difficult to capture the presence of features in an accurate and efficient fashion. We propose a semi-supervised approach to address large geographical feature detection. Our approach has two main components. First, we represent a heterogeneous geoscience data in a unified high-dimensional space, which can facilitate us to evaluate the similarity of data points with respect to geolocation, time, and variable values. We characterize the data from these measures, and use a set of hash functions to parameterize the initial knowledge of the data. Second, for any user query, our approach can automatically extract the initial results based on the hash functions. To improve the accuracy of querying, our approach provides a visualization interface to display the querying results and allow users to interactively explore and refine them. The user feedback will be used to enhance our knowledge base in an iterative manner. In our implementation, we use high-performance computing techniques to accelerate the construction of hash functions. Our design facilitates a parallelization scheme for feature detection and extraction, which is a traditionally challenging problem for large-scale data. We evaluate our approach and demonstrate the effectiveness using both synthetic and real world datasets.

Primordial power spectrum features and consequences

NASA Astrophysics Data System (ADS)

Goswami, G.

2014-03-01

The present Cosmic Microwave Background (CMB) temperature and polarization anisotropy data is consistent with not only a power law scalar primordial power spectrum (PPS) with a small running but also with the scalar PPS having very sharp features. This has motivated inflationary models with such sharp features. Recently, even the possibility of having nulls in the power spectrum (at certain scales) has been considered. The existence of these nulls has been shown in linear perturbation theory. What shall be the effect of higher order corrections on such nulls? Inspired by this question, we have attempted to calculate quantum radiative corrections to the Fourier transform of the 2-point function in a toy field theory and address the issue of how these corrections to the power spectrum behave in models in which the tree-level power spectrum has a sharp dip (but not a null). In particular, we have considered the possibility of the relative enhancement of radiative corrections in a model in which the tree-level spectrum goes through a dip in power at a certain scale. The mode functions of the field (whose power spectrum is to be evaluated) are chosen such that they undergo the kind of dynamics that leads to a sharp dip in the tree level power spectrum. Next, we have considered the situation in which this field has quartic self interactions, and found one loop correction in a suitably chosen renormalization scheme. Thus, we have attempted to answer the following key question in the context of this toy model (which is as important in the realistic case): In the chosen renormalization scheme, can quantum radiative corrections be enhanced relative to tree-level power spectrum at scales, at which sharp dips appear in the tree-level spectrum?

Image feature extraction based on the camouflage effectiveness evaluation

NASA Astrophysics Data System (ADS)

Yuan, Xin; Lv, Xuliang; Li, Ling; Wang, Xinzhu; Zhang, Zhi

2018-04-01

The key step of camouflage effectiveness evaluation is how to combine the human visual physiological features, psychological features to select effectively evaluation indexes. Based on the predecessors' camo comprehensive evaluation method, this paper chooses the suitable indexes combining with the image quality awareness, and optimizes those indexes combining with human subjective perception. Thus, it perfects the theory of index extraction.

Characterizing Functional Domains for TIM-Mediated Enveloped Virus Entry

PubMed Central

Moller-Tank, Sven; Albritton, Lorraine M.; Rennert, Paul D.

2014-01-01

ABSTRACT T-cell immunoglobulin and mucin domain 1 (TIM-1) and other TIM family members were recently identified as phosphatidylserine (PtdSer)-mediated virus entry-enhancing receptors (PVEERs). These proteins enhance entry of Ebola virus (EBOV) and other viruses by binding PtdSer on the viral envelope, concentrating virus on the cell surface, and promoting subsequent internalization. The PtdSer-binding activity of the immunoglobulin-like variable (IgV) domain is essential for both virus binding and internalization by TIM-1. However, TIM-3, whose IgV domain also binds PtdSer, does not effectively enhance virus entry, indicating that other domains of TIM proteins are functionally important. Here, we investigate the domains supporting enhancement of enveloped virus entry, thereby defining the features necessary for a functional PVEER. Using a variety of chimeras and deletion mutants, we found that in addition to a functional PtdSer-binding domain PVEERs require a stalk domain of sufficient length, containing sequences that promote an extended structure. Neither the cytoplasmic nor the transmembrane domain of TIM-1 is essential for enhancing virus entry, provided the protein is still plasma membrane bound. Based on these defined characteristics, we generated a mimic lacking TIM sequences and composed of annexin V, the mucin-like domain of α-dystroglycan, and a glycophosphatidylinositol anchor that functioned as a PVEER to enhance transduction of virions displaying Ebola, Chikungunya, Ross River, or Sindbis virus glycoproteins. This identification of the key features necessary for PtdSer-mediated enhancement of virus entry provides a basis for more effective recognition of unknown PVEERs. IMPORTANCE T-cell immunoglobulin and mucin domain 1 (TIM-1) and other TIM family members are recently identified phosphatidylserine (PtdSer)-mediated virus entry-enhancing receptors (PVEERs). These proteins enhance virus entry by binding the phospholipid, PtdSer, present on the viral

A novel feature-tracking echocardiographic method for the quantitation of regional myocardial function: validation in an animal model of ischemia-reperfusion.

PubMed

Pirat, Bahar; Khoury, Dirar S; Hartley, Craig J; Tiller, Les; Rao, Liyun; Schulz, Daryl G; Nagueh, Sherif F; Zoghbi, William A

2008-02-12

The aim of this study was to validate a novel, angle-independent, feature-tracking method for the echocardiographic quantitation of regional function. A new echocardiographic method, Velocity Vector Imaging (VVI) (syngo Velocity Vector Imaging technology, Siemens Medical Solutions, Ultrasound Division, Mountain View, California), has been introduced, based on feature tracking-incorporating speckle and endocardial border tracking, that allows the quantitation of endocardial strain, strain rate (SR), and velocity. Seven dogs were studied during baseline, and various interventions causing alterations in regional function: dobutamine, 5-min coronary occlusion with reperfusion up to 1 h, followed by dobutamine and esmolol infusions. Echocardiographic images were acquired from short- and long-axis views of the left ventricle. Segment-length sonomicrometry crystals were used as the reference method. Changes in systolic strain in ischemic segments were tracked well with VVI during the different states of regional function. There was a good correlation between circumferential and longitudinal systolic strain by VVI and sonomicrometry (r = 0.88 and r = 0.83, respectively, p < 0.001). Strain measurements in the nonischemic basal segments also demonstrated a significant correlation between the 2 methods (r = 0.65, p < 0.001). Similarly, a significant relation was observed for circumferential and longitudinal SR between the 2 methods (r = 0.94, p < 0.001 and r = 0.90, p < 0.001, respectively). The endocardial velocity relation to changes in strain by sonomicrometry was weaker owing to significant cardiac translation. Velocity Vector Imaging, a new feature-tracking method, can accurately assess regional myocardial function at the endocardial level and is a promising clinical tool for the simultaneous quantification of regional and global myocardial function.

Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions

PubMed Central

Ruan, Peiying; Hayashida, Morihiro; Maruyama, Osamu; Akutsu, Tatsuya

2013-01-01

Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes. PMID:23776458

Endocardial left ventricle feature tracking and reconstruction from tri-plane trans-esophageal echocardiography data

NASA Astrophysics Data System (ADS)

Dangi, Shusil; Ben-Zikri, Yehuda K.; Cahill, Nathan; Schwarz, Karl Q.; Linte, Cristian A.

2015-03-01

Two-dimensional (2D) ultrasound (US) has been the clinical standard for over two decades for monitoring and assessing cardiac function and providing support via intra-operative visualization and guidance for minimally invasive cardiac interventions. Developments in three-dimensional (3D) image acquisition and transducer design and technology have revolutionized echocardiography imaging enabling both real-time 3D trans-esophageal and intra-cardiac image acquisition. However, in most cases the clinicians do not access the entire 3D image volume when analyzing the data, rather they focus on several key views that render the cardiac anatomy of interest during the US imaging exam. This approach enables image acquisition at a much higher spatial and temporal resolution. Two such common approaches are the bi-plane and tri-plane data acquisition protocols; as their name states, the former comprises two orthogonal image views, while the latter depicts the cardiac anatomy based on three co-axially intersecting views spaced at 600 to one another. Since cardiac anatomy is continuously changing, the intra-operative anatomy depicted using real-time US imaging also needs to be updated by tracking the key features of interest and endocardial left ventricle (LV) boundaries. Therefore, rapid automatic feature tracking in US images is critical for three reasons: 1) to perform cardiac function assessment; 2) to identify location of surgical targets for accurate tool to target navigation and on-target instrument positioning; and 3) to enable pre- to intra-op image registration as a means to fuse pre-op CT or MR images used during planning with intra-operative images for enhanced guidance. In this paper we utilize monogenic filtering, graph-cut based segmentation and robust spline smoothing in a combined work flow to process the acquired tri-plane TEE time series US images and demonstrate robust and accurate tracking of the LV endocardial features. We reconstruct the endocardial LV

Inkjet Printing of Functional and Structural Materials: Fluid Property Requirements, Feature Stability, and Resolution

NASA Astrophysics Data System (ADS)

Derby, Brian

2010-08-01

Inkjet printing is viewed as a versatile manufacturing tool for applications in materials fabrication in addition to its traditional role in graphics output and marking. The unifying feature in all these applications is the dispensing and precise positioning of very small volumes of fluid (1-100 picoliters) on a substrate before transformation to a solid. The application of inkjet printing to the fabrication of structures for structural or functional materials applications requires an understanding as to how the physical processes that operate during inkjet printing interact with the properties of the fluid precursors used. Here we review the current state of understanding of the mechanisms of drop formation and how this defines the fluid properties that are required for a given liquid to be printable. The interactions between individual drops and the substrate as well as between adjacent drops are important in defining the resolution and accuracy of printed objects. Pattern resolution is limited by the extent to which a liquid drop spreads on a substrate and how spreading changes with the overlap of adjacent drops to form continuous features. There are clearly defined upper and lower bounds to the width of a printed continuous line, which can be defined in terms of materials and process variables. Finer-resolution features can be achieved through appropriate patterning and structuring of the substrate prior to printing, which is essential if polymeric semiconducting devices are to be fabricated. Low advancing and receding contact angles promote printed line stability but are also more prone to solute segregation or “coffee staining” on drying.

Structural and functional adaptations of the mammalian nuclear envelope to meet the meiotic requirements.

PubMed

Link, Jana; Jahn, Daniel; Alsheimer, Manfred

2015-01-01

Numerous studies in the past years provided definite evidence that the nuclear envelope is much more than just a simple barrier. It rather constitutes a multifunctional platform combining structural and dynamic features to fulfill many fundamental functions such as chromatin organization, regulation of transcription, signaling, but also structural duties like maintaining general nuclear architecture and shape. One additional and, without doubt, highly impressive aspect is the recently identified key function of selected nuclear envelope components in driving meiotic chromosome dynamics, which in turn is essential for accurate recombination and segregation of the homologous chromosomes. Here, we summarize the recent work identifying new key players in meiotic telomere attachment and movement and discuss the latest advances in our understanding of the actual function of the meiotic nuclear envelope.

Coding of visual object features and feature conjunctions in the human brain.

PubMed

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

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

PubMed

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

2013-11-01

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

Use and satisfaction with key functions of a common commercial electronic health record: a survey of primary care providers.

PubMed

Makam, Anil N; Lanham, Holly J; Batchelor, Kim; Samal, Lipika; Moran, Brett; Howell-Stampley, Temple; Kirk, Lynne; Cherukuri, Manjula; Santini, Noel; Leykum, Luci K; Halm, Ethan A

2013-08-09

Despite considerable financial incentives for adoption, there is little evidence available about providers' use and satisfaction with key functions of electronic health records (EHRs) that meet "meaningful use" criteria. We surveyed primary care providers (PCPs) in 11 general internal medicine and family medicine practices affiliated with 3 health systems in Texas about their use and satisfaction with performing common tasks (documentation, medication prescribing, preventive services, problem list) in the Epic EHR, a common commercial system. Most practices had greater than 5 years of experience with the Epic EHR. We used multivariate logistic regression to model predictors of being a structured documenter, defined as using electronic templates or prepopulated dot phrases to document at least two of the three note sections (history, physical, assessment and plan). 146 PCPs responded (70%). The majority used free text to document the history (51%) and assessment and plan (54%) and electronic templates to document the physical exam (57%). Half of PCPs were structured documenters (55%) with family medicine specialty (adjusted OR 3.3, 95% CI, 1.4-7.8) and years since graduation (nonlinear relationship with youngest and oldest having lowest probabilities) being significant predictors. Nearly half (43%) reported spending at least one extra hour beyond each scheduled half-day clinic completing EHR documentation. Three-quarters were satisfied with documenting completion of pneumococcal vaccinations and half were satisfied with documenting cancer screening (57% for breast, 45% for colorectal, and 46% for cervical). Fewer were satisfied with reminders for overdue pneumococcal vaccination (48%) and cancer screening (38% for breast, 37% for colorectal, and 31% for cervical). While most believed the problem list was helpful (70%) and kept an up-to-date list for their patients (68%), half thought they were unreliable and inaccurate (51%). Dissatisfaction with and suboptimal use

Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

PubMed

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2015-07-08

features separately. This result is key to understanding attentional selection in complex (natural) scenes, where relevant stimuli are likely to be defined by a combination of stimulus features. Copyright © 2015 the authors 0270-6474/15/359912-08$15.00/0.

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

Provably secure and high-rate quantum key distribution with time-bin qudits

PubMed Central

Islam, Nurul T.; Lim, Charles Ci Wen; Cahall, Clinton; Kim, Jungsang; Gauthier, Daniel J.

2017-01-01

The security of conventional cryptography systems is threatened in the forthcoming era of quantum computers. Quantum key distribution (QKD) features fundamentally proven security and offers a promising option for quantum-proof cryptography solution. Although prototype QKD systems over optical fiber have been demonstrated over the years, the key generation rates remain several orders of magnitude lower than current classical communication systems. In an effort toward a commercially viable QKD system with improved key generation rates, we developed a discrete-variable QKD system based on time-bin quantum photonic states that can generate provably secure cryptographic keys at megabit-per-second rates over metropolitan distances. We use high-dimensional quantum states that transmit more than one secret bit per received photon, alleviating detector saturation effects in the superconducting nanowire single-photon detectors used in our system that feature very high detection efficiency (of more than 70%) and low timing jitter (of less than 40 ps). Our system is constructed using commercial off-the-shelf components, and the adopted protocol can be readily extended to free-space quantum channels. The security analysis adopted to distill the keys ensures that the demonstrated protocol is robust against coherent attacks, finite-size effects, and a broad class of experimental imperfections identified in our system. PMID:29202028

Provably secure and high-rate quantum key distribution with time-bin qudits.

PubMed

Islam, Nurul T; Lim, Charles Ci Wen; Cahall, Clinton; Kim, Jungsang; Gauthier, Daniel J

2017-11-01

The security of conventional cryptography systems is threatened in the forthcoming era of quantum computers. Quantum key distribution (QKD) features fundamentally proven security and offers a promising option for quantum-proof cryptography solution. Although prototype QKD systems over optical fiber have been demonstrated over the years, the key generation rates remain several orders of magnitude lower than current classical communication systems. In an effort toward a commercially viable QKD system with improved key generation rates, we developed a discrete-variable QKD system based on time-bin quantum photonic states that can generate provably secure cryptographic keys at megabit-per-second rates over metropolitan distances. We use high-dimensional quantum states that transmit more than one secret bit per received photon, alleviating detector saturation effects in the superconducting nanowire single-photon detectors used in our system that feature very high detection efficiency (of more than 70%) and low timing jitter (of less than 40 ps). Our system is constructed using commercial off-the-shelf components, and the adopted protocol can be readily extended to free-space quantum channels. The security analysis adopted to distill the keys ensures that the demonstrated protocol is robust against coherent attacks, finite-size effects, and a broad class of experimental imperfections identified in our system.

Person Response Functions and the Definition of Units in the Social Sciences

ERIC Educational Resources Information Center

Engelhard, George, Jr.; Perkins, Aminah F.

2011-01-01

Humphry (this issue) has written a thought-provoking piece on the interpretation of item discrimination parameters as scale units in item response theory. One of the key features of his work is the description of an item response theory (IRT) model that he calls the logistic measurement function that combines aspects of two traditions in IRT that…

Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection.

PubMed

Pan, Xiaoyong; Hu, Xiaohua; Zhang, Yu Hang; Feng, Kaiyan; Wang, Shao Peng; Chen, Lei; Huang, Tao; Cai, Yu Dong

2018-04-12

Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew's correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles.

Defeating feature fatigue.

PubMed

Rust, Roland T; Thompson, Debora Viana; Hamilton, Rebecca W

2006-02-01

Consider a coffeemaker that offers 12 drink options, a car with more than 700 features on the dashboard, and a mouse pad that's also a clock, calculator, and FM radio. All are examples of "feature bloat", or "featuritis", the result of an almost irresistible temptation to load products with lots of bells and whistles. The problem is that the more features a product boasts, the harder it is to use. Manufacturers that increase a product's capability--the number of useful functions it can perform--at the expense of its usability are exposing their customers to feature fatigue. The authors have conducted three studies to gain a better understanding of how consumers weigh a product's capability relative to its usability. They found that even though consumers know that products with more features are harder to use, they initially choose high-feature models. They also pile on more features when given the chance to customize a product for their needs. Once consumers have actually worked with a product, however, usability starts to matter more to them than capability. For managers in consumer products companies, these findings present a dilemma: Should they maximize initial sales by designing high-feature models, which consumers consistently choose, or should they limit the number of features in order to enhance the lifetime value of their customers? The authors' analytical model guides companies toward a happy middle ground: maximizing the net present value of the typical customer's profit stream. The authors also advise companies to build simpler products, help consumers learn which products suit their needs, develop products that do one thing very well, and design market research in which consumers use actual products or prototypes.

A Novel Real-Time Reference Key Frame Scan Matching Method

PubMed Central

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-01-01

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems. PMID:28481285

A Novel Real-Time Reference Key Frame Scan Matching Method.

PubMed

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-05-07

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions' environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Do key dimensions of seed and seedling functional trait variation capture variation in recruitment probability?

PubMed

Larson, Julie E; Sheley, Roger L; Hardegree, Stuart P; Doescher, Paul S; James, Jeremy J

2016-05-01

Seedling recruitment is a critical driver of population dynamics and community assembly, yet we know little about functional traits that define different recruitment strategies. For the first time, we examined whether trait relatedness across germination and seedling stages allows the identification of general recruitment strategies which share core functional attributes and also correspond to recruitment outcomes in applied settings. We measured six seed and eight seedling traits (lab- and field-collected, respectively) for 47 varieties of dryland grasses and used principal component analysis (PCA) and cluster analysis to identify major dimensions of trait variation and to isolate trait-based recruitment groups, respectively. PCA highlighted some links between seed and seedling traits, suggesting that relative growth rate and root elongation rate are simultaneously but independently associated with seed mass and initial root mass (first axis), and with leaf dry matter content, specific leaf area, coleoptile tissue density and germination rate (second axis). Third and fourth axes captured separate tradeoffs between hydrothermal time and base water potential for germination, and between specific root length and root mass ratio, respectively. Cluster analysis separated six recruitment types along dimensions of germination and growth rates, but classifications did not correspond to patterns of germination, emergence or recruitment in the field under either of two watering treatments. Thus, while we have begun to identify major threads of functional variation across seed and seedling stages, our understanding of how this variation influences demographic processes-particularly germination and emergence-remains a key gap in functional ecology.

Ecological Understanding 2: Transformation--A Key to Ecological Understanding.

ERIC Educational Resources Information Center

Carlsson, Britta

2002-01-01

Describes the structure and general features of the phenomenon of ecological understanding. Presents qualitatively different ways of experiencing cycling of matter and the flow of energy in the context of ecosystems. The idea of transformation is key to the development of ecological understanding. (Contains 17 references.) (Author/YDS)

Experimental quantum key distribution with source flaws

NASA Astrophysics Data System (ADS)

Xu, Feihu; Wei, Kejin; Sajeed, Shihan; Kaiser, Sarah; Sun, Shihai; Tang, Zhiyuan; Qian, Li; Makarov, Vadim; Lo, Hoi-Kwong

2015-09-01

Decoy-state quantum key distribution (QKD) is a standard technique in current quantum cryptographic implementations. Unfortunately, existing experiments have two important drawbacks: the state preparation is assumed to be perfect without errors and the employed security proofs do not fully consider the finite-key effects for general attacks. These two drawbacks mean that existing experiments are not guaranteed to be proven to be secure in practice. Here, we perform an experiment that shows secure QKD with imperfect state preparations over long distances and achieves rigorous finite-key security bounds for decoy-state QKD against coherent attacks in the universally composable framework. We quantify the source flaws experimentally and demonstrate a QKD implementation that is tolerant to channel loss despite the source flaws. Our implementation considers more real-world problems than most previous experiments, and our theory can be applied to general discrete-variable QKD systems. These features constitute a step towards secure QKD with imperfect devices.

Feature Binding in Visual Working Memory Evaluated by Type Identification Paradigm

ERIC Educational Resources Information Center

Saiki, Jun; Miyatsuji, Hirofumi

2007-01-01

Memory for feature binding comprises a key ingredient in coherent object representations. Previous studies have been equivocal about human capacity for objects in the visual working memory. To evaluate memory for feature binding, a type identification paradigm was devised and used with a multiple-object permanence tracking task. Using objects…

For Dr. Nancy Snyderman's Parents, Staying Close to Family Is Key

MedlinePlus

... Issues Feature: Senior Living For Dr. Nancy Snyderman's Parents, Staying Close to Family Is Key Past Issues / ... home. "Watching my children grow closer to my parents has been a blessing, and having us nearby ...

Effective Feature Selection for Classification of Promoter Sequences.

PubMed

K, Kouser; P G, Lavanya; Rangarajan, Lalitha; K, Acharya Kshitish

2016-01-01

Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM) features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine), KNN (K Nearest Neighbor) and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method) but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation.

PubMed

Mourad, Raphaël; Cuvier, Olivier

2016-05-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1.

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation

PubMed Central

Mourad, Raphaël; Cuvier, Olivier

2016-01-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1. PMID:27203237

An adaptive multi-feature segmentation model for infrared image

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

2016-04-01

Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Consistency relations for sharp inflationary non-Gaussian features

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

Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming frommore » the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.« less

A fingerprint encryption scheme based on irreversible function and secure authentication.

PubMed

Yang, Yijun; Yu, Jianping; Zhang, Peng; Wang, Shulan

2015-01-01

A fingerprint encryption scheme based on irreversible function has been designed in this paper. Since the fingerprint template includes almost the entire information of users' fingerprints, the personal authentication can be determined only by the fingerprint features. This paper proposes an irreversible transforming function (using the improved SHA1 algorithm) to transform the original minutiae which are extracted from the thinned fingerprint image. Then, Chinese remainder theorem is used to obtain the biokey from the integration of the transformed minutiae and the private key. The result shows that the scheme has better performance on security and efficiency comparing with other irreversible function schemes.

Key Practices of the Capability Maturity Model, Version 1.1

DTIC Science & Technology

1993-02-01

0-W31 4 Interpreting the CMM ............................................................ 0-35 4.1 Interpreting the Key...Practices............................................. 0-35 4.2 Interpreting the Common Features ..................................... 0-w35 4.2.1...4.2.5 Verifying Implementation ....................................... 0-47 4.3 Interpreting Software Process Definition

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

PubMed Central

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

PubMed

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

Specific features of goal setting in road traffic safety

NASA Astrophysics Data System (ADS)

Kolesov, V. I.; Danilov, O. F.; Petrov, A. I.

2017-10-01

Road traffic safety (RTS) management is inherently a branch of cybernetics and therefore requires clear formalization of the task. The paper aims at identification of the specific features of goal setting in RTS management under the system approach. The paper presents the results of cybernetic modeling of the cause-to-effect mechanism of a road traffic accident (RTA); in here, the mechanism itself is viewed as a complex system. A designed management goal function is focused on minimizing the difficulty in achieving the target goal. Optimization of the target goal has been performed using the Lagrange principle. The created working algorithms have passed the soft testing. The key role of the obtained solution in the tactical and strategic RTS management is considered. The dynamics of the management effectiveness indicator has been analyzed based on the ten-year statistics for Russia.

Stability, surface features, and atom leaching of palladium nanoparticles: toward prediction of catalytic functionality.

PubMed

Ramezani-Dakhel, Hadi; Mirau, Peter A; Naik, Rajesh R; Knecht, Marc R; Heinz, Hendrik

2013-04-21

Surfactant-stabilized metal nanoparticles have shown promise as catalysts although specific surface features and their influence on catalytic performance have not been well understood. We quantify the thermodynamic stability, the facet composition of the surface, and distinct atom types that affect rates of atom leaching for a series of twenty near-spherical Pd nanoparticles of 1.8 to 3.1 nm size using computational models. Cohesive energies indicate higher stability of certain particles that feature an approximate 60/20/20 ratio of {111}, {100}, and {110} facets while less stable particles exhibit widely variable facet composition. Unique patterns of atom types on the surface cause apparent differences in binding energies and changes in reactivity. Estimates of the relative rate of atom leaching as a function of particle size were obtained by the summation of Boltzmann-weighted binding energies over all surface atoms. Computed leaching rates are in good qualitative correlation with the measured catalytic activity of peptide-stabilized Pd nanoparticles of the same shape and size in Stille coupling reactions. The agreement supports rate-controlling contributions by atom leaching in the presence of reactive substrates. The computational approach provides a pathway to estimate the catalytic activity of metal nanostructures of engineered shape and size, and possible further refinements are described.

Two-key concurrent responding: response-reinforcement dependencies and blackouts1

PubMed Central

Herbert, Emily W.

1970-01-01

Two-key concurrent responding was maintained for three pigeons by a single variable-interval 1-minute schedule of reinforcement in conjunction with a random number generator that assigned feeder operations between keys with equal probability. The duration of blackouts was varied between keys when each response initiated a blackout, and grain arranged by the variable-interval schedule was automatically presented after a blackout (Exp. I). In Exp. II every key peck, except for those that produced grain, initiated a blackout, and grain was dependent upon a response following a blackout. For each pigeon in Exp. I and for one pigeon in Exp. II, the relative frequency of responding on a key approximated, i.e., matched, the relative reciprocal of the duration of the blackout interval on that key. In a third experiment, blackouts scheduled on a variable-interval were of equal duration on the two keys. For one key, grain automatically followed each blackout; for the other key, grain was dependent upon a response and never followed a blackout. The relative frequency of responding on the former key, i.e., the delay key, better approximated the negative exponential function obtained by Chung (1965) than the matching function predicted by Chung and Herrnstein (1967). PMID:16811458

Neuropsychological functioning in Wernicke's encephalopathy

PubMed Central

Behura, Sushree Sangita; Swain, Sarada Prasanna

2015-01-01

Context: Wernicke's encephalopathy (WE) is caused by thiamine (Vitamin B1) deficiency and most commonly found in chronic alcoholism and malnutrition. Clinically, the key features are mental status disturbances (global confusion), oculomotor abnormalities, and gait disturbances (ataxia). Apart from these clinical features, we can find deficits in neuropsychological functioning in patients with WE, which is more prominent after the improvement in the physical conditions. Neuropsychological functioning includes both basic cognitive processes (i.e., attention-concentration) as well as higher order cognitive processes (i.e., memory, executive functioning, reasoning), which is much vital for the maintenance of quality of life of an individual. However, unfortunately, in most of the cases, neuropsychological functioning is ignored by the clinicians. Materials and Methods: In this study four case reports of WE have been presented. The patients were taken from the outdoor department of Mental Health Institute, S.C.B. Medical College, Cuttack, Odisha. Neuropsychological functioning was measured by administration of PGIBBD and Quality of Life was measured by WHO-QOL BREF Odia Version. Discussion: As described in the literature, among the three cardinal signs (global confusion, ataxia, and ocular sings), the first two were present in all cases, but nystagmus was present in only two cases. Memory dysfunction was so disabling that the persons were unable to maintain a good Quality of Life and occupational impairment was prominent. There are disturbances in recent, remote memory, immediate recall, delayed recall, and attention and concentration, ultimately creating both physical and mental disability. PGI-BBD findings also suggest the overall impairment in neuropsychological functioning other than memory, that is, executive functioning, visual acuity, and depth perception. Findings of WHO-QOL BREF suggest the impairment of four domains of QOL in all the cases, but the severity

District-Wide Involvement: The Key to Successful School Improvement.

ERIC Educational Resources Information Center

Mundell, Scott; Babich, George

1989-01-01

Describes the self-study process used by the Marana Unified School District to meet accreditation requirements with minimal expense, to emphasize curriculum development, and to improve the school. Considers the key feature of the cyclical review model to be the personal involvement of nearly every faculty member in the 10-school district. (DMM)

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

Feature Selection for Ridge Regression with Provable Guarantees.

PubMed

Paul, Saurabh; Drineas, Petros

2016-04-01

We introduce single-set spectral sparsification as a deterministic sampling-based feature selection technique for regularized least-squares classification, which is the classification analog to ridge regression. The method is unsupervised and gives worst-case guarantees of the generalization power of the classification function after feature selection with respect to the classification function obtained using all features. We also introduce leverage-score sampling as an unsupervised randomized feature selection method for ridge regression. We provide risk bounds for both single-set spectral sparsification and leverage-score sampling on ridge regression in the fixed design setting and show that the risk in the sampled space is comparable to the risk in the full-feature space. We perform experiments on synthetic and real-world data sets; a subset of TechTC-300 data sets, to support our theory. Experimental results indicate that the proposed methods perform better than the existing feature selection methods.

Registration algorithm of point clouds based on multiscale normal features

NASA Astrophysics Data System (ADS)

Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua

2015-01-01

The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.

Nonclinical and Clinical Enterococcus faecium Strains, but Not Enterococcus faecalis Strains, Have Distinct Structural and Functional Genomic Features

PubMed Central

Kim, Eun Bae

2014-01-01

Certain strains of Enterococcus faecium and Enterococcus faecalis contribute beneficially to animal health and food production, while others are associated with nosocomial infections. To determine whether there are structural and functional genomic features that are distinct between nonclinical (NC) and clinical (CL) strains of those species, we analyzed the genomes of 31 E. faecium and 38 E. faecalis strains. Hierarchical clustering of 7,017 orthologs found in the E. faecium pangenome revealed that NC strains clustered into two clades and are distinct from CL strains. NC E. faecium genomes are significantly smaller than CL genomes, and this difference was partly explained by significantly fewer mobile genetic elements (ME), virulence factors (VF), and antibiotic resistance (AR) genes. E. faecium ortholog comparisons identified 68 and 153 genes that are enriched for NC and CL strains, respectively. Proximity analysis showed that CL-enriched loci, and not NC-enriched loci, are more frequently colocalized on the genome with ME. In CL genomes, AR genes are also colocalized with ME, and VF are more frequently associated with CL-enriched loci. Genes in 23 functional groups are also differentially enriched between NC and CL E. faecium genomes. In contrast, differences were not observed between NC and CL E. faecalis genomes despite their having larger genomes than E. faecium. Our findings show that unlike E. faecalis, NC and CL E. faecium strains are equipped with distinct structural and functional genomic features indicative of adaptation to different environments. PMID:24141120

[Elucidation of key genes in sex determination in genetics teaching].

PubMed

Li, Meng; He, Zhumei

2014-06-01

Sex is an important and complex feature of organisms, which is controlled by the genetic and environmental factors. The genetic factors, i.e., genes, are vital in sex determination. However, not all the related genes play the same roles, and some key genes play a vital role in the sex determination and differentiation. With the development of the modern genetics, a great progress on the key genes has been made in sex determination. In this review, we summarize the mechanism of sex determination and the strategy of how to study the key genes in sex determination. It will help us to understand the mechanism of sex determination better in the teaching of genetics.

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

Provably secure and high-rate quantum key distribution with time-bin qudits

DOE PAGES

Islam, Nurul T.; Lim, Charles Ci Wen; Cahall, Clinton; ...

2017-11-24

The security of conventional cryptography systems is threatened in the forthcoming era of quantum computers. Quantum key distribution (QKD) features fundamentally proven security and offers a promising option for quantum-proof cryptography solution. Although prototype QKD systems over optical fiber have been demonstrated over the years, the key generation rates remain several orders of magnitude lower than current classical communication systems. In an effort toward a commercially viable QKD system with improved key generation rates, we developed a discrete-variable QKD system based on time-bin quantum photonic states that can generate provably secure cryptographic keys at megabit-per-second rates over metropolitan distances. Wemore » use high-dimensional quantum states that transmit more than one secret bit per received photon, alleviating detector saturation effects in the superconducting nanowire single-photon detectors used in our system that feature very high detection efficiency (of more than 70%) and low timing jitter (of less than 40 ps). Our system is constructed using commercial off-the-shelf components, and the adopted protocol can be readily extended to free-space quantum channels. In conclusion, the security analysis adopted to distill the keys ensures that the demonstrated protocol is robust against coherent attacks, finite-size effects, and a broad class of experimental imperfections identified in our system.« less

Provably secure and high-rate quantum key distribution with time-bin qudits

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

Islam, Nurul T.; Lim, Charles Ci Wen; Cahall, Clinton

The security of conventional cryptography systems is threatened in the forthcoming era of quantum computers. Quantum key distribution (QKD) features fundamentally proven security and offers a promising option for quantum-proof cryptography solution. Although prototype QKD systems over optical fiber have been demonstrated over the years, the key generation rates remain several orders of magnitude lower than current classical communication systems. In an effort toward a commercially viable QKD system with improved key generation rates, we developed a discrete-variable QKD system based on time-bin quantum photonic states that can generate provably secure cryptographic keys at megabit-per-second rates over metropolitan distances. Wemore » use high-dimensional quantum states that transmit more than one secret bit per received photon, alleviating detector saturation effects in the superconducting nanowire single-photon detectors used in our system that feature very high detection efficiency (of more than 70%) and low timing jitter (of less than 40 ps). Our system is constructed using commercial off-the-shelf components, and the adopted protocol can be readily extended to free-space quantum channels. In conclusion, the security analysis adopted to distill the keys ensures that the demonstrated protocol is robust against coherent attacks, finite-size effects, and a broad class of experimental imperfections identified in our system.« less

Shielding voices: The modulation of binding processes between voice features and response features by task representations.

PubMed

Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

2017-09-01

Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

Molecular Features of Wheat Endosperm Arabinoxylan Inclusion in Functional Bread

PubMed Central

Li, Weili; Hu, Hui; Wang, Qi; Brennan, Charles J.

2013-01-01

Arabinoxylan (AX) is a major dietary fibre component found in a variety of cereals. Numerous health benefits of arabinoxylans have been reported to be associated with their solubility and molecular features. The current study reports the development of a functional bread using a combination of AX-enriched material (AEM) and optimal commercial endoxylanase. The total AX content of bread was increased to 8.2 g per 100 g available carbohydrates. The extractability of AX in breads with and without endoxylanase was determined. The results demonstrate that water-extractable AX (WE-AX) increased progressively through the bread making process. The application of endoxylanase also increased WE-AX content. The presence of 360 ppm of endoxylanase had positive effects on the bread characteristics in terms of bread volume and firmness by converting the water unextractable (WU)-AX to WE-AX. In addition, the molecular weight (Mw) distribution of the WE-AX of bread with and without endoxylanase was characterized by size-exclusion chromatography. The results show that as the portion of WE-AX increased, the amount of high Mw WE-AX (higher than 100 kDa) decreased, whereas the amount of low Mw WE-AX (lower than 100 kDa) increased from 33.2% to 44.2% through the baking process. The low Mw WE-AX further increased to 75.5% with the application of the optimal endoxylanase (360 ppm). PMID:28239111

Key features of wave energy.

PubMed

Rainey, R C T

2012-01-28

For a weak point source or dipole, or a small body operating as either, we show that the power from a wave energy converter (WEC) is the product of the particle velocity in the waves, and the wave force (suitably defined). There is a thus a strong analogy with a wind or tidal turbine, where the power is the product of the fluid velocity through the turbine, and the force on it. As a first approximation, the cost of a structure is controlled by the force it has to carry, which governs its strength, and the distance it has to be carried, which governs its size. Thus, WECs are at a disadvantage compared with wind and tidal turbines because the fluid velocities are lower, and hence the forces are higher. On the other hand, the distances involved are lower. As with turbines, the implication is also that a WEC must make the most of its force-carrying ability-ideally, to carry its maximum force all the time, the '100% sweating WEC'. It must be able to limit the wave force on it in larger waves, ultimately becoming near-transparent to them in the survival condition-just like a turbine in extreme conditions, which can stop and feather its blades. A turbine of any force rating can achieve its maximum force in low wind speeds, if its diameter is sufficiently large. This is not possible with a simple monopole or dipole WEC, however, because of the 'nλ/2π' capture width limits. To achieve reasonable 'sweating' in typical wave climates, the force is limited to about 1 MN for a monopole device, or 2 MN for a dipole. The conclusion is that the future of wave energy is in devices that are not simple monopoles or dipoles, but multi-body devices or other shapes equivalent to arrays.

Integrated command, control, communications and computation system functional architecture

NASA Technical Reports Server (NTRS)

Cooley, C. G.; Gilbert, L. E.

1981-01-01

The functional architecture for an integrated command, control, communications, and computation system applicable to the command and control portion of the NASA End-to-End Data. System is described including the downlink data processing and analysis functions required to support the uplink processes. The functional architecture is composed of four elements: (1) the functional hierarchy which provides the decomposition and allocation of the command and control functions to the system elements; (2) the key system features which summarize the major system capabilities; (3) the operational activity threads which illustrate the interrelationahip between the system elements; and (4) the interfaces which illustrate those elements that originate or generate data and those elements that use the data. The interfaces also provide a description of the data and the data utilization and access techniques.

Conformational diversity analysis reveals three functional mechanisms in proteins

PubMed Central

Fornasari, María Silvina

2017-01-01

Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call “rigid” (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions. PMID:28192432

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

A Social Competence Intervention for Young Children with High Functioning Autism and Asperger Syndrome: A Pilot Study

ERIC Educational Resources Information Center

Minne, Elizabeth Portman; Semrud-Clikeman, Margaret

2012-01-01

The key features of Asperger Syndrome (AS) and high functioning autism (HFA) include marked and sustained impairment in social interactions. A multi-session, small group program was developed to increase social perception based on the assumption perceptual or interpretive problems underlying these social difficulties. Additionally, the group…

A Plant Cryptochrome Controls Key Features of the Chlamydomonas Circadian Clock and Its Life Cycle.

PubMed

Müller, Nico; Wenzel, Sandra; Zou, Yong; Künzel, Sandra; Sasso, Severin; Weiß, Daniel; Prager, Katja; Grossman, Arthur; Kottke, Tilman; Mittag, Maria

2017-05-01

Cryptochromes are flavin-binding proteins that act as blue light receptors in bacteria, fungi, plants, and insects and are components of the circadian oscillator in mammals. Animal and plant cryptochromes are evolutionarily divergent, although the unicellular alga Chlamydomonas reinhardtii ( Chlamydomonas throughout) has both an animal-like cryptochrome and a plant cryptochrome (pCRY; formerly designated CPH1). Here, we show that the pCRY protein accumulates at night as part of a complex. Functional characterization of pCRY was performed based on an insertional mutant that expresses only 11% of the wild-type pCRY level. The pcry mutant is defective for central properties of the circadian clock. In the mutant, the period is lengthened significantly, ultimately resulting in arrhythmicity, while blue light-based phase shifts show large deviations from what is observed in wild-type cells. We also show that pCRY is involved in gametogenesis in Chlamydomonas pCRY is down-regulated in pregametes and gametes, and in the pcry mutant, there is altered transcript accumulation under blue light of the strictly light-dependent, gamete-specific gene GAS28 pCRY acts as a negative regulator for the induction of mating ability in the light and for the loss of mating ability in the dark. Moreover, pCRY is necessary for light-dependent germination, during which the zygote undergoes meiosis that gives rise to four vegetative cells. In sum, our data demonstrate that pCRY is a key blue light receptor in Chlamydomonas that is involved in both circadian timing and life cycle progression. © 2017 American Society of Plant Biologists. All Rights Reserved.

Characterizing Feature Matching Performance Over Long Time Periods (Author’s Manuscript)

DTIC Science & Technology

2015-01-05

older imagery. These applications, including approaches to geo-location, geo- orientation [13], geo-tagging [16], landmark recognition [23], image... orientation between features is less than 10 degrees. We calculate the percent of features from the reference image that fit into each of these three...always because the key point detection algorithm did not find feature points at the same locations and orientation . 5. Conclusions In this paper, we offer

Delayed reverberation through time windows as a key to cerebellar function.

PubMed

Kistler, W M; Leo van Hemmen, J

1999-11-01

We present a functional model of the cerebellum comprising cerebellar cortex, inferior olive, deep cerebellar nuclei, and brain stem nuclei. The discerning feature of the model being time coding, we consistently describe the system in terms of postsynaptic potentials, synchronous action potentials, and propagation delays. We show by means of detailed single-neuron modeling that (i) Golgi cells can fulfill a gating task in that they form short and well-defined time windows within which granule cells can reach firing threshold, thus organizing neuronal activity in discrete 'time slices', and that (ii) rebound firing in cerebellar nuclei cells is a robust mechanism leading to a delayed reverberation of Purkinje cell activity through cerebellar-reticular projections back to the cerebellar cortex. Computer simulations of the whole cerebellar network consisting of several thousand neurons reveal that reverberation in conjunction with long-term plasticity at the parallel fiber-Purkinje cell synapses enables the system to learn, store, and recall spatio-temporal patterns of neuronal activity. Climbing fiber spikes act both as a synchronization and as a teacher signal, not as an error signal. They are due to intrinsic oscillatory properties of inferior olivary neurons and to delayed reverberation within the network. In addition to clear experimental predictions the present theory sheds new light on a number of experimental observation such as the synchronicity of climbing fiber spikes and provides a novel explanation of how the cerebellum solves timing tasks on a time scale of several hundreds of milliseconds.

Design Features for Linguistically-Mediated Meaning Construction: The Relative Roles of the Linguistic and Conceptual Systems in Subserving the Ideational Function of Language

PubMed Central

Evans, Vyvyan

2016-01-01

Recent research in language and cognitive science proposes that the linguistic system evolved to provide an “executive” control system on the evolutionarily more ancient conceptual system (e.g., Barsalou et al., 2008; Evans, 2009, 2015a,b; Bergen, 2012). In short, the claim is that embodied representations in the linguistic system interface with non-linguistic representations in the conceptual system, facilitating rich meanings, or simulations, enabling linguistically mediated communication. In this paper I build on these proposals by examining the nature of what I identify as design features for this control system. In particular, I address how the ideational function of language—our ability to deploy linguistic symbols to convey meanings of great complexity—is facilitated. The central proposal of this paper is as follows. The linguistic system of any given language user, of any given linguistic system—spoken or signed—facilitates access to knowledge representation—concepts—in the conceptual system, which subserves this ideational function. In the most general terms, the human meaning-making capacity is underpinned by two distinct, although tightly coupled representational systems: the conceptual system and the linguistic system. Each system contributes to meaning construction in qualitatively distinct ways. This leads to the first design feature: given that the two systems are representational—they are populated by semantic representations—the nature and function of the representations are qualitatively different. This proposed design feature I term the bifurcation in semantic representation. After all, it stands to reason that if a linguistic system has a different function, vis-à-vis the conceptual system, which is of far greater evolutionary antiquity, then the semantic representations will be complementary, and as such, qualitatively different, reflecting the functional distinctions of the two systems, in collectively giving rise to

Design Features for Linguistically-Mediated Meaning Construction: The Relative Roles of the Linguistic and Conceptual Systems in Subserving the Ideational Function of Language.

PubMed

Evans, Vyvyan

2016-01-01

Recent research in language and cognitive science proposes that the linguistic system evolved to provide an "executive" control system on the evolutionarily more ancient conceptual system (e.g., Barsalou et al., 2008; Evans, 2009, 2015a,b; Bergen, 2012). In short, the claim is that embodied representations in the linguistic system interface with non-linguistic representations in the conceptual system, facilitating rich meanings, or simulations, enabling linguistically mediated communication. In this paper I build on these proposals by examining the nature of what I identify as design features for this control system. In particular, I address how the ideational function of language-our ability to deploy linguistic symbols to convey meanings of great complexity-is facilitated. The central proposal of this paper is as follows. The linguistic system of any given language user, of any given linguistic system-spoken or signed-facilitates access to knowledge representation-concepts-in the conceptual system, which subserves this ideational function. In the most general terms, the human meaning-making capacity is underpinned by two distinct, although tightly coupled representational systems: the conceptual system and the linguistic system. Each system contributes to meaning construction in qualitatively distinct ways. This leads to the first design feature: given that the two systems are representational-they are populated by semantic representations-the nature and function of the representations are qualitatively different. This proposed design feature I term the bifurcation in semantic representation. After all, it stands to reason that if a linguistic system has a different function, vis-à-vis the conceptual system, which is of far greater evolutionary antiquity, then the semantic representations will be complementary, and as such, qualitatively different, reflecting the functional distinctions of the two systems, in collectively giving rise to meaning. I consider the

Multiple Paths to Mathematics Practice in Al-Kashi's "Key to Arithmetic"

ERIC Educational Resources Information Center

Taani, Osama

2014-01-01

In this paper, I discuss one of the most distinguishing features of Jamshid al-Kashi's pedagogy from his "Key to Arithmetic", a well-known Arabic mathematics textbook from the fifteenth century. This feature is the multiple paths that he includes to find a desired result. In the first section light is shed on al-Kashi's life…

Kinetic Assessment of Golf Shoe Outer Sole Design Features

PubMed Central

Smith, Neal A.; Dyson, Rosemary J.

2009-01-01

This study assessed human kinetics in relation to golf shoe outer sole design features during the golf swing using a driver club by measuring both within the shoe, and beneath the shoe at the natural grass interface. Three different shoes were assessed: metal 7- spike shoe, alternative 7-spike shoe, and a flat soled shoe. In-shoe plantar pressure data were recorded using Footscan RS International pressure insoles and sampling at 500 Hz. Simultaneously ground reaction force at the shoe outer sole was measured using 2 natural grass covered Kistler force platforms and 1000 Hz data acquisition. Video recording of the 18 right-handed golfers at 200 Hz was undertaken while the golfer performed 5 golf shots with his own driver in each type of shoe. Front foot (nearest to shot direction) maximum vertical force and torque were greater than at the back foot, and there was no significant difference related to the shoe type. Wearing the metal spike shoe when using a driver was associated with more torque generation at the back foot (p < 0. 05) than when the flat soled shoe was worn. Within shoe regional pressures differed significantly with golf shoe outer sole design features (p < 0.05). Comparison of the metal spike and alternative spike shoe results provided indications of the quality of regional traction on the outer sole. Potential golf shoe outer sole design features and traction were presented in relation to phases of the golf swing movement. Application of two kinetic measurement methods identified that moderated (adapted) muscular control of foot and body movement may be induced by golf shoe outer sole design features. Ground reaction force measures inform comparisons of overall shoe functional performance, and insole pressure measurements inform comparisons of the underfoot conditions induced by specific regions of the golf shoe outer sole. Key points Assessments of within golf shoe pressures and beneath shoe forces at the natural grass interface were conducted

How Task Features Impact Evidence from Assessments Embedded in Simulations and Games

ERIC Educational Resources Information Center

Almond, Russell G.; Kim, Yoon Jeon; Velasquez, Gertrudes; Shute, Valerie J.

2014-01-01

One of the key ideas of evidence-centered assessment design (ECD) is that task features can be deliberately manipulated to change the psychometric properties of items. ECD identifies a number of roles that task-feature variables can play, including determining the focus of evidence, guiding form creation, determining item difficulty and…

Multiple Paths to Mathematics Practice in Al-Kashi's Key to Arithmetic

NASA Astrophysics Data System (ADS)

Taani, Osama

2014-01-01

In this paper, I discuss one of the most distinguishing features of Jamshid al-Kashi's pedagogy from his Key to Arithmetic, a well-known Arabic mathematics textbook from the fifteenth century. This feature is the multiple paths that he includes to find a desired result. In the first section light is shed on al-Kashi's life and his contributions to mathematics and astronomy. Section 2 starts with a brief discussion of the contents and pedagogy of the Key to Arithmetic. Al-Kashi's multiple approaches are discussed through four different examples of his versatility in presenting a topic from multiple perspectives. These examples are multiple definitions, multiple algorithms, multiple formulas, and multiple methods for solving word problems. Section 3 is devoted to some benefits that can be gained by implementing al-Kashi's multiple paths approach in modern curricula. For this discussion, examples from two teaching modules taken from the Key to Arithmetic and implemented in Pre-Calculus and mathematics courses for preservice teachers are discussed. Also, the conclusions are supported by some aspects of these modules. This paper is an attempt to help mathematics educators explore more benefits from reading from original sources.

Oversampling the Minority Class in the Feature Space.

PubMed

Perez-Ortiz, Maria; Gutierrez, Pedro Antonio; Tino, Peter; Hervas-Martinez, Cesar

2016-09-01

The imbalanced nature of some real-world data is one of the current challenges for machine learning researchers. One common approach oversamples the minority class through convex combination of its patterns. We explore the general idea of synthetic oversampling in the feature space induced by a kernel function (as opposed to input space). If the kernel function matches the underlying problem, the classes will be linearly separable and synthetically generated patterns will lie on the minority class region. Since the feature space is not directly accessible, we use the empirical feature space (EFS) (a Euclidean space isomorphic to the feature space) for oversampling purposes. The proposed method is framed in the context of support vector machines, where the imbalanced data sets can pose a serious hindrance. The idea is investigated in three scenarios: 1) oversampling in the full and reduced-rank EFSs; 2) a kernel learning technique maximizing the data class separation to study the influence of the feature space structure (implicitly defined by the kernel function); and 3) a unified framework for preferential oversampling that spans some of the previous approaches in the literature. We support our investigation with extensive experiments over 50 imbalanced data sets.

Distinguishing obsessive features and worries: the role of thought-action fusion.

PubMed

Coles, M E; Mennin, D S; Heimberg, R G

2001-08-01

Obsessions are a key feature of obsessive-compulsive disorder (OCD), and chronic worry is the cardinal feature of generalized anxiety disorder (GAD). However, these two cognitive processes are conceptually very similar, and there is a need to determine how they differ. Recent studies have attempted to identify cognitive processes that may be differentially related to obsessive features and worry. In the current study we proposed that (1) obsessive features and worry could be differentiated and that (2) a measure of the cognitive process thought-action fusion would distinguish between obsessive features and worry, being strongly related to obsessive features after controlling for the effects of worry. These hypotheses were supported in a sample of 173 undergraduate students. Thought-action fusion may be a valuable construct in differentiating between obsessive features and worry.

Attacks on quantum key distribution protocols that employ non-ITS authentication

NASA Astrophysics Data System (ADS)

Pacher, C.; Abidin, A.; Lorünser, T.; Peev, M.; Ursin, R.; Zeilinger, A.; Larsson, J.-Å.

2016-01-01

We demonstrate how adversaries with large computing resources can break quantum key distribution (QKD) protocols which employ a particular message authentication code suggested previously. This authentication code, featuring low key consumption, is not information-theoretically secure (ITS) since for each message the eavesdropper has intercepted she is able to send a different message from a set of messages that she can calculate by finding collisions of a cryptographic hash function. However, when this authentication code was introduced, it was shown to prevent straightforward man-in-the-middle (MITM) attacks against QKD protocols. In this paper, we prove that the set of messages that collide with any given message under this authentication code contains with high probability a message that has small Hamming distance to any other given message. Based on this fact, we present extended MITM attacks against different versions of BB84 QKD protocols using the addressed authentication code; for three protocols, we describe every single action taken by the adversary. For all protocols, the adversary can obtain complete knowledge of the key, and for most protocols her success probability in doing so approaches unity. Since the attacks work against all authentication methods which allow to calculate colliding messages, the underlying building blocks of the presented attacks expose the potential pitfalls arising as a consequence of non-ITS authentication in QKD post-processing. We propose countermeasures, increasing the eavesdroppers demand for computational power, and also prove necessary and sufficient conditions for upgrading the discussed authentication code to the ITS level.

Structural and Functional Features of a Developmentally Regulated Lipopolysaccharide-Binding Protein

PubMed Central

Krasity, Benjamin C.; Troll, Joshua V.; Lehnert, Erik M.; Hackett, Kathleen T.; Dillard, Joseph P.; Apicella, Michael A.; Goldman, William E.

2015-01-01

ABSTRACT Mammalian lipopolysaccharide (LPS) binding proteins (LBPs) occur mainly in extracellular fluids and promote LPS delivery to specific host cell receptors. The function of LBPs has been studied principally in the context of host defense; the possible role of LBPs in nonpathogenic host-microbe interactions has not been well characterized. Using the Euprymna scolopes-Vibrio fischeri model, we analyzed the structure and function of an LBP family protein, E. scolopes LBP1 (EsLBP1), and provide evidence for its role in triggering a symbiont-induced host developmental program. Previous studies showed that, during initial host colonization, the LPS of V. fischeri synergizes with peptidoglycan (PGN) monomer to induce morphogenesis of epithelial tissues of the host animal. Computationally modeled EsLBP1 shares some but not all structural features of mammalian LBPs that are thought important for LPS binding. Similar to human LBP, recombinant EsLBP1 expressed in insect cells bound V. fischeri LPS and Neisseria meningitidis lipooligosaccharide (LOS) with nanomolar or greater affinity but bound Francisella tularensis LPS only weakly and did not bind PGN monomer. Unlike human LBP, EsLBP1 did not bind N. meningitidis LOS:CD14 complexes. The eslbp1 transcript was upregulated ~22-fold by V. fischeri at 24 h postinoculation. Surprisingly, this upregulation was not induced by exposure to LPS but, rather, to the PGN monomer alone. Hybridization chain reaction-fluorescent in situ hybridization (HCR-FISH) and immunocytochemistry (ICC) localized eslbp1 transcript and protein in crypt epithelia, where V. fischeri induces morphogenesis. The data presented here provide a window into the evolution of LBPs and the scope of their roles in animal symbioses. PMID:26463160

Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.

PubMed

Gao, Yu-Fei; Li, Bi-Qing; Cai, Yu-Dong; Feng, Kai-Yan; Li, Zhan-Dong; Jiang, Yang

2013-01-27

Identification of catalytic residues plays a key role in understanding how enzymes work. Although numerous computational methods have been developed to predict catalytic residues and active sites, the prediction accuracy remains relatively low with high false positives. In this work, we developed a novel predictor based on the Random Forest algorithm (RF) aided by the maximum relevance minimum redundancy (mRMR) method and incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility to predict active sites of enzymes and achieved an overall accuracy of 0.885687 and MCC of 0.689226 on an independent test dataset. Feature analysis showed that every category of the features except disorder contributed to the identification of active sites. It was also shown via the site-specific feature analysis that the features derived from the active site itself contributed most to the active site determination. Our prediction method may become a useful tool for identifying the active sites and the key features identified by the paper may provide valuable insights into the mechanism of catalysis.

A Fingerprint Encryption Scheme Based on Irreversible Function and Secure Authentication

PubMed Central

Yu, Jianping; Zhang, Peng; Wang, Shulan

2015-01-01

A fingerprint encryption scheme based on irreversible function has been designed in this paper. Since the fingerprint template includes almost the entire information of users' fingerprints, the personal authentication can be determined only by the fingerprint features. This paper proposes an irreversible transforming function (using the improved SHA1 algorithm) to transform the original minutiae which are extracted from the thinned fingerprint image. Then, Chinese remainder theorem is used to obtain the biokey from the integration of the transformed minutiae and the private key. The result shows that the scheme has better performance on security and efficiency comparing with other irreversible function schemes. PMID:25873989

CT Features of Ovarian Tumors: Defining Key Differences Between Serous Borderline Tumors and Low-Grade Serous Carcinomas.

PubMed

Nougaret, Stephanie; Lakhman, Yulia; Molinari, Nicolas; Feier, Diana; Scelzo, Chiara; Vargas, Hebert A; Sosa, Ramon E; Hricak, Hedvig; Soslow, Robert A; Grisham, Rachel N; Sala, Evis

2018-04-01

The objective of our study was to investigate whether the CT features of serous borderline tumors (SBTs) differ from those of low-grade serous carcinomas (LGSCs) and to evaluate if mutation status is associated with distinct CT phenotypes. This retrospective study included 59 women, 37 with SBT and 22 with LGSC, who underwent CT before primary surgical resection. Thirty of 59 patients were genetically profiled. Two radiologists (readers 1 and 2) independently and retrospectively reviewed CT examinations for qualitative features and quantified total tumor volumes (TTVs), solid tumor volumes (STVs), and solid proportion of ovarian masses. Univariate and multivariate associations of the CT features with histopathologic diagnoses and mutations were evaluated, and interreader agreement was determined. At multivariate analysis, the presence of bilateral ovarian masses (p = 0.03), the presence of peritoneal disease (PD) (p = 0.002), and higher STV of ovarian masses (p = 0.002) were associated with LGSC. The presence of nodular PD pattern (p < 0.001 each reader) and the presence of PD calcifications (reader 1, p = 0.02; reader 2, p = 0.003) were associated with invasive peritoneal lesions (i.e., LGSC). The presence of bilateral ovarian masses (p = 0.04 each reader), PD (reader 1, p = 0.01; reader 2, p = 0.004), and higher STV (p = 0.03 for each reader) were associated with the absence of BRAF mutation (i.e., wild type [wt]-BRAF). The CT features of LGSCs were distinct from those of SBTs. The CT manifestations of LGSC and the wt-BRAF phenotype were similar.

ClinicalKey 2.0: Upgrades in a Point-of-Care Search Engine.

PubMed

Huslig, Mary Ann; Vardell, Emily

2015-01-01

ClinicalKey 2.0, launched September 23, 2014, offers a mobile-friendly design with a search history feature for targeting point-of-care resources for health care professionals. Browsing is improved with searchable, filterable listings of sources highlighting new resources. ClinicalKey 2.0 improvements include more than 1,400 new Topic Pages for quick access to point-of-care content. A sample search details some of the upgrades and content options.

Weighted Feature Gaussian Kernel SVM for Emotion Recognition

PubMed Central

Jia, Qingxuan

2016-01-01

Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods. PMID:27807443

Virtual-optical information security system based on public key infrastructure

NASA Astrophysics Data System (ADS)

Peng, Xiang; Zhang, Peng; Cai, Lilong; Niu, Hanben

2005-01-01

A virtual-optical based encryption model with the aid of public key infrastructure (PKI) is presented in this paper. The proposed model employs a hybrid architecture in which our previously published encryption method based on virtual-optics scheme (VOS) can be used to encipher and decipher data while an asymmetric algorithm, for example RSA, is applied for enciphering and deciphering the session key(s). The whole information security model is run under the framework of international standard ITU-T X.509 PKI, which is on basis of public-key cryptography and digital signatures. This PKI-based VOS security approach has additional features like confidentiality, authentication, and integrity for the purpose of data encryption under the environment of network. Numerical experiments prove the effectiveness of the method. The security of proposed model is briefly analyzed by examining some possible attacks from the viewpoint of a cryptanalysis.

Key neurological impairments influence function-related group outcomes after stroke.

PubMed

Han, Lu; Law-Gibson, Diane; Reding, Michael

2002-07-01

The function-related group (FRG) classification is based on functional assessment and has been assumed to encompass the effects of different patterns and severity of neurological impairments. This assumption may not be correct. It has been proposed as a means of comparing rehabilitation outcome across institutions. If neurological impairments significantly affect FRG outcome, then higher FRG outcome scores may reflect selection bias favoring patients with fewer neurological impairments rather than better quality of rehabilitation care. The goal of this study was to assess the influence of motor, somatosensory, and hemianopic visual impairments on FRG outcomes after stroke. All 288 consecutive stroke patients discharged in 1999 from an acute rehabilitation hospital were assigned to 1 of 5 FRGs on the basis of their Functional Independence Measure (FIM) mobility subscore and age. Each FRG was also stratified into 1 of 4 cohorts on the basis of the presence or absence of key neurological impairments: motor impairment only (M), motor plus either somatosensory or hemianopic visual impairment (MS/MV), motor plus somatosensory plus hemianopic visual impairment (MSV), and other combinations of impairments. FIM scores were available every 10 days for all patients from admission to discharge. The effect of impairment group on outcome was assessed within each FRG category through repeated-measures analysis of variance to assess differences in serial FIM scores across the 4 impairment groups. The distribution of each of the 4 impairment groups across the 5 FRGs was assessed with chi2 analysis. The numbers of patients in each of the 5 FRGs from the lowest level, FRG-11, to the highest, FRG-15, were as follows: 78 (27%), 47 (16%), 75 (26%), 55 (19%), and 33 (11%). Different neurological impairments were associated with significantly different mean+/-SD discharge FIM scores as follows: for FRG-11, MSV=63+/-16, MS/MV=68+/-19, and M=81+/-13 (P=0.04); for FRG-12, MSV=47+/-14, MS

[Age-related features of neuromuscular function in rats with hyperthyroidism].

PubMed

Nerush, P O; Makiĭ, Ie A; Rodyns'kyĭ, O H

2001-01-01

Studied features of functioning of nervous-muscular system at white rats of two age groups: preadolescent (5 weeks) and puberal (24 weeks), in conditions experimental hyperthyroidism (HT). It is established, that in conditions HT at action of the raised concentration thyroxine characteristics of excitation gastrocnemius muscles essentially changed at irritation of a sciatic nerve in groups preadolescent and puberal animals. In all age groups in conditions HT increase of a threshold of excitation gastrocnemius muscles is marked at indirect stimulation and decrease at direct stimulation; also in all age groups in conditions HT reduction of time chronaxy muscles is fixed, both at direct, and at indirect irritation. At preadolescent animals, as against puberal in conditions HT at action of the raised concentration thyroxine on nervous-muscular system it is not revealed authentic change of the latent period and amplitude of potential of action (PA). The conclusion is made, that in conditions HT change of a threshold of excitation and chronaxy gastrocnemius muscles both at direct, and at indirect irritation do not carry age specificity and have an identical orientation, both at preadolescent, and at puberal rats. At preadolescent animals in conditions HT, as against puberal the parameter of amplitude and latent period PA authentically did not change, that can testify to smaller sensitivity of the caused answers gastrocnemius muscles to the raised concentration thyroxine, probably, by virtue of immaturity peripheral neuromotor the device.

Coupling Functions Enable Secure Communications

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; McClintock, Peter V. E.; Stefanovska, Aneta

2014-01-01

Secure encryption is an essential feature of modern communications, but rapid progress in illicit decryption brings a continuing need for new schemes that are harder and harder to break. Inspired by the time-varying nature of the cardiorespiratory interaction, here we introduce a new class of secure communications that is highly resistant to conventional attacks. Unlike all earlier encryption procedures, this cipher makes use of the coupling functions between interacting dynamical systems. It results in an unbounded number of encryption key possibilities, allows the transmission or reception of more than one signal simultaneously, and is robust against external noise. Thus, the information signals are encrypted as the time variations of linearly independent coupling functions. Using predetermined forms of coupling function, we apply Bayesian inference on the receiver side to detect and separate the information signals while simultaneously eliminating the effect of external noise. The scheme is highly modular and is readily extendable to support different communications applications within the same general framework.

Dimensional feature weighting utilizing multiple kernel learning for single-channel talker location discrimination using the acoustic transfer function.

PubMed

Takashima, Ryoichi; Takiguchi, Tetsuya; Ariki, Yasuo

2013-02-01

This paper presents a method for discriminating the location of the sound source (talker) using only a single microphone. In a previous work, the single-channel approach for discriminating the location of the sound source was discussed, where the acoustic transfer function from a user's position is estimated by using a hidden Markov model of clean speech in the cepstral domain. In this paper, each cepstral dimension of the acoustic transfer function is newly weighted, in order to obtain the cepstral dimensions having information that is useful for classifying the user's position. Then, this paper proposes a feature-weighting method for the cepstral parameter using multiple kernel learning, defining the base kernels for each cepstral dimension of the acoustic transfer function. The user's position is trained and classified by support vector machine. The effectiveness of this method has been confirmed by sound source (talker) localization experiments performed in different room environments.

Poly(2-vinyl pyridine)-block-poly(ethylene oxide) featuring a furan group at the block junction-synthesis and functionalization.

PubMed

Rudolph, Tobias; Barthel, Markus J; Kretschmer, Florian; Mansfeld, Ulrich; Hoeppener, Stephanie; Hager, Martin D; Schubert, Ulrich S; Schacher, Felix H

2014-05-01

Furfuryl glycidyl ether (FGE) represents a highly versatile monomer for the preparation of reversibly cross-linkable nanostructured materials via Diels-Alder reactions. Here, the use of FGE for the mid-chain functionalization of a P2VP-b-PEO diblock copolymer is reported. The material features one furan moiety at the block junction, P2VP68 -FGE-b-PEO390 , which can be subsequently addressed in Diels-Alder reactions using maleimide-functionalized counterparts. The presence of the FGE moiety enables the introduction of dyes as model labels or the formation of hetero-grafted brushes as shell on hybrid Au@Polymer nanoparticles. This renders P2VP68 -FGE-b-PEO390 , a powerful tool for selective functionalization reactions, including the modification of surfaces. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Muscle RANK is a key regulator of Ca2+ storage, SERCA activity, and function of fast-twitch skeletal muscles.

PubMed

Dufresne, Sébastien S; Dumont, Nicolas A; Boulanger-Piette, Antoine; Fajardo, Val A; Gamu, Daniel; Kake-Guena, Sandrine-Aurélie; David, Rares Ovidiu; Bouchard, Patrice; Lavergne, Éliane; Penninger, Josef M; Pape, Paul C; Tupling, A Russell; Frenette, Jérôme

2016-04-15

Receptor-activator of nuclear factor-κB (RANK), its ligand RANKL, and the soluble decoy receptor osteoprotegerin are the key regulators of osteoclast differentiation and bone remodeling. Here we show that RANK is also expressed in fully differentiated myotubes and skeletal muscle. Muscle RANK deletion has inotropic effects in denervated, but not in sham, extensor digitorum longus (EDL) muscles preventing the loss of maximum specific force while promoting muscle atrophy, fatigability, and increased proportion of fast-twitch fibers. In denervated EDL muscles, RANK deletion markedly increased stromal interaction molecule 1 content, a Ca(2+)sensor, and altered activity of the sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA) modulating Ca(2+)storage. Muscle RANK deletion had no significant effects on the sham or denervated slow-twitch soleus muscles. These data identify a novel role for RANK as a key regulator of Ca(2+)storage and SERCA activity, ultimately affecting denervated skeletal muscle function. Copyright © 2016 the American Physiological Society.

Muscle RANK is a key regulator of Ca2+ storage, SERCA activity, and function of fast-twitch skeletal muscles

PubMed Central

Dufresne, Sébastien S.; Dumont, Nicolas A.; Boulanger-Piette, Antoine; Fajardo, Val A.; Gamu, Daniel; Kake-Guena, Sandrine-Aurélie; David, Rares Ovidiu; Bouchard, Patrice; Lavergne, Éliane; Penninger, Josef M.; Pape, Paul C.; Tupling, A. Russell

2016-01-01

Receptor-activator of nuclear factor-κB (RANK), its ligand RANKL, and the soluble decoy receptor osteoprotegerin are the key regulators of osteoclast differentiation and bone remodeling. Here we show that RANK is also expressed in fully differentiated myotubes and skeletal muscle. Muscle RANK deletion has inotropic effects in denervated, but not in sham, extensor digitorum longus (EDL) muscles preventing the loss of maximum specific force while promoting muscle atrophy, fatigability, and increased proportion of fast-twitch fibers. In denervated EDL muscles, RANK deletion markedly increased stromal interaction molecule 1 content, a Ca2+ sensor, and altered activity of the sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) modulating Ca2+ storage. Muscle RANK deletion had no significant effects on the sham or denervated slow-twitch soleus muscles. These data identify a novel role for RANK as a key regulator of Ca2+ storage and SERCA activity, ultimately affecting denervated skeletal muscle function. PMID:26825123

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Visual feature integration with an attention deficit.

PubMed

Arguin, M; Cavanagh, P; Joanette, Y

1994-01-01

Treisman's feature integration theory proposes that the perception of illusory conjunctions of correctly encoded visual features is due to the failure of an attentional process. This hypothesis was examined by studying brain-damaged subjects who had previously been shown to have difficulty in attending to contralesional stimulation. These subjects exhibited a massive feature integration deficit for contralesional stimulation relative to ipsilesional displays. In contrast, both normal age-matched controls and brain-damaged subjects who did not exhibit any evidence of an attention deficit showed comparable feature integration performance with left- and right-hemifield stimulation. These observations indicate the crucial function of attention for visual feature integration in normal perception.

The Progressive BSSG Rat Model of Parkinson's: Recapitulating Multiple Key Features of the Human Disease

PubMed Central

Van Kampen, Jackalina M.; Baranowski, David C.; Robertson, Harold A.; Shaw, Christopher A.; Kay, Denis G.

2015-01-01

The development of effective neuroprotective therapies for Parkinson's disease (PD) has been severely hindered by the notable lack of an appropriate animal model for preclinical screening. Indeed, most models currently available are either acute in nature or fail to recapitulate all characteristic features of the disease. Here, we present a novel progressive model of PD, with behavioural and cellular features that closely approximate those observed in patients. Chronic exposure to dietary phytosterol glucosides has been found to be neurotoxic. When fed to rats, β-sitosterol β-d-glucoside (BSSG) triggers the progressive development of parkinsonism, with clinical signs and histopathology beginning to appear following cessation of exposure to the neurotoxic insult and continuing to develop over several months. Here, we characterize the progressive nature of this model, its non-motor features, the anatomical spread of synucleinopathy, and response to levodopa administration. In Sprague Dawley rats, chronic BSSG feeding for 4 months triggered the progressive development of a parkinsonian phenotype and pathological events that evolved slowly over time, with neuronal loss beginning only after toxin exposure was terminated. At approximately 3 months following initiation of BSSG exposure, animals displayed the early emergence of an olfactory deficit, in the absence of significant dopaminergic nigral cell loss or locomotor deficits. Locomotor deficits developed gradually over time, initially appearing as locomotor asymmetry and developing into akinesia/bradykinesia, which was reversed by levodopa treatment. Late-stage cognitive impairment was observed in the form of spatial working memory deficits, as assessed by the radial arm maze. In addition to the progressive loss of TH+ cells in the substantia nigra, the appearance of proteinase K-resistant intracellular α-synuclein aggregates was also observed to develop progressively, appearing first in the olfactory bulb, then

Information security system based on virtual-optics imaging methodology and public key infrastructure

NASA Astrophysics Data System (ADS)

Peng, Xiang; Zhang, Peng; Cai, Lilong

In this paper, we present a virtual-optical based information security system model with the aid of public-key-infrastructure (PKI) techniques. The proposed model employs a hybrid architecture in which our previously published encryption algorithm based on virtual-optics imaging methodology (VOIM) can be used to encipher and decipher data while an asymmetric algorithm, for example RSA, is applied for enciphering and deciphering the session key(s). For an asymmetric system, given an encryption key, it is computationally infeasible to determine the decryption key and vice versa. The whole information security model is run under the framework of PKI, which is on basis of public-key cryptography and digital signatures. This PKI-based VOIM security approach has additional features like confidentiality, authentication, and integrity for the purpose of data encryption under the environment of network.

Key Elements for Judging the Quality of a Risk Assessment

PubMed Central

Fenner-Crisp, Penelope A.; Dellarco, Vicki L.

2016-01-01

Background: Many reports have been published that contain recommendations for improving the quality, transparency, and usefulness of decision making for risk assessments prepared by agencies of the U.S. federal government. A substantial measure of consensus has emerged regarding the characteristics that high-quality assessments should possess. Objective: The goal was to summarize the key characteristics of a high-quality assessment as identified in the consensus-building process and to integrate them into a guide for use by decision makers, risk assessors, peer reviewers and other interested stakeholders to determine if an assessment meets the criteria for high quality. Discussion: Most of the features cited in the guide are applicable to any type of assessment, whether it encompasses one, two, or all four phases of the risk-assessment paradigm; whether it is qualitative or quantitative; and whether it is screening level or highly sophisticated and complex. Other features are tailored to specific elements of an assessment. Just as agencies at all levels of government are responsible for determining the effectiveness of their programs, so too should they determine the effectiveness of their assessments used in support of their regulatory decisions. Furthermore, if a nongovernmental entity wishes to have its assessments considered in the governmental regulatory decision-making process, then these assessments should be judged in the same rigorous manner and be held to similar standards. Conclusions: The key characteristics of a high-quality assessment can be summarized and integrated into a guide for judging whether an assessment possesses the desired features of high quality, transparency, and usefulness. Citation: Fenner-Crisp PA, Dellarco VL. 2016. Key elements for judging the quality of a risk assessment. Environ Health Perspect 124:1127–1135; http://dx.doi.org/10.1289/ehp.1510483 PMID:26862984

Six-State Quantum Key Distribution Using Photons with Orbital Angular Momentum

NASA Astrophysics Data System (ADS)

Li, Jun-Lin; Wang, Chuan

2010-11-01

A new implementation of high-dimensional quantum key distribution (QKD) protocol is discussed. Using three mutual unbiased bases, we present a d-level six-state QKD protocol that exploits the orbital angular momentum with the spatial mode of the light beam. The protocol shows that the feature of a high capacity since keys are encoded using photon modes in d-level Hilbert space. The devices for state preparation and measurement are also discussed. This protocol has high security and the alignment of shared reference frames is not needed between sender and receiver.

The method for froth floatation condition recognition based on adaptive feature weighted

NASA Astrophysics Data System (ADS)

Wang, Jieran; Zhang, Jun; Tian, Jinwen; Zhang, Daimeng; Liu, Xiaomao

2018-03-01

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.

Human action recognition based on spatial-temporal descriptors using key poses

NASA Astrophysics Data System (ADS)

Hu, Shuo; Chen, Yuxin; Wang, Huaibao; Zuo, Yaqing

2014-11-01

Human action recognition is an important area of pattern recognition today due to its direct application and need in various occasions like surveillance and virtual reality. In this paper, a simple and effective human action recognition method is presented based on the key poses of human silhouette and the spatio-temporal feature. Firstly, the contour points of human silhouette have been gotten, and the key poses are learned by means of K-means clustering based on the Euclidean distance between each contour point and the centre point of the human silhouette, and then the type of each action is labeled for further match. Secondly, we obtain the trajectories of centre point of each frame, and create a spatio-temporal feature value represented by W to describe the motion direction and speed of each action. The value W contains the information of location and temporal order of each point on the trajectories. Finally, the matching stage is performed by comparing the key poses and W between training sequences and test sequences, the nearest neighbor sequences is found and its label supplied the final result. Experiments on the public available Weizmann datasets show the proposed method can improve accuracy by distinguishing amphibious poses and increase suitability for real-time applications by reducing the computational cost.

Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing

NASA Astrophysics Data System (ADS)

La Barbera, Selina; Vincent, Adrien F.; Vuillaume, Dominique; Querlioz, Damien; Alibart, Fabien

2016-12-01

Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.

Identifying the distinct features of geometric structures for hole trapping to generate radicals on rutile TiO₂(110) in photooxidation using density functional theory calculations with hybrid functional.

PubMed

Wang, Dong; Wang, Haifeng; Hu, P

2015-01-21

Using density functional theory calculations with HSE 06 functional, we obtained the structures of spin-polarized radicals on rutile TiO2(110), which is crucial to understand the photooxidation at the atomic level, and further calculate the thermodynamic stabilities of these radicals. By analyzing the results, we identify the structural features for hole trapping in the system, and reveal the mutual effects among the geometric structures, the energy levels of trapped hole states and their hole trapping capacities. Furthermore, the results from HSE 06 functional are compared to those from DFT + U and the stability trend of radicals against the number of slabs is tested. The effect of trapped holes on two important steps of the oxygen evolution reaction, i.e. water dissociation and the oxygen removal, is investigated and discussed.

Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions.

PubMed

Aksu, Yaman; Miller, David J; Kesidis, George; Yang, Qing X

2010-05-01

Feature selection for classification in high-dimensional spaces can improve generalization, reduce classifier complexity, and identify important, discriminating feature "markers." For support vector machine (SVM) classification, a widely used technique is recursive feature elimination (RFE). We demonstrate that RFE is not consistent with margin maximization, central to the SVM learning approach. We thus propose explicit margin-based feature elimination (MFE) for SVMs and demonstrate both improved margin and improved generalization, compared with RFE. Moreover, for the case of a nonlinear kernel, we show that RFE assumes that the squared weight vector 2-norm is strictly decreasing as features are eliminated. We demonstrate this is not true for the Gaussian kernel and, consequently, RFE may give poor results in this case. MFE for nonlinear kernels gives better margin and generalization. We also present an extension which achieves further margin gains, by optimizing only two degrees of freedom--the hyperplane's intercept and its squared 2-norm--with the weight vector orientation fixed. We finally introduce an extension that allows margin slackness. We compare against several alternatives, including RFE and a linear programming method that embeds feature selection within the classifier design. On high-dimensional gene microarray data sets, University of California at Irvine (UCI) repository data sets, and Alzheimer's disease brain image data, MFE methods give promising results.

Neocentromeres and epigenetically inherited features of centromeres

PubMed Central

Burrack, Laura S.; Berman, Judith

2012-01-01

Neocentromeres are ectopic sites where new functional kinetochores assemble and permit chromosome segregation. Neocentromeres usually form following genomic alterations that remove or disrupt centromere function. The ability to form neocentromeres is conserved in eukaryotes ranging from fungi to mammals. Neocentromeres that rescue chromosome fragments in cells with gross chromosomal rearrangements are found in several types of human cancers, and in patients with developmental disabilities. In this review, we discuss the importance of neocentromeres to human health and evaluate recently developed model systems to study neocentromere formation, maintenance, and function in chromosome segregation. Additionally, studies of neocentromeres provide insight into native centromeres; analysis of neocentromeres found in human clinical samples and induced in model organisms distinguishes features of centromeres that are dependent on centromere DNA from features that are epigenetically inherited together with the formation of a functional kinetochore. PMID:22723125

Tumors of the Testis: Morphologic Features and Molecular Alterations.

PubMed

Howitt, Brooke E; Berney, Daniel M

2015-12-01

This article reviews the most frequently encountered tumor of the testis; pure and mixed malignant testicular germ cell tumors (TGCT), with emphasis on adult (postpubertal) TGCTs and their differential diagnoses. We additionally review TGCT in the postchemotherapy setting, and findings to be integrated into the surgical pathology report, including staging of testicular tumors and other problematic issues. The clinical features, gross pathologic findings, key histologic features, common differential diagnoses, the use of immunohistochemistry, and molecular alterations in TGCTs are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Features of Discontinuous Galerkin Algorithms in Gkeyll, and Exponentially-Weighted Basis Functions

NASA Astrophysics Data System (ADS)

Hammett, G. W.; Hakim, A.; Shi, E. L.

2016-10-01

There are various versions of Discontinuous Galerkin (DG) algorithms that have interesting features that could help with challenging problems of higher-dimensional kinetic problems (such as edge turbulence in tokamaks and stellarators). We are developing the gyrokinetic code Gkeyll based on DG methods. Higher-order methods do more FLOPS to extract more information per byte, thus reducing memory and communication costs (which are a bottleneck for exascale computing). The inner product norm can be chosen to preserve energy conservation with non-polynomial basis functions (such as Maxwellian-weighted bases), which alternatively can be viewed as a Petrov-Galerkin method. This allows a full- F code to benefit from similar Gaussian quadrature employed in popular δf continuum gyrokinetic codes. We show some tests for a 1D Spitzer-Härm heat flux problem, which requires good resolution for the tail. For two velocity dimensions, this approach could lead to a factor of 10 or more speedup. Supported by the Max-Planck/Princeton Center for Plasma Physics, the SciDAC Center for the Study of Plasma Microturbulence, and DOE Contract DE-AC02-09CH11466.

Structural white matter asymmetries in relation to functional asymmetries during speech perception and production.

PubMed

Ocklenburg, Sebastian; Hugdahl, Kenneth; Westerhausen, René

2013-12-01

Functional hemispheric asymmetries of speech production and perception are a key feature of the human language system, but their neurophysiological basis is still poorly understood. Using a combined fMRI and tract-based spatial statistics approach, we investigated the relation of microstructural asymmetries in language-relevant white matter pathways and functional activation asymmetries during silent verb generation and passive listening to spoken words. Tract-based spatial statistics revealed several leftward asymmetric clusters in the arcuate fasciculus and uncinate fasciculus that were differentially related to activation asymmetries in the two functional tasks. Frontal and temporal activation asymmetries during silent verb generation were positively related to the strength of specific microstructural white matter asymmetries in the arcuate fasciculus. In contrast, microstructural uncinate fasciculus asymmetries were related to temporal activation asymmetries during passive listening. These findings suggest that white matter asymmetries may indeed be one of the factors underlying functional hemispheric asymmetries. Moreover, they also show that specific localized white matter asymmetries might be of greater relevance for functional activation asymmetries than microstructural features of whole pathways. © 2013.

Key-value store with internal key-value storage interface

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

Bent, John M.; Faibish, Sorin; Ting, Dennis P. J.

A key-value store is provided having one or more key-value storage interfaces. A key-value store on at least one compute node comprises a memory for storing a plurality of key-value pairs; and an abstract storage interface comprising a software interface module that communicates with at least one persistent storage device providing a key-value interface for persistent storage of one or more of the plurality of key-value pairs, wherein the software interface module provides the one or more key-value pairs to the at least one persistent storage device in a key-value format. The abstract storage interface optionally processes one or moremore » batch operations on the plurality of key-value pairs. A distributed embodiment for a partitioned key-value store is also provided.« less

Online feature selection with streaming features.

PubMed

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

2013-05-01

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

A delphi exercise to identify characteristic features of gout - opinions from patients and physicians, the first stage in developing new classification criteria.

PubMed

Prowse, Rebecca L; Dalbeth, Nicola; Kavanaugh, Arthur; Adebajo, Adewale O; Gaffo, Angelo L; Terkeltaub, Robert; Mandell, Brian F; Suryana, Bagus P P; Goldenstein-Schainberg, Claudia; Diaz-Torne, Cèsar; Khanna, Dinesh; Lioté, Frederic; Mccarthy, Geraldine; Kerr, Gail S; Yamanaka, Hisashi; Janssens, Hein; Baraf, Herbert F; Chen, Jiunn-Horng; Vazquez-Mellado, Janitzia; Harrold, Leslie R; Stamp, Lisa K; Van De Laar, Mart A; Janssen, Matthijs; Doherty, Michael; Boers, Maarten; Edwards, N Lawrence; Gow, Peter; Chapman, Peter; Khanna, Puja; Helliwell, Philip S; Grainger, Rebecca; Schumacher, H Ralph; Neogi, Tuhina; Jansen, Tim L; Louthrenoo, Worawit; Sivera, Francisca; Taylor, William J; Alten, Rieke

2013-04-01

To identify a comprehensive list of features that might discriminate between gout and other rheumatic musculoskeletal conditions, to be used subsequently for a case-control study to develop and test new classification criteria for gout. Two Delphi exercises were conducted using Web-based questionnaires: one with physicians from several countries who had an interest in gout and one with patients from New Zealand who had gout. Physicians rated a list of potentially discriminating features that were identified by literature review and expert opinion, and patients rated a list of features that they generated themselves. Agreement was defined by the RAND/UCLA disagreement index. Forty-four experienced physicians and 9 patients responded to all iterations. For physicians, 71 items were identified by literature review and 15 more were suggested by physicians. The physician survey showed agreement for 26 discriminatory features and 15 as not discriminatory. The patients identified 46 features of gout, for which there was agreement on 25 items as being discriminatory and 7 items as not discriminatory. Patients and physicians agreed upon several key features of gout. Physicians emphasized objective findings, imaging, and patterns of symptoms, whereas patients emphasized severity, functional results, and idiographic perception of symptoms.

Low cost, small form factor, and integration as the key features for the optical component industry takeoff

NASA Astrophysics Data System (ADS)

Schiattone, Francesco; Bonino, Stefano; Gobbi, Luigi; Groppi, Angelamaria; Marazzi, Marco; Musio, Maurizio

2003-04-01

In the past the optical component market has been mainly driven by performances. Today, as the number of competitors has drastically increased, the system integrators have a wide range of possible suppliers and solutions giving them the possibility to be more focused on cost and also on footprint reduction. So, if performances are still essential, low cost and Small Form Factor issues are becoming more and more crucial in selecting components. Another evolution in the market is the current request of the optical system companies to simplify the supply chain in order to reduce the assembling and testing steps at system level. This corresponds to a growing demand in providing subassemblies, modules or hybrid integrated components: that means also Integration will be an issue in which all the optical component companies will compete to gain market shares. As we can see looking several examples offered by electronic market, to combine low cost and SFF is a very challenging task but Integration can help in achieving both features. In this work we present how these issues could be approached giving examples of some advanced solutions applied to LiNbO3 modulators. In particular we describe the progress made on automation, new materials and low cost fabrication methods for the parts. We also introduce an approach in integrating optical and electrical functionality on LiNbO3 modulators including RF driver, bias control loop, attenuator and photodiode integrated in a single device.

Diagnostic features of Alzheimer's disease extracted from PET sinograms

NASA Astrophysics Data System (ADS)

Sayeed, A.; Petrou, M.; Spyrou, N.; Kadyrov, A.; Spinks, T.

2002-01-01

Texture analysis of positron emission tomography (PET) images of the brain is a very difficult task, due to the poor signal to noise ratio. As a consequence, very few techniques can be implemented successfully. We use a new global analysis technique known as the Trace transform triple features. This technique can be applied directly to the raw sinograms to distinguish patients with Alzheimer's disease (AD) from normal volunteers. FDG-PET images of 18 AD and 10 normal controls obtained from the same CTI ECAT-953 scanner were used in this study. The Trace transform triple feature technique was used to extract features that were invariant to scaling, translation and rotation, referred to as invariant features, as well as features that were sensitive to rotation but invariant to scaling and translation, referred to as sensitive features in this study. The features were used to classify the groups using discriminant function analysis. Cross-validation tests using stepwise discriminant function analysis showed that combining both sensitive and invariant features produced the best results, when compared with the clinical diagnosis. Selecting the five best features produces an overall accuracy of 93% with sensitivity of 94% and specificity of 90%. This is comparable with the classification accuracy achieved by Kippenhan et al (1992), using regional metabolic activity.

Designing ECG-based physical unclonable function for security of wearable devices.

PubMed

Shihui Yin; Chisung Bae; Sang Joon Kim; Jae-Sun Seo

2017-07-01

As a plethora of wearable devices are being introduced, significant concerns exist on the privacy and security of personal data stored on these devices. Expanding on recent works of using electrocardiogram (ECG) as a modality for biometric authentication, in this work, we investigate the possibility of using personal ECG signals as the individually unique source for physical unclonable function (PUF), which eventually can be used as the key for encryption and decryption engines. We present new signal processing and machine learning algorithms that learn and extract maximally different ECG features for different individuals and minimally different ECG features for the same individual over time. Experimental results with a large 741-subject in-house ECG database show that the distributions of the intra-subject (same person) Hamming distance of extracted ECG features and the inter-subject Hamming distance have minimal overlap. 256-b random numbers generated from the ECG features of 648 (out of 741) subjects pass the NIST randomness tests.

Deducing trapdoor primitives in public key encryption schemes

NASA Astrophysics Data System (ADS)

Pandey, Chandra

2005-03-01

Semantic security of public key encryption schemes is often interchangeable with the art of building trapdoors. In the frame of reference of Random Oracle methodology, the "Key Privacy" and "Anonymity" has often been discussed. However to a certain degree the security of most public key encryption schemes is required to be analyzed with formal proofs using one-way functions. This paper evaluates the design of El Gamal and RSA based schemes and attempts to parallelize the trapdoor primitives used in the computation of the cipher text, thereby magnifying the decryption error δp in the above schemes.

Partitioned key-value store with atomic memory operations

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

Bent, John M.; Faibish, Sorin; Grider, Gary

A partitioned key-value store is provided that supports atomic memory operations. A server performs a memory operation in a partitioned key-value store by receiving a request from an application for at least one atomic memory operation, the atomic memory operation comprising a memory address identifier; and, in response to the atomic memory operation, performing one or more of (i) reading a client-side memory location identified by the memory address identifier and storing one or more key-value pairs from the client-side memory location in a local key-value store of the server; and (ii) obtaining one or more key-value pairs from themore » local key-value store of the server and writing the obtained one or more key-value pairs into the client-side memory location identified by the memory address identifier. The server can perform functions obtained from a client-side memory location and return a result to the client using one or more of the atomic memory operations.« less

Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

PubMed

Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

2017-06-09

In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

Embedded Incremental Feature Selection for Reinforcement Learning

DTIC Science & Technology

2012-05-01

Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature

Nanoparticles for Cardiovascular Imaging and Therapeutic Delivery, Part 1: Compositions and Features.

PubMed

Stendahl, John C; Sinusas, Albert J

2015-10-01

Imaging agents made from nanoparticles are functionally versatile and have unique properties that may translate to clinical utility in several key cardiovascular imaging niches. Nanoparticles exhibit size-based circulation, biodistribution, and elimination properties different from those of small molecules and microparticles. In addition, nanoparticles provide versatile platforms that can be engineered to create both multimodal and multifunctional imaging agents with tunable properties. With these features, nanoparticulate imaging agents can facilitate fusion of high-sensitivity and high-resolution imaging modalities and selectively bind tissues for targeted molecular imaging and therapeutic delivery. Despite their intriguing attributes, nanoparticulate imaging agents have thus far achieved only limited clinical use. The reasons for this restricted advancement include an evolving scope of applications, the simplicity and effectiveness of existing small-molecule agents, pharmacokinetic limitations, safety concerns, and a complex regulatory environment. This review describes general features of nanoparticulate imaging agents and therapeutics and discusses challenges associated with clinical translation. A second, related review to appear in a subsequent issue of JNM highlights nuclear-based nanoparticulate probes in preclinical cardiovascular imaging. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Can interface features affect aggression resulting from violent video game play? An examination of realistic controller and large screen size.

PubMed

Kim, Ki Joon; Sundar, S Shyam

2013-05-01

Aggressiveness attributed to violent video game play is typically studied as a function of the content features of the game. However, can interface features of the game also affect aggression? Guided by the General Aggression Model (GAM), we examine the controller type (gun replica vs. mouse) and screen size (large vs. small) as key technological aspects that may affect the state aggression of gamers, with spatial presence and arousal as potential mediators. Results from a between-subjects experiment showed that a realistic controller and a large screen display induced greater aggression, presence, and arousal than a conventional mouse and a small screen display, respectively, and confirmed that trait aggression was a significant predictor of gamers' state aggression. Contrary to GAM, however, arousal showed no effects on aggression; instead, presence emerged as a significant mediator.

Visualizing bacterial tRNA identity determinants and antideterminants using function logos and inverse function logos

PubMed Central

Freyhult, Eva; Moulton, Vincent; Ardell, David H.

2006-01-01

Sequence logos are stacked bar graphs that generalize the notion of consensus sequence. They employ entropy statistics very effectively to display variation in a structural alignment of sequences of a common function, while emphasizing its over-represented features. Yet sequence logos cannot display features that distinguish functional subclasses within a structurally related superfamily nor do they display under-represented features. We introduce two extensions to address these needs: function logos and inverse logos. Function logos display subfunctions that are over-represented among sequences carrying a specific feature. Inverse logos generalize both sequence logos and function logos by displaying under-represented, rather than over-represented, features or functions in structural alignments. To make inverse logos, a compositional inverse is applied to the feature or function frequency distributions before logo construction, where a compositional inverse is a mathematical transform that makes common features or functions rare and vice versa. We applied these methods to a database of structurally aligned bacterial tDNAs to create highly condensed, birds-eye views of potentially all so-called identity determinants and antideterminants that confer specific amino acid charging or initiator function on tRNAs in bacteria. We recovered both known and a few potentially novel identity elements. Function logos and inverse logos are useful tools for exploratory bioinformatic analysis of structure–function relationships in sequence families and superfamilies. PMID:16473848

Variability In Long-Wave Runup as a Function of Nearshore Bathymetric Features

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

Dunkin, Lauren McNeill

Beaches and barrier islands are vulnerable to extreme storm events, such as hurricanes, that can cause severe erosion and overwash to the system. Having dunes and a wide beach in front of coastal infrastructure can provide protection during a storm, but the influence that nearshore bathymetric features have in protecting the beach and barrier island system is not completely understood. The spatial variation in nearshore features, such as sand bars and beach cusps, can alter nearshore hydrodynamics, including wave setup and runup. The influence of bathymetric features on long-wave runup can be used in evaluating the vulnerability of coastal regionsmore » to erosion and dune overtopping, evaluating the changing morphology, and implementing plans to protect infrastructure. In this thesis, long-wave runup variation due to changing bathymetric features as determined with the numerical model XBeach is quantified (eXtreme Beach behavior model). Wave heights are analyzed to determine the energy through the surfzone. XBeach assumes that coastal erosion at the land-sea interface is dominated by bound long-wave processes. Several hydrodynamic conditions are used to force the numerical model. The XBeach simulation results suggest that bathymetric irregularity induces significant changes in the extreme long-wave runup at the beach and the energy indicator through the surfzone.« less

Nanometer polymer surface features: the influence on surface energy, protein adsorption and endothelial cell adhesion

NASA Astrophysics Data System (ADS)

Carpenter, Joseph; Khang, Dongwoo; Webster, Thomas J.

2008-12-01

Current small diameter (<5 mm) synthetic vascular graft materials exhibit poor long-term patency due to thrombosis and intimal hyperplasia. Tissue engineered solutions have yielded functional vascular tissue, but some require an eight-week in vitro culture period prior to implantation—too long for immediate clinical bedside applications. Previous in vitro studies have shown that nanostructured poly(lactic-co-glycolic acid) (PLGA) surfaces elevated endothelial cell adhesion, proliferation, and extracellular matrix synthesis when compared to nanosmooth surfaces. Nonetheless, these studies failed to address the importance of lateral and vertical surface feature dimensionality coupled with surface free energy; nor did such studies elicit an optimum specific surface feature size for promoting endothelial cell adhesion. In this study, a series of highly ordered nanometer to submicron structured PLGA surfaces of identical chemistry were created using a technique employing polystyrene nanobeads and poly(dimethylsiloxane) (PDMS) molds. Results demonstrated increased endothelial cell adhesion on PLGA surfaces with vertical surface features of size less than 18.87 nm but greater than 0 nm due to increased surface energy and subsequently protein (fibronectin and collagen type IV) adsorption. Furthermore, this study provided evidence that the vertical dimension of nanometer surface features, rather than the lateral dimension, is largely responsible for these increases. In this manner, this study provides key design parameters that may promote vascular graft efficacy.

Escalator design features evaluation

NASA Technical Reports Server (NTRS)

Zimmerman, W. F.; Deshpande, G. K.

1982-01-01

Escalators are available with design features such as dual speed (90 and 120 fpm), mat operation and flat steps. These design features were evaluated based on the impact of each on capital and operating costs, traffic flow, and safety. A human factors engineering model was developed to analyze the need for flat steps at various speeds. Mat operation of escalators was found to be cost effective in terms of energy savings. Dual speed operation of escalators with the higher speed used during peak hours allows for efficient operation. A minimum number of flat steps required as a function of escalator speed was developed to ensure safety for the elderly.

Florida Keys

NASA Image and Video Library

2002-12-13

The Florida Keys are a chain of islands, islets and reefs extending from Virginia Key to the Dry Tortugas for about 309 kilometers (192 miles). The keys are chiefly limestone and coral formations. The larger islands of the group are Key West (with its airport), Key Largo, Sugarloaf Key, and Boca Chica Key. A causeway extends from the mainland to Key West. This image was acquired on October 28, 2001, by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. With its 14 spectral bands from the visible to the thermal infrared wavelength region, and its high spatial resolution of 15 to 90 meters (about 50 to 300 feet), ASTER images Earth to map and monitor the changing surface of our planet. http://photojournal.jpl.nasa.gov/catalog/PIA03890

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

Spin-Multiplet Components and Energy Splittings by Multistate Density Functional Theory.

PubMed

Grofe, Adam; Chen, Xin; Liu, Wenjian; Gao, Jiali

2017-10-05

Kohn-Sham density functional theory has been tremendously successful in chemistry and physics. Yet, it is unable to describe the energy degeneracy of spin-multiplet components with any approximate functional. This work features two contributions. (1) We present a multistate density functional theory (MSDFT) to represent spin-multiplet components and to determine multiplet energies. MSDFT is a hybrid approach, taking advantage of both wave function theory and density functional theory. Thus, the wave functions, electron densities and energy density-functionals for ground and excited states and for different components are treated on the same footing. The method is illustrated on valence excitations of atoms and molecules. (2) Importantly, a key result is that for cases in which the high-spin components can be determined separately by Kohn-Sham density functional theory, the transition density functional in MSDFT (which describes electronic coupling) can be defined rigorously. The numerical results may be explored to design and optimize transition density functionals for configuration coupling in multiconfigurational DFT.

Spectral feature design in high dimensional multispectral data

NASA Technical Reports Server (NTRS)

Chen, Chih-Chien Thomas; Landgrebe, David A.

1988-01-01

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture.

PubMed

Layher, Georg; Brosch, Tobias; Neumann, Heiko

2017-01-01

Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks ( Eedn ) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based

Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture

PubMed Central

Layher, Georg; Brosch, Tobias; Neumann, Heiko

2017-01-01

Intelligent agents, such as robots, have to serve a multitude of autonomous functions. Examples are, e.g., collision avoidance, navigation and route planning, active sensing of its environment, or the interaction and non-verbal communication with people in the extended reach space. Here, we focus on the recognition of the action of a human agent based on a biologically inspired visual architecture of analyzing articulated movements. The proposed processing architecture builds upon coarsely segregated streams of sensory processing along different pathways which separately process form and motion information (Layher et al., 2014). Action recognition is performed in an event-based scheme by identifying representations of characteristic pose configurations (key poses) in an image sequence. In line with perceptual studies, key poses are selected unsupervised utilizing a feature-driven criterion which combines extrema in the motion energy with the horizontal and the vertical extendedness of a body shape. Per class representations of key pose frames are learned using a deep convolutional neural network consisting of 15 convolutional layers. The network is trained using the energy-efficient deep neuromorphic networks (Eedn) framework (Esser et al., 2016), which realizes the mapping of the trained synaptic weights onto the IBM Neurosynaptic System platform (Merolla et al., 2014). After the mapping, the trained network achieves real-time capabilities for processing input streams and classify input images at about 1,000 frames per second while the computational stages only consume about 70 mW of energy (without spike transduction). Particularly regarding mobile robotic systems, a low energy profile might be crucial in a variety of application scenarios. Cross-validation results are reported for two different datasets and compared to state-of-the-art action recognition approaches. The results demonstrate, that (I) the presented approach is on par with other key pose based

Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme

PubMed Central

Wang, Chengqi; Zhang, Xiao; Zheng, Zhiming

2016-01-01

With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.’s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks. PMID:26866606

Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme.

PubMed

Wang, Chengqi; Zhang, Xiao; Zheng, Zhiming

2016-01-01

With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.'s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks.

Kidneys: Key Modulators of HDL Levels and Function

PubMed Central

Yang, Haichun; Fogo, Agnes B.; Kon, Valentina

2016-01-01

Purpose of review This review will examine advances in our understanding of the role kidneys play in HDL metabolism and the effect on levels, composition, and function of HDL particles. Recent findings Components of the HDL particles can cross the glomerular filtration barrier. Some of these components, including apolipoproteins and enzymes involved in lipid metabolism, are taken up by the proximal tubule and degraded, modified, salvaged/returned to the circulation, or lost in the urine. Injury of the glomerular capillaries or tubules can affect these intrarenal processes and modify HDL. Changes in the plasma and urine levels of HDL may be novel markers of kidney damage and/or mechanism(s) of kidney disease. Summary The kidneys have a significant role in metabolism of individual HDL components, which in turn modulate HDL levels, composition and functionality of HDL particles. These intrarenal effects may be useful markers of kidney damage and have consequences on kidney-related perturbations in HDL. PMID:27008596

Boosting instance prototypes to detect local dermoscopic features.

PubMed

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

Functional Utrastructure of Genlisea (Lentibulariaceae) Digestive Hairs

PubMed Central

Płachno, Bartosz Jan; Kozieradzka-Kiszkurno, Małgorzata; Świątek, Piotr

2007-01-01

Background and Aims Digestive structures of carnivorous plants produce external digestive enzymes, and play the main role in absorption. In Lentibulariaceae, the ultrastructure of digestive hairs has been examined in some detail in Pinguicula and Utricularia, but the sessile digestive hairs of Genlisea have received very little attention so far. The aim of this study was to fill this gap by expanding their morphological, anatomical and histochemical characterization. Methods Several imaging techniques were used, including light, confocal and electron microscopy, to reveal the structure and function of the secretory hairs of Genlisea traps. This report demonstrates the application of cryo-SEM for fast imaging of whole, physically fixed plant secretory structures. Key Results and Conclusion The concentration of digestive hairs along vascular bundles in subgenus Genlisea is a primitive feature, indicating its basal position within the genus. Digestive hairs of Genlisea consist of three compartments with different ultrastructure and function. In subgenus Tayloria the terminal hair cells are transfer cells, but not in species of subgenus Genlisea. A digestive pool of viscous fluid occurs in Genlisea traps. In spite of their similar architecture, the digestive-absorptive hairs of Lentibulariaceae feature differences in morphology and ultrastructure. PMID:17550910

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques

PubMed Central

Sui, Jing; Adali, Tülay; Pearlson, Godfrey D.; Calhoun, Vince D.

2013-01-01

Extraction of relevant features from multitask functional MRI (fMRI) data in order to identify potential biomarkers for disease, is an attractive goal. In this paper, we introduce a novel feature-based framework, which is sensitive and accurate in detecting group differences (e.g. controls vs. patients) by proposing three key ideas. First, we integrate two goal-directed techniques: coefficient-constrained independent component analysis (CC-ICA) and principal component analysis with reference (PCA-R), both of which improve sensitivity to group differences. Secondly, an automated artifact-removal method is developed for selecting components of interest derived from CC-ICA, with an average accuracy of 91%. Finally, we propose a strategy for optimal feature/component selection, aiming to identify optimal group-discriminative brain networks as well as the tasks within which these circuits are engaged. The group-discriminating performance is evaluated on 15 fMRI feature combinations (5 single features and 10 joint features) collected from 28 healthy control subjects and 25 schizophrenia patients. Results show that a feature from a sensorimotor task and a joint feature from a Sternberg working memory (probe) task and an auditory oddball (target) task are the top two feature combinations distinguishing groups. We identified three optimal features that best separate patients from controls, including brain networks consisting of temporal lobe, default mode and occipital lobe circuits, which when grouped together provide improved capability in classifying group membership. The proposed framework provides a general approach for selecting optimal brain networks which may serve as potential biomarkers of several brain diseases and thus has wide applicability in the neuroimaging research community. PMID:19457398

Image Mosaic Method Based on SIFT Features of Line Segment

PubMed Central

Zhu, Jun; Ren, Mingwu

2014-01-01

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

Protein analysis: key to the future.

PubMed

Boodhun, Nawsheen

2018-05-01

Protein analysis is crucial to elucidating the function of proteins and understanding the impact of their presence, absence and alteration. This is key to advancing knowledge about diseases, providing the opportunity for biomarker discovery and development of therapeutics. In this issue of Tech News, Nawsheen Boodhun explores the various means of protein analysis.

Adaptive feature selection using v-shaped binary particle swarm optimization.

PubMed

Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

Adaptive feature selection using v-shaped binary particle swarm optimization

PubMed Central

Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers. PMID:28358850

Personality Disorder Features and Insomnia Status amongst Hypnotic-Dependent Adults

PubMed Central

Ruiter, Megan E.; Lichstein, Kenneth L.; Nau, Sidney D.; Geyer, James

2012-01-01

Objective To determine the prevalence of personality disorders and their relation to insomnia parameters among persons with chronic insomnia with hypnotic dependence. Methods Eighty-four adults with chronic insomnia with hypnotic dependence completed the SCID-II personality questionnaire, two-weeks of sleep diaries, polysomnography, and measures of insomnia severity, impact, fatigue severity, depression, anxiety, and quality of life. Frequencies, between-subjects t-tests and hierarchical regression models were conducted. Results Cluster C personality disorders were most prevalent (50%). Obsessive-compulsive personality disorder (OCPD) was most common (n=39). These individuals compared to participants with no personality disorders did not differ in objective and subjective sleep parameters. Yet, they had poorer insomnia-related daytime functioning. OCPD and Avoidant personality disorders features were associated with poorer daytime functioning. OCPD features were related to greater fatigue severity, and overestimation of time awake was trending. Schizotypal and Schizoid features were positively associated with insomnia severity. Dependent personality disorder features were related to underestimating time awake. Conclusions Cluster C personality disorders were highly prevalent in patients with chronic insomnia with hypnotic dependence. Features of Cluster C and A personality disorders were variously associated with poorer insomnia-related daytime functioning, fatigue, and estimation of nightly wake-time. Future interventions may need to address these personality features. PMID:22938862

Personality disorder features and insomnia status amongst hypnotic-dependent adults.

PubMed

Ruiter, Megan E; Lichstein, Kenneth L; Nau, Sidney D; Geyer, James D

2012-10-01

To determine the prevalence of personality disorders and their relation to insomnia parameters among persons with chronic insomnia with hypnotic dependence. Eighty-four adults with chronic insomnia with hypnotic dependence completed the SCID-II personality questionnaire, two-weeks of sleep diaries, polysomnography, and measures of insomnia severity, impact, fatigue severity, depression, anxiety, and quality of life. Frequencies, between-subjects t-tests and hierarchical regression models were conducted. Cluster C personality disorders were most prevalent (50%). Obsessive-Compulsive personality disorder (OCPD) was most common (n=39). These individuals compared to participants with no personality disorders did not differ in objective and subjective sleep parameters. Yet, they had poorer insomnia-related daytime functioning. OCPD and Avoidant personality disorders features were associated with poorer daytime functioning. OCPD features were related to greater fatigue severity, and overestimation of time awake was trending. Schizotypal and Schizoid features were positively associated with insomnia severity. Dependent personality disorder features were related to underestimating time awake. Cluster C personality disorders were highly prevalent in patients with chronic insomnia with hypnotic dependence. Features of Cluster C and A personality disorders were variously associated with poorer insomnia-related daytime functioning, fatigue, and estimation of nightly wake-time. Future interventions may need to address these personality features. Copyright © 2012 Elsevier B.V. All rights reserved.

Microbiota, a key player in alcoholic liver disease.

PubMed

Cassard, Anne-Marie; Ciocan, Dragos

2017-12-22

Alcoholic liver disease (ALD) is a major cause of morbidity and mortality worldwide. Only 20% of heavy alcohol consumers develop alcoholic liver cirrhosis. The intestinal microbiota (IM) has been recently identified as a key player in the severity of liver injury in ALD. Common features of ALD include a decrease of gut epithelial tight junction protein expression, mucin production, and antimicrobial peptide levels. This disruption of the gut barrier, which is a prerequisite for ALD, leads to the passage of bacterial products into the blood stream (endotoxemia). Moreover, metabolites produced by bacteria, such as short chain fatty acids, volatile organic compounds (VOS), and bile acids (BA), are involved in ALD pathology. Probiotic treatment, IM transplantation, or the consumption of dietary fiber, such as pectin, which all alter the ratio of bacterial species, have been shown to improve liver injury in animal models of ALD and to be associated with an improvement in gut barrier function. Although the connections between the microbiota and the host in ALD are well established, the underlying mechanisms are still an active area of research. Targeting the microbiome through the use of prebiotic, probiotic, and postbiotic modalities could be an attractive new approach to manage ALD.

Neural networks: further insights into error function, generalized weights and others

PubMed Central

2016-01-01

The article is a continuum of a previous one providing further insights into the structure of neural network (NN). Key concepts of NN including activation function, error function, learning rate and generalized weights are introduced. NN topology can be visualized with generic plot() function by passing a “nn” class object. Generalized weights assist interpretation of NN model with respect to the independent effect of individual input variables. A large variance of generalized weights for a covariate indicates non-linearity of its independent effect. If generalized weights of a covariate are approximately zero, the covariate is considered to have no effect on outcome. Finally, prediction of new observations can be performed using compute() function. Make sure that the feature variables passed to the compute() function are in the same order to that in the training NN. PMID:27668220

A quality function deployment framework for the service quality of health information websites.

PubMed

Chang, Hyejung; Kim, Dohoon

2010-03-01

This research was conducted to identify both the users' service requirements on health information websites (HIWs) and the key functional elements for running HIWs. With the quality function deployment framework, the derived service attributes (SAs) are mapped into the suppliers' functional characteristics (FCs) to derive the most critical FCs for the users' satisfaction. Using the survey data from 228 respondents, the SAs, FCs and their relationships were analyzed using various multivariate statistical methods such as principal component factor analysis, discriminant analysis, correlation analysis, etc. Simple and compound FC priorities were derived by matrix calculation. Nine factors of SAs and five key features of FCs were identified, and these served as the basis for the house of quality model. Based on the compound FC priorities, the functional elements pertaining to security and privacy, and usage support should receive top priority in the course of enhancing HIWs. The quality function deployment framework can improve the FCs of the HIWs in an effective, structured manner, and it can also be utilized for critical success factors together with their strategic implications for enhancing the service quality of HIWs. Therefore, website managers could efficiently improve website operations by considering this study's results.

Key Features of the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) System Architecture

NASA Astrophysics Data System (ADS)

Pela, F.; Tsugawa, R. K.; Andreoli, L. J.

2004-12-01

The National Polar-Orbiting NPOESS, a tri-agency program, supports missions of the Department of Commerce (DOC)/National Oceanic and Atmospheric Administration (NOAA), the Department of Defense (DoD), and the National Aeronautics and Space Administration (NASA). NPOESS provides a critical, timely, reliable, and high quality space-based sensing capability to acquire and process global and regional environmental imagery and specialized meteorological, climatic, terrestrial, oceanographic, solar-geophysical, and other data products. These products are delivered to national weather and environmental facilities operated by NOAA and DoD, to NASA, and to environmental remote sensing science community users to support civil and military functions. These data are also provided in real time to field terminals deployed worldwide. The NPOESS architecture is built on a foundation of affordability, and the three pillars of data quality, latency, availability. Affordability refers to an over-arching awareness of cost to provide the best value to the government for implementing a converged system; some dimensions of cost include the cost for system development and implementation, the balance between development costs and operation and maintenance costs, and the fiscal year expenditure plans that meet schedule commitments. Data quality is characterized in terms of the attributes associated with Environmental Data Records (EDRs), and the products that are delivered to the four US Operational Centrals and field users. These EDRs are generated by the system using raw data from the space-borne sensors and spacecraft, in conjunction with science algorithms and calibration factors. Data latency refers to the time period between the detection of energy by a space-borne sensor to the delivery of a corresponding EDR. The system was designed to minimize data latency, and hence provide users with timely data. Availability refers to both data availability and system operational availability

High resolution as a key feature to perform accurate ELISPOT measurements using Zeiss KS ELISPOT readers.

PubMed

Malkusch, Wolf

2005-01-01

The enzyme-linked immunospot (ELISPOT) assay was originally developed for the detection of individual antibody secreting B-cells. Since then, the method has been improved, and ELISPOT is used for the determination of the production of tumor necrosis factor (TNF)-alpha, interferon (IFN)-gamma, or various interleukins (IL)-4, IL-5. ELISPOT measurements are performed in 96-well plates with nitrocellulose membranes either visually or by means of image analysis. Image analysis offers various procedures to overcome variable background intensity problems and separate true from false spots. ELISPOT readers offer a complete solution for precise and automatic evaluation of ELISPOT assays. Number, size, and intensity of each single spot can be determined, printed, or saved for further statistical evaluation. Cytokine spots are always round, but because of floating edges with the background, they have a nonsmooth borderline. Resolution is a key feature for a precise detection of ELISPOT. In standard applications shape and edge steepness are essential parameters in addition to size and color for an accurate spot recognition. These parameters need a minimum spot diameter of 6 pixels. Collecting one single image per well with a standard color camera with 750 x 560 pixels will result in a resolution much too low to get all of the spots in a specimen. IFN-gamma spots may have only 25 microm diameters, and TNF-alpha spots just 15 microm. A 750 x 560 pixel image of a 6-mm well has a pixel size of 12 microm, resulting in only 1 or 2 pixel for a spot. Using a precise microscope optic in combination with a high resolution (1300 x 1030 pixel) integrating digital color camera, and at least 2 x 2 images per well will result in a pixel size of 2.5 microm and, as a minimum, 6 pixel diameter per spot. New approaches try to detect two cytokines per cell at the same time (i.e., IFN-gamma and IL-5). Standard staining procedures produce brownish spots (horseradish peroxidase) and blue spots

Quantum key distribution: vulnerable if imperfectly implemented

NASA Astrophysics Data System (ADS)

Leuchs, G.

2013-10-01

We report several vulnerabilities found in Clavis2, the flagship quantum key distribution (QKD) system from ID Quantique. We show the hacking of a calibration sequence run by Clavis2 to synchronize the Alice and Bob devices before performing the secret key exchange. This hack induces a temporal detection efficiency mismatch in Bob that can allow Eve to break the security of the cryptosystem using faked states. We also experimentally investigate the superlinear behaviour in the single-photon detectors (SPDs) used by Bob. Due to this superlinearity, the SPDs feature an actual multi-photon detection probability which is generally higher than the theoretically-modelled value. We show how this increases the risk of detector control attacks on QKD systems (including Clavis2) employing such SPDs. Finally, we review the experimental feasibility of Trojan-horse attacks. In the case of Clavis2, the objective is to read Bob's phase modulator to acquire knowledge of his basis choice as this information suffices for constructing the raw key in the Scarani-Acin-Ribordy-Gisin 2004 (SARG04) protocol. We work in close collaboration with ID Quantique and for all these loopholes, we notified them in advance. Wherever possible, we or ID Quantique proposed countermeasures and they implemented suitable patches and upgrade their systems.

LINKING LUNG AIRWAY STRUCTURE TO PULMONARY FUNCTION VIA COMPOSITE BRIDGE REGRESSION

PubMed Central

Chen, Kun; Hoffman, Eric A.; Seetharaman, Indu; Jiao, Feiran; Lin, Ching-Long; Chan, Kung-Sik

2017-01-01

The human lung airway is a complex inverted tree-like structure. Detailed airway measurements can be extracted from MDCT-scanned lung images, such as segmental wall thickness, airway diameter, parent-child branch angles, etc. The wealth of lung airway data provides a unique opportunity for advancing our understanding of the fundamental structure-function relationships within the lung. An important problem is to construct and identify important lung airway features in normal subjects and connect these to standardized pulmonary function test results such as FEV1%. Among other things, the problem is complicated by the fact that a particular airway feature may be an important (relevant) predictor only when it pertains to segments of certain generations. Thus, the key is an efficient, consistent method for simultaneously conducting group selection (lung airway feature types) and within-group variable selection (airway generations), i.e., bi-level selection. Here we streamline a comprehensive procedure to process the lung airway data via imputation, normalization, transformation and groupwise principal component analysis, and then adopt a new composite penalized regression approach for conducting bi-level feature selection. As a prototype of composite penalization, the proposed composite bridge regression method is shown to admit an efficient algorithm, enjoy bi-level oracle properties, and outperform several existing methods. We analyze the MDCT lung image data from a cohort of 132 subjects with normal lung function. Our results show that, lung function in terms of FEV1% is promoted by having a less dense and more homogeneous lung comprising an airway whose segments enjoy more heterogeneity in wall thicknesses, larger mean diameters, lumen areas and branch angles. These data hold the potential of defining more accurately the “normal” subject population with borderline atypical lung functions that are clearly influenced by many genetic and environmental factors. PMID

Concurrent evolution of feature extractors and modular artificial neural networks

NASA Astrophysics Data System (ADS)

Hannak, Victor; Savakis, Andreas; Yang, Shanchieh Jay; Anderson, Peter

2009-05-01

This paper presents a new approach for the design of feature-extracting recognition networks that do not require expert knowledge in the application domain. Feature-Extracting Recognition Networks (FERNs) are composed of interconnected functional nodes (feurons), which serve as feature extractors, and are followed by a subnetwork of traditional neural nodes (neurons) that act as classifiers. A concurrent evolutionary process (CEP) is used to search the space of feature extractors and neural networks in order to obtain an optimal recognition network that simultaneously performs feature extraction and recognition. By constraining the hill-climbing search functionality of the CEP on specific parts of the solution space, i.e., individually limiting the evolution of feature extractors and neural networks, it was demonstrated that concurrent evolution is a necessary component of the system. Application of this approach to a handwritten digit recognition task illustrates that the proposed methodology is capable of producing recognition networks that perform in-line with other methods without the need for expert knowledge in image processing.

Larvae of five horticulturally important species of Chrysopodes (Neuroptera, Chrysopidae): shared generic features, descriptions and keys

PubMed Central

Silva, Patrícia S.; Tauber, Catherine A.; Albuquerque, Gilberto S.; Tauber, Maurice J.

2013-01-01

Abstract An expanded list of generic level larval characteristics is presented for Chrysopodes; it includes a reinterpretation of the mesothoracic and metathoracic structure and setation. Keys, descriptions and images of Semaphoront A (first instar) and Semaphoront B (second and third instars) are offered for identifying five species of Chrysopodes (Chrysopodes) that are commonly reported from horticultural habitats in the Neotropical region. PMID:23653514

Attractiveness as a Function of Skin Tone and Facial Features: Evidence from Categorization Studies.

PubMed

Stepanova, Elena V; Strube, Michael J

2018-01-01

Participants rated the attractiveness and racial typicality of male faces varying in their facial features from Afrocentric to Eurocentric and in skin tone from dark to light in two experiments. Experiment 1 provided evidence that facial features and skin tone have an interactive effect on perceptions of attractiveness and mixed-race faces are perceived as more attractive than single-race faces. Experiment 2 further confirmed that faces with medium levels of skin tone and facial features are perceived as more attractive than faces with extreme levels of these factors. Black phenotypes (combinations of dark skin tone and Afrocentric facial features) were rated as more attractive than White phenotypes (combinations of light skin tone and Eurocentric facial features); ambiguous faces (combinations of Afrocentric and Eurocentric physiognomy) with medium levels of skin tone were rated as the most attractive in Experiment 2. Perceptions of attractiveness were relatively independent of racial categorization in both experiments.

Binding of multiple features in memory by high-functioning adults with autism spectrum disorder.

PubMed

Bowler, Dermot M; Gaigg, Sebastian B; Gardiner, John M

2014-09-01

Diminished episodic memory and diminished use of semantic information to aid recall by individuals with autism spectrum disorder (ASD) are both thought to result from diminished relational binding of elements of complex stimuli. To test this hypothesis, we asked high-functioning adults with ASD and typical comparison participants to study grids in which some cells contained drawings of objects in non-canonical colours. Participants were told at study which features (colour, item, location) would be tested in a later memory test. In a second experiment, participants studied similar grids and were told that they would be tested on object-location or object-colour combinations. Recognition of combinations was significantly diminished in ASD, which survived covarying performance on the Color Trails Test (D'Elia et al. Color trails test. Professional manual. Psychological Assessment Resources, Lutz, 1996), a test of executive difficulties. The findings raise the possibility that medial temporal as well as frontal lobe processes are dysfunctional in ASD.

Specific features of after-school program quality: associations with children's functioning in middle childhood.

PubMed

Pierce, Kim M; Bolt, Daniel M; Vandell, Deborah Lowe

2010-06-01

This longitudinal study examined associations between three after-school program quality features (positive staff-child relations, available activities, programming flexibility) and child developmental outcomes (reading and math grades, work habits, and social skills with peers) in Grade 2 and then Grade 3. Participants (n = 120 in Grade 2, n = 91 in Grade 3) attended after-school programs more than 4 days per week, on average. Controlling for child and family background factors and children's prior functioning on the developmental outcomes, positive staff-child relations in the programs were positively associated with children's reading grades in both Grades 2 and 3, and math grades in Grade 2. Positive staff-child relations also were positively associated with social skills in Grade 2, for boys only. The availability of a diverse array of age-appropriate activities at the programs was positively associated with children's math grades and classroom work habits in Grade 3. Programming flexibility (child choice of activities) was not associated with child outcomes.

Finding functional features in Saccharomyces genomes by phylogenetic footprinting.

PubMed

Cliften, Paul; Sudarsanam, Priya; Desikan, Ashwin; Fulton, Lucinda; Fulton, Bob; Majors, John; Waterston, Robert; Cohen, Barak A; Johnston, Mark

2003-07-04

The sifting and winnowing of DNA sequence that occur during evolution cause nonfunctional sequences to diverge, leaving phylogenetic footprints of functional sequence elements in comparisons of genome sequences. We searched for such footprints among the genome sequences of six Saccharomyces species and identified potentially functional sequences. Comparison of these sequences allowed us to revise the catalog of yeast genes and identify sequence motifs that may be targets of transcriptional regulatory proteins. Some of these conserved sequence motifs reside upstream of genes with similar functional annotations or similar expression patterns or those bound by the same transcription factor and are thus good candidates for functional regulatory sequences.

Short Review on Quantum Key Distribution Protocols.

PubMed

Giampouris, Dimitris

2017-01-01

Cryptographic protocols and mechanisms are widely investigated under the notion of quantum computing. Quantum cryptography offers particular advantages over classical ones, whereas in some cases established protocols have to be revisited in order to maintain their functionality. The purpose of this paper is to provide the basic definitions and review the most important theoretical advancements concerning the BB84 and E91 protocols. It also aims to offer a summary on some key developments on the field of quantum key distribution, closely related with the two aforementioned protocols. The main goal of this study is to provide the necessary background information along with a thorough review on the theoretical aspects of QKD, concentrating on specific protocols. The BB84 and E91 protocols have been chosen because most other protocols are similar to these, a fact that makes them important for the general understanding of how the QKD mechanism functions.

Integrating anatomy and function for zebrafish circuit analysis.

PubMed

Arrenberg, Aristides B; Driever, Wolfgang

2013-01-01

Due to its transparency, virtually every brain structure of the larval zebrafish is accessible to light-based interrogation of circuit function. Advanced stimulation techniques allow the activation of optogenetic actuators at different resolution levels, and genetically encoded calcium indicators report the activity of a large proportion of neurons in the CNS. Large datasets result and need to be analyzed to identify cells that have specific properties-e.g., activity correlation to sensory stimulation or behavior. Advances in three-dimensional (3D) functional mapping in zebrafish are promising; however, the mere coordinates of implicated neurons are not sufficient. To comprehensively understand circuit function, these functional maps need to be placed into the proper context of morphological features and projection patterns, neurotransmitter phenotypes, and key anatomical landmarks. We discuss the prospect of merging functional and anatomical data in an integrated atlas from the perspective of our work on long-range dopaminergic neuromodulation and the oculomotor system. We propose that such a resource would help researchers to surpass current hurdles in circuit analysis to achieve an integrated understanding of anatomy and function.

A free-access online key to identify Amazonian ferns.

PubMed

Zuquim, Gabriela; Tuomisto, Hanna; Prado, Jefferson

2017-01-01

There is urgent need for more data on species distributions in order to improve conservation planning. A crucial but challenging aspect of producing high-quality data is the correct identification of organisms. Traditional printed floras and dichotomous keys are difficult to use for someone not familiar with the technical jargon. In poorly known areas, such as Amazonia, they also become quickly outdated as new species are described or ranges extended. Recently, online tools have allowed developing dynamic, interactive, and accessible keys that make species identification possible for a broader public. In order to facilitate identifying plants collected in field inventories, we developed an internet-based free-access tool to identify Amazonian fern species. We focused on ferns, because they are easy to collect and their edaphic affinities are relatively well known, so they can be used as an indicator group for habitat mapping. Our key includes 302 terrestrial and aquatic entities mainly from lowland Amazonian forests. It is a free-access key, so the user can freely choose which morphological features to use and in which order to assess them. All taxa are richly illustrated, so specimens can be identified by a combination of character choices, visual comparison, and written descriptions. The identification tool was developed in Lucid 3.5 software and it is available at http://keyserver.lucidcentral.org:8080/sandbox/keys.jsp.

A free-access online key to identify Amazonian ferns

PubMed Central

Zuquim, Gabriela; Tuomisto, Hanna; Prado, Jefferson

2017-01-01

Abstract There is urgent need for more data on species distributions in order to improve conservation planning. A crucial but challenging aspect of producing high-quality data is the correct identification of organisms. Traditional printed floras and dichotomous keys are difficult to use for someone not familiar with the technical jargon. In poorly known areas, such as Amazonia, they also become quickly outdated as new species are described or ranges extended. Recently, online tools have allowed developing dynamic, interactive, and accessible keys that make species identification possible for a broader public. In order to facilitate identifying plants collected in field inventories, we developed an internet-based free-access tool to identify Amazonian fern species. We focused on ferns, because they are easy to collect and their edaphic affinities are relatively well known, so they can be used as an indicator group for habitat mapping. Our key includes 302 terrestrial and aquatic entities mainly from lowland Amazonian forests. It is a free-access key, so the user can freely choose which morphological features to use and in which order to assess them. All taxa are richly illustrated, so specimens can be identified by a combination of character choices, visual comparison, and written descriptions. The identification tool was developed in Lucid 3.5 software and it is available at http://keyserver.lucidcentral.org:8080/sandbox/keys.jsp. PMID:28781548

Immunohistological features related to functional impairment in lymphangioleiomyomatosis.

PubMed

Nascimento, Ellen Caroline Toledo do; Baldi, Bruno Guedes; Mariani, Alessandro Wasum; Annoni, Raquel; Kairalla, Ronaldo Adib; Pimenta, Suzana Pinheiro; da Silva, Luiz Fernando Ferraz; Carvalho, Carlos Roberto Ribeiro; Dolhnikoff, Marisa

2018-05-08

Lymphangioleiomyomatosis (LAM) is a low-grade neoplasm characterized by the pulmonary infiltration of smooth muscle-like cells (LAM cells) and cystic destruction. Patients usually present with airway obstruction in pulmonary function tests (PFTs). Previous studies have shown correlations among histological parameters, lung function abnormalities and prognosis in LAM. We investigated the lung tissue expression of proteins related to the mTOR pathway, angiogenesis and enzymatic activity and its correlation with functional parameters in LAM patients. We analyzed morphological and functional parameters of thirty-three patients. Two groups of disease severity were identified according to FEV1 values. Lung tissue from open biopsies or lung transplants was immunostained for SMA, HMB-45, mTOR, VEGF-D, MMP-9 and D2-40. Density of cysts, density of nodules and protein expression were measured by image analysis and correlated with PFT parameters. There was no difference in the expression of D2-40 between the more severe and the less severe groups. All other immunohistological parameters showed significantly higher values in the more severe group (p ≤ 0.002). The expression of VEGF-D, MMP-9 and mTOR in LAM cells was associated with the density of both cysts and nodules. The density of cysts and nodules as well as the expression of MMP-9 and VEGF-D were associated with the impairment of PFT parameters. Severe LAM represents an active phase of the disease with high expression of VEGF-D, mTOR, and MMP-9, as well as LAM cell infiltration. Our findings suggest that the tissue expression levels of VEGF-D and MMP-9 are important parameters associated with the loss of pulmonary function and could be considered as potential severity markers in open lung biopsies of LAM patients.

Incidental and context-responsive activation of structure- and function-based action features during object identification

PubMed Central

Lee, Chia-lin; Middleton, Erica; Mirman, Daniel; Kalénine, Solène; Buxbaum, Laurel J.

2012-01-01

Previous studies suggest that action representations are activated during object processing, even when task-irrelevant. In addition, there is evidence that lexical-semantic context may affect such activation during object processing. Finally, prior work from our laboratory and others indicates that function-based (“use”) and structure-based (“move”) action subtypes may differ in their activation characteristics. Most studies assessing such effects, however, have required manual object-relevant motor responses, thereby plausibly influencing the activation of action representations. The present work utilizes eyetracking and a Visual World Paradigm task without object-relevant actions to assess the time course of activation of action representations, as well as their responsiveness to lexical-semantic context. In two experiments, participants heard a target word and selected its referent from an array of four objects. Gaze fixations on non-target objects signal activation of features shared between targets and non-targets. The experiments assessed activation of structure-based (Experiment 1) or function-based (Experiment 2) distractors, using neutral sentences (“S/he saw the …”) or sentences with a relevant action verb (Experiment 1: “S/he picked up the……”; Experiment 2: “S/he used the….”). We observed task-irrelevant activations of action information in both experiments. In neutral contexts, structure-based activation was relatively faster-rising but more transient than function-based activation. Additionally, action verb contexts reliably modified patterns of activation in both Experiments. These data provide fine-grained information about the dynamics of activation of function-based and structure-based actions in neutral and action-relevant contexts, in support of the “Two Action System” model of object and action processing (e.g., Buxbaum & Kalénine, 2010). PMID:22390294

Lipid Processing in the Brain: A Key Regulator of Systemic Metabolism

PubMed Central

Bruce, Kimberley D.; Zsombok, Andrea; Eckel, Robert H.

2017-01-01

Metabolic disorders, particularly aberrations in lipid homeostasis, such as obesity, type 2 diabetes mellitus, and hypertriglyceridemia often manifest together as the metabolic syndrome (MetS). Despite major advances in our understanding of the pathogenesis of these disorders, the prevalence of the MetS continues to rise. It is becoming increasingly apparent that intermediary metabolism within the central nervous system is a major contributor to the regulation of systemic metabolism. In particular, lipid metabolism within the brain is tightly regulated to maintain neuronal structure and function and may signal nutrient status to modulate metabolism in key peripheral tissues such as the liver. There is now a growing body of evidence to suggest that fatty acid (FA) sensing in hypothalamic neurons via accumulation of FAs or FA metabolites may signal nutritional sufficiency and may decrease hepatic glucose production, lipogenesis, and VLDL-TG secretion. In addition, recent studies have highlighted the existence of liver-related neurons that have the potential to direct such signals through parasympathetic and sympathetic nervous system activity. However, to date whether these liver-related neurons are FA sensitive remain to be determined. The findings discussed in this review underscore the importance of the autonomic nervous system in the regulation of systemic metabolism and highlight the need for further research to determine the key features of FA neurons, which may serve as novel therapeutic targets for the treatment of metabolic disorders. PMID:28421037

Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer's disease patients.

PubMed

Son, Seong-Jin; Kim, Jonghoon; Park, Hyunjin

2017-01-01

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer's disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint.

Functional Nanofibers and Colloidal Gels: Key Elements to Enhance Functionality

NASA Astrophysics Data System (ADS)

Vogel, Nancy Amanda

Nanomaterials bridge the gap between bulk materials and molecular structures and are known for their unique material properties and highly functional nature which make them attractive for a variety of potential applications, from energy storage and pollution sensors to agricultural and biomedical products. These potential applications, coupled with advances in nanotechnology, have generated considerable interest in nanostructure research. The work presented in this dissertation focuses on two such nanostructures, electrospun nanofibers and nanodiamond particles, with an overarching goal of tailoring the material behavior for a desired outcome. Our first research theme focuses on realizing the full potential of chitosan electrospinning by understanding the mechanism that enables fiber formation through cyclodextrin complexation as a function of solution properties, solvent types, and cyclodextrin content. We demonstrate that cyclodextrin addition not only enables chitosan fiber formation, but also extends the composition and solvent window for nanofiber synthesis while introducing a variety of mat topologies, including three-dimensional, self-supporting mats. These fiber formation improvements cannot be fully explained by conventional electrospinning parameters, but instead seem to be related to the molecular interactions between chitosan and cyclodextrin. Our second research theme entails the modification of highly water soluble, poly(vinyl alcohol) (PVA) nanofibers dissolution properties via atomic layer deposition (ALD) post treatments. In this work, we demonstrate that applying different thicknesses of aluminum oxide nano-coatings can improve the stability of PVA nanofibers in high humidity conditions and significantly decrease the solubility of electrospun PVA mats in water, from seconds to multiple weeks. Controlling mat dissolution allows for the unique opportunity to modulate small molecule, such as drug, release from nanofibers without altering the core

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.

A Key Major Guideline for Engineering Bioactive Multicomponent Nanofunctionalization for Biomedicine and Other Applications: Fundamental Models Confirmed by Both Direct and Indirect Evidence

PubMed Central

Scherrieble, Andreas; Bahrizadeh, Shiva; Avareh Sadrabadi, Fatemeh; Hedayat, Laleh

2017-01-01

This paper deals with the engineering multicomponent nanofunctionalization process considering fundamental physicochemical features of nanostructures such as surface energy, chemical bonds, and electrostatic interactions. It is pursued by modeling the surface nanopatterning and evaluating the proposed technique and the models. To this end, the effects of surface modifications of nanoclay on surface interactions, orientations, and final features of TiO2/Mt nanocolloidal textiles functionalization have been investigated. Various properties of cross-linkable polysiloxanes (XPs) treated samples as well as untreated samples with XPs have been compared to one another. The complete series of samples have been examined in terms of bioactivity and some physical properties, given to provide indirect evidence on the surface nanopatterning. The results disclosed a key role of the selected factors on the final features of treated surfaces. The effects have been thoroughly explained and modeled according to the fundamental physicochemical features. The developed models and associated hypotheses interestingly demonstrated a full agreement with all measured properties and were appreciably confirmed by FESEM evidence (direct evidence). Accordingly, a guideline has been developed to facilitate engineering and optimizing the pre-, main, and post-multicomponent nanofunctionalization procedures in terms of fundamental features of nanostructures and substrates for biomedical applications and other approaches. PMID:29333437

Measurement of the decay rate of the SiH feature as a function of temperature

NASA Technical Reports Server (NTRS)

Nuth, Joseph A., III; Kraus, George F.

1994-01-01

We have previously suggested that the SiH fundamental stretch could serve as a diagnostic indicator of the oxidation state of silicate surfaces exposed to the solar wind for prolonged periods. We have now measured the primary decay rate of SiH in vacuo as a function of temperature and find that the primary rate constant for the decay can be characterized by the following equation: k(min(exp -1)) approximately equals 0.186 exp(-9/RT) min(exp -1), where R = 2 x 10(exp -3) kcal deg(exp -1) mole(exp -1). This means that the half-life for the decay of the SiH feature at room temperature is approximately 20 yrs, whereas the half-life at a peak lunar regolith temperature of approximately 500K would be only approximately 20 days. At the somewhat lower temperature of approximately 400K the half-life for the decay is on the order of 200 days. The rate of loss of SiH as a function of temperature provides an upper limit to the quantity of H implanted by the solar wind which can be retained by a silicate grain in a planetary regolith. This will be discussed in more detail here.

E-referral Solutions: Successful Experiences, Key Features and Challenges- a Systematic Review.

PubMed

Naseriasl, Mansour; Adham, Davoud; Janati, Ali

2015-06-01