Skeleton-based human action recognition using multiple sequence alignment

NASA Astrophysics Data System (ADS)

Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong

2015-05-01

Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.

Hemispheric asymmetries of a motor memory in a recognition test after learning a movement sequence.

PubMed

Leinen, Peter; Panzer, Stefan; Shea, Charles H

2016-11-01

Two experiments utilizing a spatial-temporal movement sequence were designed to determine if the memory of the sequence is lateralized in the left or right hemisphere. In Experiment 1, dominant right-handers were randomly assigned to one of two acquisition groups: a left-hand starter and a right-hand starter group. After an acquisition phase, reaction time (RT) was measured in a recognition test by providing the learned sequential pattern in the left or right visual half-field for 150ms. In a retention test and two transfer tests the dominant coordinate system for sequence production was evaluated. In Experiment 2 dominant left-handers and dominant right-handers had to acquire the sequence with their dominant limb. The results of Experiment 1 indicated that RT was significantly shorter when the acquired sequence was provided in the right visual field during the recognition test. The same results occurred in Experiment 2 for dominant right-handers and left-handers. These results indicated a right visual field left hemisphere advantage in the recognition test for the practiced stimulus for dominant left and right-handers, when the task was practiced with the dominant limb. Copyright © 2016 Elsevier B.V. All rights reserved.

Perceptions and Participation in Community Radio Stations in Nariño-Colombia

ERIC Educational Resources Information Center

Martínez-Roa, Omar-Gerardo; Ortega-Erazo, Elsy-Genith

2018-01-01

This work investigates the relationships between community radio and their audiences in the Department of Nariño, Colombia, considering Latin American and European experiences, and participation as a key element for social sustainability. The aim is to investigate whether the participation of citizens in the production, diffusion and radio…

Minimizing effects of over-water docks on federally listed fish stocks in McNary Reservoir: A literature review for criteria

USGS Publications Warehouse

Rondorf, Dennis W.; Rutz, Gary L.; Charrier, Jodi C.

2010-01-01

McNary Lock and Dam were completed in 1953, creating McNary Reservoir, or Lake Wallula. The shoreline of the reservoir is federally owned and as a result the U.S. Army Corps of Engineers (USACE) has certain land and fish habitat management responsibilities to balance with other multipurpose benefits. The Endangered Species Act (ESA) listing of Columbia and Snake River salmon stocks has changed the management of salmon harvest, hydropower operations, hatchery practices, and habitat management in recent years. There are 12 salmon Oncorhynchus spp., steelhead Oncorhynchus mykiss, and bull trout Salvelinus confluentus evolutionarily significant units (ESU‘s) that use this reach of the Columbia River at one or more stages in their life history. Of those 12, 8 are listed as threatened or endangered under the federal Endangered Species Act. The entire portion of the Columbia River in the Hanford Reach and McNary Reservoir is designated critical habitat for seven ESA-listed salmon species. The USACE is in the process of updating the 1983 McNary Lakeshore Management Plan. The updated Shoreline Plan provides criteria for private use of the federal shoreline of McNary Reservoir, specifically the permitting of private docks, over-water structures, and modifications to shoreline vegetation by adjacent land owners. The previous Shoreline Plan was written prior to the federal listing of salmon species. At the request of the USACE, the purpose of this report is to review information from the literature and determine the extent to which the criteria proposed by USACE for the docks and over-water structures are supported by the current body of scientific knowledge.

Rectal and Naris Swabs: Practical and Informative Samples for Analyzing the Microbiota of Critically Ill Patients.

PubMed

Bansal, Saumya; Nguyen, Jenny P; Leligdowicz, Aleksandra; Zhang, Yu; Kain, Kevin C; Ricciuto, Daniel R; Coburn, Bryan

2018-06-27

Commensal microbiota are immunomodulatory, and their pathological perturbation can affect the risk and outcomes of infectious and inflammatory diseases. Consequently, the human microbiota is an emerging diagnostic and therapeutic target in critical illness. In this study, we compared four sample types-rectal, naris, and antecubital swabs and stool samples-for 16S rRNA gene microbiota sequencing in intensive care unit (ICU) patients. Stool samples were obtained in only 31% of daily attempts, while swabs were reliably obtained (≥97% of attempts). Swabs were compositionally distinct by anatomical site, and rectal swabs identified within-patient temporal trends in microbiota composition. Rectal swabs from ICU patients demonstrated differences from healthy stool similar to those observed in comparing stool samples from ICU patients to those from the same healthy controls. Rectal swabs are a useful complement to other sample types for analysis of the intestinal microbiota in critical illness, particularly when obtaining stool may not be feasible or practical. IMPORTANCE Perturbation of the microbiome has been correlated with various infectious and inflammatory diseases and is common in critically ill patients. Stool is typically used to sample the microbiota in human observational studies; however, it is often unavailable for collection from critically ill patients, reducing its utility as a sample type to study this population. Our research identified alternatives to stool for sampling the microbiota during critical illness. Rectal and naris swabs were practical alternatives for use in these patients, as they were observed to be more reliably obtained than stool, were suitable for culture-independent analysis, and successfully captured within- and between-patient microbiota differences. Copyright © 2018 Bansal et al.

Identification of Biomolecular Building Blocks by Recognition Tunneling: Stride towards Nanopore Sequencing of Biomolecules

NASA Astrophysics Data System (ADS)

Sen, Suman

DNA, RNA and Protein are three pivotal biomolecules in human and other organisms, playing decisive roles in functionality, appearance, diseases development and other physiological phenomena. Hence, sequencing of these biomolecules acquires the prime interest in the scientific community. Single molecular identification of their building blocks can be done by a technique called Recognition Tunneling (RT) based on Scanning Tunneling Microscope (STM). A single layer of specially designed recognition molecule is attached to the STM electrodes, which trap the targeted molecules (DNA nucleoside monophosphates, RNA nucleoside monophosphates or amino acids) inside the STM nanogap. Depending on their different binding interactions with the recognition molecules, the analyte molecules generate stochastic signal trains accommodating their "electronic fingerprints". Signal features are used to detect the molecules using a machine learning algorithm and different molecules can be identified with significantly high accuracy. This, in turn, paves the way for rapid, economical nanopore sequencing platform, overcoming the drawbacks of Next Generation Sequencing (NGS) techniques. To read DNA nucleotides with high accuracy in an STM tunnel junction a series of nitrogen-based heterocycles were designed and examined to check their capabilities to interact with naturally occurring DNA nucleotides by hydrogen bonding in the tunnel junction. These recognition molecules are Benzimidazole, Imidazole, Triazole and Pyrrole. Benzimidazole proved to be best among them showing DNA nucleotide classification accuracy close to 99%. Also, Imidazole reader can read an abasic monophosphate (AP), a product from depurination or depyrimidination that occurs 10,000 times per human cell per day. In another study, I have investigated a new universal reader, 1-(2-mercaptoethyl)pyrene (Pyrene reader) based on stacking interactions, which should be more specific to the canonical DNA nucleosides. In addition

Muscles involved in naris dilation and nose motion in rat

PubMed Central

Deschênes, Martin; Haidarliu, Sebastian; Demers, Maxime; Moore, Jeffrey; Kleinfeld, David; Ahissar, Ehud

2016-01-01

In a number of mammals muscle dilator nasi (naris) is known as a muscle that reduces nasal airflow resistance by dilating the nostrils. Here we show that in rats the tendon of this muscle inserts into the aponeurosis above the nasal cartilage. Electrical stimulation of this muscle lifts the nose and deflects it sideway towards the side of stimulation, but does not change the size of the nares. In the head-fixed alert rat, electromyographic activity of muscle dilator nasi is tightly coupled to nose motion, not to opening of the nares. Yet, contraction of muscle dilator nasi occurs during the pre-inspiratory phase of the respiratory cycle, suggesting a role in sniffing and sampling odorants. We also show that opening of the nares results from contraction of pars maxillaris profunda of the muscle nasolabialis profundus. This muscle attaches to the outer wall of the nasal cartilage and to the plate of the mystacial pad. Contraction of this muscle exerts a dual action: it pulls the lateral nasal cartilage outwardly, thus dilating the naris, and it drags the plate of the mystacial pad rostralward, provoking a slight retraction of the whiskers. On the basis of these results, we propose that muscle dilator nasi of the rat be renamed muscle deflector nasi, and that pars maxillaris profunda of the muscle nasolabialis profundus be named muscle dilator nasi. PMID:25257748

Enantiospecific recognition of DNA sequences by a proflavine Tröger base.

PubMed

Bailly, C; Laine, W; Demeunynck, M; Lhomme, J

2000-07-05

The DNA interaction of a chiral Tröger base derived from proflavine was investigated by DNA melting temperature measurements and complementary biochemical assays. DNase I footprinting experiments demonstrate that the binding of the proflavine-based Tröger base is both enantio- and sequence-specific. The (+)-isomer poorly interacts with DNA in a non-sequence-selective fashion. In sharp contrast, the corresponding (-)-isomer recognizes preferentially certain DNA sequences containing both A. T and G. C base pairs, such as the motifs 5'-GTT. AAC and 5'-ATGA. TCAT. This is the first experimental demonstration that acridine-type Tröger bases can be used for enantiospecific recognition of DNA sequences. Copyright 2000 Academic Press.

Learning and recognition of tactile temporal sequences by mice and humans

PubMed Central

Bale, Michael R; Bitzidou, Malamati; Pitas, Anna; Brebner, Leonie S; Khazim, Lina; Anagnou, Stavros T; Stevenson, Caitlin D; Maravall, Miguel

2017-01-01

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order. This temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently learned tactile sequences. Mouse sequence recognition depended on detecting transitions in noise amplitude; animals could base their decision on the earliest information available. Humans appeared to use additional cues, including the duration of noise modulation segments. DOI: http://dx.doi.org/10.7554/eLife.27333.001 PMID:28812976

Dactyl Alphabet Gesture Recognition in a Video Sequence Using Microsoft Kinect

NASA Astrophysics Data System (ADS)

Artyukhin, S. G.; Mestetskiy, L. M.

2015-05-01

This paper presents an efficient framework for solving the problem of static gesture recognition based on data obtained from the web cameras and depth sensor Kinect (RGB-D - data). Each gesture given by a pair of images: color image and depth map. The database store gestures by it features description, genereated by frame for each gesture of the alphabet. Recognition algorithm takes as input a video sequence (a sequence of frames) for marking, put in correspondence with each frame sequence gesture from the database, or decide that there is no suitable gesture in the database. First, classification of the frame of the video sequence is done separately without interframe information. Then, a sequence of successful marked frames in equal gesture is grouped into a single static gesture. We propose a method combined segmentation of frame by depth map and RGB-image. The primary segmentation is based on the depth map. It gives information about the position and allows to get hands rough border. Then, based on the color image border is specified and performed analysis of the shape of the hand. Method of continuous skeleton is used to generate features. We propose a method of skeleton terminal branches, which gives the opportunity to determine the position of the fingers and wrist. Classification features for gesture is description of the position of the fingers relative to the wrist. The experiments were carried out with the developed algorithm on the example of the American Sign Language. American Sign Language gesture has several components, including the shape of the hand, its orientation in space and the type of movement. The accuracy of the proposed method is evaluated on the base of collected gestures consisting of 2700 frames.

A multi-year analysis of passage and survival at McNary Dam, 2004-09

USGS Publications Warehouse

Adams, Noah S.; Walker, C.E.; Perry, R.W.

2011-01-01

We analyzed 6 years (2004–09) of passage and survival data collected at McNary Dam to determine how dam operations and environmental conditions affect passage and survival of juvenile salmonids. A multinomial logistic regression was used to examine how environmental variables and dam operations relate to passage behavior of juvenile salmonids at McNary Dam. We used the Cormack-Jolly-Seber release-recapture model to determine how the survival of juvenile salmonids passing through McNary Dam relates to environmental variables and dam operations. Total project discharge and the proportion of flow passing the spillway typically had a positive effect on survival for all species and routes. As the proportion of water through the spillway increased, the number of fish passing the spillway increased, as did overall survival. Additionally, survival generally was higher at night. There was no meaningful difference in survival for fish that passed through the north or south portions of the spillway or powerhouse. Similarly, there was no difference in survival for fish released in the north, middle, or south portions of the tailrace. For subyearling Chinook salmon migrating during the summer season, increased temperatures had a drastic effect on passage and survival. As temperature increased, survival of subyearling Chinook salmon decreased through all passage routes and the number of fish that passed through the turbines increased. During years when the temporary spillway weirs (TSWs) were installed, passage through the spillway increased for spring migrants. However, due to the changes made in the location of the TSW between years and the potential effect of other confounding environmental conditions, it is not certain if the increase in spillway passage was due solely to the presence of the TSWs. The TSWs appeared to improve forebay survival during years when they were operated.

Pattern recognition of electronic bit-sequences using a semiconductor mode-locked laser and spatial light modulators

NASA Astrophysics Data System (ADS)

Bhooplapur, Sharad; Akbulut, Mehmetkan; Quinlan, Franklyn; Delfyett, Peter J.

2010-04-01

A novel scheme for recognition of electronic bit-sequences is demonstrated. Two electronic bit-sequences that are to be compared are each mapped to a unique code from a set of Walsh-Hadamard codes. The codes are then encoded in parallel on the spectral phase of the frequency comb lines from a frequency-stabilized mode-locked semiconductor laser. Phase encoding is achieved by using two independent spatial light modulators based on liquid crystal arrays. Encoded pulses are compared using interferometric pulse detection and differential balanced photodetection. Orthogonal codes eight bits long are compared, and matched codes are successfully distinguished from mismatched codes with very low error rates, of around 10-18. This technique has potential for high-speed, high accuracy recognition of bit-sequences, with applications in keyword searches and internet protocol packet routing.

Foundations for a syntatic pattern recognition system for genomic DNA sequences

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Learning and Recognition of a Non-conscious Sequence of Events in Human Primary Visual Cortex.

PubMed

Rosenthal, Clive R; Andrews, Samantha K; Antoniades, Chrystalina A; Kennard, Christopher; Soto, David

2016-03-21

Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations [1] and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol-designed to induce activity in V1, without modulation from visual awareness-to test whether human V1 is implicated in human observers rapidly learning and then later (15-20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of "implicit" sequence learning that involved motor responses and visible stimuli (e.g., [4]). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. [5]) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory [6]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Recognition of the DNA sequence by an inorganic crystal surface

PubMed Central

Sampaolese, Beatrice; Bergia, Anna; Scipioni, Anita; Zuccheri, Giampaolo; Savino, Maria; Samorì, Bruno; De Santis, Pasquale

2002-01-01

The sequence-dependent curvature is generally recognized as an important and biologically relevant property of DNA because it is involved in the formation and stability of association complexes with proteins. When a DNA tract, intrinsically curved for the periodical recurrence on the same strand of A-tracts phased with the B-DNA periodicity, is deposited on a flat surface, it exposes to that surface either a T- or an A-rich face. The surface of a freshly cleaved mica crystal recognizes those two faces and preferentially interacts with the former one. Statistical analysis of scanning force microscopy (SFM) images provides evidence of this recognition between an inorganic crystal surface and nanoscale structures of double-stranded DNA. This finding could open the way toward the use of the sequence-dependent adhesion to specific crystal faces for nanotechnological purposes. PMID:12361979

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Oceanic response to Typhoon Nari (2007) in the East China Sea

NASA Astrophysics Data System (ADS)

Oh, Kyung-Hee; Lee, Seok; Kang, Sok-Kuh; Song, Kyu-Min

2017-06-01

The oceanic response to a typhoon in the East China Sea (ECS) was examined using thermal and current structures obtained from ocean surface drifters and a bottom-moored current profiler installed on the right side of the typhoon's track. Typhoon Nari (2007) had strong winds as it passed the central region of the ECS. The thermal structure in the ECS responded to Typhoon Nari (2007) very quickly: the seasonal thermocline abruptly collapsed and the sea surface temperature dropped immediately by about 4°C after the typhoon passed. The strong vertical mixing and surface cooling caused by the typhoon resulted in a change in the thermal structure. Strong near-inertial oscillation occurred immediately after the typhoon passed and lasted for at least 4-5 days, during which a strong vertical current existed in the lower layer. Characteristics of the near-inertial internal oscillation were observed in the middle layer. The clockwise component of the inertial frequency was enhanced in the surface layer and at 63 m depth after the typhoon passed, with these layers almost perfectly out of phase. The vertical shear current was intensified by the interaction of the wind-driven current in the upper layer and the background semi-diurnal tidal current during the arrival of the typhoon, and also by the near-inertial internal oscillation after the typhoon passage. The strong near-inertial internal oscillation persisted without significant interfacial structure after the mixing of the thermocline, which could enhance the vertical mixing over several days.

Summary of juvenile salmonid passage and survival at McNary Dam-Acoustic survival studies, 2006-09

USGS Publications Warehouse

Adams, Noah S.; Evans, Scott D.

2011-01-01

Passage and survival data were collected at McNary Dam between 2006 and 2009. These data have provided critical information for resource managers to implement structural and operational changes designed to improve the survival of juvenile salmonids as they migrate past the dam. Given the importance of these annual studies, the primary objectives of this report were to summarize the findings of these annual studies to ensure that passage and survival metrics are consistently calculated and reported across all years and to consolidate this information in a single document, thereby making it easier to reference. It is worth noting that this report does not contain all the information from all the annual reports. The intent of this report was to summarize the key findings from multiple years of research. The reader is encouraged to reference the annual reports if more detailed information is needed. Chapter 1 summarizes existing behavior, passage, and survival results for fish released 10 rkm upstream of McNary Dam and from the McNary Dam tailrace during 2006-09. Chapter 2 summarizes existing behavior, passage, and survival results for fish released in the mid-Columbia River and detected at McNary Dam during 2006-09. Results from 2006 indicated that higher spill discharge generally resulted in higher fish passage through spill, and in turn, higher fish survival through the entire dam. Within the spillway, passage effectiveness was highest for the south spill bays, adjacent to the powerhouse. Increased passage in this area, combined with detailed 3-dimensional approach paths, aided in the design and location of the temporary spillway weirs (TSWs) at McNary Dam prior to the 2007 migration of juvenile salmonids. During the 2007 study, the TSWs were tested under two spill treatments during the spring and summer: a "2006 Modified spill," and a "2007 test spill." In the spring, slightly higher discharge through spill bays 14-17 was the primary difference between the spill

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

PubMed

Ibrahim, Wisam; Abadeh, Mohammad Saniee

2017-05-21

Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid sequences to obtain better classifiers. In this paper, we have proposed six descriptors to extract features from protein sequences. These descriptors are applied in the first stage of a three-stage framework PCA-DELM-LDA to extract feature vectors from the amino-acid sequences. Principal Component Analysis PCA has been implemented to reduce the number of extracted features. The extracted feature vectors have been used with original features to improve the performance of the Deep Extreme Learning Machine DELM in the second stage. Four new features have been extracted from the second stage and used in the third stage by Linear Discriminant Analysis LDA to classify the instances into 27 folds. The proposed framework is implemented on the independent and combined feature sets in SCOP datasets. The experimental results show that extracted feature vectors in the first stage could improve the performance of DELM in extracting new useful features in second stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sequence-Specific Recognition of DNA by Proteins: Binding Motifs Discovered Using a Novel Statistical/Computational Analysis

PubMed Central

Jakubec, David; Laskowski, Roman A.; Vondrasek, Jiri

2016-01-01

Decades of intensive experimental studies of the recognition of DNA sequences by proteins have provided us with a view of a diverse and complicated world in which few to no features are shared between individual DNA-binding protein families. The originally conceived direct readout of DNA residue sequences by amino acid side chains offers very limited capacity for sequence recognition, while the effects of the dynamic properties of the interacting partners remain difficult to quantify and almost impossible to generalise. In this work we investigated the energetic characteristics of all DNA residue—amino acid side chain combinations in the conformations found at the interaction interface in a very large set of protein—DNA complexes by the means of empirical potential-based calculations. General specificity-defining criteria were derived and utilised to look beyond the binding motifs considered in previous studies. Linking energetic favourability to the observed geometrical preferences, our approach reveals several additional amino acid motifs which can distinguish between individual DNA bases. Our results remained valid in environments with various dielectric properties. PMID:27384774

Measurement Marker Recognition In A Time Sequence Of Infrared Images For Biomedical Applications

NASA Astrophysics Data System (ADS)

Fiorini, A. R.; Fumero, R.; Marchesi, R.

1986-03-01

In thermographic measurements, quantitative surface temperature evaluation is often uncertain. The main reason is in the lack of available reference points in transient conditions. Reflective markers were used for automatic marker recognition and pixel coordinate computations. An algorithm selects marker icons to match marker references where particular luminance conditions are satisfied. Automatic marker recognition allows luminance compensation and temperature calibration of recorded infrared images. A biomedical application is presented: the dynamic behaviour of the surface temperature distributions is investigated in order to study the performance of two different pumping systems for extracorporeal circulation. Sequences of images are compared and results are discussed. Finally, the algorithm allows to monitor the experimental environment and to alert for the presence of unusual experimental conditions.

HIV-1 gp140 epitope recognition is influenced by immunoglobulin DH gene segment sequence

PubMed Central

Wang, Yuge; Kapoor, Pratibha; Parks, Robert; Silva-Sanchez, Aaron; Alam, S. Munir; Verkoczy, Laurent; Liao, Hua-Xin; Zhuang, Yingxin; Burrows, Peter; Levinson, Michael; Elgavish, Ada; Cui, Xiangqin; Haynes, Barton F.; Schroeder, Harry

2015-01-01

Complementarity determining region 3 of the immunoglobulin (Ig) H chain (CDR-H3) lies at the center of the antigen binding site where it often plays a decisive role in antigen recognition and binding. Amino acids encoded by the diversity (DH) gene segment are the main component of CDR-H3. Each DH has the potential to rearrange into one of six DH reading frames (RFs), each of which exhibits a characteristic amino acid hydrophobicity signature that has been conserved among jawed vertebrates by natural selection. A preference for use of RF1 promotes the incorporation of tyrosine into CDR-H3 while suppressing the inclusion of hydrophobic or charged amino acids. To test the hypothesis that these evolutionary constraints on DH sequence influence epitope recognition, we used mice with a single DH that has been altered to preferentially use RF2 or inverted RF1. B cells in these mice produce a CDR-H3 repertoire that is enriched for valine or arginine in place of tyrosine. We serially immunized this panel of mice with gp140 from HIV-1 JR-FL isolate and then used ELISA or peptide microarray to assess antibody binding to key or overlapping HIV-1 envelope epitopes. By ELISA, serum reactivity to key epitopes varied by DH sequence. By microarray, sera with Ig CDR-H3s enriched for arginine bound to linear peptides with a greater range of hydrophobicity, but had a lower intensity of binding than sera containing Ig CDR-H3s enriched for tyrosine or valine. We conclude that patterns of epitope recognition and binding can be heavily influenced by DH germline sequence. This may help explain why antibodies in HIV infected patients must undergo extensive somatic mutation in order to bind to specific viral epitopes and achieve neutralization. PMID:26687685

Comparative study of methods for recognition of an unknown person's action from a video sequence

NASA Astrophysics Data System (ADS)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

[Dialogue and respect: the basis for constructing an intercultural health system for indigenous communities in Puerto Nariño, Amazonas, Colombia].

PubMed

Patiño Suaza, Ana Eugenia; Sandín Vásquez, María

2014-12-01

This paper presents the ideas on health and disease as well as proposals regarding the health care system voiced by indigenous communities belonging to the Tikunas, Cocama and Yagua ethnicities of the Puerto Nariño municipality in the department of Amazonas, Colombia. The study was conducted between 2010 and 2013. The tools used to obtain the data were participant observation, interviews and discussion groups. The study evidenced a profound lack of information and understanding on the part of state health agencies. As a principal demand, indigenous communities ask to be heard when decisions affecting their health or their way of understanding health are made. These results should be taken into account in the development of future health programs and provide a basis for the construction of an adequate intercultural health system for the town of Port Nariño.

[Neuronal activity of monkey dorso-lateral premotor cortex during tasks of figure recognition guided motor sequence vs memorized spatial motor sequence].

PubMed

Chen, Y C; Huang, F D; Chen, N H; Shou, J Y; Wu, L

1998-04-01

In the last 2-3 decades the role of the premotor cortex (PM) of monkey in memorized spatial sequential (MSS) movements has been amply investigated. However, it is as yet not known whether PM participates in the movement sequence behaviour guided by recognition of visual figures (i.e. the figure-recognition sequence, FRS). In the present work three monkeys were trained to perform both FRS and MSS tasks. Postmortem examination showed that 202 cells were in the dorso-lateral premotor cortex. Among 111 cells recorded during the two tasks, more than 50% changed their activity during the cue periods in either task. During the response period, the ratios of cells with changes of firing rate in both FRS and MSS were high and roughly equal to each other, while during the image period, the proportion in the FRS (83.7%) was significantly higher than that in the MSS (66.7%). Comparison of neuronal activities during same motor sequence of two different tasks showed that during the image periods PM neuronal activities were more closely related to the FRS task, while during the cue periods no difference could be found. Analysis of cell responses showed that the neurons with longer latency were much more in MSS than in FRS in either cue or image period. The present results indicate that the premotor cortex participates in FRS motor sequence as well as in MSS and suggest that the dorso-lateral PM represents another subarea in function shared by both FRS and MSS tasks. However, in view of the differences of PM neuronal responses in cue or image periods of FRS and MSS tasks, it seems likely that neural networks involved in FRS and MSS tasks are different.

Influence of motion on face recognition.

PubMed

Bonfiglio, Natale S; Manfredi, Valentina; Pessa, Eliano

2012-02-01

The influence of motion information and temporal associations on recognition of non-familiar faces was investigated using two groups which performed a face recognition task. One group was presented with regular temporal sequences of face views designed to produce the impression of motion of the face rotating in depth, the other group with random sequences of the same views. In one condition, participants viewed the sequences of the views in rapid succession with a negligible interstimulus interval (ISI). This condition was characterized by three different presentation times. In another condition, participants were presented a sequence with a 1-sec. ISI among the views. That regular sequences of views with a negligible ISI and a shorter presentation time were hypothesized to give rise to better recognition, related to a stronger impression of face rotation. Analysis of data from 45 participants showed a shorter presentation time was associated with significantly better accuracy on the recognition task; however, differences between performances associated with regular and random sequences were not significant.

Effects of Mitigative Measures on Productivity of White Sturgeon Populations in the Columbia River Downstream from McNary Dam: Determine Status and Habitat Requirements of White Sturgeon Populations in the Columbia and Snake Rivers Upstream from McNary Dam, 1997-1998 Annual Report.

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

Ward, David L.

The authors report on their progress from April 1997 through March 1998 on determining the effects of mitigative measures on productivity of white sturgeon populations in the Columbia River downstream from McNary Dam, and on determining the status and habitat requirements of white sturgeon populations in the Columbia and Snake rivers upstream from McNary Dam. The study is a cooperative effort by the Oregon Department of Fish and Wildlife (ODFW; Report A), Washington Department of Fish and Wildlife (WDFW; Report B), U.S. Geological Survey Biological Resources Division (USGS; Report C), National Marine Fisheries Service (NMFS; Report D), U.S. Fish andmore » Wildlife Service (USFWS; Report E), and Columbia River Inter-Tribal Fish Commission (CRITFC; Report F). This is a multi-year study with many objectives requiring more than one year to complete. Therefore, findings from a given year may be part of more significant findings yet to be reported. Highlights of results of the work from April 1997 through March 1998 listed.« less

Simian T Lymphotropic Virus 1 Infection of Papio anubis: tax Sequence Heterogeneity and T Cell Recognition.

PubMed

Termini, James M; Magnani, Diogo M; Maxwell, Helen S; Lauer, William; Castro, Iris; Pecotte, Jerilyn; Barber, Glen N; Watkins, David I; Desrosiers, Ronald C

2017-10-15

Baboons naturally infected with simian T lymphotropic virus (STLV) are a potentially useful model system for the study of vaccination against human T lymphotropic virus (HTLV). Here we expanded the number of available full-length baboon STLV-1 sequences from one to three and related the T cell responses that recognize the immunodominant Tax protein to the tax sequences present in two individual baboons. Continuously growing T cell lines were established from two baboons, animals 12141 and 12752. Next-generation sequencing (NGS) of complete STLV genome sequences from these T cell lines revealed them to be closely related but distinct from each other and from the baboon STLV-1 sequence in the NCBI sequence database. Overlapping peptides corresponding to each unique Tax sequence and to the reference baboon Tax sequence were used to analyze recognition by T cells from each baboon using intracellular cytokine staining (ICS). Individual baboons expressed more gamma interferon and tumor necrosis factor alpha in response to Tax peptides corresponding to their own STLV-1 sequence than in response to Tax peptides corresponding to the reference baboon STLV-1 sequence. Thus, our analyses revealed distinct but closely related STLV-1 genome sequences in two baboons, extremely low heterogeneity of STLV sequences within each baboon, no evidence for superinfection within each baboon, and a ready ability of T cells in each baboon to recognize circulating Tax sequences. While amino acid substitutions that result in escape from CD8 + T cell recognition were not observed, premature stop codons were observed in 7% and 56% of tax sequences from peripheral blood mononuclear cells from animals 12141 and 12752, respectively. IMPORTANCE It has been estimated that approximately 100,000 people suffer serious morbidity and 10,000 people die each year from the consequences associated with human T lymphotropic virus (HTLV) infection. There are no antiviral drugs and no preventive vaccine. A

Survival and migration behavior of juvenile salmonids at McNary Dam, 2004, Final report of research

USGS Publications Warehouse

Perry, Russell W.; Braatz, Amy C.; Fielding, Scott D.; Lucchesi, Joel N.; Plumb, John M.; Adams, Noah S.; Rondorf, Dennis W.

2005-01-01

During 2004, the USGS Columbia River Research Laboratory conducted a study at McNary Dam using radio telemetry to estimate passage and survival parameters of juvenile salmonids. Our primary objective was to estimate these parameters under ambient environmental and operational conditions, and thus project-wide treatments were not implemented. The primary dam operation consisted of “biop” spill, where spill occurred at night between 1800 and 0600 hours, and no spill occurred between 0600 and 1800 hours for the majority of our study period. During the spring study period, we radio-tagged and released 1,896 yearling Chinook salmon and 1,888 juvenile steelhead. During the summer study period, we radio-tagged and released 1,919 subyearling Chinook salmon. All fish were tagged using gastric techniques to implant transmitters weighing 1.58 g for yearling Chinook salmon, 1.93 g for juvenile steelhead, and 0.96 g for subyearling Chinook salmon. Minimum fish sizes were based on a 6.5% tag:fish weight ratio, and the size of tagged fish represented about 91%, 100%, and 17% of the population, respectively for yearling Chinook salmon, juvenile steelhead, and subyearling Chinook salmon. About 60% of radio-tagged fish were released 10 km upstream of McNary Dam at Hat Rock State Park, Oregon, with the remainder released as control groups 400 m downstream of the dam.

A Markov chain analysis of the movements of juvenile salmonids in the forebay of McNary Dam, Washington and Oregon, 2006-09

USGS Publications Warehouse

Adams, Noah S.; Hatton, Tyson W.

2012-01-01

Passage and survival data for yearling and subyearling Chinook salmon and juvenile steelhead were collected at McNary Dam between 2006 and 2009. These data have provided critical information for resource managers to implement structural and operational changes designed to improve the survival of juvenile salmonids as they migrate past the dam. Much of the information collected at McNary Dam was in the form of three-dimensional tracks of fish movements in the forebay. These data depicted the behavior of multiple species (in three dimensions) during different diel periods, spill conditions, powerhouse operations, and test configurations of the surface bypass structures (temporary spillway weirs; TSWs). One of the challenges in reporting three-dimensional results is presenting the information in a manner that allows interested parties to summarize the behavior of many fish over many different conditions across multiple years. To accomplish this, we investigated the feasibility of using a Markov chain analysis to characterize fish movement patterns in the forebay of McNary Dam. The Markov chain analysis is one way that can be used to summarize numerically the behavior of fish in the forebay. Numerically summarizing the behavior of juvenile salmonids in the forebay of McNary Dam using the Markov chain analysis allowed us to confirm what had been previously summarized using visualization software. For example, proportions of yearling and subyearling Chinook salmon passing the three powerhouse areas was often greater in the southern and middle areas, compared to the northern area. The opposite generally was observed for steelhead. Results of this analysis also allowed us to confirm and quantify the extent of milling behavior that had been observed for steelhead. For fish that were first detected in the powerhouse region, less than 0.10 of the steelhead, on average, passed within each of the powerhouse areas. Instead, steelhead transitioned to adjoining areas in the

Survival and Passage of Yearling and Subyearling Chinook Salmon and Juvenile Steelhead at McNary Dam, 2012

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

Hughes, James S.; Weiland, Mark A.; Woodley, Christa M.

The study was designed to evaluate the passage and survival of yearling and subyearling Chinook salmon and juvenile steelhead at McNary Dam as stipulated by the 2008 Biological Opinion and Fish Accords and to assess performance measures including route-specific fish passage proportions, travel times, and survival based upon a virtual/paired-release model. This study supports the USACE’s continual effort to improve conditions for juvenile anadromous fish passing through Columbia River dams.

Creation of a type IIS restriction endonuclease with a long recognition sequence

PubMed Central

Lippow, Shaun M.; Aha, Patti M.; Parker, Matthew H.; Blake, William J.; Baynes, Brian M.; Lipovšek, Daša

2009-01-01

Type IIS restriction endonucleases cleave DNA outside their recognition sequences, and are therefore particularly useful in the assembly of DNA from smaller fragments. A limitation of type IIS restriction endonucleases in assembly of long DNA sequences is the relative abundance of their target sites. To facilitate ligation-based assembly of extremely long pieces of DNA, we have engineered a new type IIS restriction endonuclease that combines the specificity of the homing endonuclease I-SceI with the type IIS cleavage pattern of FokI. We linked a non-cleaving mutant of I-SceI, which conveys to the chimeric enzyme its specificity for an 18-bp DNA sequence, to the catalytic domain of FokI, which cuts DNA at a defined site outside the target site. Whereas previously described chimeric endonucleases do not produce type IIS-like precise DNA overhangs suitable for ligation, our chimeric endonuclease cleaves double-stranded DNA exactly 2 and 6 nt from the target site to generate homogeneous, 5′, four-base overhangs, which can be ligated with 90% fidelity. We anticipate that these enzymes will be particularly useful in manipulation of DNA fragments larger than a thousand bases, which are very likely to contain target sites for all natural type IIS restriction endonucleases. PMID:19304757

A protein block based fold recognition method for the annotation of twilight zone sequences.

PubMed

Suresh, V; Ganesan, K; Parthasarathy, S

2013-03-01

The description of protein backbone was recently improved with a group of structural fragments called Structural Alphabets instead of the regular three states (Helix, Sheet and Coil) secondary structure description. Protein Blocks is one of the Structural Alphabets used to describe each and every region of protein backbone including the coil. According to de Brevern (2000) the Protein Blocks has 16 structural fragments and each one has 5 residues in length. Protein Blocks fragments are highly informative among the available Structural Alphabets and it has been used for many applications. Here, we present a protein fold recognition method based on Protein Blocks for the annotation of twilight zone sequences. In our method, we align the predicted Protein Blocks of a query amino acid sequence with a library of assigned Protein Blocks of 953 known folds using the local pair-wise alignment. The alignment results with z-value ≥ 2.5 and P-value ≤ 0.08 are predicted as possible folds. Our method is able to recognize the possible folds for nearly 35.5% of the twilight zone sequences with their predicted Protein Block sequence obtained by pb_prediction, which is available at Protein Block Export server.

Conforth Ranch Wildlife Mitigation Feasibility Study, McNary, Oregon : Annual Report.

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

Rasmussen, Larry; Wright, Patrick; Giger, Richard

1991-03-01

The 2,860-acre Conforth Ranch near Umatilla, Oregon is being considered for acquisition and management to partially mitigate wildlife losses associated with McNary Hydroelectric Project. The Habitat Evaluation Procedures (HEP) estimated that management for wildlife would result in habitat unit gains of 519 for meadowlark, 420 for quail, 431 for mallard, 466 for Canada goose, 405 for mink, 49 for downy woodpecker, 172 for yellow warbler, and 34 for spotted sandpiper. This amounts to a total combined gain of 2,495 habitat units -- a 110 percent increase over the existing values for these species combined of 2,274 habitat units. Current watermore » delivery costs, estimated at $50,000 per year, are expected to increase to $125,000 per year. A survey of local interest indicated a majority of respondents favored the concept with a minority opposed. No contaminants that would preclude the Fish and Wildlife Service from agreeing to accept the property were identified. 21 refs., 3 figs., 5 tabs.« less

A Markov chain analysis of the movements of juvenile salmonids, including sockeye salmon, in the forebay of McNary Dam, Washington and Oregon, 2006-09

USGS Publications Warehouse

Adams, Noah S.; Hatton, Tyson W.

2012-01-01

Passage and survival data were collected at McNary Dam between 2006 and 2009. These data have provided critical information for resource managers to implement structural and operational changes designed to improve the survival of juvenile salmonids as they migrate past the dam. Much of the valuable information collected at McNary Dam was in the form of three-dimensional (hereafter referred to as 3-D) tracks of fish movements in the forebay. These data depicted the behavior of multiple species (in three dimensions) during different diel periods, spill conditions, powerhouse operations, and testing of the surface bypass structures (temporary spillway weirs; TSWs). One of the challenges in reporting 3-D results is presenting the information in a manner that allows interested parties to summarize the behavior of many fish over many different conditions across multiple years. To accomplish this, we used a Markov chain analysis to characterize fish movement patterns in the forebay of McNary Dam. The Markov chain analysis allowed us to numerically summarize the behavior of fish in the forebay. This report is the second report published in 2012 that uses this analytical method. The first report included only fish released as part of the annual studies conducted at McNary Dam. This second report includes sockeye salmon that were released as part of studies conducted by the Chelan and Grant County Public Utility Districts at mid-Columbia River dams. The studies conducted in the mid-Columbia used the same transmitters as were used for McNary Dam studies, but transmitter pulse width was different between studies. Additionally, no passive integrated transponder tags were implanted in sockeye salmon. Differences in transmitter pulse width resulted in lower detection probabilities for sockeye salmon at McNary Dam. The absence of passive integrated transponder tags prevented us from determining if fish passed the powerhouse through the juvenile bypass system (JBS) or turbines. To

Biosensors for DNA sequence detection

NASA Technical Reports Server (NTRS)

Vercoutere, Wenonah; Akeson, Mark

2002-01-01

DNA biosensors are being developed as alternatives to conventional DNA microarrays. These devices couple signal transduction directly to sequence recognition. Some of the most sensitive and functional technologies use fibre optics or electrochemical sensors in combination with DNA hybridization. In a shift from sequence recognition by hybridization, two emerging single-molecule techniques read sequence composition using zero-mode waveguides or electrical impedance in nanoscale pores.

High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

2005-09-01

Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

A conserved mechanism for replication origin recognition and binding in archaea.

PubMed

Majerník, Alan I; Chong, James P J

2008-01-15

To date, methanogens are the only group within the archaea where firing DNA replication origins have not been demonstrated in vivo. In the present study we show that a previously identified cluster of ORB (origin recognition box) sequences do indeed function as an origin of replication in vivo in the archaeon Methanothermobacter thermautotrophicus. Although the consensus sequence of ORBs in M. thermautotrophicus is somewhat conserved when compared with ORB sequences in other archaea, the Cdc6-1 protein from M. thermautotrophicus (termed MthCdc6-1) displays sequence-specific binding that is selective for the MthORB sequence and does not recognize ORBs from other archaeal species. Stabilization of in vitro MthORB DNA binding by MthCdc6-1 requires additional conserved sequences 3' to those originally described for M. thermautotrophicus. By testing synthetic sequences bearing mutations in the MthORB consensus sequence, we show that Cdc6/ORB binding is critically dependent on the presence of an invariant guanine found in all archaeal ORB sequences. Mutation of a universally conserved arginine residue in the recognition helix of the winged helix domain of archaeal Cdc6-1 shows that specific origin sequence recognition is dependent on the interaction of this arginine residue with the invariant guanine. Recognition of a mutated origin sequence can be achieved by mutation of the conserved arginine residue to a lysine or glutamine residue. Thus despite a number of differences in protein and DNA sequences between species, the mechanism of origin recognition and binding appears to be conserved throughout the archaea.

Xenopus origin recognition complex (ORC) initiates DNA replication preferentially at sequences targeted by Schizosaccharomyces pombe ORC

PubMed Central

Kong, Daochun; Coleman, Thomas R.; DePamphilis, Melvin L.

2003-01-01

Budding yeast (Saccharomyces cerevisiae) origin recognition complex (ORC) requires ATP to bind specific DNA sequences, whereas fission yeast (Schizosaccharomyces pombe) ORC binds to specific, asymmetric A:T-rich sites within replication origins, independently of ATP, and frog (Xenopus laevis) ORC seems to bind DNA non-specifically. Here we show that despite these differences, ORCs are functionally conserved. Firstly, SpOrc1, SpOrc4 and SpOrc5, like those from other eukaryotes, bound ATP and exhibited ATPase activity, suggesting that ATP is required for pre-replication complex (pre-RC) assembly rather than origin specificity. Secondly, SpOrc4, which is solely responsible for binding SpORC to DNA, inhibited up to 70% of XlORC-dependent DNA replication in Xenopus egg extract by preventing XlORC from binding to chromatin and assembling pre-RCs. Chromatin-bound SpOrc4 was located at AT-rich sequences. XlORC in egg extract bound preferentially to asymmetric A:T-sequences in either bare DNA or in sperm chromatin, and it recruited XlCdc6 and XlMcm proteins to these sequences. These results reveal that XlORC initiates DNA replication preferentially at the same or similar sites to those targeted in S.pombe. PMID:12840006

Exploring 3D Human Action Recognition: from Offline to Online.

PubMed

Liu, Zhenyu; Li, Rui; Tan, Jianrong

2018-02-20

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems-including real-time performance and sequence segmentation-are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset.

Exploring 3D Human Action Recognition: from Offline to Online

PubMed Central

Li, Rui; Liu, Zhenyu; Tan, Jianrong

2018-01-01

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems—including real-time performance and sequence segmentation—are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset. PMID:29461502

Monitoring and Evaluation of Smolt Migration in the Columbia Basin : Volume XV : Evaluation of the 2007 Predictions of the Run-Timing of Wild and Hatchery-Reared Salmon and Steelhead Smolts to Rock Island, Lower Granite, McNary, John Day, and Bonneville Dams using Program RealTime.

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

Griswold, Jim; Townsend, Richard L.; Skalski, John R.

Program RealTime provided monitoring and forecasting of the 2007 inseason outmigrations via the internet for 26 PIT-tagged stocks of wild ESU Chinook salmon and steelhead to Lower Granite and/or McNary dams, one PIT-tagged hatchery-reared ESU of sockeye salmon to Lower Granite Dam, one PIT-tagged wild stock of sockeye salmon to McNary Dam, and 20 passage-indexed runs-at-large, five each to Rock Island, McNary, John Day, and Bonneville dams. Nineteen stocks are of wild yearling Chinook salmon which were captured, PIT-tagged, and released at sites above Lower Granite Dam in 2007 and have at least one year's historical migration data previous tomore » the 2007 migration. These stocks originate in 19 tributaries of the Salmon, Grande Ronde and Clearwater Rivers, all tributaries to the Snake River, and are subsequently detected through tag identification and monitored at Lower Granite Dam. Seven wild PIT-tagged runs-at-large of Snake or Upper Columbia River ESU salmon and steelhead were monitored at McNary Dam. Three wild PIT-tagged runs-at-large were monitored at Lower Granite Dam, consisting of the yearling and subyearling Chinook salmon and the steelhead runs. The hatchery-reared PIT-tagged sockeye salmon stock from Redfish Lake was monitored outmigrating through Lower Granite Dam. Passage-indexed stocks (stocks monitored by FPC passage indices) included combined wild and hatchery runs-at-large of subyearling and yearling Chinook, coho, and sockeye salmon, and steelhead forecasted to Rock Island, McNary, John Day, and Bonneville dams.« less

Recognition of DNA abasic site nanocavity by fluorophore-switched probe: Suitable for all sequence environments

NASA Astrophysics Data System (ADS)

Wang, Ying; Hu, Yuehua; Wu, Tao; Zhang, Lihua; Liu, Hua; Zhou, Xiaoshun; Shao, Yong

2016-01-01

Removal of a damaged base in DNA produces an abasic site (AP site) nanocavity. If left un-repaired in vivo by the specific enzyme, this nanocavity will result in nucleotide mutation in the following DNA replication. Therefore, selective recognition of AP site nanocavity by small molecules is important for identification of such DNA damage and development of genetic drugs. In this work, we investigate the fluorescence behavior of isoquinoline alkaloids including palmatine (PAL), berberine (BER), epiberberine (EPI), jatrorrhizine (JAT), coptisine (COP), coralyne (COR), worenine (WOR), berberrubine (BEU), sanguinarine (SAN), chelerythrine (CHE), and nitidine (NIT) upon binding with the AP nanocavity. PAL is screened out as the most efficient fluorophore-switched probe to recognize the AP nanocavity over the fully matched DNA. Its fluorescence enhancement occurs for all of the AP nanocavity sequence environments, which has not been achieved by the previously used probes. The bridged π conjugation effect should partially contribute to the AP nanocavity-specific fluorescence, as opposed to the solvent effect. Due to the strong binding with the AP nanocavity, PAL will find wide applications in the DNA damage recognition and sensor development.

Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Effects of Mitigation Measures on Productivity of the White Sturgeon Populations in the Columbia River Downstream from McNary Dam, and Status and Habitat Requirements of White Sturgeon Populations in the Columbia and Snake Rivers Upstream from McNary Dam, 1992-1993 Annual Report.

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

Beamesdorfer, Raymond C.; Nigro, Anthony A.

We report on our progress from April 1992-March 1993 in research on white sturgeon in the lower Columbia River. The study began in July 1986 and progress through 1992 was summarized in a comprehensive report in 2 volumes (Beamesderfer and Nigro 1993a, 1993b). This report details activities during the first year of Phase II of this sturgeon research. In Phase I, we assessed the status and habitat requirements of the white sturgeon populations in the Columbia River downstream from McNary Dam. Phase II will examine the effects on white sturgeon productivity of mitigative measures recommended in Phase I. The statusmore » and habitat requirements of white sturgeon populations upstream from McNary Dam will also be examined in Phase II. The study is a cooperative effort by the Oregon Department of Fish and Wildlife, Washington Department of Fisheries, U.S. Fish and Wildlife Service, and National Marine Fisheries Service. Work during the past year has focused on: (1) analysis of results of limited sampling conducted in 1992, (2) submission of Phase I results to the peer-review literature to ensure widespread dissemination, clarity of presentation, and credibility of findings, and (3) preparations for additional field work in 1993. In report sections A to D, each agency reports 1992 results if applicable and the current status of manuscripts. Results of field work conducted in 1993 will be reported in the 1994 annual report.« less

Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein.

PubMed

Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S; Prasad, Manoj

2011-10-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncations of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T][T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein.

Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein

PubMed Central

Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S

2011-01-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncation of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T] [T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein. PMID:21918373

Textual emotion recognition for enhancing enterprise computing

NASA Astrophysics Data System (ADS)

Quan, Changqin; Ren, Fuji

2016-05-01

The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

Deep Recurrent Neural Networks for Human Activity Recognition

PubMed Central

Murad, Abdulmajid

2017-01-01

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103

Deep Recurrent Neural Networks for Human Activity Recognition.

PubMed

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Base-Displaced Intercalated Conformation of the 2-Amino-3-methylimidazo[4,5-f]quinoline N2-dG DNA Adduct Positioned at the Nonreiterated G1 in the NarI Restriction Site

PubMed Central

2016-01-01

The conformation of an N2-dG adduct arising from the heterocyclic amine 2-amino-3-methylimidazo[4,5-f]quinoline (IQ), a potent food mutagen, was determined in 5′-d(C1T2C3X4G5C6G7C8C9A10T11C12)-3′:5′-d(G13A14T15G16G17C18G19C20C21G22A23G24)-3′; X = N2-dG-IQ, in which the modified nucleotide X4 corresponds to G1 in the 5′-d(G1G2CG3CC)-3′ NarI restriction endonuclease site. Circular dichroism (CD) revealed blue shifts relative to the unmodified duplex, consistent with adduct-induced twisting, and a hypochromic effect for the IQ absorbance in the near UV region. NMR revealed that the N2-dG-IQ adduct adopted a base-displaced intercalated conformation in which the modified guanine remained in the anti conformation about the glycosidic bond, the IQ moiety intercalated into the duplex, and the complementary base C21 was displaced into the major groove. The processing of the N2-dG-IQ lesion by hpol η is sequence-dependent; when placed at the reiterated G3 position, but not at the G1 position, this lesion exhibits a propensity for frameshift replication [Choi, J. Y., et al. (2006) J. Biol. Chem., 281, 25297–25306]. The structure of the N2-dG-IQ adduct at the nonreiterated G1 position was compared to that of the same adduct placed at the G3 position [Stavros, K. M., et al. (2014) Nucleic Acids Res., 42, 3450–3463]. CD indicted minimal spectral differences between the G1 vs G3N2-dG-IQ adducts. NMR indicated that the N2-dG-IQ adduct exhibited similar base-displaced intercalated conformations at both the G1 and G3 positions. This result differed as compared to the corresponding C8-dG-IQ adducts placed at the same positions. The C8-dG-IQ adduct adopted a minor groove conformation when placed at position G1 but a base-displaced intercalated conformation when placed at position G3 in the NarI sequence. The present studies suggest that differences in lesion bypass by hpol η may be mediated by differences in the 3′-flanking sequences, perhaps modulating the ability

Songbirds use spectral shape, not pitch, for sound pattern recognition

PubMed Central

Bregman, Micah R.; Patel, Aniruddh D.; Gentner, Timothy Q.

2016-01-01

Humans easily recognize “transposed” musical melodies shifted up or down in log frequency. Surprisingly, songbirds seem to lack this capacity, although they can learn to recognize human melodies and use complex acoustic sequences for communication. Decades of research have led to the widespread belief that songbirds, unlike humans, are strongly biased to use absolute pitch (AP) in melody recognition. This work relies almost exclusively on acoustically simple stimuli that may belie sensitivities to more complex spectral features. Here, we investigate melody recognition in a species of songbird, the European Starling (Sturnus vulgaris), using tone sequences that vary in both pitch and timbre. We find that small manipulations altering either pitch or timbre independently can drive melody recognition to chance, suggesting that both percepts are poor descriptors of the perceptual cues used by birds for this task. Instead we show that melody recognition can generalize even in the absence of pitch, as long as the spectral shapes of the constituent tones are preserved. These results challenge conventional views regarding the use of pitch cues in nonhuman auditory sequence recognition. PMID:26811447

Vander Lugt correlation of DNA sequence data

NASA Astrophysics Data System (ADS)

Christens-Barry, William A.; Hawk, James F.; Martin, James C.

1990-12-01

DNA, the molecule containing the genetic code of an organism, is a linear chain of subunits. It is the sequence of subunits, of which there are four kinds, that constitutes the unique blueprint of an individual. This sequence is the focus of a large number of analyses performed by an army of geneticists, biologists, and computer scientists. Most of these analyses entail searches for specific subsequences within the larger set of sequence data. Thus, most analyses are essentially pattern recognition or correlation tasks. Yet, there are special features to such analysis that influence the strategy and methods of an optical pattern recognition approach. While the serial processing employed in digital electronic computers remains the main engine of sequence analyses, there is no fundamental reason that more efficient parallel methods cannot be used. We describe an approach using optical pattern recognition (OPR) techniques based on matched spatial filtering. This allows parallel comparison of large blocks of sequence data. In this study we have simulated a Vander Lugt1 architecture implementing our approach. Searches for specific target sequence strings within a block of DNA sequence from the Co/El plasmid2 are performed.

Segmentation and Recognition of Continuous Human Activity

DTIC Science & Technology

2001-01-01

This paper presents a methodology for automatic segmentation and recognition of continuous human activity . We segment a continuous human activity into...commencement or termination. We use single action sequences for the training data set. The test sequences, on the other hand, are continuous sequences of human ... activity that consist of three or more actions in succession. The system has been tested on continuous activity sequences containing actions such as

Investigation of DNA sequence recognition by a streptomycete MarR family transcriptional regulator through surface plasmon resonance and X-ray crystallography

PubMed Central

Stevenson, Clare E. M.; Assaad, Aoun; Chandra, Govind; Le, Tung B. K.; Greive, Sandra J.; Bibb, Mervyn J.; Lawson, David M.

2013-01-01

Consistent with their complex lifestyles and rich secondary metabolite profiles, the genomes of streptomycetes encode a plethora of transcription factors, the vast majority of which are uncharacterized. Herein, we use Surface Plasmon Resonance (SPR) to identify and delineate putative operator sites for SCO3205, a MarR family transcriptional regulator from Streptomyces coelicolor that is well represented in sequenced actinomycete genomes. In particular, we use a novel SPR footprinting approach that exploits indirect ligand capture to vastly extend the lifetime of a standard streptavidin SPR chip. We define two operator sites upstream of sco3205 and a pseudopalindromic consensus sequence derived from these enables further potential operator sites to be identified in the S. coelicolor genome. We evaluate each of these through SPR and test the importance of the conserved bases within the consensus sequence. Informed by these results, we determine the crystal structure of a SCO3205-DNA complex at 2.8 Å resolution, enabling molecular level rationalization of the SPR data. Taken together, our observations support a DNA recognition mechanism involving both direct and indirect sequence readout. PMID:23748564

Specific and Modular Binding Code for Cytosine Recognition in Pumilio/FBF (PUF) RNA-binding Domains

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

Dong, Shuyun; Wang, Yang; Cassidy-Amstutz, Caleb

2011-10-28

Pumilio/fem-3 mRNA-binding factor (PUF) proteins possess a recognition code for bases A, U, and G, allowing designed RNA sequence specificity of their modular Pumilio (PUM) repeats. However, recognition side chains in a PUM repeat for cytosine are unknown. Here we report identification of a cytosine-recognition code by screening random amino acid combinations at conserved RNA recognition positions using a yeast three-hybrid system. This C-recognition code is specific and modular as specificity can be transferred to different positions in the RNA recognition sequence. A crystal structure of a modified PUF domain reveals specific contacts between an arginine side chain and themore » cytosine base. We applied the C-recognition code to design PUF domains that recognize targets with multiple cytosines and to generate engineered splicing factors that modulate alternative splicing. Finally, we identified a divergent yeast PUF protein, Nop9p, that may recognize natural target RNAs with cytosine. This work deepens our understanding of natural PUF protein target recognition and expands the ability to engineer PUF domains to recognize any RNA sequence.« less

Serial position effects in recognition memory for odors: a reexamination.

PubMed

Miles, Christopher; Hodder, Kathryn

2005-10-01

Seven experiments examined recognition memory for sequentially presented odors. Following Reed (2000), participants were presented with a sequence of odors and then required to identify an odor from the sequence in a test probe comprising 2 odors. The pattern of results obtained by Reed (2000, although statistically marginal) demonstrated enhanced recognition for odors presented at the start (primacy) and end (recency) of the sequence: a result that we failed to replicate in any of the experiments reported here. Experiments 1 and 3 were designed to replicate Reed (2000), employing five-item and seven-item sequences, respectively, and each demonstrated significant recency, with evidence of primacy in Experiment 3 only. Experiment 2 replicated Experiment 1, with reduced interstimulus intervals, and produced a null effect of serial position. The ease with which the odors could be verbally labeled was manipulated in Experiments 4 and 5. Nameable odors produced a null effect of serial position (Experiment 4), and hard-to-name odors produced a pronounced recency effect (Experiment 5); nevertheless, overall rates of recognition were remarkably similar for the two experiments at around 70%. Articulatory suppression reduced recognition accuracy (Experiment 6), but recency was again present in the absence of primacy. Odor recognition performance was immune to the effects of an interleaved odor (Experiment 7), and, again, both primacy and recency effects were absent. There was no evidence of olfactory fatigue: Recognition accuracy improved across trials (Experiment 1). It is argued that the results of the experiments reported here are generally consistent with that body of work employing hard-to-name visual stimuli, where recency is obtained in the absence of primacy when the retention interval is short.

Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

PubMed

Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

2015-12-01

Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

The effect of letter string length and report condition on letter recognition accuracy.

PubMed

Raghunandan, Avesh; Karmazinaite, Berta; Rossow, Andrea S

Letter sequence recognition accuracy has been postulated to be limited primarily by low-level visual factors. The influence of high level factors such as visual memory (load and decay) has been largely overlooked. This study provides insight into the role of these factors by investigating the interaction between letter sequence recognition accuracy, letter string length and report condition. Letter sequence recognition accuracy for trigrams and pentagrams were measured in 10 adult subjects for two report conditions. In the complete report condition subjects reported all 3 or all 5 letters comprising trigrams and pentagrams, respectively. In the partial report condition, subjects reported only a single letter in the trigram or pentagram. Letters were presented for 100ms and rendered in high contrast, using black lowercase Courier font that subtended 0.4° at the fixation distance of 0.57m. Letter sequence recognition accuracy was consistently higher for trigrams compared to pentagrams especially for letter positions away from fixation. While partial report increased recognition accuracy in both string length conditions, the effect was larger for pentagrams, and most evident for the final letter positions within trigrams and pentagrams. The effect of partial report on recognition accuracy for the final letter positions increased as eccentricity increased away from fixation, and was independent of the inner/outer position of a letter. Higher-level visual memory functions (memory load and decay) play a role in letter sequence recognition accuracy. There is also suggestion of additional delays imposed on memory encoding by crowded letter elements. Copyright © 2016 Spanish General Council of Optometry. Published by Elsevier España, S.L.U. All rights reserved.

An evolution based biosensor receptor DNA sequence generation algorithm.

PubMed

Kim, Eungyeong; Lee, Malrey; Gatton, Thomas M; Lee, Jaewan; Zang, Yupeng

2010-01-01

A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.

The Coding of Biological Information: From Nucleotide Sequence to Protein Recognition

NASA Astrophysics Data System (ADS)

Štambuk, Nikola

The paper reviews the classic results of Swanson, Dayhoff, Grantham, Blalock and Root-Bernstein, which link genetic code nucleotide patterns to the protein structure, evolution and molecular recognition. Symbolic representation of the binary addresses defining particular nucleotide and amino acid properties is discussed, with consideration of: structure and metric of the code, direct correspondence between amino acid and nucleotide information, and molecular recognition of the interacting protein motifs coded by the complementary DNA and RNA strands.

Exploring the sequence-structure protein landscape in the glycosyltransferase family

PubMed Central

Zhang, Ziding; Kochhar, Sunil; Grigorov, Martin

2003-01-01

To understand the molecular basis of glycosyltransferases’ (GTFs) catalytic mechanism, extensive structural information is required. Here, fold recognition methods were employed to assign 3D protein shapes (folds) to the currently known GTF sequences, available in public databases such as GenBank and Swissprot. First, GTF sequences were retrieved and classified into clusters, based on sequence similarity only. Intracluster sequence similarity was chosen sufficiently high to ensure that the same fold is found within a given cluster. Then, a representative sequence from each cluster was selected to compose a subset of GTF sequences. The members of this reduced set were processed by three different fold recognition methods: 3D-PSSM, FUGUE, and GeneFold. Finally, the results from different fold recognition methods were analyzed and compared to sequence-similarity search methods (i.e., BLAST and PSI-BLAST). It was established that the folds of about 70% of all currently known GTF sequences can be confidently assigned by fold recognition methods, a value which is higher than the fold identification rate based on sequence comparison alone (48% for BLAST and 64% for PSI-BLAST). The identified folds were submitted to 3D clustering, and we found that most of the GTF sequences adopt the typical GTF A or GTF B folds. Our results indicate a lack of evidence that new GTF folds (i.e., folds other than GTF A and B) exist. Based on cases where fold identification was not possible, we suggest several sequences as the most promising targets for a structural genomics initiative focused on the GTF protein family. PMID:14500887

Monitoring and Evaluation of Smolt Migration in the Columbia Basin, Volume XIV; Evaluation of 2006 Prediction of the Run-Timing of Wild and Hatchery-Reared Salmon and Steelhead at Rock Island, Lower Granite, McNary, John Day and Bonneville Dams using Program Real Time, Technical Report 2006.

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

Griswold, Jim

Program RealTime provided monitoring and forecasting of the 2006 inseason outmigrations via the internet for 32 PIT-tagged stocks of wild ESU chinook salmon and steelhead to Lower Granite and/or McNary dams, one PIT-tagged hatchery-reared ESU of sockeye salmon to Lower Granite Dam, and 20 passage-indexed runs-at-large, five each to Rock Island, McNary, John Day, and Bonneville Dams. Twenty-four stocks are of wild yearling chinook salmon which were captured, PIT-tagged, and released at sites above Lower Granite Dam in 2006, and have at least one year's historical migration data previous to the 2006 migration. These stocks originate in drainages of themore » Salmon, Grande Ronde and Clearwater Rivers, all tributaries to the Snake River, and are subsequently detected through the tag identification and monitored at Lower Granite Dam. In addition, seven wild PIT-tagged runs-at-large of Snake or Upper Columbia River ESU salmon and steelhead were monitored at McNary Dam. Three wild PIT-tagged runs-at-large were monitored at Lower Granite Dam, consisting of the yearling and subyearling chinook salmon and the steelhead trout runs. The hatchery-reared PIT-tagged sockeye salmon stock from Redfish Lake was monitored outmigrating through Lower Granite Dam. Passage-indexed stocks (stocks monitored by FPC passage indices) included combined wild and hatchery runs-at-large of subyearling and yearling chinook, coho, and sockeye salmon, and steelhead trout forecasted to Rock Island, McNary, John Day, and Bonneville Dams.« less

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Survival and migration behavior of juvenile salmonids at McNary Dam, 2005: Final report of research

USGS Publications Warehouse

Perry, Russell W.; Braatz, Amy C.; Novick, Marc S.; Lucchesi, Joel N.; Rutz, Gary L.; Koch, Ryan C.; Schei, Jacquelyn L.; Adams, Noah S.; Rondorf, Dennis W.

2007-01-01

During 2005, we used radio-telemetry at McNary Dam to estimate passage and survival parameters of juvenile salmonids. During the spring migration period, two treatments were implemented: 1) 12-h spill operations with spill occurring between 1800 hours and 0600 hours, and 2) 24-h spill with spill occurring 24 hours per day. Treatments were not implemented during the summer migration period. However, a court-order was issued by Judge James Redden, U.S. 9th District Court, mandating a maximum powerhouse discharge of 50 kcfs with the remaining discharge to be spilled over the 24-h diel cycle between 1 July and 31 August 2005. Consequently, our study was conducted during two distinct periods: 1) a short period of involuntary spill for 24-h per day that occurred between 22 June and 30 June 2005, and 2) the period of court-ordered spill that was implemented after 1 July 2005.

KM+, a mannose-binding lectin from Artocarpus integrifolia: amino acid sequence, predicted tertiary structure, carbohydrate recognition, and analysis of the beta-prism fold.

PubMed Central

Rosa, J. C.; De Oliveira, P. S.; Garratt, R.; Beltramini, L.; Resing, K.; Roque-Barreira, M. C.; Greene, L. J.

1999-01-01

The complete amino acid sequence of the lectin KM+ from Artocarpus integrifolia (jackfruit), which contains 149 residues/mol, is reported and compared to those of other members of the Moraceae family, particularly that of jacalin, also from jackfruit, with which it shares 52% sequence identity. KM+ presents an acetyl-blocked N-terminus and is not posttranslationally modified by proteolytic cleavage as is the case for jacalin. Rather, it possesses a short, glycine-rich linker that unites the regions homologous to the alpha- and beta-chains of jacalin. The results of homology modeling implicate the linker sequence in sterically impeding rotation of the side chain of Asp141 within the binding site pocket. As a consequence, the aspartic acid is locked into a conformation adequate only for the recognition of equatorial hydroxyl groups on the C4 epimeric center (alpha-D-mannose, alpha-D-glucose, and their derivatives). In contrast, the internal cleavage of the jacalin chain permits free rotation of the homologous aspartic acid, rendering it capable of accepting hydrogen bonds from both possible hydroxyl configurations on C4. We suggest that, together with direct recognition of epimeric hydroxyls and the steric exclusion of disfavored ligands, conformational restriction of the lectin should be considered to be a new mechanism by which selectivity may be built into carbohydrate binding sites. Jacalin and KM+ adopt the beta-prism fold already observed in two unrelated protein families. Despite presenting little or no sequence similarity, an analysis of the beta-prism reveals a canonical feature repeatedly present in all such structures, which is based on six largely hydrophobic residues within a beta-hairpin containing two classic-type beta-bulges. We suggest the term beta-prism motif to describe this feature. PMID:10210179

DNA sequence similarity recognition by hybridization to short oligomers

DOEpatents

Milosavljevic, Aleksandar

1999-01-01

Methods are disclosed for the comparison of nucleic acid sequences. Data is generated by hybridizing sets of oligomers with target nucleic acids. The data thus generated is manipulated simultaneously with respect to both (i) matching between oligomers and (ii) matching between oligomers and putative reference sequences available in databases. Using data compression methods to manipulate this mutual information, sequences for the target can be constructed.

Illumination-invariant hand gesture recognition

NASA Astrophysics Data System (ADS)

Mendoza-Morales, América I.; Miramontes-Jaramillo, Daniel; Kober, Vitaly

2015-09-01

In recent years, human-computer interaction (HCI) has received a lot of interest in industry and science because it provides new ways to interact with modern devices through voice, body, and facial/hand gestures. The application range of the HCI is from easy control of home appliances to entertainment. Hand gesture recognition is a particularly interesting problem because the shape and movement of hands usually are complex and flexible to be able to codify many different signs. In this work we propose a three step algorithm: first, detection of hands in the current frame is carried out; second, hand tracking across the video sequence is performed; finally, robust recognition of gestures across subsequent frames is made. Recognition rate highly depends on non-uniform illumination of the scene and occlusion of hands. In order to overcome these issues we use two Microsoft Kinect devices utilizing combined information from RGB and infrared sensors. The algorithm performance is tested in terms of recognition rate and processing time.

Unravelling Glucan Recognition Systems by Glycome Microarrays Using the Designer Approach and Mass Spectrometry*

PubMed Central

Palma, Angelina S.; Liu, Yan; Zhang, Hongtao; Zhang, Yibing; McCleary, Barry V.; Yu, Guangli; Huang, Qilin; Guidolin, Leticia S.; Ciocchini, Andres E.; Torosantucci, Antonella; Wang, Denong; Carvalho, Ana Luísa; Fontes, Carlos M. G. A.; Mulloy, Barbara; Childs, Robert A.; Feizi, Ten; Chai, Wengang

2015-01-01

Glucans are polymers of d-glucose with differing linkages in linear or branched sequences. They are constituents of microbial and plant cell-walls and involved in important bio-recognition processes, including immunomodulation, anticancer activities, pathogen virulence, and plant cell-wall biodegradation. Translational possibilities for these activities in medicine and biotechnology are considerable. High-throughput micro-methods are needed to screen proteins for recognition of specific glucan sequences as a lead to structure–function studies and their exploitation. We describe construction of a “glucome” microarray, the first sequence-defined glycome-scale microarray, using a “designer” approach from targeted ligand-bearing glucans in conjunction with a novel high-sensitivity mass spectrometric sequencing method, as a screening tool to assign glucan recognition motifs. The glucome microarray comprises 153 oligosaccharide probes with high purity, representing major sequences in glucans. Negative-ion electrospray tandem mass spectrometry with collision-induced dissociation was used for complete linkage analysis of gluco-oligosaccharides in linear “homo” and “hetero” and branched sequences. The system is validated using antibodies and carbohydrate-binding modules known to target α- or β-glucans in different biological contexts, extending knowledge on their specificities, and applied to reveal new information on glucan recognition by two signaling molecules of the immune system against pathogens: Dectin-1 and DC-SIGN. The sequencing of the glucan oligosaccharides by the MS method and their interrogation on the microarrays provides detailed information on linkage, sequence and chain length requirements of glucan-recognizing proteins, and are a sensitive means of revealing unsuspected sequences in the polysaccharides. PMID:25670804

Structure and DNA-Binding Sites of the SWI1 AT-rich Interaction Domain (ARID) Suggest Determinants for Sequence-Specific DNA Recognition

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

Kim, Suhkmann; Zhang, Ziming; Upchurch, Sean

2004-04-16

2 ARID is a homologous family of DNA-binding domains that occur in DNA binding proteins from a wide variety of species, ranging from yeast to nematodes, insects, mammals and plants. SWI1, a member of the SWI/SNF protein complex that is involved in chromatin remodeling during transcription, contains the ARID motif. The ARID domain of human SWI1 (also known as p270) does not select for a specific DNA sequence from a random sequence pool. The lack of sequence specificity shown by the SWI1 ARID domain stands in contrast to the other characterized ARID domains, which recognize specific AT-rich sequences. We havemore » solved the three-dimensional structure of human SWI1 ARID using solution NMR methods. In addition, we have characterized non-specific DNA-binding by the SWI1 ARID domain. Results from this study indicate that a flexible long internal loop in ARID motif is likely to be important for sequence specific DNA-recognition. The structure of human SWI1 ARID domain also represents a distinct structural subfamily. Studies of ARID indicate that boundary of the DNA binding structural and functional domains can extend beyond the sequence homologous region in a homologous family of proteins. Structural studies of homologous domains such as ARID family of DNA-binding domains should provide information to better predict the boundary of structural and functional domains in structural genomic studies. Key Words: ARID, SWI1, NMR, structural genomics, protein-DNA interaction.« less

Mining sequential patterns for protein fold recognition.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2008-02-01

Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. Protein classification in terms of fold recognition plays an important role in computational protein analysis, since it can contribute to the determination of the function of a protein whose structure is unknown. Specifically, one of the most efficient SPM algorithms, cSPADE, is employed for the analysis of protein sequence. A classifier uses the extracted sequential patterns to classify proteins in the appropriate fold category. For training and evaluating the proposed method we used the protein sequences from the Protein Data Bank and the annotation of the SCOP database. The method exhibited an overall accuracy of 25% in a classification problem with 36 candidate categories. The classification performance reaches up to 56% when the five most probable protein folds are considered.

Recognition of Double Stranded RNA by Guanidine-Modified Peptide Nucleic Acids (GPNA)

PubMed Central

Gupta, Pankaj; Muse, Oluwatoyosi; Rozners, Eriks

2011-01-01

Double helical RNA has become an attractive target for molecular recognition because many non-coding RNAs play important roles in control of gene expression. Recently, we discovered that short peptide nucleic acids (PNA) bind strongly and sequence selectively to a homopurine tract of double helical RNA via triple helix formation. Herein we tested if the molecular recognition of RNA can be enhanced by α-guanidine modification of PNA. Our study was motivated by the discovery of Ly and co-workers that the guanidine modification greatly enhances the cellular delivery of PNA. Isothermal titration calorimetry showed that the guanidine-modified PNA (GPNA) had reduced affinity and sequence selectivity for triple helical recognition of RNA. The data suggested that in contrast to unmodified PNA, which formed a 1:1 PNA-RNA triple helix, GPNA preferred a 2:1 GPNA-RNA triplex-invasion complex. Nevertheless, promising results were obtained for recognition of biologically relevant double helical RNA. Consistent with enhanced strand invasion ability, GPNA derived from D-arginine recognized the transactivation response element (TAR) of HIV-1 with high affinity and sequence selectivity, presumably via Watson-Crick duplex formation. On the other hand, strong and sequence selective triple helices were formed by unmodified and nucelobase-modified PNAs and the purine rich strand of bacterial A-site. These results suggest that appropriate chemical modifications of PNA may enhance molecular recognition of complex non-coding RNAs. PMID:22146072

Codebook-based electrooculography data analysis towards cognitive activity recognition.

PubMed

Lagodzinski, P; Shirahama, K; Grzegorzek, M

2018-04-01

With the advancement in mobile/wearable technology, people started to use a variety of sensing devices to track their daily activities as well as health and fitness conditions in order to improve the quality of life. This work addresses an idea of eye movement analysis, which due to the strong correlation with cognitive tasks can be successfully utilized in activity recognition. Eye movements are recorded using an electrooculographic (EOG) system built into the frames of glasses, which can be worn more unobtrusively and comfortably than other devices. Since the obtained information is low-level sensor data expressed as a sequence representing values in constant intervals (100 Hz), the cognitive activity recognition problem is formulated as sequence classification. However, it is unclear what kind of features are useful for accurate cognitive activity recognition. Thus, a machine learning algorithm like a codebook approach is applied, which instead of focusing on feature engineering is using a distribution of characteristic subsequences (codewords) to describe sequences of recorded EOG data, where the codewords are obtained by clustering a large number of subsequences. Further, statistical analysis of the codeword distribution results in discovering features which are characteristic to a certain activity class. Experimental results demonstrate good accuracy of the codebook-based cognitive activity recognition reflecting the effective usage of the codewords. Copyright © 2017 Elsevier Ltd. All rights reserved.

Continuous Chinese sign language recognition with CNN-LSTM

NASA Astrophysics Data System (ADS)

Yang, Su; Zhu, Qing

2017-07-01

The goal of sign language recognition (SLR) is to translate the sign language into text, and provide a convenient tool for the communication between the deaf-mute and the ordinary. In this paper, we formulate an appropriate model based on convolutional neural network (CNN) combined with Long Short-Term Memory (LSTM) network, in order to accomplish the continuous recognition work. With the strong ability of CNN, the information of pictures captured from Chinese sign language (CSL) videos can be learned and transformed into vector. Since the video can be regarded as an ordered sequence of frames, LSTM model is employed to connect with the fully-connected layer of CNN. As a recurrent neural network (RNN), it is suitable for sequence learning tasks with the capability of recognizing patterns defined by temporal distance. Compared with traditional RNN, LSTM has performed better on storing and accessing information. We evaluate this method on our self-built dataset including 40 daily vocabularies. The experimental results show that the recognition method with CNN-LSTM can achieve a high recognition rate with small training sets, which will meet the needs of real-time SLR system.

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds.

PubMed

de Jong, Maarten; Chen, Wei; Notestine, Randy; Persson, Kristin; Ceder, Gerbrand; Jain, Anubhav; Asta, Mark; Gamst, Anthony

2016-10-03

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials.

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds

PubMed Central

de Jong, Maarten; Chen, Wei; Notestine, Randy; Persson, Kristin; Ceder, Gerbrand; Jain, Anubhav; Asta, Mark; Gamst, Anthony

2016-01-01

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials. PMID:27694824

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds

DOE PAGES

de Jong, Maarten; Chen, Wei; Notestine, Randy; ...

2016-10-03

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. Themore » approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials.« less

Method of determining the necessary number of observations for video stream documents recognition

NASA Astrophysics Data System (ADS)

Arlazarov, Vladimir V.; Bulatov, Konstantin; Manzhikov, Temudzhin; Slavin, Oleg; Janiszewski, Igor

2018-04-01

This paper discusses a task of document recognition on a sequence of video frames. In order to optimize the processing speed an estimation is performed of stability of recognition results obtained from several video frames. Considering identity document (Russian internal passport) recognition on a mobile device it is shown that significant decrease is possible of the number of observations necessary for obtaining precise recognition result.

High throughput profile-profile based fold recognition for the entire human proteome.

PubMed

McGuffin, Liam J; Smith, Richard T; Bryson, Kevin; Sørensen, Søren-Aksel; Jones, David T

2006-06-07

In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power. In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

PSS-3D1D: an improved 3D1D profile method of protein fold recognition for the annotation of twilight zone sequences.

PubMed

Ganesan, K; Parthasarathy, S

2011-12-01

Annotation of any newly determined protein sequence depends on the pairwise sequence identity with known sequences. However, for the twilight zone sequences which have only 15-25% identity, the pair-wise comparison methods are inadequate and the annotation becomes a challenging task. Such sequences can be annotated by using methods that recognize their fold. Bowie et al. described a 3D1D profile method in which the amino acid sequences that fold into a known 3D structure are identified by their compatibility to that known 3D structure. We have improved the above method by using the predicted secondary structure information and employ it for fold recognition from the twilight zone sequences. In our Protein Secondary Structure 3D1D (PSS-3D1D) method, a score (w) for the predicted secondary structure of the query sequence is included in finding the compatibility of the query sequence to the known fold 3D structures. In the benchmarks, the PSS-3D1D method shows a maximum of 21% improvement in predicting correctly the α + β class of folds from the sequences with twilight zone level of identity, when compared with the 3D1D profile method. Hence, the PSS-3D1D method could offer more clues than the 3D1D method for the annotation of twilight zone sequences. The web based PSS-3D1D method is freely available in the PredictFold server at http://bioinfo.bdu.ac.in/servers/ .

A multi-year analysis of spillway survival for juvenile salmonids as a function of spill bay operations at McNary Dam, Washington and Oregon, 2004-09

USGS Publications Warehouse

Adams, Noah S.; Hansel, Hal C.; Perry, Russell W.; Evans, Scott D.

2012-01-01

We analyzed 6 years (2004-09) of passage and survival data collected at McNary Dam to examine how spill bay operations affect survival of juvenile salmonids passing through the spillway at McNary Dam. We also examined the relations between spill bay operations and survival through the juvenile fish bypass in an attempt to determine if survival through the bypass is influenced by spill bay operations. We used a Cormack-Jolly-Seber release-recapture model (CJS model) to determine how the survival of juvenile salmonids passing through McNary Dam relates to spill bay operations. Results of these analyses, while not designed to yield predictive models, can be used to help develop dam-operation strategies that optimize juvenile salmonid survival. For example, increasing total discharge typically had a positive effect on both spillway and bypass survival for all species except sockeye salmon (Oncorhynchus nerka). Likewise, an increase in spill bay discharge improved spillway survival for yearling Chinook salmon (Oncorhynchus tshawytscha), and an increase in spillway discharge positively affected spillway survival for juvenile steelhead (Oncorhynchus mykiss). The strong linear relation between increased spill and increased survival indicates that increasing the amount of water through the spillway is one strategy that could be used to improve spillway survival for yearling Chinook salmon and juvenile steelhead. However, increased spill did not improve spillway survival for subyearling Chinook salmon and sockeye salmon. Our results indicate that a uniform spill pattern would provide the highest spillway survival and bypass survival for subyearling Chinook salmon. Conversely, a predominantly south spill pattern provided the highest spillway survival for yearling Chinook salmon and juvenile steelhead. Although spill pattern was not a factor for spillway survival of sockeye salmon, spill bay operations that optimize passage through the north and south spill bays maximized

Event-related potential correlates of declarative and non-declarative sequence knowledge.

PubMed

Ferdinand, Nicola K; Rünger, Dennis; Frensch, Peter A; Mecklinger, Axel

2010-07-01

The goal of the present study was to demonstrate that declarative and non-declarative knowledge acquired in an incidental sequence learning task contributes differentially to memory retrieval and leads to dissociable ERP signatures in a recognition memory task. For this purpose, participants performed a sequence learning task and were classified as verbalizers, partial verbalizers, or nonverbalizers according to their ability to verbally report the systematic response sequence. Thereafter, ERPs were recorded in a recognition memory task time-locked to sequence triplets that were either part of the previously learned sequence or not. Although all three groups executed old sequence triplets faster than new triplets in the recognition memory task, qualitatively distinct ERP patterns were found for participants with and without reportable knowledge. Verbalizers and, to a lesser extent, partial verbalizers showed an ERP correlate of recollection for parts of the incidentally learned sequence. In contrast, nonverbalizers showed a different ERP effect with a reverse polarity that might reflect priming. This indicates that an ensemble of qualitatively different processes is at work when declarative and non-declarative sequence knowledge is retrieved. By this, our findings favor a multiple-systems view postulating that explicit and implicit learning are supported by different and functionally independent systems. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Improving Protein Fold Recognition by Deep Learning Networks

NASA Astrophysics Data System (ADS)

Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

2015-12-01

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl’s benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

Improving Protein Fold Recognition by Deep Learning Networks.

PubMed

Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

2015-12-04

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl's benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

Individual differences in language and working memory affect children's speech recognition in noise.

PubMed

McCreery, Ryan W; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc

2017-05-01

We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Ninety-six children with normal hearing, who were between 5 and 12 years of age. Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Working memory and language both influence children's speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child's auditory skills, consistent with the Ease of Language Understanding model.

Evidence of automatic processing in sequence learning using process-dissociation

PubMed Central

Mong, Heather M.; McCabe, David P.; Clegg, Benjamin A.

2012-01-01

This paper proposes a way to apply process-dissociation to sequence learning in addition and extension to the approach used by Destrebecqz and Cleeremans (2001). Participants were trained on two sequences separated from each other by a short break. Following training, participants self-reported their knowledge of the sequences. A recognition test was then performed which required discrimination of two trained sequences, either under the instructions to call any sequence encountered in the experiment “old” (the inclusion condition), or only sequence fragments from one half of the experiment “old” (the exclusion condition). The recognition test elicited automatic and controlled process estimates using the process dissociation procedure, and suggested both processes were involved. Examining the underlying processes supporting performance may provide more information on the fundamental aspects of the implicit and explicit constructs than has been attainable through awareness testing. PMID:22679465

Toxins of Prokaryotic Toxin-Antitoxin Systems with Sequence-Specific Endoribonuclease Activity

PubMed Central

Masuda, Hisako; Inouye, Masayori

2017-01-01

Protein translation is the most common target of toxin-antitoxin system (TA) toxins. Sequence-specific endoribonucleases digest RNA in a sequence-specific manner, thereby blocking translation. While past studies mainly focused on the digestion of mRNA, recent analysis revealed that toxins can also digest tRNA, rRNA and tmRNA. Purified toxins can digest single-stranded portions of RNA containing recognition sequences in the absence of ribosome in vitro. However, increasing evidence suggests that in vivo digestion may occur in association with ribosomes. Despite the prevalence of recognition sequences in many mRNA, preferential digestion seems to occur at specific positions within mRNA and also in certain reading frames. In this review, a variety of tools utilized to study the nuclease activities of toxins over the past 15 years will be reviewed. A recent adaptation of an RNA-seq-based technique to analyze entire sets of cellular RNA will be introduced with an emphasis on its strength in identifying novel targets and redefining recognition sequences. The differences in biochemical properties and postulated physiological roles will also be discussed. PMID:28420090

The chemical structure of DNA sequence signals for RNA transcription

NASA Technical Reports Server (NTRS)

George, D. G.; Dayhoff, M. O.

1982-01-01

The proposed recognition sites for RNA transcription for E. coli NRA polymerase, bacteriophage T7 RNA polymerase, and eukaryotic RNA polymerase Pol II are evaluated in the light of the requirements for efficient recognition. It is shown that although there is good experimental evidence that specific nucleic acid sequence patterns are involved in transcriptional regulation in bacteria and bacterial viruses, among the sequences now available, only in the case of the promoters recognized by bacteriophage T7 polymerase does it seem likely that the pattern is sufficient. It is concluded that the eukaryotic pattern that is investigated is not restrictive enough to serve as a recognition site.

Specific minor groove solvation is a crucial determinant of DNA binding site recognition

PubMed Central

Harris, Lydia-Ann; Williams, Loren Dean; Koudelka, Gerald B.

2014-01-01

The DNA sequence preferences of nearly all sequence specific DNA binding proteins are influenced by the identities of bases that are not directly contacted by protein. Discrimination between non-contacted base sequences is commonly based on the differential abilities of DNA sequences to allow narrowing of the DNA minor groove. However, the factors that govern the propensity of minor groove narrowing are not completely understood. Here we show that the differential abilities of various DNA sequences to support formation of a highly ordered and stable minor groove solvation network are a key determinant of non-contacted base recognition by a sequence-specific binding protein. In addition, disrupting the solvent network in the non-contacted region of the binding site alters the protein's ability to recognize contacted base sequences at positions 5–6 bases away. This observation suggests that DNA solvent interactions link contacted and non-contacted base recognition by the protein. PMID:25429976

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Conserved Sequence Preferences Contribute to Substrate Recognition by the Proteasome*

PubMed Central

Yu, Houqing; Singh Gautam, Amit K.; Wilmington, Shameika R.; Wylie, Dennis; Martinez-Fonts, Kirby; Kago, Grace; Warburton, Marie; Chavali, Sreenivas; Inobe, Tomonao; Finkelstein, Ilya J.; Babu, M. Madan

2016-01-01

The proteasome has pronounced preferences for the amino acid sequence of its substrates at the site where it initiates degradation. Here, we report that modulating these sequences can tune the steady-state abundance of proteins over 2 orders of magnitude in cells. This is the same dynamic range as seen for inducing ubiquitination through a classic N-end rule degron. The stability and abundance of His3 constructs dictated by the initiation site affect survival of yeast cells and show that variation in proteasomal initiation can affect fitness. The proteasome's sequence preferences are linked directly to the affinity of the initiation sites to their receptor on the proteasome and are conserved between Saccharomyces cerevisiae, Schizosaccharomyces pombe, and human cells. These findings establish that the sequence composition of unstructured initiation sites influences protein abundance in vivo in an evolutionarily conserved manner and can affect phenotype and fitness. PMID:27226608

Integrated segmentation and recognition of connected Ottoman script

NASA Astrophysics Data System (ADS)

Yalniz, Ismet Zeki; Altingovde, Ismail Sengor; Güdükbay, Uğur; Ulusoy, Özgür

2009-11-01

We propose a novel context-sensitive segmentation and recognition method for connected letters in Ottoman script. This method first extracts a set of segments from a connected script and determines the candidate letters to which extracted segments are most similar. Next, a function is defined for scoring each different syntactically correct sequence of these candidate letters. To find the candidate letter sequence that maximizes the score function, a directed acyclic graph is constructed. The letters are finally recognized by computing the longest path in this graph. Experiments using a collection of printed Ottoman documents reveal that the proposed method provides >90% precision and recall figures in terms of character recognition. In a further set of experiments, we also demonstrate that the framework can be used as a building block for an information retrieval system for digital Ottoman archives.

A promoter recognition mechanism common to yeast mitochondrial and phage t7 RNA polymerases.

PubMed

Nayak, Dhananjaya; Guo, Qing; Sousa, Rui

2009-05-15

Yeast mitochondrial (YMt) and phage T7 RNA polymerases (RNAPs) are two divergent representatives of a large family of single subunit RNAPs that are also found in the mitochondria and chloroplasts of higher eukaryotes, mammalian nuclei, and many other bacteriophage. YMt and phage T7 promoters differ greatly in sequence and length, and the YMt RNAP uses an accessory factor for initiation, whereas T7 RNAP does not. We obtain evidence here that, despite these apparent differences, both the YMt and T7 RNAPs utilize a similar promoter recognition loop to bind their respective promoters. Mutations in this element in YMt RNAP specifically disrupt mitochondrial promoter utilization, and experiments with site-specifically tethered chemical nucleases indicate that this element binds the mitochondrial promoter almost identically to how the promoter recognition loop from the phage RNAP binds its promoter. Sequence comparisons reveal that the other members of the single subunit RNAP family display loops of variable sequence and size at a position corresponding to the YMt and T7 RNAP promoter recognition loops. We speculate that these elements may be involved in promoter recognition in most or all of these enzymes and that this element's structure allows it to accommodate significant sequence and length variation to provide a mechanism for rapid evolution of new promoter specificities in this RNAP family.

Bio-recognitive photonics of a DNA-guided organic semiconductor.

PubMed

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-04

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Bio-recognitive photonics of a DNA-guided organic semiconductor

NASA Astrophysics Data System (ADS)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Do pattern recognition skills transfer across sports? A preliminary analysis.

PubMed

Smeeton, Nicholas J; Ward, Paul; Williams, A Mark

2004-02-01

The ability to recognize patterns of play is fundamental to performance in team sports. While typically assumed to be domain-specific, pattern recognition skills may transfer from one sport to another if similarities exist in the perceptual features and their relations and/or the strategies used to encode and retrieve relevant information. A transfer paradigm was employed to compare skilled and less skilled soccer, field hockey and volleyball players' pattern recognition skills. Participants viewed structured and unstructured action sequences from each sport, half of which were randomly represented with clips not previously seen. The task was to identify previously viewed action sequences quickly and accurately. Transfer of pattern recognition skill was dependent on the participant's skill, sport practised, nature of the task and degree of structure. The skilled soccer and hockey players were quicker than the skilled volleyball players at recognizing structured soccer and hockey action sequences. Performance differences were not observed on the structured volleyball trials between the skilled soccer, field hockey and volleyball players. The skilled field hockey and soccer players were able to transfer perceptual information or strategies between their respective sports. The less skilled participants' results were less clear. Implications for domain-specific expertise, transfer and diversity across domains are discussed.

Structural basis of DNA sequence recognition by the response regulator PhoP in Mycobacterium tuberculosis.

PubMed

He, Xiaoyuan; Wang, Liqin; Wang, Shuishu

2016-04-15

The transcriptional regulator PhoP is an essential virulence factor in Mycobacterium tuberculosis, and it presents a target for the development of new anti-tuberculosis drugs and attenuated tuberculosis vaccine strains. PhoP binds to DNA as a highly cooperative dimer by recognizing direct repeats of 7-bp motifs with a 4-bp spacer. To elucidate the PhoP-DNA binding mechanism, we determined the crystal structure of the PhoP-DNA complex. The structure revealed a tandem PhoP dimer that bound to the direct repeat. The surprising tandem arrangement of the receiver domains allowed the four domains of the PhoP dimer to form a compact structure, accounting for the strict requirement of a 4-bp spacer and the highly cooperative binding of the dimer. The PhoP-DNA interactions exclusively involved the effector domain. The sequence-recognition helix made contact with the bases of the 7-bp motif in the major groove, and the wing interacted with the adjacent minor groove. The structure provides a starting point for the elucidation of the mechanism by which PhoP regulates the virulence of M. tuberculosis and guides the design of screening platforms for PhoP inhibitors.

HMMerThread: detecting remote, functional conserved domains in entire genomes by combining relaxed sequence-database searches with fold recognition.

PubMed

Bradshaw, Charles Richard; Surendranath, Vineeth; Henschel, Robert; Mueller, Matthias Stefan; Habermann, Bianca Hermine

2011-03-10

Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs) are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10), a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in proteins based on weak

HMMerThread: Detecting Remote, Functional Conserved Domains in Entire Genomes by Combining Relaxed Sequence-Database Searches with Fold Recognition

PubMed Central

Bradshaw, Charles Richard; Surendranath, Vineeth; Henschel, Robert; Mueller, Matthias Stefan; Habermann, Bianca Hermine

2011-01-01

Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs) are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10), a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in proteins based on weak

Molecular recognition in protein modification with rhodium metallopeptides

PubMed Central

Ball, Zachary T.

2015-01-01

Chemical manipulation of natural, unengineered proteins is a daunting challenge which tests the limits of reaction design. By combining transition-metal or other catalysts with molecular recognition ideas, it is possible to achieve site-selective protein reactivity without the need for engineered recognition sequences or reactive sites. Some recent examples in this area have used ruthenium photocatalysis, pyridine organocatalysis, and rhodium(II) metallocarbene catalysis, indicating that the fundamental ideas provide opportunities for using diverse reactivity on complex protein substrates and in complex cell-like environments. PMID:25588960

Detection of possible restriction sites for type II restriction enzymes in DNA sequences.

PubMed

Gagniuc, P; Cimponeriu, D; Ionescu-Tîrgovişte, C; Mihai, Andrada; Stavarachi, Monica; Mihai, T; Gavrilă, L

2011-01-01

In order to make a step forward in the knowledge of the mechanism operating in complex polygenic disorders such as diabetes and obesity, this paper proposes a new algorithm (PRSD -possible restriction site detection) and its implementation in Applied Genetics software. This software can be used for in silico detection of potential (hidden) recognition sites for endonucleases and for nucleotide repeats identification. The recognition sites for endonucleases may result from hidden sequences through deletion or insertion of a specific number of nucleotides. Tests were conducted on DNA sequences downloaded from NCBI servers using specific recognition sites for common type II restriction enzymes introduced in the software database (n = 126). Each possible recognition site indicated by the PRSD algorithm implemented in Applied Genetics was checked and confirmed by NEBcutter V2.0 and Webcutter 2.0 software. In the sequence NG_008724.1 (which includes 63632 nucleotides) we found a high number of potential restriction sites for ECO R1 that may be produced by deletion (n = 43 sites) or insertion (n = 591 sites) of one nucleotide. The second module of Applied Genetics has been designed to find simple repeats sizes with a real future in understanding the role of SNPs (Single Nucleotide Polymorphisms) in the pathogenesis of the complex metabolic disorders. We have tested the presence of simple repetitive sequences in five DNA sequence. The software indicated exact position of each repeats detected in the tested sequences. Future development of Applied Genetics can provide an alternative for powerful tools used to search for restriction sites or repetitive sequences or to improve genotyping methods.

Codon-Anticodon Recognition in the Bacillus subtilis glyQS T Box Riboswitch

PubMed Central

Caserta, Enrico; Liu, Liang-Chun; Grundy, Frank J.; Henkin, Tina M.

2015-01-01

Many amino acid-related genes in Gram-positive bacteria are regulated by the T box riboswitch. The leader RNA of genes in the T box family controls the expression of downstream genes by monitoring the aminoacylation status of the cognate tRNA. Previous studies identified a three-nucleotide codon, termed the “Specifier Sequence,” in the riboswitch that corresponds to the amino acid identity of the downstream genes. Pairing of the Specifier Sequence with the anticodon of the cognate tRNA is the primary determinant of specific tRNA recognition. This interaction mimics codon-anticodon pairing in translation but occurs in the absence of the ribosome. The goal of the current study was to determine the effect of a full range of mismatches for comparison with codon recognition in translation. Mutations were individually introduced into the Specifier Sequence of the glyQS leader RNA and tRNAGly anticodon to test the effect of all possible pairing combinations on tRNA binding affinity and antitermination efficiency. The functional role of the conserved purine 3′ of the Specifier Sequence was also verifiedin this study. We found that substitutions at the Specifier Sequence resulted in reduced binding, the magnitude of which correlates well with the predicted stability of the RNA-RNA pairing. However, the tolerance for specific mismatches in antitermination was generally different from that during decoding, which reveals a unique tRNA recognition pattern in the T box antitermination system. PMID:26229106

Iterative cross section sequence graph for handwritten character segmentation.

PubMed

Dawoud, Amer

2007-08-01

The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.

Bio-recognitive photonics of a DNA-guided organic semiconductor

PubMed Central

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA–DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an ‘inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA–DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition. PMID:26725969

An Integrated Korean Biodiversity and Genetic Information Retrieval System

PubMed Central

Lim, Jeongheui; Bhak, Jong; Oh, Hee-Mock; Kim, Chang-Bae; Park, Yong-Ha; Paek, Woon Kee

2008-01-01

Background On-line biodiversity information databases are growing quickly and being integrated into general bioinformatics systems due to the advances of fast gene sequencing technologies and the Internet. These can reduce the cost and effort of performing biodiversity surveys and genetic searches, which allows scientists to spend more time researching and less time collecting and maintaining data. This will cause an increased rate of knowledge build-up and improve conservations. The biodiversity databases in Korea have been scattered among several institutes and local natural history museums with incompatible data types. Therefore, a comprehensive database and a nation wide web portal for biodiversity information is necessary in order to integrate diverse information resources, including molecular and genomic databases. Results The Korean Natural History Research Information System (NARIS) was built and serviced as the central biodiversity information system to collect and integrate the biodiversity data of various institutes and natural history museums in Korea. This database aims to be an integrated resource that contains additional biological information, such as genome sequences and molecular level diversity. Currently, twelve institutes and museums in Korea are integrated by the DiGIR (Distributed Generic Information Retrieval) protocol, with Darwin Core2.0 format as its metadata standard for data exchange. Data quality control and statistical analysis functions have been implemented. In particular, integrating molecular and genetic information from the National Center for Biotechnology Information (NCBI) databases with NARIS was recently accomplished. NARIS can also be extended to accommodate other institutes abroad, and the whole system can be exported to establish local biodiversity management servers. Conclusion A Korean data portal, NARIS, has been developed to efficiently manage and utilize biodiversity data, which includes genetic resources. NARIS aims

Training the max-margin sequence model with the relaxed slack variables.

PubMed

Niu, Lingfeng; Wu, Jianmin; Shi, Yong

2012-09-01

Sequence models are widely used in many applications such as natural language processing, information extraction and optical character recognition, etc. We propose a new approach to train the max-margin based sequence model by relaxing the slack variables in this paper. With the canonical feature mapping definition, the relaxed problem is solved by training a multiclass Support Vector Machine (SVM). Compared with the state-of-the-art solutions for the sequence learning, the new method has the following advantages: firstly, the sequence training problem is transformed into a multiclassification problem, which is more widely studied and already has quite a few off-the-shelf training packages; secondly, this new approach reduces the complexity of training significantly and achieves comparable prediction performance compared with the existing sequence models; thirdly, when the size of training data is limited, by assigning different slack variables to different microlabel pairs, the new method can use the discriminative information more frugally and produces more reliable model; last but not least, by employing kernels in the intermediate multiclass SVM, nonlinear feature space can be easily explored. Experimental results on the task of named entity recognition, information extraction and handwritten letter recognition with the public datasets illustrate the efficiency and effectiveness of our method. Copyright © 2012 Elsevier Ltd. All rights reserved.

Extrinsic Cognitive Load Impairs Spoken Word Recognition in High- and Low-Predictability Sentences.

PubMed

Hunter, Cynthia R; Pisoni, David B

Listening effort (LE) induced by speech degradation reduces performance on concurrent cognitive tasks. However, a converse effect of extrinsic cognitive load on recognition of spoken words in sentences has not been shown. The aims of the present study were to (a) examine the impact of extrinsic cognitive load on spoken word recognition in a sentence recognition task and (b) determine whether cognitive load and/or LE needed to understand spectrally degraded speech would differentially affect word recognition in high- and low-predictability sentences. Downstream effects of speech degradation and sentence predictability on the cognitive load task were also examined. One hundred twenty young adults identified sentence-final spoken words in high- and low-predictability Speech Perception in Noise sentences. Cognitive load consisted of a preload of short (low-load) or long (high-load) sequences of digits, presented visually before each spoken sentence and reported either before or after identification of the sentence-final word. LE was varied by spectrally degrading sentences with four-, six-, or eight-channel noise vocoding. Level of spectral degradation and order of report (digits first or words first) were between-participants variables. Effects of cognitive load, sentence predictability, and speech degradation on accuracy of sentence-final word identification as well as recall of preload digit sequences were examined. In addition to anticipated main effects of sentence predictability and spectral degradation on word recognition, we found an effect of cognitive load, such that words were identified more accurately under low load than high load. However, load differentially affected word identification in high- and low-predictability sentences depending on the level of sentence degradation. Under severe spectral degradation (four-channel vocoding), the effect of cognitive load on word identification was present for high-predictability sentences but not for low

A bio-inspired system for spatio-temporal recognition in static and video imagery

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

2007-04-01

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model

PubMed Central

Eum, Hyukmin; Yoon, Changyong; Lee, Heejin; Park, Mignon

2015-01-01

In this paper, we propose a new method for spotting and recognizing continuous human actions using a vision sensor. The method is comprised of depth-MHI-HOG (DMH), action modeling, action spotting, and recognition. First, to effectively separate the foreground from background, we propose a method called DMH. It includes a standard structure for segmenting images and extracting features by using depth information, MHI, and HOG. Second, action modeling is performed to model various actions using extracted features. The modeling of actions is performed by creating sequences of actions through k-means clustering; these sequences constitute HMM input. Third, a method of action spotting is proposed to filter meaningless actions from continuous actions and to identify precise start and end points of actions. By employing the spotter model, the proposed method improves action recognition performance. Finally, the proposed method recognizes actions based on start and end points. We evaluate recognition performance by employing the proposed method to obtain and compare probabilities by applying input sequences in action models and the spotter model. Through various experiments, we demonstrate that the proposed method is efficient for recognizing continuous human actions in real environments. PMID:25742172

Applying Suffix Rules to Organization Name Recognition

NASA Astrophysics Data System (ADS)

Inui, Takashi; Murakami, Koji; Hashimoto, Taiichi; Utsumi, Kazuo; Ishikawa, Masamichi

This paper presents a method for boosting the performance of the organization name recognition, which is a part of named entity recognition (NER). Although gazetteers (lists of the NEs) have been known as one of the effective features for supervised machine learning approaches on the NER task, the previous methods which have applied the gazetteers to the NER were very simple. The gazetteers have been used just for searching the exact matches between input text and NEs included in them. The proposed method generates regular expression rules from gazetteers, and, with these rules, it can realize a high-coverage searches based on looser matches between input text and NEs. To generate these rules, we focus on the two well-known characteristics of NE expressions; 1) most of NE expressions can be divided into two parts, class-reference part and instance-reference part, 2) for most of NE expressions the class-reference parts are located at the suffix position of them. A pattern mining algorithm runs on the set of NEs in the gazetteers, and some frequent word sequences from which NEs are constructed are found. Then, we employ only word sequences which have the class-reference part at the suffix position as suffix rules. Experimental results showed that our proposed method improved the performance of the organization name recognition, and achieved the 84.58 F-value for evaluation data.

Three RNA recognition motifs participate in RNA recognition and structural organization by the pro-apoptotic factor TIA-1

PubMed Central

Bauer, William J.; Heath, Jason; Jenkins, Jermaine L.; Kielkopf, Clara L.

2012-01-01

T-cell intracellular antigen-1 (TIA-1) regulates developmental and stress-responsive pathways through distinct activities at the levels of alternative pre-mRNA splicing and mRNA translation. The TIA-1 polypeptide contains three RNA recognition motifs (RRMs). The central RRM2 and C-terminal RRM3 associate with cellular mRNAs. The N-terminal RRM1 enhances interactions of a C-terminal Q-rich domain of TIA-1 with the U1-C splicing factor, despite linear separation of the domains in the TIA-1 sequence. Given the expanded functional repertoire of the RRM family, it was unknown whether TIA-1 RRM1 contributes to RNA binding as well as documented protein interactions. To address this question, we used isothermal titration calorimetry and small-angle X-ray scattering (SAXS) to dissect the roles of the TIA-1 RRMs in RNA recognition. Notably, the fas RNA exhibited two binding sites with indistinguishable affinities for TIA-1. Analyses of TIA-1 variants established that RRM1 was dispensable for binding AU-rich fas sites, yet all three RRMs were required to bind a polyU RNA with high affinity. SAXS analyses demonstrated a `V' shape for a TIA-1 construct comprising the three RRMs, and revealed that its dimensions became more compact in the RNA-bound state. The sequence-selective involvement of TIA-1 RRM1 in RNA recognition suggests a possible role for RNA sequences in regulating the distinct functions of TIA-1. Further implications for U1-C recruitment by the adjacent TIA-1 binding sites of the fas pre-mRNA and the bent TIA-1 shape, which organizes the N- and C-termini on the same side of the protein, are discussed. PMID:22154808

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.

A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views.

PubMed

Chaaraoui, Alexandros Andre; Flórez-Revuelta, Francisco

2014-01-01

This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled.

Short communication: evidence of HIV type 1 clade C env clones containing low V3 loop charge obtained from an AIDS patient in India that uses CXCR6 and CCR8 for entry in addition to CCR5.

PubMed

Gharu, Lavina; Ringe, Rajesh; Satyakumar, Anupindi; Patil, Ajit; Bhattacharya, Jayanta

2011-02-01

Abstract HIV-1 clade C is the major subtype circulating in India and preferentially uses CCR5 during the entire disease course. We have recently shown that env clones from an Indian patient; NARI-VB105 uses multiple coreceptors for entry and was presented with an unusual V3 loop sequence giving rise to high net V3 loop positive charges. Here we show that env clones belonging to subtype C obtained from an AIDS patient, NARI-VB52, use CXCR6 and CCR8 in addition to CCR5 for entry. However, unlike the NARI-105 patient, the env clones contained a low V3 loop net charge of +3 with a conserved GPGQ motif typical of CCR5 using subtype C strains, indicating that residues outside the V3 loop contributed to extended coreceptor use in this particular patient.

Recognition intent and visual word recognition.

PubMed

Wang, Man-Ying; Ching, Chi-Le

2009-03-01

This study adopted a change detection task to investigate whether and how recognition intent affects the construction of orthographic representation in visual word recognition. Chinese readers (Experiment 1-1) and nonreaders (Experiment 1-2) detected color changes in radical components of Chinese characters. Explicit recognition demand was imposed in Experiment 2 by an additional recognition task. When the recognition was implicit, a bias favoring the radical location informative of character identity was found in Chinese readers (Experiment 1-1), but not nonreaders (Experiment 1-2). With explicit recognition demands, the effect of radical location interacted with radical function and word frequency (Experiment 2). An estimate of identification performance under implicit recognition was derived in Experiment 3. These findings reflect the joint influence of recognition intent and orthographic regularity in shaping readers' orthographic representation. The implication for the role of visual attention in word recognition was also discussed.

Scalable Kernel Methods and Algorithms for General Sequence Analysis

ERIC Educational Resources Information Center

Kuksa, Pavel

2011-01-01

Analysis of large-scale sequential data has become an important task in machine learning and pattern recognition, inspired in part by numerous scientific and technological applications such as the document and text classification or the analysis of biological sequences. However, current computational methods for sequence comparison still lack…

Genetic determinants of mate recognition in Brachionus manjavacas (Rotifera).

PubMed

Snell, Terry W; Shearer, Tonya L; Smith, Hilary A; Kubanek, Julia; Gribble, Kristin E; Welch, David B Mark

2009-09-09

Mate choice is of central importance to most animals, influencing population structure, speciation, and ultimately the survival of a species. Mating behavior of male brachionid rotifers is triggered by the product of a chemosensory gene, a glycoprotein on the body surface of females called the mate recognition pheromone. The mate recognition pheromone has been biochemically characterized, but little was known about the gene(s). We describe the isolation and characterization of the mate recognition pheromone gene through protein purification, N-terminal amino acid sequence determination, identification of the mate recognition pheromone gene from a cDNA library, sequencing, and RNAi knockdown to confirm the functional role of the mate recognition pheromone gene in rotifer mating. A 29 kD protein capable of eliciting rotifer male circling was isolated by high-performance liquid chromatography. Two transcript types containing the N-terminal sequence were identified in a cDNA library; further characterization by screening a genomic library and by polymerase chain reaction revealed two genes belonging to each type. Each gene begins with a signal peptide region followed by nearly perfect repeats of an 87 to 92 codon motif with no codons between repeats and the final motif prematurely terminated by the stop codon. The two Type A genes contain four and seven repeats and the two Type B genes contain three and five repeats, respectively. Only the Type B gene with three repeats encodes a peptide with a molecular weight of 29 kD. Each repeat of the Type B gene products contains three asparagines as potential sites for N-glycosylation; there are no asparagines in the Type A genes. RNAi with Type A double-stranded RNA did not result in less circling than in the phosphate-buffered saline control, but transfection with Type B double-stranded RNA significantly reduced male circling by 17%. The very low divergence between repeat units, even at synonymous positions, suggests that the

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

NASA Astrophysics Data System (ADS)

Liu, Jun; Wang, Gang; Duan, Ling-Yu; Abdiyeva, Kamila; Kot, Alex C.

2018-04-01

Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition.

The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

PubMed

Bahlmann, Claus; Burkhardt, Hans

2004-03-01

In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

Sequence conservation and antibody cross-recognition of clade B human immunodeficiency virus (HIV) type 1 Tat protein in HIV-1-infected Italians, Ugandans, and South Africans.

PubMed

Buttò, Stefano; Fiorelli, Valeria; Tripiciano, Antonella; Ruiz-Alvarez, Maria J; Scoglio, Arianna; Ensoli, Fabrizio; Ciccozzi, Massimo; Collacchi, Barbara; Sabbatucci, Michela; Cafaro, Aurelio; Guzmán, Carlos A; Borsetti, Alessandra; Caputo, Antonella; Vardas, Eftyhia; Colvin, Mark; Lukwiya, Matthew; Rezza, Giovanni; Ensoli, Barbara

2003-10-15

We determined immune cross-recognition and the degree of Tat conservation in patients infected by local human immunodeficiency virus (HIV) type 1 strains. The data indicated a similar prevalence of total and epitope-specific anti-Tat IgG in 578 serum samples from HIV-infected Italian (n=302), Ugandan (n=139), and South African (n=137) subjects, using the same B clade Tat protein that is being used in vaccine trials. In particular, anti-Tat antibodies were detected in 13.2%, 10.8%, and 13.9% of HIV-1-infected individuals from Italy, Uganda, and South Africa, respectively. Sequence analysis results indicated a high similarity of Tat from the different circulating viruses with BH-10 Tat, particularly in the 1-58 amino acid region, which contains most of the immunogenic epitopes. These data indicate an effective cross-recognition of a B-clade laboratory strain-derived Tat protein vaccine by individuals infected with different local viruses, owing to the high similarity of Tat epitopes.

PHYSICAL MODEL FOR RECOGNITION TUNNELING

PubMed Central

Krstić, Predrag; Ashcroft, Brian; Lindsay, Stuart

2015-01-01

Recognition tunneling (RT) identifies target molecules trapped between tunneling electrodes functionalized with recognition molecules that serve as specific chemical linkages between the metal electrodes and the trapped target molecule. Possible applications include single molecule DNA and protein sequencing. This paper addresses several fundamental aspects of RT by multiscale theory, applying both all-atom and coarse-grained DNA models: (1) We show that the magnitude of the observed currents are consistent with the results of non-equilibrium Green's function calculations carried out on a solvated all-atom model. (2) Brownian fluctuations in hydrogen bond-lengths lead to current spikes that are similar to what is observed experimentally. (3) The frequency characteristics of these fluctuations can be used to identify the trapped molecules with a machine-learning algorithm, giving a theoretical underpinning to this new method of identifying single molecule signals. PMID:25650375

Case-Based Plan Recognition Using Action Sequence Graphs

DTIC Science & Technology

2014-10-01

resized as necessary. Similarly, trace- based reasoning (Zarka et al., 2013) and episode -based reasoning (Sánchez-Marré, 2005) store fixed-length...is a goal state of Π, where satisfies has the same semantics as originally laid out in Ghallab, Nau & Traverso (2004). Action 0 is ...Although there are syntactic similarities between planning encoding graphs and action sequence graphs, important semantic differences exist because the

Sequence-dependent DNA deformability studied using molecular dynamics simulations.

PubMed

Fujii, Satoshi; Kono, Hidetoshi; Takenaka, Shigeori; Go, Nobuhiro; Sarai, Akinori

2007-01-01

Proteins recognize specific DNA sequences not only through direct contact between amino acids and bases, but also indirectly based on the sequence-dependent conformation and deformability of the DNA (indirect readout). We used molecular dynamics simulations to analyze the sequence-dependent DNA conformations of all 136 possible tetrameric sequences sandwiched between CGCG sequences. The deformability of dimeric steps obtained by the simulations is consistent with that by the crystal structures. The simulation results further showed that the conformation and deformability of the tetramers can highly depend on the flanking base pairs. The conformations of xATx tetramers show the most rigidity and are not affected by the flanking base pairs and the xYRx show by contrast the greatest flexibility and change their conformations depending on the base pairs at both ends, suggesting tetramers with the same central dimer can show different deformabilities. These results suggest that analysis of dimeric steps alone may overlook some conformational features of DNA and provide insight into the mechanism of indirect readout during protein-DNA recognition. Moreover, the sequence dependence of DNA conformation and deformability may be used to estimate the contribution of indirect readout to the specificity of protein-DNA recognition as well as nucleosome positioning and large-scale behavior of nucleic acids.

CD94-NKG2A recognition of human leukocyte antigen (HLA)-E bound to an HLA class I leader sequence.

PubMed

Petrie, Emma J; Clements, Craig S; Lin, Jie; Sullivan, Lucy C; Johnson, Darryl; Huyton, Trevor; Heroux, Annie; Hoare, Hilary L; Beddoe, Travis; Reid, Hugh H; Wilce, Matthew C J; Brooks, Andrew G; Rossjohn, Jamie

2008-03-17

The recognition of human leukocyte antigen (HLA)-E by the heterodimeric CD94-NKG2 natural killer (NK) receptor family is a central innate mechanism by which NK cells monitor the expression of other HLA molecules, yet the structural basis of this highly specific interaction is unclear. Here, we describe the crystal structure of CD94-NKG2A in complex with HLA-E bound to a peptide derived from the leader sequence of HLA-G. The CD94 subunit dominated the interaction with HLA-E, whereas the NKG2A subunit was more peripheral to the interface. Moreover, the invariant CD94 subunit dominated the peptide-mediated contacts, albeit with poor surface and chemical complementarity. This unusual binding mode was consistent with mutagenesis data at the CD94-NKG2A-HLA-E interface. There were few conformational changes in either CD94-NKG2A or HLA-E upon ligation, and such a "lock and key" interaction is typical of innate receptor-ligand interactions. Nevertheless, the structure also provided insight into how this interaction can be modulated by subtle changes in the peptide ligand or by the pairing of CD94 with other members of the NKG2 family. Differences in the docking strategies used by the NKG2D and CD94-NKG2A receptors provided a basis for understanding the promiscuous nature of ligand recognition by NKG2D compared with the fidelity of the CD94-NKG2 receptors.

Stable Odor Recognition by a neuro-adaptive Electronic Nose

PubMed Central

Martinelli, Eugenio; Magna, Gabriele; Polese, Davide; Vergara, Alexander; Schild, Detlev; Di Natale, Corrado

2015-01-01

Sensitivity, selectivity and stability are decisive properties of sensors. In chemical gas sensors odor recognition can be severely compromised by poor signal stability, particularly in real life applications where the sensors are exposed to unpredictable sequences of odors under changing external conditions. Although olfactory receptor neurons in the nose face similar stimulus sequences under likewise changing conditions, odor recognition is very stable and odorants can be reliably identified independently from past odor perception. We postulate that appropriate pre-processing of the output signals of chemical sensors substantially contributes to the stability of odor recognition, in spite of marked sensor instabilities. To investigate this hypothesis, we use an adaptive, unsupervised neural network inspired by the glomerular input circuitry of the olfactory bulb. Essentially the model reduces the effect of the sensors’ instabilities by utilizing them via an adaptive multicompartment feed-forward inhibition. We collected and analyzed responses of a 4 × 4 gas sensor array to a number of volatile compounds applied over a period of 18 months, whereby every sensor was sampled episodically. The network conferred excellent stability to the compounds’ identification and was clearly superior over standard classifiers, even when one of the sensors exhibited random fluctuations or stopped working at all. PMID:26043043

A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.

Intonation and dialog context as constraints for speech recognition.

PubMed

Taylor, P; King, S; Isard, S; Wright, H

1998-01-01

This paper describes a way of using intonation and dialog context to improve the performance of an automatic speech recognition (ASR) system. Our experiments were run on the DCIEM Maptask corpus, a corpus of spontaneous task-oriented dialog speech. This corpus has been tagged according to a dialog analysis scheme that assigns each utterance to one of 12 "move types," such as "acknowledge," "query-yes/no" or "instruct." Most ASR systems use a bigram language model to constrain the possible sequences of words that might be recognized. Here we use a separate bigram language model for each move type. We show that when the "correct" move-specific language model is used for each utterance in the test set, the word error rate of the recognizer drops. Of course when the recognizer is run on previously unseen data, it cannot know in advance what move type the speaker has just produced. To determine the move type we use an intonation model combined with a dialog model that puts constraints on possible sequences of move types, as well as the speech recognizer likelihoods for the different move-specific models. In the full recognition system, the combination of automatic move type recognition with the move specific language models reduces the overall word error rate by a small but significant amount when compared with a baseline system that does not take intonation or dialog acts into account. Interestingly, the word error improvement is restricted to "initiating" move types, where word recognition is important. In "response" move types, where the important information is conveyed by the move type itself--for example, positive versus negative response--there is no word error improvement, but recognition of the response types themselves is good. The paper discusses the intonation model, the language models, and the dialog model in detail and describes the architecture in which they are combined.

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

PubMed Central

2017-01-01

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. PMID:28817094

Vision-based posture recognition using an ensemble classifier and a vote filter

NASA Astrophysics Data System (ADS)

Ji, Peng; Wu, Changcheng; Xu, Xiaonong; Song, Aiguo; Li, Huijun

2016-10-01

Posture recognition is a very important Human-Robot Interaction (HRI) way. To segment effective posture from an image, we propose an improved region grow algorithm which combining with the Single Gauss Color Model. The experiment shows that the improved region grow algorithm can get the complete and accurate posture than traditional Single Gauss Model and region grow algorithm, and it can eliminate the similar region from the background at the same time. In the posture recognition part, and in order to improve the recognition rate, we propose a CNN ensemble classifier, and in order to reduce the misjudgments during a continuous gesture control, a vote filter is proposed and applied to the sequence of recognition results. Comparing with CNN classifier, the CNN ensemble classifier we proposed can yield a 96.27% recognition rate, which is better than that of CNN classifier, and the proposed vote filter can improve the recognition result and reduce the misjudgments during the consecutive gesture switch.

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition.

PubMed

Choi, Hyo-Rim; Kim, TaeYong

2017-08-17

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user's location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.

Method and apparatus for obtaining complete speech signals for speech recognition applications

NASA Technical Reports Server (NTRS)

Abrash, Victor (Inventor); Cesari, Federico (Inventor); Franco, Horacio (Inventor); George, Christopher (Inventor); Zheng, Jing (Inventor)

2009-01-01

The present invention relates to a method and apparatus for obtaining complete speech signals for speech recognition applications. In one embodiment, the method continuously records an audio stream comprising a sequence of frames to a circular buffer. When a user command to commence or terminate speech recognition is received, the method obtains a number of frames of the audio stream occurring before or after the user command in order to identify an augmented audio signal for speech recognition processing. In further embodiments, the method analyzes the augmented audio signal in order to locate starting and ending speech endpoints that bound at least a portion of speech to be processed for recognition. At least one of the speech endpoints is located using a Hidden Markov Model.

Genetic determinants of mate recognition in Brachionus manjavacas (Rotifera)

PubMed Central

Snell, Terry W; Shearer, Tonya L; Smith, Hilary A; Kubanek, Julia; Gribble, Kristin E; Welch, David B Mark

2009-01-01

Background Mate choice is of central importance to most animals, influencing population structure, speciation, and ultimately the survival of a species. Mating behavior of male brachionid rotifers is triggered by the product of a chemosensory gene, a glycoprotein on the body surface of females called the mate recognition pheromone. The mate recognition pheromone has been biochemically characterized, but little was known about the gene(s). We describe the isolation and characterization of the mate recognition pheromone gene through protein purification, N-terminal amino acid sequence determination, identification of the mate recognition pheromone gene from a cDNA library, sequencing, and RNAi knockdown to confirm the functional role of the mate recognition pheromone gene in rotifer mating. Results A 29 kD protein capable of eliciting rotifer male circling was isolated by high-performance liquid chromatography. Two transcript types containing the N-terminal sequence were identified in a cDNA library; further characterization by screening a genomic library and by polymerase chain reaction revealed two genes belonging to each type. Each gene begins with a signal peptide region followed by nearly perfect repeats of an 87 to 92 codon motif with no codons between repeats and the final motif prematurely terminated by the stop codon. The two Type A genes contain four and seven repeats and the two Type B genes contain three and five repeats, respectively. Only the Type B gene with three repeats encodes a peptide with a molecular weight of 29 kD. Each repeat of the Type B gene products contains three asparagines as potential sites for N-glycosylation; there are no asparagines in the Type A genes. RNAi with Type A double-stranded RNA did not result in less circling than in the phosphate-buffered saline control, but transfection with Type B double-stranded RNA significantly reduced male circling by 17%. The very low divergence between repeat units, even at synonymous positions

Kilo-sequencing: an ordered strategy for rapid DNA sequence data acquisition.

PubMed Central

Barnes, W M; Bevan, M

1983-01-01

A strategy for rapid DNA sequence acquisition in an ordered, nonrandom manner, while retaining all of the conveniences of the dideoxy method with M13 transducing phage DNA template, is described. Target DNA 3 to 14 kb in size can be stably carried by our M13 vectors. Suitable targets are stretches of DNA which lack an enzyme recognition site which is unique on our cloning vectors and adjacent to the sequencing primer; current sites that are so useful when lacking are Pst, Xba, HindIII, BglII, EcoRI. By an in vitro procedure, we cut RF DNA once randomly and once specifically, to create thousands of deletions which start at the unique restriction site adjacent to the dideoxy sequencing primer and extend various distances across the target DNA. Phage carrying a desired size of deletions, whose DNA as template will give rise to DNA sequence data in a desired location along the target DNA, may be purified by electrophoresis alive on agarose gels. Phage running in the same location on the agarose gel thus conveniently give rise to nucleotide sequence data from the same kilobase of target DNA. Images PMID:6298723

Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

Dissecting ant recognition systems in the age of genomics.

PubMed

Tsutsui, Neil D

2013-01-01

Hamilton is probably best known for his seminal work demonstrating the role of kin selection in social evolution. His work made it clear that, for individuals to direct their altruistic behaviours towards appropriate recipients (kin), mechanisms must exist for kin recognition. In the social insects, colonies are typically comprised of kin, and colony recognition cues are used as proxies for kinship cues. Recent years have brought rapid advances in our understanding of the genetic and molecular mechanisms that are used for this process. Here, I review some of the most notable advances, particularly the contributions from recent ant genome sequences and molecular biology.

Static hand gesture recognition from a video

NASA Astrophysics Data System (ADS)

Rokade, Rajeshree S.; Doye, Dharmpal

2011-10-01

A sign language (also signed language) is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns to convey meaning- "simultaneously combining hand shapes, orientation and movement of the hands". Sign languages commonly develop in deaf communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. In this paper, we proposed a novel system for recognition of static hand gestures from a video, based on Kohonen neural network. We proposed algorithm to separate out key frames, which include correct gestures from a video sequence. We segment, hand images from complex and non uniform background. Features are extracted by applying Kohonen on key frames and recognition is done.

Human gait recognition by pyramid of HOG feature on silhouette images

NASA Astrophysics Data System (ADS)

Yang, Guang; Yin, Yafeng; Park, Jeanrok; Man, Hong

2013-03-01

As a uncommon biometric modality, human gait recognition has a great advantage of identify people at a distance without high resolution images. It has attracted much attention in recent years, especially in the fields of computer vision and remote sensing. In this paper, we propose a human gait recognition framework that consists of a reliable background subtraction method followed by the pyramid of Histogram of Gradient (pHOG) feature extraction on the silhouette image, and a Hidden Markov Model (HMM) based classifier. Through background subtraction, the silhouette of human gait in each frame is extracted and normalized from the raw video sequence. After removing the shadow and noise in each region of interest (ROI), pHOG feature is computed on the silhouettes images. Then the pHOG features of each gait class will be used to train a corresponding HMM. In the test stage, pHOG feature will be extracted from each test sequence and used to calculate the posterior probability toward each trained HMM model. Experimental results on the CASIA Gait Dataset B1 demonstrate that with our proposed method can achieve very competitive recognition rate.

Programmable RNA recognition and cleavage by CRISPR/Cas9.

PubMed

O'Connell, Mitchell R; Oakes, Benjamin L; Sternberg, Samuel H; East-Seletsky, Alexandra; Kaplan, Matias; Doudna, Jennifer A

2014-12-11

The CRISPR-associated protein Cas9 is an RNA-guided DNA endonuclease that uses RNA-DNA complementarity to identify target sites for sequence-specific double-stranded DNA (dsDNA) cleavage. In its native context, Cas9 acts on DNA substrates exclusively because both binding and catalysis require recognition of a short DNA sequence, known as the protospacer adjacent motif (PAM), next to and on the strand opposite the twenty-nucleotide target site in dsDNA. Cas9 has proven to be a versatile tool for genome engineering and gene regulation in a large range of prokaryotic and eukaryotic cell types, and in whole organisms, but it has been thought to be incapable of targeting RNA. Here we show that Cas9 binds with high affinity to single-stranded RNA (ssRNA) targets matching the Cas9-associated guide RNA sequence when the PAM is presented in trans as a separate DNA oligonucleotide. Furthermore, PAM-presenting oligonucleotides (PAMmers) stimulate site-specific endonucleolytic cleavage of ssRNA targets, similar to PAM-mediated stimulation of Cas9-catalysed DNA cleavage. Using specially designed PAMmers, Cas9 can be specifically directed to bind or cut RNA targets while avoiding corresponding DNA sequences, and we demonstrate that this strategy enables the isolation of a specific endogenous messenger RNA from cells. These results reveal a fundamental connection between PAM binding and substrate selection by Cas9, and highlight the utility of Cas9 for programmable transcript recognition without the need for tags.

Programmable RNA recognition and cleavage by CRISPR/Cas9

PubMed Central

O’Connell, Mitchell R.; Oakes, Benjamin L.; Sternberg, Samuel H.; East-Seletsky, Alexandra; Kaplan, Matias; Doudna, Jennifer A.

2014-01-01

The CRISPR-associated protein Cas9 is an RNA-guided DNA endonuclease that uses RNA:DNA complementarity to identify target sites for sequence-specific doublestranded DNA (dsDNA) cleavage1-5. In its native context, Cas9 acts on DNA substrates exclusively because both binding and catalysis require recognition of a short DNA sequence, the protospacer adjacent motif (PAM), next to and on the strand opposite the 20-nucleotide target site in dsDNA4-7. Cas9 has proven to be a versatile tool for genome engineering and gene regulation in many cell types and organisms8, but it has been thought to be incapable of targeting RNA5. Here we show that Cas9 binds with high affinity to single-stranded RNA (ssRNA) targets matching the Cas9-associated guide RNA sequence when the PAM is presented in trans as a separate DNA oligonucleotide. Furthermore, PAM-presenting oligonucleotides (PAMmers) stimulate site-specific endonucleolytic cleavage of ssRNA targets, similar to PAM-mediated stimulation of Cas9-catalyzed DNA cleavage7. Using specially designed PAMmers, Cas9 can be specifically directed to bind or cut RNA targets while avoiding corresponding DNA sequences, and we demonstrate that this strategy enables the isolation of a specific endogenous mRNA from cells. These results reveal a fundamental connection between PAM binding and substrate selection by Cas9, and highlight the utility of Cas9 for programmable and tagless transcript recognition. PMID:25274302

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

PubMed Central

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

PubMed

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

CD94-NKG2A recognition of human leukocyte antigen (HLA)-E bound to an HLA class I leader sequence

PubMed Central

Petrie, Emma J.; Clements, Craig S.; Lin, Jie; Sullivan, Lucy C.; Johnson, Darryl; Huyton, Trevor; Heroux, Annie; Hoare, Hilary L.; Beddoe, Travis; Reid, Hugh H.; Wilce, Matthew C.J.; Brooks, Andrew G.; Rossjohn, Jamie

2008-01-01

The recognition of human leukocyte antigen (HLA)-E by the heterodimeric CD94-NKG2 natural killer (NK) receptor family is a central innate mechanism by which NK cells monitor the expression of other HLA molecules, yet the structural basis of this highly specific interaction is unclear. Here, we describe the crystal structure of CD94-NKG2A in complex with HLA-E bound to a peptide derived from the leader sequence of HLA-G. The CD94 subunit dominated the interaction with HLA-E, whereas the NKG2A subunit was more peripheral to the interface. Moreover, the invariant CD94 subunit dominated the peptide-mediated contacts, albeit with poor surface and chemical complementarity. This unusual binding mode was consistent with mutagenesis data at the CD94-NKG2A–HLA-E interface. There were few conformational changes in either CD94-NKG2A or HLA-E upon ligation, and such a “lock and key” interaction is typical of innate receptor–ligand interactions. Nevertheless, the structure also provided insight into how this interaction can be modulated by subtle changes in the peptide ligand or by the pairing of CD94 with other members of the NKG2 family. Differences in the docking strategies used by the NKG2D and CD94-NKG2A receptors provided a basis for understanding the promiscuous nature of ligand recognition by NKG2D compared with the fidelity of the CD94-NKG2 receptors. PMID:18332182

Orchestration of Molecular Information through Higher Order Chemical Recognition

NASA Astrophysics Data System (ADS)

Frezza, Brian M.

Broadly defined, higher order chemical recognition is the process whereby discrete chemical building blocks capable of specifically binding to cognate moieties are covalently linked into oligomeric chains. These chains, or sequences, are then able to recognize and bind to their cognate sequences with a high degree of cooperativity. Principally speaking, DNA and RNA are the most readily obtained examples of this chemical phenomenon, and function via Watson-Crick cognate pairing: guanine pairs with cytosine and adenine with thymine (DNA) or uracil (RNA), in an anti-parallel manner. While the theoretical principles, techniques, and equations derived herein apply generally to any higher-order chemical recognition system, in practice we utilize DNA oligomers as a model-building material to experimentally investigate and validate our hypotheses. Historically, general purpose information processing has been a task limited to semiconductor electronics. Molecular computing on the other hand has been limited to ad hoc approaches designed to solve highly specific and unique computation problems, often involving components or techniques that cannot be applied generally in a manner suitable for precise and predictable engineering. Herein, we provide a fundamental framework for harnessing high-order recognition in a modular and programmable fashion to synthesize molecular information process networks of arbitrary construction and complexity. This document provides a solid foundation for routinely embedding computational capability into chemical and biological systems where semiconductor electronics are unsuitable for practical application.

8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Code of Federal Regulations, 2010 CFR

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

The association between imitation recognition and socio-communicative competencies in chimpanzees (Pan troglodytes).

PubMed

Pope, Sarah M; Russell, Jamie L; Hopkins, William D

2015-01-01

Imitation recognition provides a viable platform from which advanced social cognitive skills may develop. Despite evidence that non-human primates are capable of imitation recognition, how this ability is related to social cognitive skills is unknown. In this study, we compared imitation recognition performance, as indicated by the production of testing behaviors, with performance on a series of tasks that assess social and physical cognition in 49 chimpanzees. In the initial analyses, we found that males were more responsive than females to being imitated and engaged in significantly greater behavior repetitions and testing sequences. We also found that subjects who consistently recognized being imitated performed better on social but not physical cognitive tasks, as measured by the Primate Cognitive Test Battery. These findings suggest that the neural constructs underlying imitation recognition are likely associated with or among those underlying more general socio-communicative abilities in chimpanzees. Implications regarding how imitation recognition may facilitate other social cognitive processes, such as mirror self-recognition, are discussed.

The association between imitation recognition and socio-communicative competencies in chimpanzees (Pan troglodytes)

PubMed Central

Pope, Sarah M.; Russell, Jamie L.; Hopkins, William D.

2015-01-01

Imitation recognition provides a viable platform from which advanced social cognitive skills may develop. Despite evidence that non-human primates are capable of imitation recognition, how this ability is related to social cognitive skills is unknown. In this study, we compared imitation recognition performance, as indicated by the production of testing behaviors, with performance on a series of tasks that assess social and physical cognition in 49 chimpanzees. In the initial analyses, we found that males were more responsive than females to being imitated and engaged in significantly greater behavior repetitions and testing sequences. We also found that subjects who consistently recognized being imitated performed better on social but not physical cognitive tasks, as measured by the Primate Cognitive Test Battery. These findings suggest that the neural constructs underlying imitation recognition are likely associated with or among those underlying more general socio-communicative abilities in chimpanzees. Implications regarding how imitation recognition may facilitate other social cognitive processes, such as mirror self-recognition, are discussed. PMID:25767454

Substrate recognition by ribonucleoprotein ribonuclease MRP

PubMed Central

Esakova, Olga; Perederina, Anna; Quan, Chao; Berezin, Igor; Krasilnikov, Andrey S.

2011-01-01

The ribonucleoprotein complex ribonuclease (RNase) MRP is a site-specific endoribonuclease essential for the survival of the eukaryotic cell. RNase MRP closely resembles RNase P (a universal endoribonuclease responsible for the maturation of the 5′ ends of tRNA) but recognizes distinct substrates including pre-rRNA and mRNA. Here we report the results of an in vitro selection of Saccharomyces cerevisiae RNase MRP substrates starting from a pool of random sequences. The results indicate that RNase MRP cleaves single-stranded RNA and is sensitive to sequences in the immediate vicinity of the cleavage site requiring a cytosine at the position +4 relative to the cleavage site. Structural implications of the differences in substrate recognition by RNases P and MRP are discussed. PMID:21173200

Substrate recognition by ribonucleoprotein ribonuclease MRP.

PubMed

Esakova, Olga; Perederina, Anna; Quan, Chao; Berezin, Igor; Krasilnikov, Andrey S

2011-02-01

The ribonucleoprotein complex ribonuclease (RNase) MRP is a site-specific endoribonuclease essential for the survival of the eukaryotic cell. RNase MRP closely resembles RNase P (a universal endoribonuclease responsible for the maturation of the 5' ends of tRNA) but recognizes distinct substrates including pre-rRNA and mRNA. Here we report the results of an in vitro selection of Saccharomyces cerevisiae RNase MRP substrates starting from a pool of random sequences. The results indicate that RNase MRP cleaves single-stranded RNA and is sensitive to sequences in the immediate vicinity of the cleavage site requiring a cytosine at the position +4 relative to the cleavage site. Structural implications of the differences in substrate recognition by RNases P and MRP are discussed.

A split recognition mode combined with cascade signal amplification strategy for highly specific, sensitive detection of microRNA.

PubMed

Wang, Rui; Wang, Lei; Zhao, Haiyan; Jiang, Wei

2016-12-15

MicroRNAs (miRNAs) are vital for many biological processes and have been regarded as cancer biomarkers. Specific and sensitive detection of miRNAs is essential for cancer diagnosis and therapy. Herein, a split recognition mode combined with cascade signal amplification strategy is developed for highly specific and sensitive detection of miRNA. The split recognition mode possesses two specific recognition processes, which are based on toehold-mediated strand displacement reaction (TSDR) and direct hybridization reaction. Two recognition probes, hairpin probe (HP) with overhanging toehold domain and assistant probe (AP), are specially designed. Firstly, the toehold domain of HP and AP recognize part of miRNA simultaneously, accompanied with TSDR to unfold the HP and form the stable DNA Y-shaped junction structure (YJS). Then, the AP in YJS can further act as primer to initiate strand displacement amplification, releasing numerous trigger sequences. Finally, the trigger sequences hybridize with padlock DNA to initiate circular rolling circle amplification and generate enhanced fluorescence responses. In this strategy, the dual recognition effect of split recognition mode guarantees the excellent selectivity to discriminate let-7b from high-homology sequences. Furthermore, the high amplification efficiency of cascade signal amplification guarantees a high sensitivity with the detection limit of 3.2 pM and the concentration of let-7b in total RNA sample extracted from Hela cells is determined. These results indicate our strategy will be a promising miRNA detection strategy in clinical diagnosis and disease treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

Impaired processing of self-face recognition in anorexia nervosa.

PubMed

Hirot, France; Lesage, Marine; Pedron, Lya; Meyer, Isabelle; Thomas, Pierre; Cottencin, Olivier; Guardia, Dewi

2016-03-01

Body image disturbances and massive weight loss are major clinical symptoms of anorexia nervosa (AN). The aim of the present study was to examine the influence of body changes and eating attitudes on self-face recognition ability in AN. Twenty-seven subjects suffering from AN and 27 control participants performed a self-face recognition task (SFRT). During the task, digital morphs between their own face and a gender-matched unfamiliar face were presented in a random sequence. Participants' self-face recognition failures, cognitive flexibility, body concern and eating habits were assessed with the Self-Face Recognition Questionnaire (SFRQ), Trail Making Test (TMT), Body Shape Questionnaire (BSQ) and Eating Disorder Inventory-2 (EDI-2), respectively. Subjects suffering from AN exhibited significantly greater difficulties than control participants in identifying their own face (p = 0.028). No significant difference was observed between the two groups for TMT (all p > 0.1, non-significant). Regarding predictors of self-face recognition skills, there was a negative correlation between SFRT and body mass index (p = 0.01) and a positive correlation between SFRQ and EDI-2 (p < 0.001) or BSQ (p < 0.001). Among factors involved, nutritional status and intensity of eating disorders could play a part in impaired self-face recognition.

Event-Related Potential Correlates of Declarative and Non-Declarative Sequence Knowledge

ERIC Educational Resources Information Center

Ferdinand, Nicola K.; Runger, Dennis; Frensch, Peter A.; Mecklinger, Axel

2010-01-01

The goal of the present study was to demonstrate that declarative and non-declarative knowledge acquired in an incidental sequence learning task contributes differentially to memory retrieval and leads to dissociable ERP signatures in a recognition memory task. For this purpose, participants performed a sequence learning task and were classified…

Optical character recognition of handwritten Arabic using hidden Markov models

NASA Astrophysics Data System (ADS)

Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

2011-04-01

The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

Optical character recognition of handwritten Arabic using hidden Markov models

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

Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.

2011-01-01

The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language ismore » initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.« less

The Influence of Phonotactic Probability on Word Recognition in Toddlers

ERIC Educational Resources Information Center

MacRoy-Higgins, Michelle; Shafer, Valerie L.; Schwartz, Richard G.; Marton, Klara

2014-01-01

This study examined the influence of phonotactic probability on word recognition in English-speaking toddlers. Typically developing toddlers completed a preferential looking paradigm using familiar words, which consisted of either high or low phonotactic probability sound sequences. The participants' looking behavior was recorded in response to…

Functional specificity of a Hox protein mediated by the recognition of minor groove structure.

PubMed

Joshi, Rohit; Passner, Jonathan M; Rohs, Remo; Jain, Rinku; Sosinsky, Alona; Crickmore, Michael A; Jacob, Vinitha; Aggarwal, Aneel K; Honig, Barry; Mann, Richard S

2007-11-02

The recognition of specific DNA-binding sites by transcription factors is a critical yet poorly understood step in the control of gene expression. Members of the Hox family of transcription factors bind DNA by making nearly identical major groove contacts via the recognition helices of their homeodomains. In vivo specificity, however, often depends on extended and unstructured regions that link Hox homeodomains to a DNA-bound cofactor, Extradenticle (Exd). Using a combination of structure determination, computational analysis, and in vitro and in vivo assays, we show that Hox proteins recognize specific Hox-Exd binding sites via residues located in these extended regions that insert into the minor groove but only when presented with the correct DNA sequence. Our results suggest that these residues, which are conserved in a paralog-specific manner, confer specificity by recognizing a sequence-dependent DNA structure instead of directly reading a specific DNA sequence.

Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

PubMed

Ming, Yue; Wang, Guangchao; Fan, Chunxiao

2015-01-01

With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition.

Video-based face recognition via convolutional neural networks

NASA Astrophysics Data System (ADS)

Bao, Tianlong; Ding, Chunhui; Karmoshi, Saleem; Zhu, Ming

2017-06-01

Face recognition has been widely studied recently while video-based face recognition still remains a challenging task because of the low quality and large intra-class variation of video captured face images. In this paper, we focus on two scenarios of video-based face recognition: 1)Still-to-Video(S2V) face recognition, i.e., querying a still face image against a gallery of video sequences; 2)Video-to-Still(V2S) face recognition, in contrast to S2V scenario. A novel method was proposed in this paper to transfer still and video face images to an Euclidean space by a carefully designed convolutional neural network, then Euclidean metrics are used to measure the distance between still and video images. Identities of still and video images that group as pairs are used as supervision. In the training stage, a joint loss function that measures the Euclidean distance between the predicted features of training pairs and expanding vectors of still images is optimized to minimize the intra-class variation while the inter-class variation is guaranteed due to the large margin of still images. Transferred features are finally learned via the designed convolutional neural network. Experiments are performed on COX face dataset. Experimental results show that our method achieves reliable performance compared with other state-of-the-art methods.

Synthesis, Physicochemical Properties, and Hydrogen Bonding of 4(5)-Substituted 1-H-Imidazole-2-carboxamide, A Potential Universal Reader for DNA Sequencing by Recognition Tunneling

PubMed Central

Liang, Feng; Li, Shengqing

2012-01-01

We have developed a chemical reagent that recognizes all naturally occurring DNA bases, a so called universal reader, for DNA sequencing by recognition tunnelling in nanopores.[1] The primary requirements for this type of molecules are the ability to form non-covalent complexes with individual DNA bases and to generate recognizable electronic signatures under an electrical bias. 1-H-imidazole-2-carboxamide was designed as such a recognition moiety to interact with the DNA bases through hydrogen bonding. In the present study, we first furnished a synthetic route to 1-H-imidazole-2-carboxamide containing a short ω-functionalized alkyl chain at its 4(5) position for its attachment to metal and carbon electrodes. The acid dissociation constants of the imidazole-2-carboxamide were then determined by UV spectroscopy. The data show that the 1-H-imidazole-2-carboxamide exists in a neutral form between pH 6–10. Density functional theory (DFT) and NMR studies indicate that the imidazole ring exists in prototropic tautomers. We propose an intramolecular mechanism for tautomerization of 1-H-imidazole-2-carboxamide. In addition, the imidazole-2-carboxamide can self-associate to form hydrogen bonded dimers. NMR titration found that naturally occurring nucleosides interacted with 1-H-imidazole-2-carboxamide through hydrogen bonding in a tendency of dG>dC≫dT> dA. These studies are indispensable to assisting us in understanding the molecular recognition that takes place in the nanopore where routinely used analytical tools such as NMR and FTIR cannot be conveniently applied. PMID:22461259

Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation

PubMed Central

Xu, Xin; Tang, Jinshan; Zhang, Xiaolong; Liu, Xiaoming; Zhang, Hong; Qiu, Yimin

2013-01-01

With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activities, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation of the performance of human activity recognition. PMID:23353144

Recognition of platinum-DNA adducts by HMGB1a.

PubMed

Ramachandran, Srinivas; Temple, Brenda; Alexandrova, Anastassia N; Chaney, Stephen G; Dokholyan, Nikolay V

2012-09-25

Cisplatin (CP) and oxaliplatin (OX), platinum-based drugs used widely in chemotherapy, form adducts on intrastrand guanines (5'GG) in genomic DNA. DNA damage recognition proteins, transcription factors, mismatch repair proteins, and DNA polymerases discriminate between CP- and OX-GG DNA adducts, which could partly account for differences in the efficacy, toxicity, and mutagenicity of CP and OX. In addition, differential recognition of CP- and OX-GG adducts is highly dependent on the sequence context of the Pt-GG adduct. In particular, DNA binding protein domain HMGB1a binds to CP-GG DNA adducts with up to 53-fold greater affinity than to OX-GG adducts in the TGGA sequence context but shows much smaller differences in binding in the AGGC or TGGT sequence contexts. Here, simulations of the HMGB1a-Pt-DNA complex in the three sequence contexts revealed a higher number of interface contacts for the CP-DNA complex in the TGGA sequence context than in the OX-DNA complex. However, the number of interface contacts was similar in the TGGT and AGGC sequence contexts. The higher number of interface contacts in the CP-TGGA sequence context corresponded to a larger roll of the Pt-GG base pair step. Furthermore, geometric analysis of stacking of phenylalanine 37 in HMGB1a (Phe37) with the platinated guanines revealed more favorable stacking modes correlated with a larger roll of the Pt-GG base pair step in the TGGA sequence context. These data are consistent with our previous molecular dynamics simulations showing that the CP-TGGA complex was able to sample larger roll angles than the OX-TGGA complex or either CP- or OX-DNA complexes in the AGGC or TGGT sequences. We infer that the high binding affinity of HMGB1a for CP-TGGA is due to the greater flexibility of CP-TGGA compared to OX-TGGA and other Pt-DNA adducts. This increased flexibility is reflected in the ability of CP-TGGA to sample larger roll angles, which allows for a higher number of interface contacts between the Pt

The species recognition system: a new corollary for the human fetoembryonic defense system hypothesis.

PubMed

Clark, G F; Dell, A; Morris, H R; Patankar, M S; Easton, R L

2001-01-01

We have previously suggested that the human fetus is protected during human development by a system of both soluble and cell surface associated glycoconjugates that utilize their carbohydrate sequences as functional groups to enable them to evoke tolerance. The proposed model has been referred to as the human fetoembryonic defense system hypothesis (hu-FEDS). In this paradigm, it has previously been proposed that similar oligosaccharides are used to mediate crucial recognition events required during both human sperm-egg binding and immune-inflammatory cell interactions. This vertical integration suggested to us that the sperm-egg binding itself is related to universal recognition events that occur between immune and inflammatory cells, except that in this case recognition of 'species' rather than recognition of 'self' is being manifested. In this paper, we have designated this component of hu-FEDS as the species recognition system (SRS). We propose that the SRS is an integral component of the hu-FEDS used to enable sperm-egg recognition and protection of the gametes from potential immune responses. Recent structural data indicates that the glycan sequences implicated in mediating murine gamete recognition are also expressed on CD45 in activated murine T lymphocytes and cytotoxic T lymphocytes. This overlap supports our contention that there is an overlap between the immune and gamete recognition systems. Therefore the hu-FEDS paradigm may be a subset of a larger model that also applies to other placental mammals. We therefore propose that the hu-FEDS model for protection should in the future be referred to as the eutherian fetoembryonic defense system hypothesis (eu-FEDS) to account for this extension. The possibility exists that the SRS component of eu-FEDS could predate eutherians and extend to all sexually reproducing organisms. Future investigation of the interactions between the immune and gamete recognition system will be required to determine the degree of

Efficient iris recognition by characterizing key local variations.

PubMed

Ma, Li; Tan, Tieniu; Wang, Yunhong; Zhang, Dexin

2004-06-01

Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.

Human activities recognition by head movement using partial recurrent neural network

NASA Astrophysics Data System (ADS)

Tan, Henry C. C.; Jia, Kui; De Silva, Liyanage C.

2003-06-01

Traditionally, human activities recognition has been achieved mainly by the statistical pattern recognition methods or the Hidden Markov Model (HMM). In this paper, we propose a novel use of the connectionist approach for the recognition of ten simple human activities: walking, sitting down, getting up, squatting down and standing up, in both lateral and frontal views, in an office environment. By means of tracking the head movement of the subjects over consecutive frames from a database of different color image sequences, and incorporating the Elman model of the partial recurrent neural network (RNN) that learns the sequential patterns of relative change of the head location in the images, the proposed system is able to robustly classify all the ten activities performed by unseen subjects from both sexes, of different race and physique, with a recognition rate as high as 92.5%. This demonstrates the potential of employing partial RNN to recognize complex activities in the increasingly popular human-activities-based applications.

A Fuzzy Aproach For Facial Emotion Recognition

NASA Astrophysics Data System (ADS)

Gîlcă, Gheorghe; Bîzdoacă, Nicu-George

2015-09-01

This article deals with an emotion recognition system based on the fuzzy sets. Human faces are detected in images with the Viola - Jones algorithm and for its tracking in video sequences we used the Camshift algorithm. The detected human faces are transferred to the decisional fuzzy system, which is based on the variable fuzzyfication measurements of the face: eyebrow, eyelid and mouth. The system can easily determine the emotional state of a person.

Exploring a recognition-induced recognition decrement

PubMed Central

Dopkins, Stephen; Ngo, Catherine Trinh; Sargent, Jesse

2007-01-01

Four experiments explored a recognition decrement that is associated with the recognition of a word from a short list. The stimulus material for demonstrating the phenomenon was a list of words of different syntactic types. A word from the list was recognized less well following a decision that a word of the same type had occurred in the list than following a decision that such a word had not occurred in the list. A recognition decrement did not occur for a word of a given type following a positive recognition decision to a word of a different type. A recognition decrement did not occur when the list consisted exclusively of nouns. It was concluded that the phenomenon may reflect a criterion shift but probably does not reflect a list strength effect, suppression, or familiarity attribution consequent to a perceived discrepancy between actual and expected fluency. PMID:17063915

Rules for the recognition of dilysine retrieval motifs by coatomer

PubMed Central

Ma, Wenfu; Goldberg, Jonathan

2013-01-01

Cytoplasmic dilysine motifs on transmembrane proteins are captured by coatomer α-COP and β′-COP subunits and packaged into COPI-coated vesicles for Golgi-to-ER retrieval. Numerous ER/Golgi proteins contain K(x)Kxx motifs, but the rules for their recognition are unclear. We present crystal structures of α-COP and β′-COP bound to a series of naturally occurring retrieval motifs—encompassing KKxx, KxKxx and non-canonical RKxx and viral KxHxx sequences. Binding experiments show that α-COP and β′-COP have generally the same specificity for KKxx and KxKxx, but only β′-COP recognizes the RKxx signal. Dilysine motif recognition involves lysine side-chain interactions with two acidic patches. Surprisingly, however, KKxx and KxKxx motifs bind differently, with their lysine residues transposed at the binding patches. We derive rules for retrieval motif recognition from key structural features: the reversed binding modes, the recognition of the C-terminal carboxylate group which enforces lysine positional context, and the tolerance of the acidic patches for non-lysine residues. PMID:23481256

Resolution of Site-Specific Conformational Heterogeneity in Proline-Rich Molecular Recognition by Src Homology 3 Domains.

PubMed

Horness, Rachel E; Basom, Edward J; Mayer, John P; Thielges, Megan C

2016-02-03

Conformational heterogeneity and dynamics are increasingly evoked in models of protein molecular recognition but are challenging to experimentally characterize. Here we combine the inherent temporal resolution of infrared (IR) spectroscopy with the spatial resolution afforded by selective incorporation of carbon-deuterium (C-D) bonds, which provide frequency-resolved absorptions within a protein IR spectrum, to characterize the molecular recognition of the Src homology 3 (SH3) domain of the yeast protein Sho1 with its cognate proline-rich (PR) sequence of Pbs2. The IR absorptions of C-D bonds introduced at residues along a peptide of the Pbs2 PR sequence report on the changes in the local environments upon binding to the SH3 domain. Interestingly, upon forming the complex the IR spectra of the peptides labeled with C-D bonds at either of the two conserved prolines of the PXXP consensus recognition sequence show more absorptions than there are C-D bonds, providing evidence for the population of multiple states. In contrast, the NMR spectra of the peptides labeled with (13)C at the same residues show only single resonances, indicating rapid interconversion on the NMR time scale. Thus, the data suggest that the SH3 domain recognizes its cognate peptide with a component of induced fit molecular recognition involving the adoption of multiples states, which have previously gone undetected due to interconversion between the populated states that is too fast to resolve using conventional methods.

Activity Recognition on Streaming Sensor Data.

PubMed

Krishnan, Narayanan C; Cook, Diane J

2014-02-01

Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a scripted or pre-segmented sequence of sensor events related to activities. In this paper we propose and evaluate a sliding window based approach to perform activity recognition in an on line or streaming fashion; recognizing activities as and when new sensor events are recorded. To account for the fact that different activities can be best characterized by different window lengths of sensor events, we incorporate the time decay and mutual information based weighting of sensor events within a window. Additional contextual information in the form of the previous activity and the activity of the previous window is also appended to the feature describing a sensor window. The experiments conducted to evaluate these techniques on real-world smart home datasets suggests that combining mutual information based weighting of sensor events and adding past contextual information into the feature leads to best performance for streaming activity recognition.

Stages of processing in associative recognition: evidence from behavior, EEG, and classification.

PubMed

Borst, Jelmer P; Schneider, Darryl W; Walsh, Matthew M; Anderson, John R

2013-12-01

In this study, we investigated the stages of information processing in associative recognition. We recorded EEG data while participants performed an associative recognition task that involved manipulations of word length, associative fan, and probe type, which were hypothesized to affect the perceptual encoding, retrieval, and decision stages of the recognition task, respectively. Analyses of the behavioral and EEG data, supplemented with classification of the EEG data using machine-learning techniques, provided evidence that generally supported the sequence of stages assumed by a computational model developed in the Adaptive Control of Thought-Rational cognitive architecture. However, the results suggested a more complex relationship between memory retrieval and decision-making than assumed by the model. Implications of the results for modeling associative recognition are discussed. The study illustrates how a classifier approach, in combination with focused manipulations, can be used to investigate the timing of processing stages.

Sequence analysis of serum albumins reveals the molecular evolution of ligand recognition properties.

PubMed

Fanali, Gabriella; Ascenzi, Paolo; Bernardi, Giorgio; Fasano, Mauro

2012-01-01

Serum albumin (SA) is a circulating protein providing a depot and carrier for many endogenous and exogenous compounds. At least seven major binding sites have been identified by structural and functional investigations mainly in human SA. SA is conserved in vertebrates, with at least 49 entries in protein sequence databases. The multiple sequence analysis of this set of entries leads to the definition of a cladistic tree for the molecular evolution of SA orthologs in vertebrates, thus showing the clustering of the considered species, with lamprey SAs (Lethenteron japonicum and Petromyzon marinus) in a separate outgroup. Sequence analysis aimed at searching conserved domains revealed that most SA sequences are made up by three repeated domains (about 600 residues), as extensively characterized for human SA. On the contrary, lamprey SAs are giant proteins (about 1400 residues) comprising seven repeated domains. The phylogenetic analysis of the SA family reveals a stringent correlation with the taxonomic classification of the species available in sequence databases. A focused inspection of the sequences of ligand binding sites in SA revealed that in all sites most residues involved in ligand binding are conserved, although the versatility towards different ligands could be peculiar of higher organisms. Moreover, the analysis of molecular links between the different sites suggests that allosteric modulation mechanisms could be restricted to higher vertebrates.

8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Code of Federal Regulations, 2010 CFR

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

Localization and recognition of traffic signs for automated vehicle control systems

NASA Astrophysics Data System (ADS)

Zadeh, Mahmoud M.; Kasvand, T.; Suen, Ching Y.

1998-01-01

We present a computer vision system for detection and recognition of traffic signs. Such systems are required to assist drivers and for guidance and control of autonomous vehicles on roads and city streets. For experiments we use sequences of digitized photographs and off-line analysis. The system contains four stages. First, region segmentation based on color pixel classification called SRSM. SRSM limits the search to regions of interest in the scene. Second, we use edge tracing to find parts of outer edges of signs which are circular or straight, corresponding to the geometrical shapes of traffic signs. The third step is geometrical analysis of the outer edge and preliminary recognition of each candidate region, which may be a potential traffic sign. The final step in recognition uses color combinations within each region and model matching. This system maybe used for recognition of other types of objects, provided that the geometrical shape and color content remain reasonably constant. The method is reliable, easy to implement, and fast, This differs form the road signs recognition method in the PROMETEUS. The overall structure of the approach is sketched.

Super Normal Vector for Human Activity Recognition with Depth Cameras.

PubMed

Yang, Xiaodong; Tian, YingLi

2017-05-01

The advent of cost-effectiveness and easy-operation depth cameras has facilitated a variety of visual recognition tasks including human activity recognition. This paper presents a novel framework for recognizing human activities from video sequences captured by depth cameras. We extend the surface normal to polynormal by assembling local neighboring hypersurface normals from a depth sequence to jointly characterize local motion and shape information. We then propose a general scheme of super normal vector (SNV) to aggregate the low-level polynormals into a discriminative representation, which can be viewed as a simplified version of the Fisher kernel representation. In order to globally capture the spatial layout and temporal order, an adaptive spatio-temporal pyramid is introduced to subdivide a depth video into a set of space-time cells. In the extensive experiments, the proposed approach achieves superior performance to the state-of-the-art methods on the four public benchmark datasets, i.e., MSRAction3D, MSRDailyActivity3D, MSRGesture3D, and MSRActionPairs3D.

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

PubMed Central

2012-01-01

SH2 domains are long known prominent players in the field of phosphotyrosine recognition within signaling protein networks. However, over the years they have been joined by an increasing number of other protein domain families that can, at least with some of their members, also recognise pTyr residues in a sequence-specific context. This superfamily of pTyr recognition modules, which includes substantial fractions of the PTB domains, as well as much smaller, or even single member fractions like the HYB domain, the PKCδ and PKCθ C2 domains and RKIP, represents a fascinating, medically relevant and hence intensely studied part of the cellular signaling architecture of metazoans. Protein tyrosine phosphorylation clearly serves a plethora of functions and pTyr recognition domains are used in a similarly wide range of interaction modes, which encompass, for example, partner protein switching, tandem recognition functionalities and the interaction with catalytically active protein domains. If looked upon closely enough, virtually no pTyr recognition and regulation event is an exact mirror image of another one in the same cell. Thus, the more we learn about the biology and ultrastructural details of pTyr recognition domains, the more does it become apparent that nature cleverly combines and varies a few basic principles to generate a sheer endless number of sophisticated and highly effective recognition/regulation events that are, under normal conditions, elegantly orchestrated in time and space. This knowledge is also valuable when exploring pTyr reader domains as diagnostic tools, drug targets or therapeutic reagents to combat human diseases. PMID:23134684

SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

Hybrid Feature Extraction-based Approach for Facial Parts Representation and Recognition

NASA Astrophysics Data System (ADS)

Rouabhia, C.; Tebbikh, H.

2008-06-01

Face recognition is a specialized image processing which has attracted a considerable attention in computer vision. In this article, we develop a new facial recognition system from video sequences images dedicated to person identification whose face is partly occulted. This system is based on a hybrid image feature extraction technique called ACPDL2D (Rouabhia et al. 2007), it combines two-dimensional principal component analysis and two-dimensional linear discriminant analysis with neural network. We performed the feature extraction task on the eyes and the nose images separately then a Multi-Layers Perceptron classifier is used. Compared to the whole face, the results of simulation are in favor of the facial parts in terms of memory capacity and recognition (99.41% for the eyes part, 98.16% for the nose part and 97.25 % for the whole face).

Still-to-video face recognition in unconstrained environments

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Liu, Changsong; Ding, Xiaoqing

2015-02-01

Face images from video sequences captured in unconstrained environments usually contain several kinds of variations, e.g. pose, facial expression, illumination, image resolution and occlusion. Motion blur and compression artifacts also deteriorate recognition performance. Besides, in various practical systems such as law enforcement, video surveillance and e-passport identification, only a single still image per person is enrolled as the gallery set. Many existing methods may fail to work due to variations in face appearances and the limit of available gallery samples. In this paper, we propose a novel approach for still-to-video face recognition in unconstrained environments. By assuming that faces from still images and video frames share the same identity space, a regularized least squares regression method is utilized to tackle the multi-modality problem. Regularization terms based on heuristic assumptions are enrolled to avoid overfitting. In order to deal with the single image per person problem, we exploit face variations learned from training sets to synthesize virtual samples for gallery samples. We adopt a learning algorithm combining both affine/convex hull-based approach and regularizations to match image sets. Experimental results on a real-world dataset consisting of unconstrained video sequences demonstrate that our method outperforms the state-of-the-art methods impressively.

Novel DNA packaging recognition in the unusual bacteriophage N15

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

Feiss, Michael; Geyer, Henriette, E-mail: henriettegeyer@gmail.com; Division of Viral Infections, Robert Koch Institute, Berlin

Phage lambda's cosB packaging recognition site is tripartite, consisting of 3 TerS binding sites, called R sequences. TerS binding to the critical R3 site positions the TerL endonuclease for nicking cosN to generate cohesive ends. The N15 cos (cos{sup N15}) is closely related to cos{sup λ}, but whereas the cosB{sup N15} subsite has R3, it lacks the R2 and R1 sites and the IHF binding site of cosB{sup λ}. A bioinformatic study of N15-like phages indicates that cosB{sup N15} also has an accessory, remote rR2 site, which is proposed to increase packaging efficiency, like R2 and R1 of lambda. N15more » plus five prophages all have the rR2 sequence, which is located in the TerS-encoding 1 gene, approximately 200 bp distal to R3. An additional set of four highly related prophages, exemplified by Monarch, has R3 sequence, but also has R2 and R1 sequences characteristic of cosB–λ. The DNA binding domain of TerS-N15 is a dimer. - Highlights: • There are two classes of DNA packaging signals in N15-related phages. • Phage N15's TerS binding site: a critical site and a possible remote accessory site. • Viral DNA recognition signals by the λ-like bacteriophages: the odd case of N15.« less

Molecular recognition of pre-tRNA by Arabidopsis protein-only Ribonuclease P.

PubMed

Klemm, Bradley P; Karasik, Agnes; Kaitany, Kipchumba J; Shanmuganathan, Aranganathan; Henley, Matthew J; Thelen, Adam Z; Dewar, Allison J L; Jackson, Nathaniel D; Koutmos, Markos; Fierke, Carol A

2017-12-01

Protein-only ribonuclease P (PRORP) is an enzyme responsible for catalyzing the 5' end maturation of precursor transfer ribonucleic acids (pre-tRNAs) encoded by various cellular compartments in many eukaryotes. PRORPs from plants act as single-subunit enzymes and have been used as a model system for analyzing the function of the metazoan PRORP nuclease subunit, which requires two additional proteins for efficient catalysis. There are currently few molecular details known about the PRORP-pre-tRNA complex. Here, we characterize the determinants of substrate recognition by the single subunit Arabidopsis thaliana PRORP1 and PRORP2 using kinetic and thermodynamic experiments. The salt dependence of binding affinity suggests 4-5 contacts with backbone phosphodiester bonds on substrates, including a single phosphodiester contact with the pre-tRNA 5' leader, consistent with prior reports of short leader requirements. PRORPs contain an N-terminal pentatricopeptide repeat (PPR) domain, truncation of which results in a >30-fold decrease in substrate affinity. While most PPR-containing proteins have been implicated in single-stranded sequence-specific RNA recognition, we find that the PPR motifs of PRORPs recognize pre-tRNA substrates differently. Notably, the PPR domain residues most important for substrate binding in PRORPs do not correspond to positions involved in base recognition in other PPR proteins. Several of these residues are highly conserved in PRORPs from algae, plants, and metazoans, suggesting a conserved strategy for substrate recognition by the PRORP PPR domain. Furthermore, there is no evidence for sequence-specific interactions. This work clarifies molecular determinants of PRORP-substrate recognition and provides a new predictive model for the PRORP-substrate complex. © 2017 Klemm et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

University of Glasgow at TREC 2009: Experiments with Terrier

DTIC Science & Technology

2009-11-01

identify entities in the category B subset of the corpus, we resort to an efficient dictionary -based named en- tity recognition approach.4 In particular...we build a large dictio- nary of entity names using DBPedia,5 a structured representation of Wikipedia. Dictionary entries comprise all known...aliases for each unique entity, as obtained from DBPedia (e.g., ‘Barack Obama’ is represented by the dictionary entries ‘Barack Obama’ and ‘44th President

Monitoring and Evaluation of Smolt Migration in the Columbia Basin : Volume IX : Evaluation of the 2001 Predictions of the Run-Timing of Wild and Hatchery-Reared Migrant Salmon and Steelhead Trout Migrating to Lower Granite, Rock Island, McNary, and John Day Dams using Program RealTime.

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

Burgess, Caitlin; Skalski, John R.

2001-12-01

Program RealTime provided tracking and forecasting of the 2001 inseason outmigration via the internet for eighteen PIT-tagged stocks of wild salmon and steelhead to Lower Granite and/or McNary dams and eleven passage-indexed stocks to Rock Island, McNary, or John Day dams. Nine of the PIT-tagged stocks tracked this year were new to the project. Thirteen ESUs of wild subyearling and yearling chinook salmon and steelhead, and one ESU of hatchery-reared sockeye salmon were tracked and forecasted to Lower Granite Dam. Eight wild ESUs of subyearling and yearling chinook salmon, sockeye salmon and steelhead were tracked to McNary Dam for themore » first time this year. Wild PIT-tagged ESUs tracked to Lower Granite Dam included yearling spring/summer chinook salmon release-recovery stocks (from Bear Valley Creek, Catherine Creek, Herd Creek, Imnaha River, Johnson Creek, Lostine River, Minam River, South Fork Salmon River, Secesh River, and Valley Creek), PIT-tagged wild runs-at-large of yearling chinook salmon and steelhead, and a PIT-tagged stock of subyearling fall chinook salmon. The stock of hatchery-reared PIT-tagged summer-run sockeye salmon smolts outmigrating to Lower Granite Dam, consisted this year of a new stock of fish from Alturas Lake Creek, Redfish Lake Creek Trap and Sawtooth Trap. The passage-indexed stocks, counted using FPC passage indices, included combined wild- and hatchery-reared runs-at-large of subyearling and yearling chinook, coho, and sockeye salmon, and steelhead migrating to Rock Island and McNary dams, and, new this year, combined wild and hatchery subyearling chinook salmon to John Day Dam. Unusual run-timing and fish passage characteristics were observed in this low-flow, negligible-spill migration year. The period for the middle 80% of fish passage (i.e., progress from the 10th to the 90th percentiles) was unusually short for nine out of ten PIT-tagged yearling spring/summer chinook salmon stocks tracked to Lower Granite Dam. It was the

Human action recognition based on kinematic similarity in real time

PubMed Central

Chen, Longting; Luo, Ailing; Zhang, Sicong

2017-01-01

Human action recognition using 3D pose data has gained a growing interest in the field of computer robotic interfaces and pattern recognition since the availability of hardware to capture human pose. In this paper, we propose a fast, simple, and powerful method of human action recognition based on human kinematic similarity. The key to this method is that the action descriptor consists of joints position, angular velocity and angular acceleration, which can meet the different individual sizes and eliminate the complex normalization. The angular parameters of joints within a short sliding time window (approximately 5 frames) around the current frame are used to express each pose frame of human action sequence. Moreover, three modified KNN (k-nearest-neighbors algorithm) classifiers are employed in our method: one for achieving the confidence of every frame in the training step, one for estimating the frame label of each descriptor, and one for classifying actions. Additional estimating of the frame’s time label makes it possible to address single input frames. This approach can be used on difficult, unsegmented sequences. The proposed method is efficient and can be run in real time. The research shows that many public datasets are irregularly segmented, and a simple method is provided to regularize the datasets. The approach is tested on some challenging datasets such as MSR-Action3D, MSRDailyActivity3D, and UTD-MHAD. The results indicate our method achieves a higher accuracy. PMID:29073131

A role for carbohydrate recognition in mammalian sperm-egg binding

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

Clark, Gary F., E-mail: clarkgf@health.missouri.edu

Highlights: • Mammalian sperm-egg binding as a carbohydrate dependent species recognition event. • The role of carbohydrate recognition in human, mouse and pig sperm-egg binding. • Historical perspective and future directions for research focused on gamete binding. - Abstract: Mammalian fertilization usually requires three sequential cell–cell interactions: (i) initial binding of sperm to the specialized extracellular matrix coating the egg known as the zona pellucida (ZP); (ii) binding of sperm to the ZP via the inner acrosomal membrane that is exposed following the induction of acrosomal exocytosis; and (iii) adhesion of acrosome-reacted sperm to the plasma membrane of the eggmore » cell, enabling subsequent fusion of these gametes. The focus of this review is on the initial binding of intact sperm to the mammalian ZP. Evidence collected over the past fifty years has confirmed that this interaction relies primarily on the recognition of carbohydrate sequences presented on the ZP by lectin-like egg binding proteins located on the plasma membrane of sperm. There is also evidence that the same carbohydrate sequences that mediate binding also function as ligands for lectins on lymphocytes that can inactivate immune responses, likely protecting the egg and the developing embryo up to the stage of blastocyst hatching. The literature related to initial sperm-ZP binding in the three major mammalian models (human, mouse and pig) is discussed. Historical perspectives and future directions for research related to this aspect of gamete adhesion are also presented.« less

Critical Determinants of Substrate Recognition by Cyclin-Dependent Kinase-like 5 (CDKL5).

PubMed

Katayama, Syouichi; Sueyoshi, Noriyuki; Kameshita, Isamu

2015-05-19

Cyclin-dependent kinase-like 5 (CDKL5) is a Ser/Thr protein kinase known to be associated with X-linked neurodevelopmental disorders. In a previous study, we identified amphiphysin 1 (Amph1) as a potential substrate for CDKL5 and identified a single phosphorylation site at Ser-293. In this study, we investigated the molecular mechanisms of substrate recognition by CDKL5 using Amph1 as a model substrate. Amph1 served as an efficient CDKL5 substrate, whereas Amph2, a structurally related homologue of Amph1, was not phosphorylated by CDKL5. The sequence around the Amph1 phosphorylation site is RPR(293)SPSQ, while the corresponding sequence in Amph2 is IPK(332)SPSQ. To define the amino acid sequence specificity of the substrate, various point mutants of Amph1 and Amph2 were prepared and phosphorylated by CDKL5. Both Amph2(I329R) and Amph1 served as efficient CDKL5 substrates, but Amph1(R290I) did not, indicating that the arginyl residue at the P -3 position is critical for substrate recognition. With regard to prolyl residues around the phosphorylation site of Amph1, Pro-291 at the P -2 position, but not Pro-294 at the P +1 position, is indispensable for phosphorylation by CDKL5. Phosphorylation experiments using various deletion mutants of Amph1 revealed that the proline-rich domain (PRD) (amino acids 247-315) alone was not phosphorylated by CDKL5. In contrast, Amph1(247-385), which comprised the PRD and CLAP domains, served as an efficient CDKL5 substrate. These results, taken together, suggest that both the phosphorylation site sequence (RPXSX) and the CLAP domain structure in Amph1 play crucial roles in recognition and phosphorylation by CDKL5.

Reconsidering the role of temporal order in spoken word recognition.

PubMed

Toscano, Joseph C; Anderson, Nathaniel D; McMurray, Bob

2013-10-01

Models of spoken word recognition assume that words are represented as sequences of phonemes. We evaluated this assumption by examining phonemic anadromes, words that share the same phonemes but differ in their order (e.g., sub and bus). Using the visual-world paradigm, we found that listeners show more fixations to anadromes (e.g., sub when bus is the target) than to unrelated words (well) and to words that share the same vowel but not the same set of phonemes (sun). This contrasts with the predictions of existing models and suggests that words are not defined as strict sequences of phonemes.

A shared representation of order between encoding and recognition in visual short-term memory.

PubMed

Kalm, Kristjan; Norris, Dennis

2017-07-15

Many complex tasks require people to bind individual events into a sequence that can be held in short term memory (STM). For this purpose information about the order of the individual events in the sequence needs to be maintained in an active and accessible form in STM over a period of few seconds. Here we investigated how the temporal order information is shared between the presentation and response phases of an STM task. We trained a classification algorithm on the fMRI activity patterns from the presentation phase of the STM task to predict the order of the items during the subsequent recognition phase. While voxels in a number of brain regions represented positional information during either presentation and recognition phases, only voxels in the lateral prefrontal cortex (PFC) and the anterior temporal lobe (ATL) represented position consistently across task phases. A shared positional code in the ATL might reflect verbal recoding of visual sequences to facilitate the maintenance of order information over several seconds. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

EMG-based speech recognition using hidden markov models with global control variables.

PubMed

Lee, Ki-Seung

2008-03-01

It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.

Aggregating and Predicting Sequence Labels from Crowd Annotations

PubMed Central

Nguyen, An T.; Wallace, Byron C.; Li, Junyi Jessy; Nenkova, Ani; Lease, Matthew

2017-01-01

Despite sequences being core to NLP, scant work has considered how to handle noisy sequence labels from multiple annotators for the same text. Given such annotations, we consider two complementary tasks: (1) aggregating sequential crowd labels to infer a best single set of consensus annotations; and (2) using crowd annotations as training data for a model that can predict sequences in unannotated text. For aggregation, we propose a novel Hidden Markov Model variant. To predict sequences in unannotated text, we propose a neural approach using Long Short Term Memory. We evaluate a suite of methods across two different applications and text genres: Named-Entity Recognition in news articles and Information Extraction from biomedical abstracts. Results show improvement over strong baselines. Our source code and data are available online1. PMID:29093611

Urdu Nasta'liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks.

PubMed

Naz, Saeeda; Umar, Arif Iqbal; Ahmed, Riaz; Razzak, Muhammad Imran; Rashid, Sheikh Faisal; Shafait, Faisal

2016-01-01

The recognition of Arabic script and its derivatives such as Urdu, Persian, Pashto etc. is a difficult task due to complexity of this script. Particularly, Urdu text recognition is more difficult due to its Nasta'liq writing style. Nasta'liq writing style inherits complex calligraphic nature, which presents major issues to recognition of Urdu text owing to diagonality in writing, high cursiveness, context sensitivity and overlapping of characters. Therefore, the work done for recognition of Arabic script cannot be directly applied to Urdu recognition. We present Multi-dimensional Long Short Term Memory (MDLSTM) Recurrent Neural Networks with an output layer designed for sequence labeling for recognition of printed Urdu text-lines written in the Nasta'liq writing style. Experiments show that MDLSTM attained a recognition accuracy of 98% for the unconstrained Urdu Nasta'liq printed text, which significantly outperforms the state-of-the-art techniques.

A universal entropy-driven mechanism for thioredoxin–target recognition

PubMed Central

Palde, Prakash B.; Carroll, Kate S.

2015-01-01

Cysteine residues in cytosolic proteins are maintained in their reduced state, but can undergo oxidation owing to posttranslational modification during redox signaling or under conditions of oxidative stress. In large part, the reduction of oxidized protein cysteines is mediated by a small 12-kDa thiol oxidoreductase, thioredoxin (Trx). Trx provides reducing equivalents for central metabolic enzymes and is implicated in redox regulation of a wide number of target proteins, including transcription factors. Despite its importance in cellular redox homeostasis, the precise mechanism by which Trx recognizes target proteins, especially in the absence of any apparent signature binding sequence or motif, remains unknown. Knowledge of the forces associated with the molecular recognition that governs Trx–protein interactions is fundamental to our understanding of target specificity. To gain insight into Trx–target recognition, we have thermodynamically characterized the noncovalent interactions between Trx and target proteins before S-S reduction using isothermal titration calorimetry (ITC). Our findings indicate that Trx recognizes the oxidized form of its target proteins with exquisite selectivity, compared with their reduced counterparts. Furthermore, we show that recognition is dependent on the conformational restriction inherent to oxidized targets. Significantly, the thermodynamic signatures for multiple Trx targets reveal favorable entropic contributions as the major recognition force dictating these protein–protein interactions. Taken together, our data afford significant new insight into the molecular forces responsible for Trx–target recognition and should aid the design of new strategies for thiol oxidoreductase inhibition. PMID:26080424

A Teaching-Learning Sequence about Weather Map Reading

ERIC Educational Resources Information Center

Mandrikas, Achilleas; Stavrou, Dimitrios; Skordoulis, Constantine

2017-01-01

In this paper a teaching-learning sequence (TLS) introducing pre-service elementary teachers (PET) to weather map reading, with emphasis on wind assignment, is presented. The TLS includes activities about recognition of wind symbols, assignment of wind direction and wind speed on a weather map and identification of wind characteristics in a…

Object Recognition using Feature- and Color-Based Methods

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu; Stubberud, Allen

2008-01-01

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Action recognition using mined hierarchical compound features.

PubMed

Gilbert, Andrew; Illingworth, John; Bowden, Richard

2011-05-01

The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial domain, their 3D (space-time) counterparts typically form the basic components used to describe actions, and in action recognition the features used are often engineered to fire sparsely. This is to ensure that the problem is tractable; however, this can sacrifice recognition accuracy as it cannot be assumed that the optimum features in terms of class discrimination are obtained from this approach. In contrast, we propose to initially use an overcomplete set of simple 2D corners in both space and time. These are grouped spatially and temporally using a hierarchical process, with an increasing search area. At each stage of the hierarchy, the most distinctive and descriptive features are learned efficiently through data mining. This allows large amounts of data to be searched for frequently reoccurring patterns of features. At each level of the hierarchy, the mined compound features become more complex, discriminative, and sparse. This results in fast, accurate recognition with real-time performance on high-resolution video. As the compound features are constructed and selected based upon their ability to discriminate, their speed and accuracy increase at each level of the hierarchy. The approach is tested on four state-of-the-art data sets, the popular KTH data set to provide a comparison with other state-of-the-art approaches, the Multi-KTH data set to illustrate performance at simultaneous multiaction classification, despite no explicit localization information provided during training. Finally, the recent Hollywood and Hollywood2 data sets provide challenging complex actions taken from commercial movie sequences. For all four data sets, the proposed hierarchical

A Fast Goal Recognition Technique Based on Interaction Estimates

NASA Technical Reports Server (NTRS)

E-Martin, Yolanda; R-Moreno, Maria D.; Smith, David E.

2015-01-01

Goal Recognition is the task of inferring an actor's goals given some or all of the actor's observed actions. There is considerable interest in Goal Recognition for use in intelligent personal assistants, smart environments, intelligent tutoring systems, and monitoring user's needs. In much of this work, the actor's observed actions are compared against a generated library of plans. Recent work by Ramirez and Geffner makes use of AI planning to determine how closely a sequence of observed actions matches plans for each possible goal. For each goal, this is done by comparing the cost of a plan for that goal with the cost of a plan for that goal that includes the observed actions. This approach yields useful rankings, but is impractical for real-time goal recognition in large domains because of the computational expense of constructing plans for each possible goal. In this paper, we introduce an approach that propagates cost and interaction information in a plan graph, and uses this information to estimate goal probabilities. We show that this approach is much faster, but still yields high quality results.

QUASAR--scoring and ranking of sequence-structure alignments.

PubMed

Birzele, Fabian; Gewehr, Jan E; Zimmer, Ralf

2005-12-15

Sequence-structure alignments are a common means for protein structure prediction in the fields of fold recognition and homology modeling, and there is a broad variety of programs that provide such alignments based on sequence similarity, secondary structure or contact potentials. Nevertheless, finding the best sequence-structure alignment in a pool of alignments remains a difficult problem. QUASAR (quality of sequence-structure alignments ranking) provides a unifying framework for scoring sequence-structure alignments that aids finding well-performing combinations of well-known and custom-made scoring schemes. Those scoring functions can be benchmarked against widely accepted quality scores like MaxSub, TMScore, Touch and APDB, thus enabling users to test their own alignment scores against 'standard-of-truth' structure-based scores. Furthermore, individual score combinations can be optimized with respect to benchmark sets based on known structural relationships using QUASAR's in-built optimization routines.

Segment-based acoustic models for continuous speech recognition

NASA Astrophysics Data System (ADS)

Ostendorf, Mari; Rohlicek, J. R.

1993-07-01

This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition, by extending previous work in segment-based modeling and by introducing a new hierarchical approach to representing intra-utterance statistical dependencies. These techniques, which are more costly than traditional approaches because of the large search space associated with higher order models, are made feasible through rescoring a set of HMM-generated N-best sentence hypotheses. We expect these different modeling techniques to result in improved recognition performance over that achieved by current systems, which handle only frame-based observations and assume that these observations are independent given an underlying state sequence. In the fourth quarter of the project, we have completed the following: (1) ported our recognition system to the Wall Street Journal task, a standard task in the ARPA community; (2) developed an initial dependency-tree model of intra-utterance observation correlation; and (3) implemented baseline language model estimation software. Our initial results on the Wall Street Journal task are quite good and represent significantly improved performance over most HMM systems reporting on the Nov. 1992 5k vocabulary test set.

The recognition and modification sites for the bacterial type I restriction systems KpnAI, StySEAI, StySENI and StySGI

PubMed Central

Kasarjian, Julie K. A.; Hidaka, Masumi; Horiuchi, Takashi; Iida, Masatake; Ryu, Junichi

2004-01-01

Using an in vivo plasmid transformation method, we have determined the DNA sequences recognized by the KpnAI, StySEAI, StySENI and StySGI R-M systems from Klebsiella oxytoca strain M5a1, Salmonella eastbourne, Salmonella enteritidis and Salmonella gelsenkirchen, respectively. These type I restriction-modification systems were originally identified using traditional phage assay, and described here is the plasmid transformation test and computer program used to determine their DNA recognition sequences. For this test, we constructed two sets of plasmids, pL and pE, that contain phage lambda and Escherichia coli K-12 chromosomal DNA fragments, respectively. Further, using the methylation sensitivities of various known type II restriction enzymes, we identified the target adenines for methylation (listed in bold italics below as A or T in case of the complementary strand). The recognition sequence and methylation sites are GAA(6N)TGCC (KpnAI), ACA(6N)TYCA (StySEAI), CGA(6N)TACC (StySENI) and TAAC(7N)RTCG (StySGI). These DNA recognition sequences all have a typical type I bipartite pattern and represent three novel specificities and one isoschizomer (StySENI). For confirmation, oligonucleotides containing each of the predicted sequences were synthesized, cloned into plasmid pMECA and transformed into each strain, resulting in a large reduction in efficiency of transformation (EOT). PMID:15199175

An SRY mutation causing human sex reversal resolves a general mechanism of structure-specific DNA recognition: application to the four-way DNA junction.

PubMed

Peters, R; King, C Y; Ukiyama, E; Falsafi, S; Donahoe, P K; Weiss, M A

1995-04-11

SRY, a genetic "master switch" for male development in mammals, exhibits two biochemical activities: sequence-specific recognition of duplex DNA and sequence-independent binding to the sharp angles of four-way DNA junctions. Here, we distinguish between these activities by analysis of a mutant SRY associated with human sex reversal (46, XY female with pure gonadal dysgenesis). The substitution (168T in human SRY) alters a nonpolar side chain in the minor-groove DNA recognition alpha-helix of the HMG box [Haqq, C.M., King, C.-Y., Ukiyama, E., Haqq, T.N., Falsalfi, S., Donahoe, P.K., & Weiss, M.A. (1994) Science 266, 1494-1500]. The native (but not mutant) side chain inserts between specific base pairs in duplex DNA, interrupting base stacking at a site of induced DNA bending. Isotope-aided 1H-NMR spectroscopy demonstrates that analogous side-chain insertion occurs on binding of SRY to a four-way junction, establishing a shared mechanism of sequence- and structure-specific DNA binding. Although the mutant DNA-binding domain exhibits > 50-fold reduction in sequence-specific DNA recognition, near wild-type affinity for four-way junctions is retained. Our results (i) identify a shared SRY-DNA contact at a site of either induced or intrinsic DNA bending, (ii) demonstrate that this contact is not required to bind an intrinsically bent DNA target, and (iii) rationalize patterns of sequence conservation or diversity among HMG boxes. Clinical association of the I68T mutation with human sex reversal supports the hypothesis that specific DNA recognition by SRY is required for male sex determination.

Recognition Tunneling

PubMed Central

Lindsay, Stuart; He, Jin; Sankey, Otto; Hapala, Prokop; Jelinek, Pavel; Zhang, Peiming; Chang, Shuai; Huang, Shuo

2010-01-01

Single molecules in a tunnel junction can now be interrogated reliably using chemically-functionalized electrodes. Monitoring stochastic bonding fluctuations between a ligand bound to one electrode and its target bound to a second electrode (“tethered molecule-pair” configuration) gives insight into the nature of the intermolecular bonding at a single molecule-pair level, and defines the requirements for reproducible tunneling data. Simulations show that there is an instability in the tunnel gap at large currents, and this results in a multiplicity of contacts with a corresponding spread in the measured currents. At small currents (i.e. large gaps) the gap is stable, and functionalizing a pair of electrodes with recognition reagents (the “free analyte” configuration) can generate a distinct tunneling signal when an analyte molecule is trapped in the gap. This opens up a new interface between chemistry and electronics with immediate implications for rapid sequencing of single DNA molecules. PMID:20522930

Phylogenetic analysis and expression profiling of the pattern recognition receptors: insights into molecular recognition of invading pathogens in Manduca sexta

PubMed Central

Zhang, Xiufeng; He, Yan; Cao, Xiaolong; Gunaratna, Ramesh T.; Chen, Yun-ru; Blissard, Gary; Kanost, Michael R.; Jiang, Haobo

2015-01-01

Pattern recognition receptors (PRRs) detect microbial pathogens and trigger innate immune responses. Previous biochemical studies have elucidated the physiological functions of eleven PRRs in Manduca sexta but our understanding of the recognition process is still limited, lacking genomic perspectives. While 34 C-type lectin-domain proteins and 16 Toll-like receptors are reported in the companion papers, we present here 120 other putative PRRs identified through the genome annotation. These include 76 leucine-rich repeat (LRR) proteins, 14 peptidoglycan recognition proteins, 6 EGF/Nim-domain proteins, 5 β-1,3-glucanase-related proteins, 4 galectins, 4 fibrinogen-related proteins, 3 thioester proteins, 5 immunoglobulin-domain proteins, 2 hemocytins, and 1 Reeler. Sequence alignment and phylogenetic analysis reveal the evolution history of a diverse repertoire of proteins for pathogen recognition. While functions of insect LRR proteins are mostly unknown, their structure diversification is phenomenal: In addition to the Toll homologs, 22 LRR proteins with a signal peptide are expected to be secreted; 18 LRR proteins lacking signal peptides may be cytoplasmic; 36 LRRs with a signal peptide and a transmembrane segment may be non-Toll receptors on the surface of cells. Expression profiles of the 120 genes in 52 tissue samples reflect complex regulation in various developmental stages and physiological states, including some likely by Rel family transcription factors via κB motifs in the promoter regions. This collection of information is expected to facilitate future biochemical studies detailing their respective roles in this model insect. PMID:25701384

Enhanced learning of natural visual sequences in newborn chicks.

PubMed

Wood, Justin N; Prasad, Aditya; Goldman, Jason G; Wood, Samantha M W

2016-07-01

To what extent are newborn brains designed to operate over natural visual input? To address this question, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) show enhanced learning of natural visual sequences at the onset of vision. We took the same set of images and grouped them into either natural sequences (i.e., sequences showing different viewpoints of the same real-world object) or unnatural sequences (i.e., sequences showing different images of different real-world objects). When raised in virtual worlds containing natural sequences, newborn chicks developed the ability to recognize familiar images of objects. Conversely, when raised in virtual worlds containing unnatural sequences, newborn chicks' object recognition abilities were severely impaired. In fact, the majority of the chicks raised with the unnatural sequences failed to recognize familiar images of objects despite acquiring over 100 h of visual experience with those images. Thus, newborn chicks show enhanced learning of natural visual sequences at the onset of vision. These results indicate that newborn brains are designed to operate over natural visual input.

Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Monitoring of facial stress during space flight: Optical computer recognition combining discriminative and generative methods

NASA Astrophysics Data System (ADS)

Dinges, David F.; Venkataraman, Sundara; McGlinchey, Eleanor L.; Metaxas, Dimitris N.

2007-02-01

Astronauts are required to perform mission-critical tasks at a high level of functional capability throughout spaceflight. Stressors can compromise their ability to do so, making early objective detection of neurobehavioral problems in spaceflight a priority. Computer optical approaches offer a completely unobtrusive way to detect distress during critical operations in space flight. A methodology was developed and a study completed to determine whether optical computer recognition algorithms could be used to discriminate facial expressions during stress induced by performance demands. Stress recognition from a facial image sequence is a subject that has not received much attention although it is an important problem for many applications beyond space flight (security, human-computer interaction, etc.). This paper proposes a comprehensive method to detect stress from facial image sequences by using a model-based tracker. The image sequences were captured as subjects underwent a battery of psychological tests under high- and low-stress conditions. A cue integration-based tracking system accurately captured the rigid and non-rigid parameters of different parts of the face (eyebrows, lips). The labeled sequences were used to train the recognition system, which consisted of generative (hidden Markov model) and discriminative (support vector machine) parts that yield results superior to using either approach individually. The current optical algorithm methods performed at a 68% accuracy rate in an experimental study of 60 healthy adults undergoing periods of high-stress versus low-stress performance demands. Accuracy and practical feasibility of the technique is being improved further with automatic multi-resolution selection for the discretization of the mask, and automated face detection and mask initialization algorithms.

A new selective developmental deficit: Impaired object recognition with normal face recognition.

PubMed

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

Contribution of finger tracing to the recognition of Chinese characters.

PubMed

Yim-Ng, Y Y; Varley, R; Andrade, J

2000-01-01

Finger tracing is a simulation of the act of writing without the use of pen and paper. It is claimed to help in the processing of Chinese characters, possibly by providing additional motor coding. In this study, blindfolded subjects were equally good at identifying Chinese characters and novel visual stimuli through passive movements made with the index finger of the preferred hand and those made with the last finger of that hand. This suggests that finger tracing provides a relatively high level of coding specific to individual characters, but non-specific to motor effectors. Beginning each stroke from the same location, i.e. removing spatial information, impaired recognition of the familiar characters and the novel nonsense figures. Passively tracing the strokes in a random sequence also impaired recognition of the characters. These results therefore suggest that the beneficial effect of finger tracing on writing or recall of Chinese characters is mediated by sequence and spatial information embedded in the motor movements, and that proprioceptive channel may play a part in mediating visuo-spatial information. Finger tracing may be a useful strategy for remediation of Chinese language impairments.

Study on recognition algorithm for paper currency numbers based on neural network

NASA Astrophysics Data System (ADS)

Li, Xiuyan; Liu, Tiegen; Li, Yuanyao; Zhang, Zhongchuan; Deng, Shichao

2008-12-01

Based on the unique characteristic, the paper currency numbers can be put into record and the automatic identification equipment for paper currency numbers is supplied to currency circulation market in order to provide convenience for financial sectors to trace the fiduciary circulation socially and provide effective supervision on paper currency. Simultaneously it is favorable for identifying forged notes, blacklisting the forged notes numbers and solving the major social problems, such as armor cash carrier robbery, money laundering. For the purpose of recognizing the paper currency numbers, a recognition algorithm based on neural network is presented in the paper. Number lines in original paper currency images can be draw out through image processing, such as image de-noising, skew correction, segmentation, and image normalization. According to the different characteristics between digits and letters in serial number, two kinds of classifiers are designed. With the characteristics of associative memory, optimization-compute and rapid convergence, the Discrete Hopfield Neural Network (DHNN) is utilized to recognize the letters; with the characteristics of simple structure, quick learning and global optimum, the Radial-Basis Function Neural Network (RBFNN) is adopted to identify the digits. Then the final recognition results are obtained by combining the two kinds of recognition results in regular sequence. Through the simulation tests, it is confirmed by simulation results that the recognition algorithm of combination of two kinds of recognition methods has such advantages as high recognition rate and faster recognition simultaneously, which is worthy of broad application prospect.

Storage and retrieval properties of dual codes for pictures and words in recognition memory.

PubMed

Snodgrass, J G; McClure, P

1975-09-01

Storage and retrieval properties of pictures and words were studied within a recognition memory paradigm. Storage was manipulated by instructing subjects either to image or to verbalize to both picture and word stimuli during the study sequence. Retrieval was manipulated by representing a proportion of the old picture and word items in their opposite form during the recognition test (i.e., some old pictures were tested with their corresponding words and vice versa). Recognition performance for pictures was identical under the two instructional conditions, whereas recognition performance for words was markedly superior under the imagery instruction condition. It was suggested that subjects may engage in dual coding of simple pictures naturally, regardless of instructions, whereas dual coding of words may occur only under imagery instructions. The form of the test item had no effect on recognition performance for either type of stimulus and under either instructional condition. However, change of form of the test item markedly reduced item-by-item correlations between the two instructional conditions. It is tentatively proposed that retrieval is required in recognition, but that the effect of a form change is simply to make the retrieval process less consistent, not less efficient.

Simultaneous fluorescence light-up and selective multicolor nucleobase recognition based on sequence-dependent strong binding of berberine to DNA abasic site.

PubMed

Wu, Fei; Shao, Yong; Ma, Kun; Cui, Qinghua; Liu, Guiying; Xu, Shujuan

2012-04-28

Label-free DNA nucleobase recognition by fluorescent small molecules has received much attention due to its simplicity in mutation identification and drug screening. However, sequence-dependent fluorescence light-up nucleobase recognition and multicolor emission with individual emission energy for individual nucleobases have been seldom realized. Herein, an abasic site (AP site) in a DNA duplex was employed as a binding field for berberine, one of isoquinoline alkaloids. Unlike weak binding of berberine to the fully matched DNAs without the AP site, strong binding of berberine to the AP site occurs and the berberine's fluorescence light-up behaviors are highly dependent on the target nucleobases opposite the AP site in which the targets thymine and cytosine produce dual emission bands, while the targets guanine and adenine only give a single emission band. Furthermore, more intense emissions are observed for the target pyrimidines than purines. The flanking bases of the AP site also produce some modifications of the berberine's emission behavior. The binding selectivity of berberine at the AP site is also confirmed by measurements of fluorescence resonance energy transfer, excited-state lifetime, DNA melting and fluorescence quenching by ferrocyanide and sodium chloride. It is expected that the target pyrimidines cause berberine to be stacked well within DNA base pairs near the AP site, which results in a strong resonance coupling of the electronic transitions to the particular vibration mode to produce the dual emissions. The fluorescent signal-on and emission energy-modulated sensing for nucleobases based on this fluorophore is substantially advantageous over the previously used fluorophores. We expect that this approach will be developed as a practical device for differentiating pyrimidines from purines by positioning an AP site toward a target that is available for readout by this alkaloid probe. This journal is © The Royal Society of Chemistry 2012

Comparison of Methods of Detection of Exceptional Sequences in Prokaryotic Genomes.

PubMed

Rusinov, I S; Ershova, A S; Karyagina, A S; Spirin, S A; Alexeevski, A V

2018-02-01

Many proteins need recognition of specific DNA sequences for functioning. The number of recognition sites and their distribution along the DNA might be of biological importance. For example, the number of restriction sites is often reduced in prokaryotic and phage genomes to decrease the probability of DNA cleavage by restriction endonucleases. We call a sequence an exceptional one if its frequency in a genome significantly differs from one predicted by some mathematical model. An exceptional sequence could be either under- or over-represented, depending on its frequency in comparison with the predicted one. Exceptional sequences could be considered biologically meaningful, for example, as targets of DNA-binding proteins or as parts of abundant repetitive elements. Several methods to predict frequency of a short sequence in a genome, based on actual frequencies of certain its subsequences, are used. The most popular are methods based on Markov chain models. But any rigorous comparison of the methods has not previously been performed. We compared three methods for the prediction of short sequence frequencies: the maximum-order Markov chain model-based method, the method that uses geometric mean of extended Markovian estimates, and the method that utilizes frequencies of all subsequences including discontiguous ones. We applied them to restriction sites in complete genomes of 2500 prokaryotic species and demonstrated that the results depend greatly on the method used: lists of 5% of the most under-represented sites differed by up to 50%. The method designed by Burge and coauthors in 1992, which utilizes all subsequences of the sequence, showed a higher precision than the other two methods both on prokaryotic genomes and randomly generated sequences after computational imitation of selective pressure. We propose this method as the first choice for detection of exceptional sequences in prokaryotic genomes.

A novel paired domain DNA recognition motif can mediate Pax2 repression of gene transcription.

PubMed

Håvik, B; Ragnhildstveit, E; Lorens, J B; Saelemyr, K; Fauske, O; Knudsen, L K; Fjose, A

1999-12-20

The paired domain (PD) is an evolutionarily conserved DNA-binding domain encoded by the Pax gene family of developmental regulators. The Pax proteins are transcription factors and are involved in a variety of processes such as brain development, patterning of the central nervous system (CNS), and B-cell development. In this report we demonstrate that the zebrafish Pax2 PD can interact with a novel type of DNA sequences in vitro, the triple-A motif, consisting of a heptameric nucleotide sequence G/CAAACA/TC with an invariant core of three adjacent adenosines. This recognition sequence was found to be conserved in known natural Pax5 repressor elements involved in controlling the expression of the p53 and J-chain genes. By identifying similar high affinity binding sites in potential target genes of the Pax2 protein, including the pax2 gene itself, we obtained further evidence that the triple-A sites are biologically significant. The putative natural target sites also provide a basis for defining an extended consensus recognition sequence. In addition, we observed in transformation assays a direct correlation between Pax2 repressor activity and the presence of triple-A sites. The results suggest that a transcriptional regulatory function of Pax proteins can be modulated by PD binding to different categories of target sequences. Copyright 1999 Academic Press.

Structural and Thermodynamic Signatures of DNA Recognition by Mycobacterium tuberculosis DnaA

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

Tsodikov, Oleg V.; Biswas, Tapan

An essential protein, DnaA, binds to 9-bp DNA sites within the origin of replication oriC. These binding events are prerequisite to forming an enigmatic nucleoprotein scaffold that initiates replication. The number, sequences, positions, and orientations of these short DNA sites, or DnaA boxes, within the oriCs of different bacteria vary considerably. To investigate features of DnaA boxes that are important for binding Mycobacterium tuberculosis DnaA (MtDnaA), we have determined the crystal structures of the DNA binding domain (DBD) of MtDnaA bound to a cognate MtDnaA-box (at 2.0 {angstrom} resolution) and to a consensus Escherichia coli DnaA-box (at 2.3 {angstrom}). Thesemore » structures, complemented by calorimetric equilibrium binding studies of MtDnaA DBD in a series of DnaA-box variants, reveal the main determinants of DNA recognition and establish the [T/C][T/A][G/A]TCCACA sequence as a high-affinity MtDnaA-box. Bioinformatic and calorimetric analyses indicate that DnaA-box sequences in mycobacterial oriCs generally differ from the optimal binding sequence. This sequence variation occurs commonly at the first 2 bp, making an in vivo mycobacterial DnaA-box effectively a 7-mer and not a 9-mer. We demonstrate that the decrease in the affinity of these MtDnaA-box variants for MtDnaA DBD relative to that of the highest-affinity box TTGTCCACA is less than 10-fold. The understanding of DnaA-box recognition by MtDnaA and E. coli DnaA enables one to map DnaA-box sequences in the genomes of M. tuberculosis and other eubacteria.« less

Exploring sequence requirements for C₃/C₄ carboxylate recognition in the Pseudomonas aeruginosa cephalosporinase: Insights into plasticity of the AmpC β-lactamase.

PubMed

Drawz, Sarah M; Taracila, Magdalena; Caselli, Emilia; Prati, Fabio; Bonomo, Robert A

2011-06-01

In Pseudomonas aeruginosa, the chromosomally encoded class C cephalosporinase (AmpC β-lactamase) is often responsible for high-level resistance to β-lactam antibiotics. Despite years of study of these important β-lactamases, knowledge regarding how amino acid sequence dictates function of the AmpC Pseudomonas-derived cephalosporinase (PDC) remains scarce. Insights into structure-function relationships are crucial to the design of both β-lactams and high-affinity inhibitors. In order to understand how PDC recognizes the C₃/C₄ carboxylate of β-lactams, we first examined a molecular model of a P. aeruginosa AmpC β-lactamase, PDC-3, in complex with a boronate inhibitor that possesses a side chain that mimics the thiazolidine/dihydrothiazine ring and the C₃/C₄ carboxylate characteristic of β-lactam substrates. We next tested the hypothesis generated by our model, i.e. that more than one amino acid residue is involved in recognition of the C₃/C₄ β-lactam carboxylate, and engineered alanine variants at three putative carboxylate binding amino acids. Antimicrobial susceptibility testing showed that the PDC-3 β-lactamase maintains a high level of activity despite the substitution of C₃/C₄ β-lactam carboxylate recognition residues. Enzyme kinetics were determined for a panel of nine penicillin and cephalosporin analog boronates synthesized as active site probes of the PDC-3 enzyme and the Arg349Ala variant. Our examination of the PDC-3 active site revealed that more than one residue could serve to interact with the C₃/C₄ carboxylate of the β-lactam. This functional versatility has implications for novel drug design, protein evolution, and resistance profile of this enzyme. Copyright © 2011 The Protein Society.

Acquisition of Malay word recognition skills: lessons from low-progress early readers.

PubMed

Lee, Lay Wah; Wheldall, Kevin

2011-02-01

Malay is a consistent alphabetic orthography with complex syllable structures. The focus of this research was to investigate word recognition performance in order to inform reading interventions for low-progress early readers. Forty-six Grade 1 students were sampled and 11 were identified as low-progress readers. The results indicated that both syllable awareness and phoneme blending were significant predictors of word recognition, suggesting that both syllable and phonemic grain-sizes are important in Malay word recognition. Item analysis revealed a hierarchical pattern of difficulty based on the syllable and the phonic structure of the words. Error analysis identified the sources of errors to be errors due to inefficient syllable segmentation, oversimplification of syllables, insufficient grapheme-phoneme knowledge and inefficient phonemic code assembly. Evidence also suggests that direct instruction in syllable segmentation, phonemic awareness and grapheme-phoneme correspondence is necessary for low-progress readers to acquire word recognition skills. Finally, a logical sequence to teach grapheme-phoneme decoding in Malay is suggested. Copyright © 2010 John Wiley & Sons, Ltd.

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition.

PubMed

Schlundt, Andreas; Tants, Jan-Niklas; Sattler, Michael

2017-04-15

Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain

Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

PubMed

Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

2016-01-01

Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned.

Exploring the energy landscape of antibody-antigen complexes: protein dynamics, flexibility, and molecular recognition.

PubMed

Thielges, Megan C; Zimmermann, Jörg; Yu, Wayne; Oda, Masayuki; Romesberg, Floyd E

2008-07-08

The production of antibodies that selectively bind virtually any foreign compound is the hallmark of the immune system. While much is understood about how sequence diversity contributes to this remarkable feat of molecular recognition, little is known about how sequence diversity impacts antibody dynamics, which is also expected to contribute to molecular recognition. Toward this goal, we examined a panel of antibodies elicited to the chromophoric antigen fluorescein. On the basis of isothermal titration calorimetry, we selected six antibodies that bind fluorescein with diverse binding entropies, suggestive of varying contributions of dynamics to molecular recognition. Sequencing revealed that two pairs of antibodies employ homologous heavy chains that were derived from common germline genes, while the other two heavy chains and all six of the light chains were derived from different germline genes and are not homologous. Interestingly, more than half of all the somatic mutations acquired during affinity maturation among the six antibodies are located in positions unlikely to contact fluorescein directly. To quantify and compare the dynamics of the antibody-fluorescein complexes, three-pulse photon echo peak shift and transient grating spectroscopy were employed. All of the antibodies exhibited motions on three distinct time scales, ultrafast motions on the <100 fs time scale, diffusive motions on the picosecond time scale, and motions that occur on time scales longer than nanoseconds and thus appear static. However, the exact frequency of the picosecond time scale motion and the relative contribution of the different motions vary significantly among the antibody-chromophore complexes, revealing a high level of dynamic diversity. Using a hierarchical model, we relate the data to features of the antibodies' energy landscapes as well as their flexibility in terms of elasticity and plasticity. In all, the data provide a consistent picture of antibody flexibility

Probing binding hot spots at protein-RNA recognition sites.

PubMed

Barik, Amita; Nithin, Chandran; Karampudi, Naga Bhushana Rao; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

2016-01-29

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein-protein and protein-RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein-RNA recognition sites with desired affinity. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Spreadsheet-based program for alignment of overlapping DNA sequences.

PubMed

Anbazhagan, R; Gabrielson, E

1999-06-01

Molecular biology laboratories frequently face the challenge of aligning small overlapping DNA sequences derived from a long DNA segment. Here, we present a short program that can be used to adapt Excel spreadsheets as a tool for aligning DNA sequences, regardless of their orientation. The program runs on any Windows or Macintosh operating system computer with Excel 97 or Excel 98. The program is available for use as an Excel file, which can be downloaded from the BioTechniques Web site. Upon execution, the program opens a specially designed customized workbook and is capable of identifying overlapping regions between two sequence fragments and displaying the sequence alignment. It also performs a number of specialized functions such as recognition of restriction enzyme cutting sites and CpG island mapping without costly specialized software.

Action Spotting and Recognition Based on a Spatiotemporal Orientation Analysis.

PubMed

Derpanis, Konstantinos G; Sizintsev, Mikhail; Cannons, Kevin J; Wildes, Richard P

2013-03-01

This paper provides a unified framework for the interrelated topics of action spotting, the spatiotemporal detection and localization of human actions in video, and action recognition, the classification of a given video into one of several predefined categories. A novel compact local descriptor of video dynamics in the context of action spotting and recognition is introduced based on visual spacetime oriented energy measurements. This descriptor is efficiently computed directly from raw image intensity data and thereby forgoes the problems typically associated with flow-based features. Importantly, the descriptor allows for the comparison of the underlying dynamics of two spacetime video segments irrespective of spatial appearance, such as differences induced by clothing, and with robustness to clutter. An associated similarity measure is introduced that admits efficient exhaustive search for an action template, derived from a single exemplar video, across candidate video sequences. The general approach presented for action spotting and recognition is amenable to efficient implementation, which is deemed critical for many important applications. For action spotting, details of a real-time GPU-based instantiation of the proposed approach are provided. Empirical evaluation of both action spotting and action recognition on challenging datasets suggests the efficacy of the proposed approach, with state-of-the-art performance documented on standard datasets.

A nonlinear heartbeat dynamics model approach for personalized emotion recognition.

PubMed

Valenza, Gaetano; Citi, Luca; Lanatà, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

2013-01-01

Emotion recognition based on autonomic nervous system signs is one of the ambitious goals of affective computing. It is well-accepted that standard signal processing techniques require relative long-time series of multivariate records to ensure reliability and robustness of recognition and classification algorithms. In this work, we present a novel methodology able to assess cardiovascular dynamics during short-time (i.e. < 10 seconds) affective stimuli, thus overcoming some of the limitations of current emotion recognition approaches. We developed a personalized, fully parametric probabilistic framework based on point-process theory where heartbeat events are modelled using a 2(nd)-order nonlinear autoregressive integrative structure in order to achieve effective performances in short-time affective assessment. Experimental results show a comprehensive emotional characterization of 4 subjects undergoing a passive affective elicitation using a sequence of standardized images gathered from the international affective picture system. Each picture was identified by the IAPS arousal and valence scores as well as by a self-reported emotional label associating a subjective positive or negative emotion. Results show a clear classification of two defined levels of arousal, valence and self-emotional state using features coming from the instantaneous spectrum and bispectrum of the considered RR intervals, reaching up to 90% recognition accuracy.

Diversity in recognition of glycans by F-type lectins and galectins: molecular, structural, and biophysical aspects

PubMed Central

Vasta, Gerardo R.; Ahmed, Hafiz; Bianchet, Mario A.; Fernández-Robledo, José A.; Amzel, L. Mario

2013-01-01

Although lectins are “hard-wired” in the germline, the presence of tandemly arrayed carbohydrate recognition domains (CRDs), of chimeric structures displaying distinct CRDs, of polymorphic genes resulting in multiple isoforms, and in some cases, of a considerable recognition plasticity of their carbohydrate binding sites, significantly expand the lectin ligand-recognition spectrum and lectin functional diversification. Analysis of structural/functional aspects of galectins and F-lectins—the most recently identified lectin family characterized by a unique CRD sequence motif (a distinctive structural fold) and nominal specificity for l-Fuc—has led to a greater understanding of self/nonself recognition by proteins with tandemly arrayed CRDs. For lectins with a single CRD, however, recognition of self and nonself glycans can only be rationalized in terms of protein oligomerization and ligand clustering and presentation. Spatial and temporal changes in lectin expression, secretion, and local concentrations in extracellular microenvironments, as well as structural diversity and spatial display of their carbohydrate ligands on the host or microbial cell surface, are suggestive of a dynamic interplay of their recognition and effector functions in development and immunity. PMID:22973821

Driving style recognition method using braking characteristics based on hidden Markov model

PubMed Central

Wu, Chaozhong; Lyu, Nengchao; Huang, Zhen

2017-01-01

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced. Thirdly, the maximum likelihood logarithm could be implied from the observable parameters. The recognition accuracy of algorithm is verified through experiments and two common pattern recognition algorithms. The results showed that the driving style discrimination based on hidden Markov model algorithm could realize effective discriminant of driving style. PMID:28837580

Phylogenetic analysis and expression profiling of the pattern recognition receptors: Insights into molecular recognition of invading pathogens in Manduca sexta.

PubMed

Zhang, Xiufeng; He, Yan; Cao, Xiaolong; Gunaratna, Ramesh T; Chen, Yun-ru; Blissard, Gary; Kanost, Michael R; Jiang, Haobo

2015-07-01

Pattern recognition receptors (PRRs) detect microbial pathogens and trigger innate immune responses. Previous biochemical studies have elucidated the physiological functions of eleven PRRs in Manduca sexta but our understanding of the recognition process is still limited, lacking genomic perspectives. While 34 C-type lectin-domain proteins and 16 Toll-like receptors are reported in the companion papers, we present here 120 other putative PRRs identified through the genome annotation. These include 76 leucine-rich repeat (LRR) proteins, 14 peptidoglycan recognition proteins, 6 EGF/Nim-domain proteins, 5 β-1,3-glucanase-related proteins, 4 galectins, 4 fibrinogen-related proteins, 3 thioester proteins, 5 immunoglobulin-domain proteins, 2 hemocytins, and 1 Reeler. Sequence alignment and phylogenetic analysis reveal the evolution history of a diverse repertoire of proteins for pathogen recognition. While functions of insect LRR proteins are mostly unknown, their structure diversification is phenomenal: In addition to the Toll homologs, 22 LRR proteins with a signal peptide are expected to be secreted; 18 LRR proteins lacking signal peptides may be cytoplasmic; 36 LRRs with a signal peptide and a transmembrane segment may be non-Toll receptors on the surface of cells. Expression profiles of the 120 genes in 52 tissue samples reflect complex regulation in various developmental stages and physiological states, including some likely by Rel family transcription factors via κB motifs in the promoter regions. This collection of information is expected to facilitate future biochemical studies detailing their respective roles in this model insect. Copyright © 2015 Elsevier Ltd. All rights reserved.

SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition

PubMed Central

Melvin, Iain; Ie, Eugene; Kuang, Rui; Weston, Jason; Stafford, William Noble; Leslie, Christina

2007-01-01

Background Predicting a protein's structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing new representations for protein sequences, called string kernels, for use with support vector machine (SVM) classifiers. However, while some of these approaches exhibit state-of-the-art performance at the binary protein classification problem, i.e. discriminating between a particular protein class and all other classes, few of these studies have addressed the real problem of multi-class superfamily or fold recognition. Moreover, there are only limited software tools and systems for SVM-based protein classification available to the bioinformatics community. Results We present a new multi-class SVM-based protein fold and superfamily recognition system and web server called SVM-Fold, which can be found at . Our system uses an efficient implementation of a state-of-the-art string kernel for sequence profiles, called the profile kernel, where the underlying feature representation is a histogram of inexact matching k-mer frequencies. We also employ a novel machine learning approach to solve the difficult multi-class problem of classifying a sequence of amino acids into one of many known protein structural classes. Binary one-vs-the-rest SVM classifiers that are trained to recognize individual structural classes yield prediction scores that are not comparable, so that standard "one-vs-all" classification fails to perform well. Moreover, SVMs for classes at different levels of the protein structural hierarchy may make useful predictions, but one-vs-all does not try to combine these multiple predictions. To deal with these problems, our method learns relative weights between one-vs-the-rest classifiers and encodes information about the protein structural hierarchy for multi-class prediction. In large-scale benchmark results based on the SCOP database, our code weighting approach significantly improves

Molecular design of sequence specific DNA alkylating agents.

PubMed

Minoshima, Masafumi; Bando, Toshikazu; Shinohara, Ken-ichi; Sugiyama, Hiroshi

2009-01-01

Sequence-specific DNA alkylating agents have great interest for novel approach to cancer chemotherapy. We designed the conjugates between pyrrole (Py)-imidazole (Im) polyamides and DNA alkylating chlorambucil moiety possessing at different positions. The sequence-specific DNA alkylation by conjugates was investigated by using high-resolution denaturing polyacrylamide gel electrophoresis (PAGE). The results showed that polyamide chlorambucil conjugates alkylate DNA at flanking adenines in recognition sequences of Py-Im polyamides, however, the reactivities and alkylation sites were influenced by the positions of conjugation. In addition, we synthesized conjugate between Py-Im polyamide and another alkylating agent, 1-(chloromethyl)-5-hydroxy-1,2-dihydro-3H-benz[e]indole (seco-CBI). DNA alkylation reactivies by both alkylating polyamides were almost comparable. In contrast, cytotoxicities against cell lines differed greatly. These comparative studies would promote development of appropriate sequence-specific DNA alkylating polyamides against specific cancer cells.

Vision-based object detection and recognition system for intelligent vehicles

NASA Astrophysics Data System (ADS)

Ran, Bin; Liu, Henry X.; Martono, Wilfung

1999-01-01

Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

Information-based approach to performance estimation and requirements allocation in multisensor fusion for target recognition

NASA Astrophysics Data System (ADS)

Harney, Robert C.

1997-03-01

A novel methodology offering the potential for resolving two of the significant problems of implementing multisensor target recognition systems, i.e., the rational selection of a specific sensor suite and optimal allocation of requirements among sensors, is presented. Based on a sequence of conjectures (and their supporting arguments) concerning the relationship of extractable information content to recognition performance of a sensor system, a set of heuristics (essentially a reformulation of Johnson's criteria applicable to all sensor and data types) is developed. An approach to quantifying the information content of sensor data is described. Coupling this approach with the widely accepted Johnson's criteria for target recognition capabilities results in a quantitative method for comparing the target recognition ability of diverse sensors (imagers, nonimagers, active, passive, electromagnetic, acoustic, etc.). Extension to describing the performance of multiple sensors is straightforward. The application of the technique to sensor selection and requirements allocation is discussed.

General tensor discriminant analysis and gabor features for gait recognition.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2007-10-01

The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine

Approximated mutual information training for speech recognition using myoelectric signals.

PubMed

Guo, Hua J; Chan, A D C

2006-01-01

A new training algorithm called the approximated maximum mutual information (AMMI) is proposed to improve the accuracy of myoelectric speech recognition using hidden Markov models (HMMs). Previous studies have demonstrated that automatic speech recognition can be performed using myoelectric signals from articulatory muscles of the face. Classification of facial myoelectric signals can be performed using HMMs that are trained using the maximum likelihood (ML) algorithm; however, this algorithm maximizes the likelihood of the observations in the training sequence, which is not directly associated with optimal classification accuracy. The AMMI training algorithm attempts to maximize the mutual information, thereby training the HMMs to optimize their parameters for discrimination. Our results show that AMMI training consistently reduces the error rates compared to these by the ML training, increasing the accuracy by approximately 3% on average.

DNA recognition by peptide nucleic acid-modified PCFs: from models to real samples

NASA Astrophysics Data System (ADS)

Selleri, S.; Coscelli, E.; Poli, F.; Passaro, D.; Cucinotta, A.; Lantano, C.; Corradini, R.; Marchelli, R.

2010-04-01

The increased concern, emerged in the last few years, on food products safety has stimulated the research on new techniques for traceability of raw food materials. DNA analysis is one of the most powerful tools for the certification of food quality, and it is presently performed through the polymerase chain reaction technique. Photonic crystal fibers, due to the presence of an array of air holes running along their length, can be exploited for performing DNA recognition by derivatizing hole surfaces and checking hybridization of complementary nucledotide chains in the sample. In this paper the application of a suspended core photonic crystal fiber in the recognition of DNA sequences is discussed. The fiber is characterized in terms of electromagnetic properties by means of a full-vector modal solver based on the finite element method. Then, the performances of the fiber in the recognition of mall synthetic oligonucleotides are discussed, together with a test of the possibility to extend this recognition to samples of DNA of applicative interest, such as olive leaves.

Sequence Similarity Presenter: a tool for the graphic display of similarities of long sequences for use in presentations.

PubMed

Fröhlich, K U

1994-04-01

A new method for the presentation of alignments of long sequences is described. The degree of identity for the aligned sequences is averaged for sections of a fixed number of residues. The resulting values are converted to shades of gray, with white corresponding to lack of identity and black corresponding to perfect identity. A sequence alignment is represented as a bar filled with varying shades of gray. The display is compact and allows for a fast and intuitive recognition of the distribution of regions with a high similarity. It is well suited for the presentation of alignments of long sequences, e.g. of protein superfamilies, in plenary lectures. The method is implemented as a HyperCard stack for Apple Macintosh computers. Several options for the modification of the output are available (e.g. background reduction, size of the summation window, consideration of amino acid similarity, inclusion of graphic markers to indicate specific domains). The output is a PostScript file which can be printed, imported as EPS or processed further with Adobe Illustrator.

TCRmodel: high resolution modeling of T cell receptors from sequence.

PubMed

Gowthaman, Ragul; Pierce, Brian G

2018-05-22

T cell receptors (TCRs), along with antibodies, are responsible for specific antigen recognition in the adaptive immune response, and millions of unique TCRs are estimated to be present in each individual. Understanding the structural basis of TCR targeting has implications in vaccine design, autoimmunity, as well as T cell therapies for cancer. Given advances in deep sequencing leading to immune repertoire-level TCR sequence data, fast and accurate modeling methods are needed to elucidate shared and unique 3D structural features of these molecules which lead to their antigen targeting and cross-reactivity. We developed a new algorithm in the program Rosetta to model TCRs from sequence, and implemented this functionality in a web server, TCRmodel. This web server provides an easy to use interface, and models are generated quickly that users can investigate in the browser and download. Benchmarking of this method using a set of nonredundant recently released TCR crystal structures shows that models are accurate and compare favorably to models from another available modeling method. This server enables the community to obtain insights into TCRs of interest, and can be combined with methods to model and design TCR recognition of antigens. The TCRmodel server is available at: http://tcrmodel.ibbr.umd.edu/.

Morphological self-organizing feature map neural network with applications to automatic target recognition

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

Recognition of Indian Sign Language in Live Video

NASA Astrophysics Data System (ADS)

Singha, Joyeeta; Das, Karen

2013-05-01

Sign Language Recognition has emerged as one of the important area of research in Computer Vision. The difficulty faced by the researchers is that the instances of signs vary with both motion and appearance. Thus, in this paper a novel approach for recognizing various alphabets of Indian Sign Language is proposed where continuous video sequences of the signs have been considered. The proposed system comprises of three stages: Preprocessing stage, Feature Extraction and Classification. Preprocessing stage includes skin filtering, histogram matching. Eigen values and Eigen Vectors were considered for feature extraction stage and finally Eigen value weighted Euclidean distance is used to recognize the sign. It deals with bare hands, thus allowing the user to interact with the system in natural way. We have considered 24 different alphabets in the video sequences and attained a success rate of 96.25%.

Sequence-Selective Formation of Synthetic H-Bonded Duplexes

PubMed Central

2017-01-01

Oligomers equipped with a sequence of phenol and pyridine N-oxide groups form duplexes via H-bonding interactions between these recognition units. Reductive amination chemistry was used to synthesize all possible 3-mer sequences: AAA, AAD, ADA, DAA, ADD, DAD, DDA, and DDD. Pairwise interactions between the oligomers were investigated using NMR titration and dilution experiments in toluene. The measured association constants vary by 3 orders of magnitude (102 to 105 M–1). Antiparallel sequence-complementary oligomers generally form more stable complexes than mismatched duplexes. Mismatched duplexes that have an excess of H-bond donors are stabilized by the interaction of two phenol donors with one pyridine N-oxide acceptor. Oligomers that have a H-bond donor and acceptor on the ends of the chain can fold to form intramolecular H-bonds in the free state. The 1,3-folding equilibrium competes with duplex formation and lowers the stability of duplexes involving these sequences. As a result, some of the mismatch duplexes are more stable than some of the sequence-complementary duplexes. However, the most stable mismatch duplexes contain DDD and compete with the most stable sequence-complementary duplex, AAA·DDD, so in mixtures that contain all eight sequences, sequence-complementary duplexes dominate. Even higher fidelity sequence selectivity can be achieved if alternating donor–acceptor sequences are avoided. PMID:28857551

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

PubMed

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

A unified framework for gesture recognition and spatiotemporal gesture segmentation.

PubMed

Alon, Jonathan; Athitsos, Vassilis; Yuan, Quan; Sclaroff, Stan

2009-09-01

Within the context of hand gesture recognition, spatiotemporal gesture segmentation is the task of determining, in a video sequence, where the gesturing hand is located and when the gesture starts and ends. Existing gesture recognition methods typically assume either known spatial segmentation or known temporal segmentation, or both. This paper introduces a unified framework for simultaneously performing spatial segmentation, temporal segmentation, and recognition. In the proposed framework, information flows both bottom-up and top-down. A gesture can be recognized even when the hand location is highly ambiguous and when information about when the gesture begins and ends is unavailable. Thus, the method can be applied to continuous image streams where gestures are performed in front of moving, cluttered backgrounds. The proposed method consists of three novel contributions: a spatiotemporal matching algorithm that can accommodate multiple candidate hand detections in every frame, a classifier-based pruning framework that enables accurate and early rejection of poor matches to gesture models, and a subgesture reasoning algorithm that learns which gesture models can falsely match parts of other longer gestures. The performance of the approach is evaluated on two challenging applications: recognition of hand-signed digits gestured by users wearing short-sleeved shirts, in front of a cluttered background, and retrieval of occurrences of signs of interest in a video database containing continuous, unsegmented signing in American Sign Language (ASL).

Sing that Tune: Infants’ Perception of Melody and Lyrics and the Facilitation of Phonetic Recognition in Songs

PubMed Central

Lebedeva, Gina C.; Kuhl, Patricia K.

2010-01-01

To better understand how infants process complex auditory input, this study investigated whether 11-month-old infants perceive the pitch (melodic) or the phonetic (lyric) components within songs as more salient, and whether melody facilitates phonetic recognition. Using a preferential looking paradigm, uni-dimensional and multi-dimensional songs were tested; either the pitch or syllable order of the stimuli varied. As a group, infants detected a change in pitch order in a 4-note sequence when the syllables were redundant (Experiment 1), but did not detect the identical pitch change with variegated syllables (Experiment 2). Infants were better able to detect a change in syllable order in a sung sequence (Experiment 2) than the identical syllable change in a spoken sequence (Experiment 1). These results suggest that by 11 months, infants cannot “ignore” phonetic information in the context of perceptually salient pitch variation. Moreover, the increased phonetic recognition in song contexts mirrors findings that demonstrate advantages of infant-directed speech. Findings are discussed in terms of how stimulus complexity interacts with the perception of sung speech in infancy. PMID:20472295

Hand gesture recognition by analysis of codons

NASA Astrophysics Data System (ADS)

Ramachandra, Poornima; Shrikhande, Neelima

2007-09-01

The problem of recognizing gestures from images using computers can be approached by closely understanding how the human brain tackles it. A full fledged gesture recognition system will substitute mouse and keyboards completely. Humans can recognize most gestures by looking at the characteristic external shape or the silhouette of the fingers. Many previous techniques to recognize gestures dealt with motion and geometric features of hands. In this thesis gestures are recognized by the Codon-list pattern extracted from the object contour. All edges of an image are described in terms of sequence of Codons. The Codons are defined in terms of the relationship between maxima, minima and zeros of curvature encountered as one traverses the boundary of the object. We have concentrated on a catalog of 24 gesture images from the American Sign Language alphabet (Letter J and Z are ignored as they are represented using motion) [2]. The query image given as an input to the system is analyzed and tested against the Codon-lists, which are shape descriptors for external parts of a hand gesture. We have used the Weighted Frequency Indexing Transform (WFIT) approach which is used in DNA sequence matching for matching the Codon-lists. The matching algorithm consists of two steps: 1) the query sequences are converted to short sequences and are assigned weights and, 2) all the sequences of query gestures are pruned into match and mismatch subsequences by the frequency indexing tree based on the weights of the subsequences. The Codon sequences with the most weight are used to determine the most precise match. Once a match is found, the identified gesture and corresponding interpretation are shown as output.

Combining point context and dynamic time warping for online gesture recognition

NASA Astrophysics Data System (ADS)

Mao, Xia; Li, Chen

2017-05-01

Previous gesture recognition methods usually focused on recognizing gestures after the entire gesture sequences were obtained. However, in many practical applications, a system has to identify gestures before they end to give instant feedback. We present an online gesture recognition approach that can realize early recognition of unfinished gestures with low latency. First, a curvature buffer-based point context (CBPC) descriptor is proposed to extract the shape feature of a gesture trajectory. The CBPC descriptor is a complete descriptor with a simple computation, and thus has its superiority in online scenarios. Then, we introduce an online windowed dynamic time warping algorithm to realize online matching between the ongoing gesture and the template gestures. In the algorithm, computational complexity is effectively decreased by adding a sliding window to the accumulative distance matrix. Lastly, the experiments are conducted on the Australian sign language data set and the Kinect hand gesture (KHG) data set. Results show that the proposed method outperforms other state-of-the-art methods especially when gesture information is incomplete.

Structural and sequencing analysis of local target DNA recognition by MLV integrase.

PubMed

Aiyer, Sriram; Rossi, Paolo; Malani, Nirav; Schneider, William M; Chandar, Ashwin; Bushman, Frederic D; Montelione, Gaetano T; Roth, Monica J

2015-06-23

Target-site selection by retroviral integrase (IN) proteins profoundly affects viral pathogenesis. We describe the solution nuclear magnetic resonance structure of the Moloney murine leukemia virus IN (M-MLV) C-terminal domain (CTD) and a structural homology model of the catalytic core domain (CCD). In solution, the isolated MLV IN CTD adopts an SH3 domain fold flanked by a C-terminal unstructured tail. We generated a concordant MLV IN CCD structural model using SWISS-MODEL, MMM-tree and I-TASSER. Using the X-ray crystal structure of the prototype foamy virus IN target capture complex together with our MLV domain structures, residues within the CCD α2 helical region and the CTD β1-β2 loop were predicted to bind target DNA. The role of these residues was analyzed in vivo through point mutants and motif interchanges. Viable viruses with substitutions at the IN CCD α2 helical region and the CTD β1-β2 loop were tested for effects on integration target site selection. Next-generation sequencing and analysis of integration target sequences indicate that the CCD α2 helical region, in particular P187, interacts with the sequences distal to the scissile bonds whereas the CTD β1-β2 loop binds to residues proximal to it. These findings validate our structural model and disclose IN-DNA interactions relevant to target site selection. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

PubMed

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

DNA Shape Dominates Sequence Affinity in Nucleosome Formation

NASA Astrophysics Data System (ADS)

Freeman, Gordon S.; Lequieu, Joshua P.; Hinckley, Daniel M.; Whitmer, Jonathan K.; de Pablo, Juan J.

2014-10-01

Nucleosomes provide the basic unit of compaction in eukaryotic genomes, and the mechanisms that dictate their position at specific locations along a DNA sequence are of central importance to genetics. In this Letter, we employ molecular models of DNA and proteins to elucidate various aspects of nucleosome positioning. In particular, we show how DNA's histone affinity is encoded in its sequence-dependent shape, including subtle deviations from the ideal straight B-DNA form and local variations of minor groove width. By relying on high-precision simulations of the free energy of nucleosome complexes, we also demonstrate that, depending on DNA's intrinsic curvature, histone binding can be dominated by bending interactions or electrostatic interactions. More generally, the results presented here explain how sequence, manifested as the shape of the DNA molecule, dominates molecular recognition in the problem of nucleosome positioning.

3D abnormal behavior recognition in power generation

NASA Astrophysics Data System (ADS)

Wei, Zhenhua; Li, Xuesen; Su, Jie; Lin, Jie

2011-06-01

So far most research of human behavior recognition focus on simple individual behavior, such as wave, crouch, jump and bend. This paper will focus on abnormal behavior with objects carrying in power generation. Such as using mobile communication device in main control room, taking helmet off during working and lying down in high place. Taking account of the color and shape are fixed, we adopted edge detecting by color tracking to recognize object in worker. This paper introduces a method, which using geometric character of skeleton and its angle to express sequence of three-dimensional human behavior data. Then adopting Semi-join critical step Hidden Markov Model, weighing probability of critical steps' output to reduce the computational complexity. Training model for every behavior, mean while select some skeleton frames from 3D behavior sample to form a critical step set. This set is a bridge linking 2D observation behavior with 3D human joints feature. The 3D reconstruction is not required during the 2D behavior recognition phase. In the beginning of recognition progress, finding the best match for every frame of 2D observed sample in 3D skeleton set. After that, 2D observed skeleton frames sample will be identified as a specifically 3D behavior by behavior-classifier. The effectiveness of the proposed algorithm is demonstrated with experiments in similar power generation environment.

Road sign recognition with fuzzy adaptive pre-processing models.

PubMed

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

PubMed Central

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

Crystal structure and novel recognition motif of rho ADP-ribosylating C3 exoenzyme from Clostridium botulinum: structural insights for recognition specificity and catalysis.

PubMed

Han, S; Arvai, A S; Clancy, S B; Tainer, J A

2001-01-05

Clostridium botulinum C3 exoenzyme inactivates the small GTP-binding protein family Rho by ADP-ribosylating asparagine 41, which depolymerizes the actin cytoskeleton. C3 thus represents a major family of the bacterial toxins that transfer the ADP-ribose moiety of NAD to specific amino acids in acceptor proteins to modify key biological activities in eukaryotic cells, including protein synthesis, differentiation, transformation, and intracellular signaling. The 1.7 A resolution C3 exoenzyme structure establishes the conserved features of the core NAD-binding beta-sandwich fold with other ADP-ribosylating toxins despite little sequence conservation. Importantly, the central core of the C3 exoenzyme structure is distinguished by the absence of an active site loop observed in many other ADP-ribosylating toxins. Unlike the ADP-ribosylating toxins that possess the active site loop near the central core, the C3 exoenzyme replaces the active site loop with an alpha-helix, alpha3. Moreover, structural and sequence similarities with the catalytic domain of vegetative insecticidal protein 2 (VIP2), an actin ADP-ribosyltransferase, unexpectedly implicates two adjacent, protruding turns, which join beta5 and beta6 of the toxin core fold, as a novel recognition specificity motif for this newly defined toxin family. Turn 1 evidently positions the solvent-exposed, aromatic side-chain of Phe209 to interact with the hydrophobic region of Rho adjacent to its GTP-binding site. Turn 2 evidently both places the Gln212 side-chain for hydrogen bonding to recognize Rho Asn41 for nucleophilic attack on the anomeric carbon of NAD ribose and holds the key Glu214 catalytic side-chain in the adjacent catalytic pocket. This proposed bipartite ADP-ribosylating toxin turn-turn (ARTT) motif places the VIP2 and C3 toxin classes into a single ARTT family characterized by analogous target protein recognition via turn 1 aromatic and turn 2 hydrogen-bonding side-chain moieties. Turn 2 centrally anchors

Supplement Analysis for the Transmission System Vegetation Management Program FEIS (DOE/EIS-0285-SA-32) - Re-Vegetation Plot Study Along the Lower Monumental-McNary Transmission Line ROW

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

Hutchinson, Ken

2001-11-15

Re-vegetation Plot Study along the Lower Monumental-McNary Transmission Line ROW. The study area sections are located near structures 38/4 and 39/3. The line is a 500kV Single Circuit Transmission Line having an easement width of 165 feet. The proposed work will be accomplished in the indicated sections of the transmission line corridor as indicated on the attached checklist. A summer of 2001 fire burned the subject area leaving the ROW in a bare ground situation. Before, the fire the site was dominated by annual vegetation (cheatgrass) and noxious weeds (yellowstar thistle). As a study of plant succession after the firemore » for a local Boy Scout group, two 100 X 100 foot areas will be identified for study over the next 2-3 years. The two test plots will be identified and permanently marked. One will receive treatment while the other will not be treated and used as a control plot.« less

Method for traffic-sign detection within a picture by color identification and external shape recognition

NASA Astrophysics Data System (ADS)

Falcoff, Daniel E.; Canali, Luis R.

1999-08-01

This work present one method aimed to individualization and recognition of vial signs in route and city. It is based fundamentally on the identification by means of color and form of the vial sing, located in the border of the route or street in city, and then recognition. To do so the obtained RGB image is processed, carrying out diverse filtrates in the sequence of input image, or intensifying the colors of the same ones otherwise, recognizing their silhouette and then segmenting the sign and comparing the symbology of them with the previously stored and classified database.

Sequence Dependent Interactions Between DNA and Single-Walled Carbon Nanotubes

NASA Astrophysics Data System (ADS)

Roxbury, Daniel

It is known that single-stranded DNA adopts a helical wrap around a single-walled carbon nanotube (SWCNT), forming a water-dispersible hybrid molecule. The ability to sort mixtures of SWCNTs based on chirality (electronic species) has recently been demonstrated using special short DNA sequences that recognize certain matching SWCNTs of specific chirality. This thesis investigates the intricacies of DNA-SWCNT sequence-specific interactions through both experimental and molecular simulation studies. The DNA-SWCNT binding strengths were experimentally quantified by studying the kinetics of DNA replacement by a surfactant on the surface of particular SWCNTs. Recognition ability was found to correlate strongly with measured binding strength, e.g. DNA sequence (TAT)4 was found to bind 20 times stronger to the (6,5)-SWCNT than sequence (TAT)4T. Next, using replica exchange molecular dynamics (REMD) simulations, equilibrium structures formed by (a) single-strands and (b) multiple-strands of 12-mer oligonucleotides adsorbed on various SWCNTs were explored. A number of structural motifs were discovered in which the DNA strand wraps around the SWCNT and 'stitches' to itself via hydrogen bonding. Great variability among equilibrium structures was observed and shown to be directly influenced by DNA sequence and SWCNT type. For example, the (6,5)-SWCNT DNA recognition sequence, (TAT)4, was found to wrap in a tight single-stranded right-handed helical conformation. In contrast, DNA sequence T12 forms a beta-barrel left-handed structure on the same SWCNT. These are the first theoretical indications that DNA-based SWCNT selectivity can arise on a molecular level. In a biomedical collaboration with the Mayo Clinic, pathways for DNA-SWCNT internalization into healthy human endothelial cells were explored. Through absorbance spectroscopy, TEM imaging, and confocal fluorescence microscopy, we showed that intracellular concentrations of SWCNTs far exceeded those of the incubation

Detection of EEG-patterns associated with real and imaginary movements using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Pavlov, Alexey N.; Runnova, Anastasiya E.; Maksimenko, Vladimir A.; Grishina, Daria S.; Hramov, Alexander E.

2018-02-01

Authentic recognition of specific patterns of electroencephalograms (EEGs) associated with real and imagi- nary movements is an important stage for the development of brain-computer interfaces. In experiments with untrained participants, the ability to detect the motor-related brain activity based on the multichannel EEG processing is demonstrated. Using the detrended fluctuation analysis, changes in the EEG patterns during the imagination of hand movements are reported. It is discussed how the ability to recognize brain activity related to motor executions depends on the electrode position.

Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

Design and Development of Aerogel-Based Antennas for Aerospace Applications: A Final Report to the NARI Seedling

NASA Technical Reports Server (NTRS)

Meador, Mary Ann B.; Miranda, Felix A.

2014-01-01

As highly porous solids possessing low density and low dielectric permittivity combined with good mechanical properties, polyimide (PI) aerogels offer great promise as an enabling technology for lightweight aircraft antenna systems. While they have been aggressively explored for thermal insulation, barely any effort has been made to leverage these materials for antennas or other applications that take advantage of their aforementioned attributes. In Phase I of the NARI Seedling Project, we fabricated PI aerogels with properties tailored to enable new antenna concepts with performance characteristics (wide bandwidth and high gain) and material properties (low density, environmental stability, and robustness) superior to the state of practice (SOP). We characterized electromagnetic properties, including permittivity, reflectivity, and propagation losses for the aerogels. Simple, prototype planar printed circuit patch antennas from down-selected aerogel formulations were fabricated by molding the aerogels to net shapes and by gold-metalizing the pattern onto the templates via electron beam evaporation in a clean room environment. These aerogel based antennas were benchmarked against current antenna SOP, and exhibited both broader bandwidth and comparable or higher gain performance at appreciably lower mass. Phase II focused on the success of the Phase I results pushing the PI aerogel based antenna technology further by exploring alternative antenna design (i.e., slot coupled antennas) and by examining other techniques for fabricating the antennas including ink jet printing with the goal of optimizing antenna performance and simplifying production. We also examined new aerogel formulations with better moisture and solvent resistance to survive processing conditions. In addition, we investigated more complex antenna designs including passive phased arrays such as 2x4 and 4x8 element arrays to assess the scalability of the aerogel antenna concept. Furthermore, we

Juvenile Salmonid survival, passage, and egress at McNary Dam during tests of temporary spillway weirs, 2009

USGS Publications Warehouse

Adams, N.S.; Liedtke, T.L.

2010-01-01

The TSWs proved to be a relatively effective way to pass juvenile salmonids at McNary Dam (Summary Tables 1.1, 1.2, and 1.3), as was the case in 2007 and 2008. The TSWs passed about 14% of yearling Chinook salmon and 34% of juvenile steelhead with only 5-10% of total project discharge flowing through the TSWs. The TSWs and adjacent spill bays 16-18 passed 27% of subyearling Chinook salmon in the summer with 6-16% of total project discharge flowing through the TSWs. Based on the number of fish passing per the proportion of water flowing through the spillway (i.e., passage effectiveness), the TSWs were the most effective passage route. Passage effectiveness for fish passing through both TSW structures was 2.0 for yearling Chinook salmon, 5.2 for juvenile steelhead, and 2.7 subyearling Chinook salmon for TSW 20 alone. Higher passage of juvenile steelhead through the TSWs could have resulted from juvenile steelhead being more surface-oriented during migration (Plumb et al. 2004; Beeman et al. 2007; Beeman and Maule 2006). Based on passage performance and effectiveness metrics, TSW 4, located on the north end of the spillway, did not perform as well as TSW 20, located on the south end of the spillway. Passage proportions for TSW 4 were at least half that of the levels observed for TSW 20 for both yearling Chinook salmon and juvenile steelhead. This difference may be attributed to TSW location or other variables such as dam operations. Regardless of which TSW was used by fish passing the dam, survival through both TSWs was high (> 0.98 for paired-release dam survival) for yearling Chinook salmon and juvenile steelhead.

Modelling Errors in Automatic Speech Recognition for Dysarthric Speakers

NASA Astrophysics Data System (ADS)

Caballero Morales, Santiago Omar; Cox, Stephen J.

2009-12-01

Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited phonemic repertoire decrease speech recognition accuracy, making conventional speaker adaptation algorithms perform poorly on dysarthric speakers. In this work, rather than adapting the acoustic models, we model the errors made by the speaker and attempt to correct them. For this task, two techniques have been developed: (1) a set of "metamodels" that incorporate a model of the speaker's phonetic confusion matrix into the ASR process; (2) a cascade of weighted finite-state transducers at the confusion matrix, word, and language levels. Both techniques attempt to correct the errors made at the phonetic level and make use of a language model to find the best estimate of the correct word sequence. Our experiments show that both techniques outperform standard adaptation techniques.

Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network.

PubMed

Zhao, Yongjia; Zhou, Suiping

2017-02-28

The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN) without the need to manually extract discriminative features. The CNN's input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI). AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1) the McGill University dataset, which is collected under realistic conditions; and (2) the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns.

Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network

PubMed Central

Zhao, Yongjia; Zhou, Suiping

2017-01-01

The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN) without the need to manually extract discriminative features. The CNN’s input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI). AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1) the McGill University dataset, which is collected under realistic conditions; and (2) the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns. PMID:28264503

Single Molecule Spectroscopy of Amino Acids and Peptides by Recognition Tunneling

PubMed Central

Zhao, Yanan; Ashcroft, Brian; Zhang, Peiming; Liu, Hao; Sen, Suman; Song, Weisi; Im, JongOne; Gyarfas, Brett; Manna, Saikat; Biswas, Sovan; Borges, Chad; Lindsay, Stuart

2014-01-01

The human proteome has millions of protein variants due to alternative RNA splicing and post-translational modifications, and variants that are related to diseases are frequently present in minute concentrations. For DNA and RNA, low concentrations can be amplified using the polymerase chain reaction, but there is no such reaction for proteins. Therefore, the development of single molecule protein sequencing is a critical step in the search for protein biomarkers. Here we show that single amino acids can be identified by trapping the molecules between two electrodes that are coated with a layer of recognition molecules and measuring the electron tunneling current across the junction. A given molecule can bind in more than one way in the junction, and we therefore use a machine-learning algorithm to distinguish between the sets of electronic ‘fingerprints’ associated with each binding motif. With this recognition tunneling technique, we are able to identify D, L enantiomers, a methylated amino acid, isobaric isomers, and short peptides. The results suggest that direct electronic sequencing of single proteins could be possible by sequentially measuring the products of processive exopeptidase digestion, or by using a molecular motor to pull proteins through a tunnel junction integrated with a nanopore. PMID:24705512

Distorted Character Recognition Via An Associative Neural Network

NASA Astrophysics Data System (ADS)

Messner, Richard A.; Szu, Harold H.

1987-03-01

The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

Modeling Geometric-Temporal Context With Directional Pyramid Co-Occurrence for Action Recognition.

PubMed

Yuan, Chunfeng; Li, Xi; Hu, Weiming; Ling, Haibin; Maybank, Stephen J

2014-02-01

In this paper, we present a new geometric-temporal representation for visual action recognition based on local spatio-temporal features. First, we propose a modified covariance descriptor under the log-Euclidean Riemannian metric to represent the spatio-temporal cuboids detected in the video sequences. Compared with previously proposed covariance descriptors, our descriptor can be measured and clustered in Euclidian space. Second, to capture the geometric-temporal contextual information, we construct a directional pyramid co-occurrence matrix (DPCM) to describe the spatio-temporal distribution of the vector-quantized local feature descriptors extracted from a video. DPCM characterizes the co-occurrence statistics of local features as well as the spatio-temporal positional relationships among the concurrent features. These statistics provide strong descriptive power for action recognition. To use DPCM for action recognition, we propose a directional pyramid co-occurrence matching kernel to measure the similarity of videos. The proposed method achieves the state-of-the-art performance and improves on the recognition performance of the bag-of-visual-words (BOVWs) models by a large margin on six public data sets. For example, on the KTH data set, it achieves 98.78% accuracy while the BOVW approach only achieves 88.06%. On both Weizmann and UCF CIL data sets, the highest possible accuracy of 100% is achieved.

Structural requirements for recognition of the HLA-Dw14 class II epitope: A key HLA determinant associated with rheumatoid arthritis

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

Hiraiwa, Akikazu; Yamanaka, Katsuo; Kwok, W.W.

Although HLA genes have been shown to be associated with certain diseases, the basis for this association is unknown. Recent studies, however, have documented patterns of nucleotide sequence variation among some HLA genes associated with a particular disease. For rheumatoid arthritis, HLA genes in most patients have a shared nucleotide sequence encoding a key structural element of an HLA class II polypeptide; this sequence element is critical for the interaction of the HLA molecule with antigenic peptides and with responding T cells, suggestive of a direct role for this sequence element in disease susceptibility. The authors describe the serological andmore » cellular immunologic characteristics encoded by this rheumatoid arthritis-associated sequence element. Site-directed mutagenesis of the DRB1 gene was used to define amino acids critical for antibody and T-cell recognition of this structural element, focusing on residues that distinguish the rheumatoid arthritis-associated alleles Dw4 and Dw14 from a closely related allele, Dw10, not associated with disease. Both the gain and loss of rheumatoid arthritis-associated epitopes were highly dependent on three residues within a discrete domain of the HLA-DR molecule. Recognition was most strongly influenced by the following amino acids (in order): 70 > 71 > 67. Some alloreactive T-cell clones were also influenced by amino acid variation in portions of the DR molecule lying outside the shared sequence element.« less

A TATA binding protein mutant with increased affinity for DNA directs transcription from a reversed TATA sequence in vivo.

PubMed

Spencer, J Vaughn; Arndt, Karen M

2002-12-01

The TATA-binding protein (TBP) nucleates the assembly and determines the position of the preinitiation complex at RNA polymerase II-transcribed genes. We investigated the importance of two conserved residues on the DNA binding surface of Saccharomyces cerevisiae TBP to DNA binding and sequence discrimination. Because they define a significant break in the twofold symmetry of the TBP-TATA interface, Ala100 and Pro191 have been proposed to be key determinants of TBP binding orientation and transcription directionality. In contrast to previous predictions, we found that substitution of an alanine for Pro191 did not allow recognition of a reversed TATA box in vivo; however, the reciprocal change, Ala100 to proline, resulted in efficient utilization of this and other variant TATA sequences. In vitro assays demonstrated that TBP mutants with the A100P and P191A substitutions have increased and decreased affinity for DNA, respectively. The TATA binding defect of TBP with the P191A mutation could be intragenically suppressed by the A100P substitution. Our results suggest that Ala100 and Pro191 are important for DNA binding and sequence recognition by TBP, that the naturally occurring asymmetry of Ala100 and Pro191 is not essential for function, and that a single amino acid change in TBP can lead to elevated DNA binding affinity and recognition of a reversed TATA sequence.

Rice MEL2, the RNA recognition motif (RRM) protein, binds in vitro to meiosis-expressed genes containing U-rich RNA consensus sequences in the 3'-UTR.

PubMed

Miyazaki, Saori; Sato, Yutaka; Asano, Tomoya; Nagamura, Yoshiaki; Nonomura, Ken-Ichi

2015-10-01

Post-transcriptional gene regulation by RNA recognition motif (RRM) proteins through binding to cis-elements in the 3'-untranslated region (3'-UTR) is widely used in eukaryotes to complete various biological processes. Rice MEIOSIS ARRESTED AT LEPTOTENE2 (MEL2) is the RRM protein that functions in the transition to meiosis in proper timing. The MEL2 RRM preferentially associated with the U-rich RNA consensus, UUAGUU[U/A][U/G][A/U/G]U, dependently on sequences and proportionally to MEL2 protein amounts in vitro. The consensus sequences were located in the putative looped structures of the RNA ligand. A genome-wide survey revealed a tendency of MEL2-binding consensus appearing in 3'-UTR of rice genes. Of 249 genes that conserved the consensus in their 3'-UTR, 13 genes spatiotemporally co-expressed with MEL2 in meiotic flowers, and included several genes whose function was supposed in meiosis; such as Replication protein A and OsMADS3. The proteome analysis revealed that the amounts of small ubiquitin-related modifier-like protein and eukaryotic translation initiation factor3-like protein were dramatically altered in mel2 mutant anthers. Taken together with transcriptome and gene ontology results, we propose that the rice MEL2 is involved in the translational regulation of key meiotic genes on 3'-UTRs to achieve the faithful transition of germ cells to meiosis.

Facial Affect Recognition in Violent and Nonviolent Antisocial Behavior Subtypes.

PubMed

Schönenberg, Michael; Mayer, Sarah Verena; Christian, Sandra; Louis, Katharina; Jusyte, Aiste

2016-10-01

Prior studies provide evidence for impaired recognition of distress cues in individuals exhibiting antisocial behavior. However, it remains unclear whether this deficit is generally associated with antisociality or may be specific to violent behavior only. To examine whether there are meaningful differences between the two behavioral dimensions rule-breaking and aggression, violent and nonviolent incarcerated offenders as well as control participants were presented with an animated face recognition task in which a video sequence of a neutral face changed into an expression of one of the six basic emotions. The participants were instructed to press a button as soon as they were able to identify the emotional expression, allowing for an assessment of the perceived emotion onset. Both aggressive and nonaggressive offenders demonstrated a delayed perception of primarily fearful facial cues as compared to controls. These results suggest the importance of targeting impaired emotional processing in both types of antisocial behavior.

Principal Component 2-D Long Short-Term Memory for Font Recognition on Single Chinese Characters.

PubMed

Tao, Dapeng; Lin, Xu; Jin, Lianwen; Li, Xuelong

2016-03-01

Chinese character font recognition (CCFR) has received increasing attention as the intelligent applications based on optical character recognition becomes popular. However, traditional CCFR systems do not handle noisy data effectively. By analyzing in detail the basic strokes of Chinese characters, we propose that font recognition on a single Chinese character is a sequence classification problem, which can be effectively solved by recurrent neural networks. For robust CCFR, we integrate a principal component convolution layer with the 2-D long short-term memory (2DLSTM) and develop principal component 2DLSTM (PC-2DLSTM) algorithm. PC-2DLSTM considers two aspects: 1) the principal component layer convolution operation helps remove the noise and get a rational and complete font information and 2) simultaneously, 2DLSTM deals with the long-range contextual processing along scan directions that can contribute to capture the contrast between character trajectory and background. Experiments using the frequently used CCFR dataset suggest the effectiveness of PC-2DLSTM compared with other state-of-the-art font recognition methods.

From Birdsong to Human Speech Recognition: Bayesian Inference on a Hierarchy of Nonlinear Dynamical Systems

PubMed Central

Yildiz, Izzet B.; von Kriegstein, Katharina; Kiebel, Stefan J.

2013-01-01

Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents—an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments. PMID:24068902

From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

PubMed

Yildiz, Izzet B; von Kriegstein, Katharina; Kiebel, Stefan J

2013-01-01

Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

Measures of Working Memory, Sequence Learning, and Speech Recognition in the Elderly.

ERIC Educational Resources Information Center

Humes, Larry E.; Floyd, Shari S.

2005-01-01

This study describes the measurement of 2 cognitive functions, working-memory capacity and sequence learning, in 2 groups of listeners: young adults with normal hearing and elderly adults with impaired hearing. The measurement of these 2 cognitive abilities with a unique, nonverbal technique capable of auditory, visual, and auditory-visual…

Gene sequence analyses and other DNA-based methods for yeast species recognition

USDA-ARS?s Scientific Manuscript database

DNA sequence analyses, as well as other DNA-based methodologies, have transformed the way in which yeasts are identified. The focus of this chapter will be on the resolution of species using various types of DNA comparisons. In other chapters in this book, Rozpedowska, Piškur and Wolfe discuss mul...

The role of movement in the recognition of famous faces.

PubMed

Lander, K; Christie, F; Bruce, V

1999-11-01

The effects of movement on the recognition of famous faces shown in difficult conditions were investigated. Images were presented as negatives, upside down (inverted), and thresholded. Results indicate that, under all these conditions, moving faces were recognized significantly better than static ones. One possible explanation of this effect could be that a moving sequence contains more static information about the different views and expressions of the face than does a single static image. However, even when the amount of static information was equated (Experiments 3 and 4), there was still an advantage for moving sequences that contained their original dynamic properties. The results suggest that the dynamics of the motion provide additional information, helping to access an established familiar face representation. Both the theoretical and the practical implications for these findings are discussed.

Familiar Person Recognition: Is Autonoetic Consciousness More Likely to Accompany Face Recognition Than Voice Recognition?

NASA Astrophysics Data System (ADS)

Barsics, Catherine; Brédart, Serge

2010-11-01

Autonoetic consciousness is a fundamental property of human memory, enabling us to experience mental time travel, to recollect past events with a feeling of self-involvement, and to project ourselves in the future. Autonoetic consciousness is a characteristic of episodic memory. By contrast, awareness of the past associated with a mere feeling of familiarity or knowing relies on noetic consciousness, depending on semantic memory integrity. Present research was aimed at evaluating whether conscious recollection of episodic memories is more likely to occur following the recognition of a familiar face than following the recognition of a familiar voice. Recall of semantic information (biographical information) was also assessed. Previous studies that investigated the recall of biographical information following person recognition used faces and voices of famous people as stimuli. In this study, the participants were presented with personally familiar people's voices and faces, thus avoiding the presence of identity cues in the spoken extracts and allowing a stricter control of frequency exposure with both types of stimuli (voices and faces). In the present study, the rate of retrieved episodic memories, associated with autonoetic awareness, was significantly higher from familiar faces than familiar voices even though the level of overall recognition was similar for both these stimuli domains. The same pattern was observed regarding semantic information retrieval. These results and their implications for current Interactive Activation and Competition person recognition models are discussed.

Conserved sequence-specific lincRNA-steroid receptor interactions drive transcriptional repression and direct cell fate

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

Hudson, William H.; Pickard, Mark R.; de Vera, Ian Mitchelle S.

2014-12-23

The majority of the eukaryotic genome is transcribed, generating a significant number of long intergenic noncoding RNAs (lincRNAs). Although lincRNAs represent the most poorly understood product of transcription, recent work has shown lincRNAs fulfill important cellular functions. In addition to low sequence conservation, poor understanding of structural mechanisms driving lincRNA biology hinders systematic prediction of their function. Here we report the molecular requirements for the recognition of steroid receptors (SRs) by the lincRNA growth arrest-specific 5 (Gas5), which regulates steroid-mediated transcriptional regulation, growth arrest and apoptosis. We identify the functional Gas5-SR interface and generate point mutations that ablate the SR-Gas5more » lincRNA interaction, altering Gas5-driven apoptosis in cancer cell lines. Further, we find that the Gas5 SR-recognition sequence is conserved among haplorhines, with its evolutionary origin as a splice acceptor site. This study demonstrates that lincRNAs can recognize protein targets in a conserved, sequence-specific manner in order to affect critical cell functions.« less

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2008-12-01

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences. In this paper, a novel building block of proteins called Top-n-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-n-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-n-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-n-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-n-grams and LSA gives significantly better results compared to related methods. The method based on Top-n-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-n-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.

Characterizing the spatio-temporal dynamics of the neural events occurring prior to and up to overt recognition of famous faces.

PubMed

Jemel, Boutheina; Schuller, Anne-Marie; Goffaux, Valérie

2010-10-01

Although it is generally acknowledged that familiar face recognition is fast, mandatory, and proceeds outside conscious control, it is still unclear whether processes leading to familiar face recognition occur in a linear (i.e., gradual) or a nonlinear (i.e., all-or-none) manner. To test these two alternative accounts, we recorded scalp ERPs while participants indicated whether they recognize as familiar the faces of famous and unfamiliar persons gradually revealed in a descending sequence of frames, from the noisier to the least noisy. This presentation procedure allowed us to characterize the changes in scalp ERP responses occurring prior to and up to overt recognition. Our main finding is that gradual and all-or-none processes are possibly involved during overt recognition of familiar faces. Although the N170 and the N250 face-sensitive responses displayed an abrupt activity change at the moment of overt recognition of famous faces, later ERPs encompassing the N400 and late positive component exhibited an incremental increase in amplitude as the point of recognition approached. In addition, famous faces that were not overtly recognized at one trial before recognition elicited larger ERP potentials than unfamiliar faces, probably reflecting a covert recognition process. Overall, these findings present evidence that recognition of familiar faces implicates spatio-temporally complex neural processes exhibiting differential pattern activity changes as a function of recognition state.

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

Towards online iris and periocular recognition under relaxed imaging constraints.

PubMed

Tan, Chun-Wei; Kumar, Ajay

2013-10-01

Online iris recognition using distantly acquired images in a less imaging constrained environment requires the development of a efficient iris segmentation approach and recognition strategy that can exploit multiple features available for the potential identification. This paper presents an effective solution toward addressing such a problem. The developed iris segmentation approach exploits a random walker algorithm to efficiently estimate coarsely segmented iris images. These coarsely segmented iris images are postprocessed using a sequence of operations that can effectively improve the segmentation accuracy. The robustness of the proposed iris segmentation approach is ascertained by providing comparison with other state-of-the-art algorithms using publicly available UBIRIS.v2, FRGC, and CASIA.v4-distance databases. Our experimental results achieve improvement of 9.5%, 4.3%, and 25.7% in the average segmentation accuracy, respectively, for the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with most competing approaches. We also exploit the simultaneously extracted periocular features to achieve significant performance improvement. The joint segmentation and combination strategy suggest promising results and achieve average improvement of 132.3%, 7.45%, and 17.5% in the recognition performance, respectively, from the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with the related competing approaches.

Criteria for the recognition and correlation of sandstone units in the Precambrian and Paleozoic-Mesozoic clastic sequence in the near east

NASA Astrophysics Data System (ADS)

Weissbrod, T.; Perath, I.

A systematic study of the Precambrian and Paleozoic-Mesozoic clastic sequences (Nubian Sandstone) in Israel and Sinai, and a comparative analysis of its stratigraphy in neighbouring countries, has shown that besides the conventional criteria of subdivision (lithology, field appearance, photogeological features, fossil content), additional criteria can be applied, which singly or in mutual conjuction enable the recognition of widespread units and boundaries. These criteria show lateral constancy, and recurrence of a similar vertical sequence over great distances, and are therefore acceptable for the identification of synchronous, region-wide sedimentary units (and consequently, major unconformities). They also enable, once the units are established, to identify detached (not in situ) samples, samples from isolated or discontinous outcrops, borehole material or archive material. The following rock properties were tested and found to be usefuls in stratigraphic interpretation, throughout large distribution areas of the clastic sequence: Landscape, which is basically the response of a particular textural-chemic al aggregate to atmospheric weathering. Characteristic outcrop feature — styles of roundness or massivity, fissuring or fliatin, slope profile, bedding — express a basic uniformity of these platform-type clastics. Colors are often stratigraphically constant over hundreds of kilometers, through various climates and topographies, and express some intrinsic unity of the rock bodies. Grain size and sorting, when cross-plotted, enable to differentiate existing unit. The method requires the analysis of representative numbers of samples. Vertical trends of median grain size and sorting show reversals, typically across unconformities. Feldstar content diminishes from 15-50% in Precambrian-Paleozoic rocks to a mere 5% or less in Mesozoic sandstones — a distinctive regionwide time trend. Dominance of certain feldstar types characterizes Precambrian and Paleozoic

Molecular Evolution of the CYP2D Subfamily in Primates: Purifying Selection on Substrate Recognition Sites without the Frequent or Long-Tract Gene Conversion

PubMed Central

Yasukochi, Yoshiki; Satta, Yoko

2015-01-01

The human cytochrome P450 (CYP) 2D6 gene is a member of the CYP2D gene subfamily, along with the CYP2D7P and CYP2D8P pseudogenes. Although the CYP2D6 enzyme has been studied extensively because of its clinical importance, the evolution of the CYP2D subfamily has not yet been fully understood. Therefore, the goal of this study was to reveal the evolutionary process of the human drug metabolic system. Here, we investigate molecular evolution of the CYP2D subfamily in primates by comparing 14 CYP2D sequences from humans to New World monkey genomes. Window analysis and statistical tests revealed that entire genomic sequences of paralogous genes were extensively homogenized by gene conversion during molecular evolution of CYP2D genes in primates. A neighbor-joining tree based on genomic sequences at the nonsubstrate recognition sites showed that CYP2D6 and CYP2D8 genes were clustered together due to gene conversion. In contrast, a phylogenetic tree using amino acid sequences at substrate recognition sites did not cluster the CYP2D6 and CYP2D8 genes, suggesting that the functional constraint on substrate specificity is one of the causes for purifying selection at the substrate recognition sites. Our results suggest that the CYP2D gene subfamily in primates has evolved to maintain the regioselectivity for a substrate hydroxylation activity between individual enzymes, even though extensive gene conversion has occurred across CYP2D coding sequences. PMID:25808902

[Prosopagnosia and facial expression recognition].

PubMed

Koyama, Shinichi

2014-04-01

This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.

Activity and function recognition for moving and static objects in urban environments from wide-area persistent surveillance inputs

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Bobick, Aaron; Jones, Eric

2010-04-01

In this paper, we describe results from experimental analysis of a model designed to recognize activities and functions of moving and static objects from low-resolution wide-area video inputs. Our model is based on representing the activities and functions using three variables: (i) time; (ii) space; and (iii) structures. The activity and function recognition is achieved by imposing lexical, syntactic, and semantic constraints on the lower-level event sequences. In the reported research, we have evaluated the utility and sensitivity of several algorithms derived from natural language processing and pattern recognition domains. We achieved high recognition accuracy for a wide range of activity and function types in the experiments using Electro-Optical (EO) imagery collected by Wide Area Airborne Surveillance (WAAS) platform.

An Internet-Accessible DNA Sequence Database for Identifying Fusaria from Human and Animal Infections

USDA-ARS?s Scientific Manuscript database

Because less than one-third of clinically relevant fusaria can be accurately identified to species level using phenotypic data (i.e., morphological species recognition), we constructed a three-locus DNA sequence database to facilitate molecular identification of the 69 Fusarium species associated wi...

Do Recognition and Priming Index a Unitary Knowledge Base? Comment on Shanks et al. (2003)

ERIC Educational Resources Information Center

Runger, Dennis; Nagy, Gabriel; Frensch, Peter A.

2009-01-01

Whether sequence learning entails a single or multiple memory systems is a moot issue. Recently, D. R. Shanks, L. Wilkinson, and S. Channon advanced a single-system model that predicts a perfect correlation between true (i.e., error free) response time priming and recognition. The Shanks model is contrasted with a dual-process model that…

Recognition of Drainage Tunnels during Glacier Lake Outburst Events from Terrestrial Image Sequences

NASA Astrophysics Data System (ADS)

Schwalbe, E.; Koschitzki, R.; Maas, H.-G.

2016-06-01

In recent years, many glaciers all over the world have been distinctly retreating and thinning. One of the consequences of this is the increase of so called glacier lake outburst flood events (GLOFs). The mechanisms ruling such GLOF events are still not yet fully understood by glaciologists. Thus, there is a demand for data and measurements that can help to understand and model the phenomena. Thereby, a main issue is to obtain information about the location and formation of subglacial channels through which some lakes, dammed by a glacier, start to drain. The paper will show how photogrammetric image sequence analysis can be used to collect such data. For the purpose of detecting a subglacial tunnel, a camera has been installed in a pilot study to observe the area of the Colonia Glacier (Northern Patagonian Ice Field) where it dams the Lake Cachet II. To verify the hypothesis, that the course of the subglacial tunnel is indicated by irregular surface motion patterns during its collapse, the camera acquired image sequences of the glacier surface during several GLOF events. Applying tracking techniques to these image sequences, surface feature motion trajectories could be obtained for a dense raster of glacier points. Since only a single camera has been used for image sequence acquisition, depth information is required to scale the trajectories. Thus, for scaling and georeferencing of the measurements a GPS-supported photogrammetric network has been measured. The obtained motion fields of the Colonia Glacier deliver information about the glacier's behaviour before during and after a GLOF event. If the daily vertical glacier motion of the glacier is integrated over a period of several days and projected into a satellite image, the location and shape of the drainage channel underneath the glacier becomes visible. The high temporal resolution of the motion fields may also allows for an analysis of the tunnels dynamic in comparison to the changing water level of the lake.

Deep sequencing methods for protein engineering and design.

PubMed

Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Programmable RNA Cleavage and Recognition by a Natural CRISPR-Cas9 System from Neisseria meningitidis.

PubMed

Rousseau, Beth A; Hou, Zhonggang; Gramelspacher, Max J; Zhang, Yan

2018-03-01

The microbial CRISPR systems enable adaptive defense against mobile elements and also provide formidable tools for genome engineering. The Cas9 proteins are type II CRISPR-associated, RNA-guided DNA endonucleases that identify double-stranded DNA targets by sequence complementarity and protospacer adjacent motif (PAM) recognition. Here we report that the type II-C CRISPR-Cas9 from Neisseria meningitidis (Nme) is capable of programmable, RNA-guided, site-specific cleavage and recognition of single-stranded RNA targets and that this ribonuclease activity is independent of the PAM sequence. We define the mechanistic feature and specificity constraint for RNA cleavage by NmeCas9 and also show that nuclease null dNmeCas9 binds to RNA target complementary to CRISPR RNA. Finally, we demonstrate that NmeCas9-catalyzed RNA cleavage can be blocked by three families of type II-C anti-CRISPR proteins. These results fundamentally expand the targeting capacities of CRISPR-Cas9 and highlight the potential utility of NmeCas9 as a single platform to target both RNA and DNA. Copyright © 2018 Elsevier Inc. All rights reserved.

Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

PubMed

Lee, Jong-Seok; Park, Cheol Hoon

2010-08-01

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.

Computer Recognition of Facial Profiles

DTIC Science & Technology

1974-08-01

facial recognition 20. ABSTRACT (Continue on reverse side It necessary and Identify by block number) A system for the recognition of human faces from...21 2.6 Classification Algorithms ........... ... 32 III FACIAL RECOGNITION AND AUTOMATIC TRAINING . . . 37 3.1 Facial Profile Recognition...provide a fair test of the classification system. The work of Goldstein, Harmon, and Lesk [81 indicates, however, that for facial recognition , a ten class

Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty.

PubMed

Mill, Ravi D; O'Connor, Akira R; Dobbins, Ian G

2016-09-01

Optimally discriminating familiar from novel stimuli demands a decision-making process informed by prior expectations. Here we demonstrate that pupillary dilation (PD) responses during recognition memory decisions are modulated by expectations, and more specifically, that pupil dilation increases for unexpected compared to expected recognition. Furthermore, multi-level modeling demonstrated that the time course of the dilation during each individual trial contains separable early and late dilation components, with the early amplitude capturing unexpected recognition, and the later trailing slope reflecting general judgment uncertainty or effort. This is the first demonstration that the early dilation response during recognition is dependent upon observer expectations and that separate recognition expectation and judgment uncertainty components are present in the dilation time course of every trial. The findings provide novel insights into adaptive memory-linked orienting mechanisms as well as the general cognitive underpinnings of the pupillary index of autonomic nervous system activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Structured prediction models for RNN based sequence labeling in clinical text.

PubMed

Jagannatha, Abhyuday N; Yu, Hong

2016-11-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

Structured prediction models for RNN based sequence labeling in clinical text

PubMed Central

Jagannatha, Abhyuday N; Yu, Hong

2016-01-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies1 for structured prediction in order to improve the exact phrase detection of various medical entities. PMID:28004040

An early illness recognition framework using a temporal Smith Waterman algorithm and NLP.

PubMed

Hajihashemi, Zahra; Popescu, Mihail

2013-01-01

In this paper we propose a framework for detecting health patterns based on non-wearable sensor sequence similarity and natural language processing (NLP). In TigerPlace, an aging in place facility from Columbia, MO, we deployed 47 sensor networks together with a nursing electronic health record (EHR) system to provide early illness recognition. The proposed framework utilizes sensor sequence similarity and NLP on EHR nursing comments to automatically notify the physician when health problems are detected. The reported methodology is inspired by genomic sequence annotation using similarity algorithms such as Smith Waterman (SW). Similarly, for each sensor sequence, we associate health concepts extracted from the nursing notes using Metamap, a NLP tool provided by Unified Medical Language System (UMLS). Since sensor sequences, unlike genomics ones, have an associated time dimension we propose a temporal variant of SW (TSW) to account for time. The main challenges presented by our framework are finding the most suitable time sequence similarity and aggregation of the retrieved UMLS concepts. On a pilot dataset from three Tiger Place residents, with a total of 1685 sensor days and 626 nursing records, we obtained an average precision of 0.64 and a recall of 0.37.

Improved Hip-Based Individual Recognition Using Wearable Motion Recording Sensor

NASA Astrophysics Data System (ADS)

Gafurov, Davrondzhon; Bours, Patrick

In todays society the demand for reliable verification of a user identity is increasing. Although biometric technologies based on fingerprint or iris can provide accurate and reliable recognition performance, they are inconvenient for periodic or frequent re-verification. In this paper we propose a hip-based user recognition method which can be suitable for implicit and periodic re-verification of the identity. In our approach we use a wearable accelerometer sensor attached to the hip of the person, and then the measured hip motion signal is analysed for identity verification purposes. The main analyses steps consists of detecting gait cycles in the signal and matching two sets of detected gait cycles. Evaluating the approach on a hip data set consisting of 400 gait sequences (samples) from 100 subjects, we obtained equal error rate (EER) of 7.5% and identification rate at rank 1 was 81.4%. These numbers are improvements by 37.5% and 11.2% respectively of the previous study using the same data set.

Electronic single-molecule identification of carbohydrate isomers by recognition tunnelling

NASA Astrophysics Data System (ADS)

Im, Jongone; Biswas, Sovan; Liu, Hao; Zhao, Yanan; Sen, Suman; Biswas, Sudipta; Ashcroft, Brian; Borges, Chad; Wang, Xu; Lindsay, Stuart; Zhang, Peiming

2016-12-01

Carbohydrates are one of the four main building blocks of life, and are categorized as monosaccharides (sugars), oligosaccharides and polysaccharides. Each sugar can exist in two alternative anomers (in which a hydroxy group at C-1 takes different orientations) and each pair of sugars can form different epimers (isomers around the stereocentres connecting the sugars). This leads to a vast combinatorial complexity, intractable to mass spectrometry and requiring large amounts of sample for NMR characterization. Combining measurements of collision cross section with mass spectrometry (IM-MS) helps, but many isomers are still difficult to separate. Here, we show that recognition tunnelling (RT) can classify many anomers and epimers via the current fluctuations they produce when captured in a tunnel junction functionalized with recognition molecules. Most importantly, RT is a nanoscale technique utilizing sub-picomole quantities of analyte. If integrated into a nanopore, RT would provide a unique approach to sequencing linear polysaccharides.

Pattern recognition and feature extraction with an optical Hough transform

NASA Astrophysics Data System (ADS)

Fernández, Ariel

2016-09-01

Pattern recognition and localization along with feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for the recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital- only methods. Starting from the integral representation of the GHT, it is possible to device an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a rotating pupil mask for orientation variation, implemented on a high-contrast spatial light modulator (SLM). Real-time (as limited by the frame rate of the device used to capture the GHT) can also be achieved, allowing for the processing of video sequences. Besides, by thresholding of the GHT (with the aid of another SLM) and inverse transforming (which is optically achieved in the incoherent system under appropriate focusing setting), the previously detected features of interest can be extracted.

Direct Sequence Detection of Structured H5 Influenza Viral RNA

PubMed Central

Kerby, Matthew B.; Freeman, Sarah; Prachanronarong, Kristina; Artenstein, Andrew W.; Opal, Steven M.; Tripathi, Anubhav

2008-01-01

We describe the development of sequence-specific molecular beacons (dual-labeled DNA probes) for identification of the H5 influenza subtype, cleavage motif, and receptor specificity when hybridized directly with in vitro transcribed viral RNA (vRNA). The cloned hemagglutinin segment from a highly pathogenic H5N1 strain, A/Hanoi/30408/2005(H5N1), isolated from humans was used as template for in vitro transcription of sense-strand vRNA. The hybridization behavior of vRNA and a conserved subtype probe was characterized experimentally by varying conditions of time, temperature, and Mg2+ to optimize detection. Comparison of the hybridization rates of probe to DNA and RNA targets indicates that conformational switching of influenza RNA structure is a rate-limiting step and that the secondary structure of vRNA dominates the binding kinetics. The sensitivity and specificity of probe recognition of other H5 strains was calculated from sequence matches to the National Center for Biotechnology Information influenza database. The hybridization specificity of the subtype probes was experimentally verified with point mutations within the probe loop at five locations corresponding to the other human H5 strains. The abundance frequencies of the hemagglutinin cleavage motif and sialic acid recognition sequences were experimentally tested for H5 in all host viral species. Although the detection assay must be coupled with isothermal amplification on the chip, the new probes form the basis of a portable point-of-care diagnostic device for influenza subtyping. PMID:18403607

Structure and immune recognition of trimeric pre-fusion HIV-1 Env

DOE PAGES

Pancera, Marie; Zhou, Tongqing; Druz, Aliaksandr; ...

2014-10-08

The human immunodeficiency virus type 1 (HIV-1) envelope (Env) spike, comprising three gp120 and three gp41 subunits, is a conformational machine that facilitates HIV-1 entry by rearranging from a mature unliganded state, through receptor-bound intermediates, to a post-fusion state. As the sole viral antigen on the HIV-1 virion surface, Env is both the target of neutralizing antibodies and a focus of vaccine efforts. Here we report the structure at 3.5 Å resolution for an HIV-1 Env trimer captured in a mature closed state by antibodies PGT122 and 35O22. This structure reveals the pre-fusion conformation of gp41, indicates rearrangements needed formore » fusion activation, and defines parameters of immune evasion and immune recognition. Pre-fusion gp41 encircles amino- and carboxy-terminal strands of gp120 with four helices that form a membrane-proximal collar, fastened by insertion of a fusion peptide-proximal methionine into a gp41-tryptophan clasp. Spike rearrangements required for entry involve opening the clasp and expelling the termini. In conclusion, N-linked glycosylation and sequence-variable regions cover the pre-fusion closed spike; we used chronic cohorts to map the prevalence and location of effective HIV-1-neutralizing responses, which were distinguished by their recognition of N-linked glycan and tolerance for epitope-sequence variation.« less

Structure and immune recognition of trimeric pre-fusion HIV-1 Env

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

Pancera, Marie; Zhou, Tongqing; Druz, Aliaksandr

The human immunodeficiency virus type 1 (HIV-1) envelope (Env) spike, comprising three gp120 and three gp41 subunits, is a conformational machine that facilitates HIV-1 entry by rearranging from a mature unliganded state, through receptor-bound intermediates, to a post-fusion state. As the sole viral antigen on the HIV-1 virion surface, Env is both the target of neutralizing antibodies and a focus of vaccine efforts. Here we report the structure at 3.5 Å resolution for an HIV-1 Env trimer captured in a mature closed state by antibodies PGT122 and 35O22. This structure reveals the pre-fusion conformation of gp41, indicates rearrangements needed formore » fusion activation, and defines parameters of immune evasion and immune recognition. Pre-fusion gp41 encircles amino- and carboxy-terminal strands of gp120 with four helices that form a membrane-proximal collar, fastened by insertion of a fusion peptide-proximal methionine into a gp41-tryptophan clasp. Spike rearrangements required for entry involve opening the clasp and expelling the termini. In conclusion, N-linked glycosylation and sequence-variable regions cover the pre-fusion closed spike; we used chronic cohorts to map the prevalence and location of effective HIV-1-neutralizing responses, which were distinguished by their recognition of N-linked glycan and tolerance for epitope-sequence variation.« less

Variability sensitivity of dynamic texture based recognition in clinical CT data

NASA Astrophysics Data System (ADS)

Kwitt, Roland; Razzaque, Sharif; Lowell, Jeffrey; Aylward, Stephen

2014-03-01

Dynamic texture recognition using a database of template models has recently shown promising results for the task of localizing anatomical structures in Ultrasound video. In order to understand its clinical value, it is imperative to study the sensitivity with respect to inter-patient variability as well as sensitivity to acquisition parameters such as Ultrasound probe angle. Fully addressing patient and acquisition variability issues, however, would require a large database of clinical Ultrasound from many patients, acquired in a multitude of controlled conditions, e.g., using a tracked transducer. Since such data is not readily attainable, we advocate an alternative evaluation strategy using abdominal CT data as a surrogate. In this paper, we describe how to replicate Ultrasound variabilities by extracting subvolumes from CT and interpreting the image material as an ordered sequence of video frames. Utilizing this technique, and based on a database of abdominal CT from 45 patients, we report recognition results on an organ (kidney) recognition task, where we try to discriminate kidney subvolumes/videos from a collection of randomly sampled negative instances. We demonstrate that (1) dynamic texture recognition is relatively insensitive to inter-patient variation while (2) viewing angle variability needs to be accounted for in the template database. Since naively extending the template database to counteract variability issues can lead to impractical database sizes, we propose an alternative strategy based on automated identification of a small set of representative models.

Chirality- and sequence-selective successive self-sorting via specific homo- and complementary-duplex formations

PubMed Central

Makiguchi, Wataru; Tanabe, Junki; Yamada, Hidekazu; Iida, Hiroki; Taura, Daisuke; Ousaka, Naoki; Yashima, Eiji

2015-01-01

Self-recognition and self-discrimination within complex mixtures are of fundamental importance in biological systems, which entirely rely on the preprogrammed monomer sequences and homochirality of biological macromolecules. Here we report artificial chirality- and sequence-selective successive self-sorting of chiral dimeric strands bearing carboxylic acid or amidine groups joined by chiral amide linkers with different sequences through homo- and complementary-duplex formations. A mixture of carboxylic acid dimers linked by racemic-1,2-cyclohexane bis-amides with different amide sequences (NHCO or CONH) self-associate to form homoduplexes in a completely sequence-selective way, the structures of which are different from each other depending on the linker amide sequences. The further addition of an enantiopure amide-linked amidine dimer to a mixture of the racemic carboxylic acid dimers resulted in the formation of a single optically pure complementary duplex with a 100% diastereoselectivity and complete sequence specificity stabilized by the amidinium–carboxylate salt bridges, leading to the perfect chirality- and sequence-selective duplex formation. PMID:26051291

Definition of a high-affinity Gag recognition structure mediating packaging of a retroviral RNA genome

PubMed Central

Gherghe, Cristina; Lombo, Tania; Leonard, Christopher W.; Datta, Siddhartha A. K.; Bess, Julian W.; Gorelick, Robert J.; Rein, Alan; Weeks, Kevin M.

2010-01-01

All retroviral genomic RNAs contain a cis-acting packaging signal by which dimeric genomes are selectively packaged into nascent virions. However, it is not understood how Gag (the viral structural protein) interacts with these signals to package the genome with high selectivity. We probed the structure of murine leukemia virus RNA inside virus particles using SHAPE, a high-throughput RNA structure analysis technology. These experiments showed that NC (the nucleic acid binding domain derived from Gag) binds within the virus to the sequence UCUG-UR-UCUG. Recombinant Gag and NC proteins bound to this same RNA sequence in dimeric RNA in vitro; in all cases, interactions were strongest with the first U and final G in each UCUG element. The RNA structural context is critical: High-affinity binding requires base-paired regions flanking this motif, and two UCUG-UR-UCUG motifs are specifically exposed in the viral RNA dimer. Mutating the guanosine residues in these two motifs—only four nucleotides per genomic RNA—reduced packaging 100-fold, comparable to the level of nonspecific packaging. These results thus explain the selective packaging of dimeric RNA. This paradigm has implications for RNA recognition in general, illustrating how local context and RNA structure can create information-rich recognition signals from simple single-stranded sequence elements in large RNAs. PMID:20974908

Identifying mRNA sequence elements for target recognition by human Argonaute proteins

PubMed Central

Li, Jingjing; Kim, TaeHyung; Nutiu, Razvan; Ray, Debashish; Hughes, Timothy R.; Zhang, Zhaolei

2014-01-01

It is commonly known that mammalian microRNAs (miRNAs) guide the RNA-induced silencing complex (RISC) to target mRNAs through the seed-pairing rule. However, recent experiments that coimmunoprecipitate the Argonaute proteins (AGOs), the central catalytic component of RISC, have consistently revealed extensive AGO-associated mRNAs that lack seed complementarity with miRNAs. We herein test the hypothesis that AGO has its own binding preference within target mRNAs, independent of guide miRNAs. By systematically analyzing the data from in vivo cross-linking experiments with human AGOs, we have identified a structurally accessible and evolutionarily conserved region (∼10 nucleotides in length) that alone can accurately predict AGO–mRNA associations, independent of the presence of miRNA binding sites. Within this region, we further identified an enriched motif that was replicable on independent AGO-immunoprecipitation data sets. We used RNAcompete to enumerate the RNA-binding preference of human AGO2 to all possible 7-mer RNA sequences and validated the AGO motif in vitro. These findings reveal a novel function of AGOs as sequence-specific RNA-binding proteins, which may aid miRNAs in recognizing their targets with high specificity. PMID:24663241

Profiles of Discourse Recognition

ERIC Educational Resources Information Center

Singer, Murray

2013-01-01

A discourse recognition theory derived from more general memory formulations would be broad in its psychological implications. This study compared discourse recognition with some established profiles of item recognition. Participants read 10 stories either once or twice each. They then rated their confidence in recognizing explicit, paraphrased,…

Sudden Event Recognition: A Survey

PubMed Central

Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

2013-01-01

Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

Sequence-controlled methacrylic multiblock copolymers via sulfur-free RAFT emulsion polymerization

NASA Astrophysics Data System (ADS)

Engelis, Nikolaos G.; Anastasaki, Athina; Nurumbetov, Gabit; Truong, Nghia P.; Nikolaou, Vasiliki; Shegiwal, Ataulla; Whittaker, Michael R.; Davis, Thomas P.; Haddleton, David M.

2017-02-01

Translating the precise monomer sequence control achieved in nature over macromolecular structure (for example, DNA) to whole synthetic systems has been limited due to the lack of efficient synthetic methodologies. So far, chemists have only been able to synthesize monomer sequence-controlled macromolecules by means of complex, time-consuming and iterative chemical strategies such as solid-state Merrifield-type approaches or molecularly dissolved solution-phase systems. Here, we report a rapid and quantitative synthesis of sequence-controlled multiblock polymers in discrete stable nanoscale compartments via an emulsion polymerization approach in which a vinyl-terminated macromolecule is used as an efficient chain-transfer agent. This approach is environmentally friendly, fully translatable to industry and thus represents a significant advance in the development of complex macromolecule synthesis, where a high level of molecular precision or monomer sequence control confers potential for molecular targeting, recognition and biocatalysis, as well as molecular information storage.

Examining the Relationships among Item Recognition, Source Recognition, and Recall from an Individual Differences Perspective

ERIC Educational Resources Information Center

Unsworth, Nash; Brewer, Gene A.

2009-01-01

The authors of the current study examined the relationships among item-recognition, source-recognition, free recall, and other memory and cognitive ability tasks via an individual differences analysis. Two independent sources of variance contributed to item-recognition and source-recognition performance, and these two constructs related…

Network Analysis Reveals the Recognition Mechanism for Mannose-binding Lectins

NASA Astrophysics Data System (ADS)

Zhao, Yunjie; Jian, Yiren; Zeng, Chen; Computational Biophysics Lab Team

The specific carbohydrate binding of mannose-binding lectin (MBL) protein in plants makes it a very useful molecular tool for cancer cell detection and other applications. The biological states of most MBL proteins are dimeric. Using dynamics network analysis on molecular dynamics (MD) simulations on the model protein of MBL, we elucidate the short- and long-range driving forces behind the dimer formation. The results are further supported by sequence coevolution analysis. We propose a general framework for deciphering the recognition mechanism underlying protein-protein interactions that may have potential applications in signaling pathways.

Conformational Smear Characterization and Binning of Single-Molecule Conductance Measurements for Enhanced Molecular Recognition.

PubMed

Korshoj, Lee E; Afsari, Sepideh; Chatterjee, Anushree; Nagpal, Prashant

2017-11-01

Electronic conduction or charge transport through single molecules depends primarily on molecular structure and anchoring groups and forms the basis for a wide range of studies from molecular electronics to DNA sequencing. Several high-throughput nanoelectronic methods such as mechanical break junctions, nanopores, conductive atomic force microscopy, scanning tunneling break junctions, and static nanoscale electrodes are often used for measuring single-molecule conductance. In these measurements, "smearing" due to conformational changes and other entropic factors leads to large variances in the observed molecular conductance, especially in individual measurements. Here, we show a method for characterizing smear in single-molecule conductance measurements and demonstrate how binning measurements according to smear can significantly enhance the use of individual conductance measurements for molecular recognition. Using quantum point contact measurements on single nucleotides within DNA macromolecules, we demonstrate that the distance over which molecular junctions are maintained is a measure of smear, and the resulting variance in unbiased single measurements depends on this smear parameter. Our ability to identify individual DNA nucleotides at 20× coverage increases from 81.3% accuracy without smear analysis to 93.9% with smear characterization and binning (SCRIB). Furthermore, merely 7 conductance measurements (7× coverage) are needed to achieve 97.8% accuracy for DNA nucleotide recognition when only low molecular smear measurements are used, which represents a significant improvement over contemporary sequencing methods. These results have important implications in a broad range of molecular electronics applications from designing robust molecular switches to nanoelectronic DNA sequencing.

A robust recognition and accurate locating method for circular coded diagonal target

NASA Astrophysics Data System (ADS)

Bao, Yunna; Shang, Yang; Sun, Xiaoliang; Zhou, Jiexin

2017-10-01

As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this paper, a new circular coded target designed by RockeTech technology Corp. Ltd is analyzed and studied, which is called circular coded diagonal target (CCDT). A novel detection and recognition method with good robustness is proposed in the paper, and implemented on Visual Studio. In this algorithm, firstly, the ellipse features of the center circle are used for rough positioning. Then, according to the characteristics of the center diagonal target, a circular frequency filter is designed to choose the correct center circle and eliminates non-target noise. The precise positioning of the coded target is done by the correlation coefficient fitting extreme value method. Finally, the coded target recognition is achieved by decoding the binary sequence in the outer ring of the extracted target. To test the proposed algorithm, this paper has carried out simulation experiments and real experiments. The results show that the CCDT recognition and accurate locating method proposed in this paper can robustly recognize and accurately locate the targets in complex and noisy background.

Molecular evolution of the CYP2D subfamily in primates: purifying selection on substrate recognition sites without the frequent or long-tract gene conversion.

PubMed

Yasukochi, Yoshiki; Satta, Yoko

2015-03-25

The human cytochrome P450 (CYP) 2D6 gene is a member of the CYP2D gene subfamily, along with the CYP2D7P and CYP2D8P pseudogenes. Although the CYP2D6 enzyme has been studied extensively because of its clinical importance, the evolution of the CYP2D subfamily has not yet been fully understood. Therefore, the goal of this study was to reveal the evolutionary process of the human drug metabolic system. Here, we investigate molecular evolution of the CYP2D subfamily in primates by comparing 14 CYP2D sequences from humans to New World monkey genomes. Window analysis and statistical tests revealed that entire genomic sequences of paralogous genes were extensively homogenized by gene conversion during molecular evolution of CYP2D genes in primates. A neighbor-joining tree based on genomic sequences at the nonsubstrate recognition sites showed that CYP2D6 and CYP2D8 genes were clustered together due to gene conversion. In contrast, a phylogenetic tree using amino acid sequences at substrate recognition sites did not cluster the CYP2D6 and CYP2D8 genes, suggesting that the functional constraint on substrate specificity is one of the causes for purifying selection at the substrate recognition sites. Our results suggest that the CYP2D gene subfamily in primates has evolved to maintain the regioselectivity for a substrate hydroxylation activity between individual enzymes, even though extensive gene conversion has occurred across CYP2D coding sequences. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Performing the unexplainable: Implicit task performance reveals individually reliable sequence learning without explicit knowledge

PubMed Central

Sanchez, Daniel J.; Gobel, Eric W.; Reber, Paul J.

2015-01-01

Memory-impaired patients express intact implicit perceptual–motor sequence learning, but it has been difficult to obtain a similarly clear dissociation in healthy participants. When explicit memory is intact, participants acquire some explicit knowledge and performance improvements from implicit learning may be subtle. Therefore, it is difficult to determine whether performance exceeds what could be expected on the basis of the concomitant explicit knowledge. Using a challenging new sequence-learning task, robust implicit learning was found in healthy participants with virtually no associated explicit knowledge. Participants trained on a repeating sequence that was selected randomly from a set of five. On a performance test of all five sequences, performance was best on the trained sequence, and two-thirds of the participants exhibited individually reliable improvement (by chi-square analysis). Participants could not reliably indicate which sequence had been trained by either recognition or recall. Only by expressing their knowledge via performance were participants able to indicate which sequence they had learned. PMID:21169570

Structural basis of UGUA recognition by the Nudix protein CFIm25 and implications for a regulatory role in mRNA 3′ processing

PubMed Central

Yang, Qin; Gilmartin, Gregory M.; Doublié, Sylvie

2010-01-01

Human Cleavage Factor Im (CFIm) is an essential component of the pre-mRNA 3′ processing complex that functions in the regulation of poly(A) site selection through the recognition of UGUA sequences upstream of the poly(A) site. Although the highly conserved 25 kDa subunit (CFIm25) of the CFIm complex possesses a characteristic α/β/α Nudix fold, CFIm25 has no detectable hydrolase activity. Here we report the crystal structures of the human CFIm25 homodimer in complex with UGUAAA and UUGUAU RNA sequences. CFIm25 is the first Nudix protein to be reported to bind RNA in a sequence-specific manner. The UGUA sequence contributes to binding specificity through an intramolecular G:A Watson–Crick/sugar-edge base interaction, an unusual pairing previously found to be involved in the binding specificity of the SAM-III riboswitch. The structures, together with mutational data, suggest a novel mechanism for the simultaneous sequence-specific recognition of two UGUA elements within the pre-mRNA. Furthermore, the mutually exclusive binding of RNA and the signaling molecule Ap4A (diadenosine tetraphosphate) by CFIm25 suggests a potential role for small molecules in the regulation of mRNA 3′ processing. PMID:20479262

Structural basis of UGUA recognition by the Nudix protein CFI(m)25 and implications for a regulatory role in mRNA 3' processing.

PubMed

Yang, Qin; Gilmartin, Gregory M; Doublié, Sylvie

2010-06-01

Human Cleavage Factor Im (CFI(m)) is an essential component of the pre-mRNA 3' processing complex that functions in the regulation of poly(A) site selection through the recognition of UGUA sequences upstream of the poly(A) site. Although the highly conserved 25 kDa subunit (CFI(m)25) of the CFI(m) complex possesses a characteristic alpha/beta/alpha Nudix fold, CFI(m)25 has no detectable hydrolase activity. Here we report the crystal structures of the human CFI(m)25 homodimer in complex with UGUAAA and UUGUAU RNA sequences. CFI(m)25 is the first Nudix protein to be reported to bind RNA in a sequence-specific manner. The UGUA sequence contributes to binding specificity through an intramolecular G:A Watson-Crick/sugar-edge base interaction, an unusual pairing previously found to be involved in the binding specificity of the SAM-III riboswitch. The structures, together with mutational data, suggest a novel mechanism for the simultaneous sequence-specific recognition of two UGUA elements within the pre-mRNA. Furthermore, the mutually exclusive binding of RNA and the signaling molecule Ap(4)A (diadenosine tetraphosphate) by CFI(m)25 suggests a potential role for small molecules in the regulation of mRNA 3' processing.

Control of transcriptional pausing by biased thermal fluctuations on repetitive genomic sequences

PubMed Central

Imashimizu, Masahiko; Afek, Ariel; Takahashi, Hiroki; Lubkowska, Lucyna; Lukatsky, David B.

2016-01-01

In the process of transcription elongation, RNA polymerase (RNAP) pauses at highly nonrandom positions across genomic DNA, broadly regulating transcription; however, molecular mechanisms responsible for the recognition of such pausing positions remain poorly understood. Here, using a combination of statistical mechanical modeling and high-throughput sequencing and biochemical data, we evaluate the effect of thermal fluctuations on the regulation of RNAP pausing. We demonstrate that diffusive backtracking of RNAP, which is biased by repetitive DNA sequence elements, causes transcriptional pausing. This effect stems from the increased microscopic heterogeneity of an elongation complex, and thus is entropy-dominated. This report shows a linkage between repetitive sequence elements encoded in the genome and regulation of RNAP pausing driven by thermal fluctuations. PMID:27830653

Closely Related Antibody Receptors Exploit Fundamentally Different Strategies for Steroid Recognition

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

Verdino, P.; Aldag, C.; Hilvert, D.

2009-05-26

Molecular recognition by the adaptive immune system relies on specific high-affinity antibody receptors that are generated from a restricted set of starting sequences through homologous recombination and somatic mutation. The steroid binding antibody DB3 and the catalytic Diels-Alderase antibody 1E9 derive from the same germ line sequences but exhibit very distinct specificities and functions. However, mutation of only two of the 36 sequence differences in the variable domains, Leu{sup H47}Trp and Arg{sup H100}Trp, converts 1E9 into a high-affinity steroid receptor with a ligand recognition profile similar to DB3. To understand how these changes switch binding specificity and function, we determinedmore » the crystal structures of the 1E9 Leu{sup H47}Trp/Arg{sup H100}Trp double mutant (1E9dm) as an unliganded Fab at 2.05 {angstrom} resolution and in complex with two configurationally distinct steroids at 2.40 and 2.85 {angstrom}. Surprisingly, despite the functional mimicry of DB3, 1E9dm employs a distinct steroid binding mechanism. Extensive structural rearrangements occur in the combining site, where residue H47 acts as a specificity switch and H100 adapts to different ligands. Unlike DB3, 1E9dm does not use alternative binding pockets or different sets of hydrogen-bonding interactions to bind configurationally distinct steroids. Rather, the different steroids are inserted more deeply into the 1E9dm combining site, creating more hydrophobic contacts that energetically compensate for the lack of hydrogen bonds. These findings demonstrate how subtle mutations within an existing molecular scaffold can dramatically modulate the function of immune receptors by inducing unanticipated, but compensating, mechanisms of ligand interaction.« less

The Legal Recognition of Sign Languages

ERIC Educational Resources Information Center

De Meulder, Maartje

2015-01-01

This article provides an analytical overview of the different types of explicit legal recognition of sign languages. Five categories are distinguished: constitutional recognition, recognition by means of general language legislation, recognition by means of a sign language law or act, recognition by means of a sign language law or act including…

PNA containing isocytidine nucleobase: synthesis and recognition of double helical RNA

PubMed Central

Zengeya, Thomas; Li, Ming; Rozners, Eriks

2011-01-01

Peptide nucleic acid (PNA1) containing a 5-methylisocytidine (iC) nucleobase has been synthesized. Triple helix formation between PNA1 and RNA hairpins having variable base pairs interacting with iC was studied using isothermal titration calorimetry. The iC nucleobase recognized the proposed target, C-G inversion in polypurine tract of RNA, with slightly higher affinity than the natural nucleobases, though the sequence selectivity of recognition was low. Compared to non-modified PNA, PNA1 had lower affinity for its RNA target. PMID:21333533

Toward open set recognition.

PubMed

Scheirer, Walter J; de Rezende Rocha, Anderson; Sapkota, Archana; Boult, Terrance E

2013-07-01

To date, almost all experimental evaluations of machine learning-based recognition algorithms in computer vision have taken the form of "closed set" recognition, whereby all testing classes are known at training time. A more realistic scenario for vision applications is "open set" recognition, where incomplete knowledge of the world is present at training time, and unknown classes can be submitted to an algorithm during testing. This paper explores the nature of open set recognition and formalizes its definition as a constrained minimization problem. The open set recognition problem is not well addressed by existing algorithms because it requires strong generalization. As a step toward a solution, we introduce a novel "1-vs-set machine," which sculpts a decision space from the marginal distances of a 1-class or binary SVM with a linear kernel. This methodology applies to several different applications in computer vision where open set recognition is a challenging problem, including object recognition and face verification. We consider both in this work, with large scale cross-dataset experiments performed over the Caltech 256 and ImageNet sets, as well as face matching experiments performed over the Labeled Faces in the Wild set. The experiments highlight the effectiveness of machines adapted for open set evaluation compared to existing 1-class and binary SVMs for the same tasks.

Structural basis of DNA folding and recognition in an AMP-DNA aptamer complex: distinct architectures but common recognition motifs for DNA and RNA aptamers complexed to AMP.

PubMed

Lin, C H; Patel, D J

1997-11-01

Structural studies by nuclear magnetic resonance (NMR) of RNA and DNA aptamer complexes identified through in vitro selection and amplification have provided a wealth of information on RNA and DNA tertiary structure and molecular recognition in solution. The RNA and DNA aptamers that target ATP (and AMP) with micromolar affinity exhibit distinct binding site sequences and secondary structures. We report below on the tertiary structure of the AMP-DNA aptamer complex in solution and compare it with the previously reported tertiary structure of the AMP-RNA aptamer complex in solution. The solution structure of the AMP-DNA aptamer complex shows, surprisingly, that two AMP molecules are intercalated at adjacent sites within a rectangular widened minor groove. Complex formation involves adaptive binding where the asymmetric internal bubble of the free DNA aptamer zippers up through formation of a continuous six-base mismatch segment which includes a pair of adjacent three-base platforms. The AMP molecules pair through their Watson-Crick edges with the minor groove edges of guanine residues. These recognition G.A mismatches are flanked by sheared G.A and reversed Hoogsteen G.G mismatch pairs. The AMP-DNA aptamer and AMP-RNA aptamer complexes have distinct tertiary structures and binding stoichiometries. Nevertheless, both complexes have similar structural features and recognition alignments in their binding pockets. Specifically, AMP targets both DNA and RNA aptamers by intercalating between purine bases and through identical G.A mismatch formation. The recognition G.A mismatch stacks with a reversed Hoogsteen G.G mismatch in one direction and with an adenine base in the other direction in both complexes. It is striking that DNA and RNA aptamers selected independently from libraries of 10(14) molecules in each case utilize identical mismatch alignments for molecular recognition with micromolar affinity within binding-site pockets containing common structural elements.

Solid-phase proximity ligation assays for individual or parallel protein analyses with readout via real-time PCR or sequencing.

PubMed

Nong, Rachel Yuan; Wu, Di; Yan, Junhong; Hammond, Maria; Gu, Gucci Jijuan; Kamali-Moghaddam, Masood; Landegren, Ulf; Darmanis, Spyros

2013-06-01

Solid-phase proximity ligation assays share properties with the classical sandwich immunoassays for protein detection. The proteins captured via antibodies on solid supports are, however, detected not by single antibodies with detectable functions, but by pairs of antibodies with attached DNA strands. Upon recognition by these sets of three antibodies, pairs of DNA strands brought in proximity are joined by ligation. The ligated reporter DNA strands are then detected via methods such as real-time PCR or next-generation sequencing (NGS). We describe how to construct assays that can offer improved detection specificity by virtue of recognition by three antibodies, as well as enhanced sensitivity owing to reduced background and amplified detection. Finally, we also illustrate how the assays can be applied for parallel detection of proteins, taking advantage of the oligonucleotide ligation step to avoid background problems that might arise with multiplexing. The protocol for the singleplex solid-phase proximity ligation assay takes ~5 h. The multiplex version of the assay takes 7-8 h depending on whether quantitative PCR (qPCR) or sequencing is used as the readout. The time for the sequencing-based protocol includes the library preparation but not the actual sequencing, as times may vary based on the choice of sequencing platform.

Super-recognition in development: A case study of an adolescent with extraordinary face recognition skills.

PubMed

Bennetts, Rachel J; Mole, Joseph; Bate, Sarah

2017-09-01

Face recognition abilities vary widely. While face recognition deficits have been reported in children, it is unclear whether superior face recognition skills can be encountered during development. This paper presents O.B., a 14-year-old female with extraordinary face recognition skills: a "super-recognizer" (SR). O.B. demonstrated exceptional face-processing skills across multiple tasks, with a level of performance that is comparable to adult SRs. Her superior abilities appear to be specific to face identity: She showed an exaggerated face inversion effect and her superior abilities did not extend to object processing or non-identity aspects of face recognition. Finally, an eye-movement task demonstrated that O.B. spent more time than controls examining the nose - a pattern previously reported in adult SRs. O.B. is therefore particularly skilled at extracting and using identity-specific facial cues, indicating that face and object recognition are dissociable during development, and that super recognition can be detected in adolescence.

A motivational determinant of facial emotion recognition: regulatory focus affects recognition of emotions in faces.

PubMed

Sassenrath, Claudia; Sassenberg, Kai; Ray, Devin G; Scheiter, Katharina; Jarodzka, Halszka

2014-01-01

Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition was observed in a promotion focus compared to a prevention focus. In Study 2, individual differences in chronic regulatory focus were assessed and attention allocation was measured using eye tracking during the facial emotion recognition task. Results indicated that the positive relation between a promotion focus and facial emotion recognition is mediated by shorter fixation duration on the face which reflects a pattern of attention allocation matched to the eager strategy in a promotion focus (i.e., striving to make hits). A prevention focus did not have an impact neither on perceptual processing nor on facial emotion recognition. Taken together, these findings demonstrate important mechanisms and consequences of observer motivational orientation for facial emotion recognition.

TIA-1 RRM23 binding and recognition of target oligonucleotides

PubMed Central

Waris, Saboora; García-Mauriño, Sofía M.; Sivakumaran, Andrew; Beckham, Simone A.; Loughlin, Fionna E.; Gorospe, Myriam; Díaz-Moreno, Irene; Wilce, Matthew C.J.

2017-01-01

Abstract TIA-1 (T-cell restricted intracellular antigen-1) is an RNA-binding protein involved in splicing and translational repression. It mainly interacts with RNA via its second and third RNA recognition motifs (RRMs), with specificity for U-rich sequences directed by RRM2. It has recently been shown that RRM3 also contributes to binding, with preferential binding for C-rich sequences. Here we designed UC-rich and CU-rich 10-nt sequences for engagement of both RRM2 and RRM3 and demonstrated that the TIA-1 RRM23 construct preferentially binds the UC-rich RNA ligand (5΄-UUUUUACUCC-3΄). Interestingly, this binding depends on the presence of Lys274 that is C-terminal to RRM3 and binding to equivalent DNA sequences occurs with similar affinity. Small-angle X-ray scattering was used to demonstrate that, upon complex formation with target RNA or DNA, TIA-1 RRM23 adopts a compact structure, showing that both RRMs engage with the target 10-nt sequences to form the complex. We also report the crystal structure of TIA-1 RRM2 in complex with DNA to 2.3 Å resolution providing the first atomic resolution structure of any TIA protein RRM in complex with oligonucleotide. Together our data support a specific mode of TIA-1 RRM23 interaction with target oligonucleotides consistent with the role of TIA-1 in binding RNA to regulate gene expression. PMID:28184449

ACCA phosphopeptide recognition by the BRCT repeats of BRCA1.

PubMed

Ray, Hind; Moreau, Karen; Dizin, Eva; Callebaut, Isabelle; Venezia, Nicole Dalla

2006-06-16

The tumour suppressor gene BRCA1 encodes a 220 kDa protein that participates in multiple cellular processes. The BRCA1 protein contains a tandem of two BRCT repeats at its carboxy-terminal region. The majority of disease-associated BRCA1 mutations affect this region and provide to the BRCT repeats a central role in the BRCA1 tumour suppressor function. The BRCT repeats have been shown to mediate phospho-dependant protein-protein interactions. They recognize phosphorylated peptides using a recognition groove that spans both BRCT repeats. We previously identified an interaction between the tandem of BRCA1 BRCT repeats and ACCA, which was disrupted by germ line BRCA1 mutations that affect the BRCT repeats. We recently showed that BRCA1 modulates ACCA activity through its phospho-dependent binding to ACCA. To delineate the region of ACCA that is crucial for the regulation of its activity by BRCA1, we searched for potential phosphorylation sites in the ACCA sequence that might be recognized by the BRCA1 BRCT repeats. Using sequence analysis and structure modelling, we proposed the Ser1263 residue as the most favourable candidate among six residues, for recognition by the BRCA1 BRCT repeats. Using experimental approaches, such as GST pull-down assay with Bosc cells, we clearly showed that phosphorylation of only Ser1263 was essential for the interaction of ACCA with the BRCT repeats. We finally demonstrated by immunoprecipitation of ACCA in cells, that the whole BRCA1 protein interacts with ACCA when phosphorylated on Ser1263.

Management of familial cancer: sequencing, surveillance and society.

PubMed

Samuel, Nardin; Villani, Anita; Fernandez, Conrad V; Malkin, David

2014-12-01

The clinical management of familial cancer begins with recognition of patterns of cancer occurrence suggestive of genetic susceptibility in a proband or pedigree, to enable subsequent investigation of the underlying DNA mutations. In this regard, next-generation sequencing of DNA continues to transform cancer diagnostics, by enabling screening for cancer-susceptibility genes in the context of known and emerging familial cancer syndromes. Increasingly, not only are candidate cancer genes sequenced, but also entire 'healthy' genomes are mapped in children with cancer and their family members. Although large-scale genomic analysis is considered intrinsic to the success of cancer research and discovery, a number of accompanying ethical and technical issues must be addressed before this approach can be adopted widely in personalized therapy. In this Perspectives article, we describe our views on how the emergence of new sequencing technologies and cancer surveillance strategies is altering the framework for the clinical management of hereditary cancer. Genetic counselling and disclosure issues are discussed, and strategies for approaching ethical dilemmas are proposed.

Challenging ocular image recognition

NASA Astrophysics Data System (ADS)

Pauca, V. Paúl; Forkin, Michael; Xu, Xiao; Plemmons, Robert; Ross, Arun A.

2011-06-01

Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.

Short memory fuzzy fusion image recognition schema employing spatial and Fourier descriptors

NASA Astrophysics Data System (ADS)

Raptis, Sotiris N.; Tzafestas, Spyros G.

2001-03-01

Single images quite often do not bear enough information for precise interpretation due to a variety of reasons. Multiple image fusion and adequate integration recently became the state of the art in the pattern recognition field. In this paper presented here and enhanced multiple observation schema is discussed investigating improvements to the baseline fuzzy- probabilistic image fusion methodology. The first innovation introduced consists in considering only a limited but seemingly ore effective part of the uncertainty information obtained by a certain time restricting older uncertainty dependencies and alleviating computational burden that is now needed for short sequence (stored into memory) of samples. The second innovation essentially grouping them into feature-blind object hypotheses. Experiment settings include a sequence of independent views obtained by camera being moved around the investigated object.

Coding visual features extracted from video sequences.

PubMed

Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2014-05-01

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory

PubMed Central

Kazerounian, Sohrob; Grossberg, Stephen

2014-01-01

How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list ABADBD. Comparisons

Evolution of I-SceI Homing Endonucleases with Increased DNA Recognition Site Specificity

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

Joshi, Rakesh; Ho, Kwok Ki; Tenney, Kristen

2013-09-18

Elucidating how homing endonucleases undergo changes in recognition site specificity will facilitate efforts to engineer proteins for gene therapy applications. I-SceI is a monomeric homing endonuclease that recognizes and cleaves within an 18-bp target. It tolerates limited degeneracy in its target sequence, including substitution of a C:G{sub +4} base pair for the wild-type A:T{sub +4} base pair. Libraries encoding randomized amino acids at I-SceI residue positions that contact or are proximal to A:T{sub +4} were used in conjunction with a bacterial one-hybrid system to select I-SceI derivatives that bind to recognition sites containing either the A:T{sub +4} or the C:G{submore » +4} base pairs. As expected, isolates encoding wild-type residues at the randomized positions were selected using either target sequence. All I-SceI proteins isolated using the C:G{sub +4} recognition site included small side-chain substitutions at G100 and either contained (K86R/G100T, K86R/G100S and K86R/G100C) or lacked (G100A, G100T) a K86R substitution. Interestingly, the binding affinities of the selected variants for the wild-type A:T{sub +4} target are 4- to 11-fold lower than that of wild-type I-SceI, whereas those for the C:G{sub +4} target are similar. The increased specificity of the mutant proteins is also evident in binding experiments in vivo. These differences in binding affinities account for the observed -36-fold difference in target preference between the K86R/G100T and wild-type proteins in DNA cleavage assays. An X-ray crystal structure of the K86R/G100T mutant protein bound to a DNA duplex containing the C:G{sub +4} substitution suggests how sequence specificity of a homing enzyme can increase. This biochemical and structural analysis defines one pathway by which site specificity is augmented for a homing endonuclease.« less

Sequence analysis of MHC class I α2 from sockeye salmon (Oncorhynchus nerka).

PubMed

McClelland, Erin K; Ming, Tobi J; Tabata, Amy; Miller, Kristina M

2011-09-01

Most studies assessing adaptive MHC diversity in salmon populations have focused on the classical class II DAB or DAA loci, as these have been most amenable to single PCR amplifications due to their relatively low level of sequence divergence. Herein, we report the characterization of the classical class I UBA α2 locus based on collections taken throughout the species range of sockeye salmon (Oncorhynchus nerka). Through use of multiple lineage-specific primer sets, denaturing gradient gel electrophoresis and sequencing, we identified thirty-four alleles from three highly divergent lineages. Sequence identity between lineages ranged from 30.0% to 56.8% but was relatively high within lineages. Allelic identity within the antigen recognition site (ARS) was greater than for the longer sequence. Global positive selection on UBA was seen at the sequence level (dN:dS = 1.012) with four codons under positive selection and 12 codons under negative selection. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

Genetic specificity of face recognition.

PubMed

Shakeshaft, Nicholas G; Plomin, Robert

2015-10-13

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

Moreland Recognition Program.

ERIC Educational Resources Information Center

Moreland Elementary School District, San Jose, CA.

THE FOLLOWING IS THE FULL TEXT OF THIS DOCUMENT: Recognition for special effort and achievement has been noted as a component of effective schools. Schools in the Moreland School District have effectively improved standards of discipline and achievement by providing forty-six different ways for children to receive positive recognition. Good…

A Longitudinal Study of Cognitive Representation in Symbolic Play, Self-recognition, and Object Permanence during the Second Year.

ERIC Educational Resources Information Center

Chapman, Michael

1987-01-01

Explores development of cognitive representation in 20 infants 12 to 24 months of age with regard to (l) their understanding of agency in symbolic play (agent use), (2) recognition of their own mirror image, and (3) object permanence. Results were generally consistent with developmental sequences predicted by Fischer's Skill Theory for agent use…

Voice Recognition in Face-Blind Patients

PubMed Central

Liu, Ran R.; Pancaroglu, Raika; Hills, Charlotte S.; Duchaine, Brad; Barton, Jason J. S.

2016-01-01

Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia. PMID:25349193

Acquired prosopagnosia without word recognition deficits.

PubMed

Susilo, Tirta; Wright, Victoria; Tree, Jeremy J; Duchaine, Bradley

2015-01-01

It has long been suggested that face recognition relies on specialized mechanisms that are not involved in visual recognition of other object categories, including those that require expert, fine-grained discrimination at the exemplar level such as written words. But according to the recently proposed many-to-many theory of object recognition (MTMT), visual recognition of faces and words are carried out by common mechanisms [Behrmann, M., & Plaut, D. C. ( 2013 ). Distributed circuits, not circumscribed centers, mediate visual recognition. Trends in Cognitive Sciences, 17, 210-219]. MTMT acknowledges that face and word recognition are lateralized, but posits that the mechanisms that predominantly carry out face recognition still contribute to word recognition and vice versa. MTMT makes a key prediction, namely that acquired prosopagnosics should exhibit some measure of word recognition deficits. We tested this prediction by assessing written word recognition in five acquired prosopagnosic patients. Four patients had lesions limited to the right hemisphere while one had bilateral lesions with more pronounced lesions in the right hemisphere. The patients completed a total of seven word recognition tasks: two lexical decision tasks and five reading aloud tasks totalling more than 1200 trials. The performances of the four older patients (3 female, age range 50-64 years) were compared to those of 12 older controls (8 female, age range 56-66 years), while the performances of the younger prosopagnosic (male, 31 years) were compared to those of 14 younger controls (9 female, age range 20-33 years). We analysed all results at the single-patient level using Crawford's t-test. Across seven tasks, four prosopagnosics performed as quickly and accurately as controls. Our results demonstrate that acquired prosopagnosia can exist without word recognition deficits. These findings are inconsistent with a key prediction of MTMT. They instead support the hypothesis that face

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

PubMed

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-18

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters' influence on performance to provide insights about their optimisation.

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

PubMed Central

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation. PMID:26797612

Examining ERP correlates of recognition memory: Evidence of accurate source recognition without recollection

PubMed Central

Addante, Richard, J.; Ranganath, Charan; Yonelinas, Andrew, P.

2012-01-01

Recollection is typically associated with high recognition confidence and accurate source memory. However, subjects sometimes make accurate source memory judgments even for items that are not confidently recognized, and it is not known whether these responses are based on recollection or some other memory process. In the current study, we measured event related potentials (ERPs) while subjects made item and source memory confidence judgments in order to determine whether recollection supported accurate source recognition responses for items that were not confidently recognized. In line with previous studies, we found that recognition memory was associated with two ERP effects: an early on-setting FN400 effect, and a later parietal old-new effect [Late Positive Component (LPC)], which have been associated with familiarity and recollection, respectively. The FN400 increased gradually with item recognition confidence, whereas the LPC was only observed for highly confident recognition responses. The LPC was also related to source accuracy, but only for items that had received a high confidence item recognition response; accurate source judgments to items that were less confidently recognized did not exhibit the typical ERP correlate of recollection or familiarity, but rather showed a late, broadly distributed negative ERP difference. The results indicate that accurate source judgments of episodic context can occur even when recollection fails. PMID:22548808

Interactive object recognition assistance: an approach to recognition starting from target objects

NASA Astrophysics Data System (ADS)

Geisler, Juergen; Littfass, Michael

1999-07-01

Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

Word Recognition in Auditory Cortex

ERIC Educational Resources Information Center

DeWitt, Iain D. J.

2013-01-01

Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

DNA recognition by an RNA-guided bacterial Argonaute

PubMed Central

Doudna, Jennifer A.

2017-01-01

Argonaute (Ago) proteins are widespread in prokaryotes and eukaryotes and share a four-domain architecture capable of RNA- or DNA-guided nucleic acid recognition. Previous studies identified a prokaryotic Argonaute protein from the eubacterium Marinitoga piezophila (MpAgo), which binds preferentially to 5′-hydroxylated guide RNAs and cleaves single-stranded RNA (ssRNA) and DNA (ssDNA) targets. Here we present a 3.2 Å resolution crystal structure of MpAgo bound to a 21-nucleotide RNA guide and a complementary 21-nucleotide ssDNA substrate. Comparison of this ternary complex to other target-bound Argonaute structures reveals a unique orientation of the N-terminal domain, resulting in a straight helical axis of the entire RNA-DNA heteroduplex through the central cleft of the protein. Additionally, mismatches introduced into the heteroduplex reduce MpAgo cleavage efficiency with a symmetric profile centered around the middle of the helix. This pattern differs from the canonical mismatch tolerance of other Argonautes, which display decreased cleavage efficiency for substrates bearing sequence mismatches to the 5′ region of the guide strand. This structural analysis of MpAgo bound to a hybrid helix advances our understanding of the diversity of target recognition mechanisms by Argonaute proteins. PMID:28520746

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition.

PubMed

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-02-08

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates ( F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware.

An ultra-sparse code underliesthe generation of neural sequences in a songbird

NASA Astrophysics Data System (ADS)

Hahnloser, Richard H. R.; Kozhevnikov, Alexay A.; Fee, Michale S.

2002-09-01

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the `grandmother cell' concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations.

Applications of statistical physics and information theory to the analysis of DNA sequences

NASA Astrophysics Data System (ADS)

Grosse, Ivo

2000-10-01

DNA carries the genetic information of most living organisms, and the of genome projects is to uncover that genetic information. One basic task in the analysis of DNA sequences is the recognition of protein coding genes. Powerful computer programs for gene recognition have been developed, but most of them are based on statistical patterns that vary from species to species. In this thesis I address the question if there exist universal statistical patterns that are different in coding and noncoding DNA of all living species, regardless of their phylogenetic origin. In search for such species-independent patterns I study the mutual information function of genomic DNA sequences, and find that it shows persistent period-three oscillations. To understand the biological origin of the observed period-three oscillations, I compare the mutual information function of genomic DNA sequences to the mutual information function of stochastic model sequences. I find that the pseudo-exon model is able to reproduce the mutual information function of genomic DNA sequences. Moreover, I find that a generalization of the pseudo-exon model can connect the existence and the functional form of long-range correlations to the presence and the length distributions of coding and noncoding regions. Based on these theoretical studies I am able to find an information-theoretical quantity, the average mutual information (AMI), whose probability distributions are significantly different in coding and noncoding DNA, while they are almost identical in all studied species. These findings show that there exist universal statistical patterns that are different in coding and noncoding DNA of all studied species, and they suggest that the AMI may be used to identify genes in different living species, irrespective of their taxonomic origin.

[Comparative studies of face recognition].

PubMed

Kawai, Nobuyuki

2012-07-01

Every human being is proficient in face recognition. However, the reason for and the manner in which humans have attained such an ability remain unknown. These questions can be best answered-through comparative studies of face recognition in non-human animals. Studies in both primates and non-primates show that not only primates, but also non-primates possess the ability to extract information from their conspecifics and from human experimenters. Neural specialization for face recognition is shared with mammals in distant taxa, suggesting that face recognition evolved earlier than the emergence of mammals. A recent study indicated that a social insect, the golden paper wasp, can distinguish their conspecific faces, whereas a closely related species, which has a less complex social lifestyle with just one queen ruling a nest of underlings, did not show strong face recognition for their conspecifics. Social complexity and the need to differentiate between one another likely led humans to evolve their face recognition abilities.

Genetic specificity of face recognition

PubMed Central

Shakeshaft, Nicholas G.; Plomin, Robert

2015-01-01

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities. PMID:26417086

A standardization model based on image recognition for performance evaluation of an oral scanner.

PubMed

Seo, Sang-Wan; Lee, Wan-Sun; Byun, Jae-Young; Lee, Kyu-Bok

2017-12-01

Accurate information is essential in dentistry. The image information of missing teeth is used in optically based medical equipment in prosthodontic treatment. To evaluate oral scanners, the standardized model was examined from cases of image recognition errors of linear discriminant analysis (LDA), and a model that combines the variables with reference to ISO 12836:2015 was designed. The basic model was fabricated by applying 4 factors to the tooth profile (chamfer, groove, curve, and square) and the bottom surface. Photo-type and video-type scanners were used to analyze 3D images after image capture. The scans were performed several times according to the prescribed sequence to distinguish the model from the one that did not form, and the results confirmed it to be the best. In the case of the initial basic model, a 3D shape could not be obtained by scanning even if several shots were taken. Subsequently, the recognition rate of the image was improved with every variable factor, and the difference depends on the tooth profile and the pattern of the floor surface. Based on the recognition error of the LDA, the recognition rate decreases when the model has a similar pattern. Therefore, to obtain the accurate 3D data, the difference of each class needs to be provided when developing a standardized model.

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Next generation sequencing--implications for clinical practice.

PubMed

Raffan, Eleanor; Semple, Robert K

2011-01-01

Genetic testing in inherited disease has traditionally relied upon recognition of the presenting clinical syndrome and targeted analysis of genes known to be linked to that syndrome. Consequently, many patients with genetic syndromes remain without a specific diagnosis. New 'next-generation' sequencing (NGS) techniques permit simultaneous sequencing of enormous amounts of DNA. A slew of research publications have recently demonstrated the tremendous power of these technologies in increasing understanding of human genetic disease. These approaches are likely to be increasingly employed in routine diagnostic practice, but the scale of the genetic information yielded about individuals means that caution must be exercised to avoid net harm in this setting. Use of NGS in a research setting will increasingly have a major but indirect beneficial impact on clinical practice. However, important technical, ethical and social challenges need to be addressed through informed professional and public dialogue before it finds its mature niche as a direct tool in the clinical diagnostic armoury.

Ease of Access to List Items in Short-Term Memory Depends on the Order of the Recognition Probes

ERIC Educational Resources Information Center

Lange, Elke B.; Cerella, John; Verhaeghen, Paul

2011-01-01

We report data from 4 experiments using a recognition design with multiple probes to be matched to specific study positions. Items could be accessed rapidly, independent of set size, when the test order matched the study order (forward condition). When the order of testing was random, backward, or in a prelearned irregular sequence (reordered…

Transfer-appropriate processing in recognition memory: perceptual and conceptual effects on recognition memory depend on task demands.

PubMed

Parks, Colleen M

2013-07-01

Research examining the importance of surface-level information to familiarity in recognition memory tasks is mixed: Sometimes it affects recognition and sometimes it does not. One potential explanation of the inconsistent findings comes from the ideas of dual process theory of recognition and the transfer-appropriate processing framework, which suggest that the extent to which perceptual fluency matters on a recognition test depends in large part on the task demands. A test that recruits perceptual processing for discrimination should show greater perceptual effects and smaller conceptual effects than standard recognition, similar to the pattern of effects found in perceptual implicit memory tasks. This idea was tested in the current experiment by crossing a levels of processing manipulation with a modality manipulation on a series of recognition tests that ranged from conceptual (standard recognition) to very perceptually demanding (a speeded recognition test with degraded stimuli). Results showed that the levels of processing effect decreased and the effect of modality increased when tests were made perceptually demanding. These results support the idea that surface-level features influence performance on recognition tests when they are made salient by the task demands. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Promoter mapping of the mouse Tcp-10bt gene in transgenic mice identifies essential male germ cell regulatory sequences.

PubMed

Ewulonu, U K; Snyder, L; Silver, L M; Schimenti, J C

1996-03-01

Transgenic mice were generated to localize essential promoter elements in the mouse testis-expressed Tcp-10 genes. These genes are expressed exclusively in male germ cells, and exhibit a diffuse range of transcriptional start sites, possibly due to the absence of a TATA box. A series of transgene constructs containing different amounts of 5' flanking DNA revealed that all sequences necessary for appropriate temporal and tissue-specific transcription of Tcp-10 reside between positions -1 to -973. All transgenic animals containing these sequences expressed a chimeric transgene at high levels, in a pattern that paralleled the endogenous genes. These experiments further defined a 227 bp fragment from -746 to -973 that was absolutely essential for expression. In a gel-shift assay, this 227-bp fragment bound nuclear protein from testis, but not other tissues, to yield two retarded bands. Sequence analysis of this fragment revealed a half-site for the AP-2 transcription factor recognition sequence. Gel shift assays using native or mutant oligonucleotides demonstrated that the putative AP-2 recognition sequence was essential for generating the retarded bands. Since the binding activity is testis-specific, but AP-2 expression is not exclusive to male germ cells, it is possible that transcription of Tcp-10 requires interaction between AP-2 and a germ cell-specific transcription factor.

Analysis of expressed sequence tags from Maize mosaic rhabdovirus-infected gut tissues of Peregrinus maidis reveals the presence of key components of insect innate immunity.

PubMed

Whitfield, A E; Rotenberg, D; Aritua, V; Hogenhout, S A

2011-04-01

The corn planthopper, Peregrinus maidis, causes direct feeding damage to plants and transmits Maize mosaic rhabdovirus (MMV) in a persistent-propagative manner. MMV must cross several insect tissue layers for successful transmission to occur, and the gut serves as an important barrier for rhabdovirus transmission. In order to facilitate the identification of proteins that may interact with MMV either by facilitating acquisition or responding to virus infection, we generated and analysed the gut transcriptome of P. maidis. From two normalized cDNA libraries, we generated a P. maidis gut transcriptome composed of 20,771 expressed sequence tags (ESTs). Assembly of the sequences yielded 1860 contigs and 14,032 singletons, and biological roles were assigned to 5793 (36%). Comparison of P. maidis ESTs with other insect amino acid sequences revealed that P. maidis shares greatest sequence similarity with another hemipteran, the brown planthopper Nilaparvata lugens. We identified 202 P. maidis transcripts with putative homology to proteins associated with insect innate immunity, including those implicated in the Toll, Imd, JAK/STAT, Jnk and the small-interfering RNA-mediated pathways. Sequence comparisons between our P. maidis gut EST collection and the currently available National Center for Biotechnology Information EST database collection for Ni. lugens revealed that a pathogen recognition receptor in the Imd pathway, peptidoglycan recognition protein-long class (PGRP-LC), is present in these two members of the family Delphacidae; however, these recognition receptors are lacking in the model hemipteran Acyrthosiphon pisum. In addition, we identified sequences in the P. maidis gut transcriptome that share significant amino acid sequence similarities with the rhabdovirus receptor molecule, acetylcholine receptor (AChR), found in other hosts. This EST analysis sheds new light on immune response pathways in hemipteran guts that will be useful for further dissecting innate

TIA-1 RRM23 binding and recognition of target oligonucleotides.

PubMed

Waris, Saboora; García-Mauriño, Sofía M; Sivakumaran, Andrew; Beckham, Simone A; Loughlin, Fionna E; Gorospe, Myriam; Díaz-Moreno, Irene; Wilce, Matthew C J; Wilce, Jacqueline A

2017-05-05

TIA-1 (T-cell restricted intracellular antigen-1) is an RNA-binding protein involved in splicing and translational repression. It mainly interacts with RNA via its second and third RNA recognition motifs (RRMs), with specificity for U-rich sequences directed by RRM2. It has recently been shown that RRM3 also contributes to binding, with preferential binding for C-rich sequences. Here we designed UC-rich and CU-rich 10-nt sequences for engagement of both RRM2 and RRM3 and demonstrated that the TIA-1 RRM23 construct preferentially binds the UC-rich RNA ligand (5΄-UUUUUACUCC-3΄). Interestingly, this binding depends on the presence of Lys274 that is C-terminal to RRM3 and binding to equivalent DNA sequences occurs with similar affinity. Small-angle X-ray scattering was used to demonstrate that, upon complex formation with target RNA or DNA, TIA-1 RRM23 adopts a compact structure, showing that both RRMs engage with the target 10-nt sequences to form the complex. We also report the crystal structure of TIA-1 RRM2 in complex with DNA to 2.3 Å resolution providing the first atomic resolution structure of any TIA protein RRM in complex with oligonucleotide. Together our data support a specific mode of TIA-1 RRM23 interaction with target oligonucleotides consistent with the role of TIA-1 in binding RNA to regulate gene expression. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

msgbsR: An R package for analysing methylation-sensitive restriction enzyme sequencing data.

PubMed

Mayne, Benjamin T; Leemaqz, Shalem Y; Buckberry, Sam; Rodriguez Lopez, Carlos M; Roberts, Claire T; Bianco-Miotto, Tina; Breen, James

2018-02-01

Genotyping-by-sequencing (GBS) or restriction-site associated DNA marker sequencing (RAD-seq) is a practical and cost-effective method for analysing large genomes from high diversity species. This method of sequencing, coupled with methylation-sensitive enzymes (often referred to as methylation-sensitive restriction enzyme sequencing or MRE-seq), is an effective tool to study DNA methylation in parts of the genome that are inaccessible in other sequencing techniques or are not annotated in microarray technologies. Current software tools do not fulfil all methylation-sensitive restriction sequencing assays for determining differences in DNA methylation between samples. To fill this computational need, we present msgbsR, an R package that contains tools for the analysis of methylation-sensitive restriction enzyme sequencing experiments. msgbsR can be used to identify and quantify read counts at methylated sites directly from alignment files (BAM files) and enables verification of restriction enzyme cut sites with the correct recognition sequence of the individual enzyme. In addition, msgbsR assesses DNA methylation based on read coverage, similar to RNA sequencing experiments, rather than methylation proportion and is a useful tool in analysing differential methylation on large populations. The package is fully documented and available freely online as a Bioconductor package ( https://bioconductor.org/packages/release/bioc/html/msgbsR.html ).

Sequence specificity of the human mRNA N6-adenosine methylase in vitro.

PubMed Central

Harper, J E; Miceli, S M; Roberts, R J; Manley, J L

1990-01-01

N6-adenosine methylation is a frequent modification of mRNAs and their precursors, but little is known about the mechanism of the reaction or the function of the modification. To explore these questions, we developed conditions to examine N6-adenosine methylase activity in HeLa cell nuclear extracts. Transfer of the methyl group from S-[3H methyl]-adenosylmethionine to unlabeled random copolymer RNA substrates of varying ribonucleotide composition revealed a substrate specificity consistent with a previously deduced consensus sequence, Pu[G greater than A]AC[A/C/U]. 32-P labeled RNA substrates of defined sequence were used to examine the minimum sequence requirements for methylation. Each RNA was 20 nucleotides long, and contained either the core consensus sequence GGACU, or some variation of this sequence. RNAs containing GGACU, either in single or multiple copies, were good substrates for methylation, whereas RNAs containing single base substitutions within the GGACU sequence gave dramatically reduced methylation. These results demonstrate that the N6-adenosine methylase has a strict sequence specificity, and that there is no requirement for extended sequences or secondary structures for methylation. Recognition of this sequence does not require an RNA component, as micrococcal nuclease pretreatment of nuclear extracts actually increased methylation efficiency. Images PMID:2216767

Supporting Quality Teachers with Recognition

ERIC Educational Resources Information Center

Andrews, Hans A.

2011-01-01

Value has been found in providing recognition and awards programs for excellent teachers. Research has also found a major lack of these programs in both the USA and in Australia. Teachers receiving recognition and awards for their teaching have praised recognition programs as providing motivation for them to continue high-level instruction.…

Subtle Changes in Peptide Conformation Profoundly Affect Recognition of the Non-Classical MHC Class I Molecule HLA-E by the CD94-NKG2 Natural Killer Cell Receptors

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

Hoare, Hilary L; Sullivan, Lucy C; Clements, Craig S

2008-03-31

Human leukocyte antigen (HLA)-E is a non-classical major histocompatibility complex class I molecule that binds peptides derived from the leader sequences of other HLA class I molecules. Natural killer cell recognition of these HLA-E molecules, via the CD94-NKG2 natural killer family, represents a central innate mechanism for monitoring major histocompatibility complex expression levels within a cell. The leader sequence-derived peptides bound to HLA-E exhibit very limited polymorphism, yet subtle differences affect the recognition of HLA-E by the CD94-NKG2 receptors. To better understand the basis for this peptide-specific recognition, we determined the structure of HLA-E in complex with two leader peptides,more » namely, HLA-Cw*07 (VMAPRALLL), which is poorly recognised by CD94-NKG2 receptors, and HLA-G*01 (VMAPRTLFL), a high-affinity ligand of CD94-NKG2 receptors. A comparison of these structures, both of which were determined to 2.5-Å resolution, revealed that allotypic variations in the bound leader sequences do not result in conformational changes in the HLA-E heavy chain, although subtle changes in the conformation of the peptide within the binding groove of HLA-E were evident. Accordingly, our data indicate that the CD94-NKG2 receptors interact with HLA-E in a manner that maximises the ability of the receptors to discriminate between subtle changes in both the sequence and conformation of peptides bound to HLA-E.« less

Document Form and Character Recognition using SVM

NASA Astrophysics Data System (ADS)

Park, Sang-Sung; Shin, Young-Geun; Jung, Won-Kyo; Ahn, Dong-Kyu; Jang, Dong-Sik

2009-08-01

Because of development of computer and information communication, EDI (Electronic Data Interchange) has been developing. There is OCR (Optical Character Recognition) of Pattern recognition technology for EDI. OCR contributed to changing many manual in the past into automation. But for the more perfect database of document, much manual is needed for excluding unnecessary recognition. To resolve this problem, we propose document form based character recognition method in this study. Proposed method is divided into document form recognition part and character recognition part. Especially, in character recognition, change character into binarization by using SVM algorithm and extract more correct feature value.

Conformational Preference of ‘CαNN’ Short Peptide Motif towards Recognition of Anions

PubMed Central

Banerjee, Raja

2013-01-01

Among several ‘anion binding motifs’, the recently described ‘CαNN’ motif occurring in the loop regions preceding a helix, is conserved through evolution both in sequence and its conformation. To establish the significance of the conserved sequence and their intrinsic affinity for anions, a series of peptides containing the naturally occurring ‘CαNN’ motif at the N-terminus of a designed helix, have been modeled and studied in a context free system using computational techniques. Appearance of a single interacting site with negative binding free-energy for both the sulfate and phosphate ions, as evidenced in docking experiments, establishes that the ‘CαNN’ segment has an intrinsic affinity for anions. Molecular Dynamics (MD) simulation studies reveal that interaction with anion triggers a conformational switch from non-helical to helical state at the ‘CαNN’ segment, which extends the length of the anchoring-helix by one turn at the N-terminus. Computational experiments substantiate the significance of sequence/structural context and justify the conserved nature of the ‘CαNN’ sequence for anion recognition through “local” interaction. PMID:23516403

Sequence-Based Prediction of RNA-Binding Residues in Proteins.

PubMed

Walia, Rasna R; El-Manzalawy, Yasser; Honavar, Vasant G; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

Sequence-Based Prediction of RNA-Binding Residues in Proteins

PubMed Central

Walia, Rasna R.; EL-Manzalawy, Yasser; Honavar, Vasant G.; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein–RNA complexes is important for understanding the molecular determinants of protein–RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein–RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein–RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner. PMID:27787829

Superficial Priming in Episodic Recognition

ERIC Educational Resources Information Center

Dopkins, Stephen; Sargent, Jesse; Ngo, Catherine T.

2010-01-01

We explored the effect of superficial priming in episodic recognition and found it to be different from the effect of semantic priming in episodic recognition. Participants made recognition judgments to pairs of items, with each pair consisting of a prime item and a test item. Correct positive responses to the test item were impeded if the prime…

Academic Recognition: Status and Challenges

ERIC Educational Resources Information Center

Bergan, Sjur

2009-01-01

The Council of Europe/UNESCO Recognition Convention (also known as the Lisbon Recognition Convention) provides the legal framework for academic recognition in Europe, and it serves a double purpose: as a legal text and as a guide to good practice. The ENIC and NARIC Networks promote the implementation of the Convention and seek to develop a better…

Human behavior recognition using a context-free grammar

NASA Astrophysics Data System (ADS)

Rosani, Andrea; Conci, Nicola; De Natale, Francesco G. B.

2014-05-01

Automatic recognition of human activities and behaviors is still a challenging problem for many reasons, including limited accuracy of the data acquired by sensing devices, high variability of human behaviors, and gap between visual appearance and scene semantics. Symbolic approaches can significantly simplify the analysis and turn raw data into chains of meaningful patterns. This allows getting rid of most of the clutter produced by low-level processing operations, embedding significant contextual information into the data, as well as using simple syntactic approaches to perform the matching between incoming sequences and models. We propose a symbolic approach to learn and detect complex activities through the sequences of atomic actions. Compared to previous methods based on context-free grammars, we introduce several important novelties, such as the capability to learn actions based on both positive and negative samples, the possibility of efficiently retraining the system in the presence of misclassified or unrecognized events, and the use of a parsing procedure that allows correct detection of the activities also when they are concatenated and/or nested one with each other. An experimental validation on three datasets with different characteristics demonstrates the robustness of the approach in classifying complex human behaviors.

BplI, a new BcgI-like restriction endonuclease, which recognizes a symmetric sequence.

PubMed Central

Vitkute, J; Maneliene, Z; Petrusyte, M; Janulaitis, A

1997-01-01

Bcg I and Bcg I-like restriction endonucleases cleave double stranded DNA specifically on both sides of their asymmetric recognition sequences which are interrupted by several ambiguous base pairs. Their heterosubunit structure, bifunctionality and stimulation by AdoMet make them different from other classified restriction enzymes. Here we report on a new Bcg I-like restriction endonuclease, Bpl I from Bacillus pumilus , which in contrast to all other Bcg I-like enzymes, recognizes a symmetric interrupted sequence, and which, like Bcg I, cleaves double stranded DNA upstream and downstream of its recognition sequence (8/13)GAGN5CTC(13/8). Like Bcg I, Bpl I is a bifunctional enzyme revealing both DNA cleavage and methyltransferase activities. There are two polypeptides in the homogeneous preparation of Bpl I with molecular masses of approximately 74 and 37 kDa. The sizes of the Bpl I subunits are close to those of Bcg I, but the proportion 1:1 in the final preparation is different from that of 2:1 in Bcg I. Low activity observed with Mg2+increases >100-fold in the presence of AdoMet. Even with AdoMet though, specific cleavage is incomplete. S -adenosylhomocysteine (AdoHcy) or sinefungin can replace AdoMet in the cleavage reaction. AdoHcy activated Bpl I yields complete cleavage of DNA. PMID:9358150

Infant visual attention and object recognition.

PubMed

Reynolds, Greg D

2015-05-15

This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy. Copyright © 2015 Elsevier B.V. All rights reserved.

Infant Visual Attention and Object Recognition

PubMed Central

Reynolds, Greg D.

2015-01-01

This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy. PMID:25596333

Analysis and Recognition of Curve Type as The Basis of Object Recognition in Image

NASA Astrophysics Data System (ADS)

Nugraha, Nurma; Madenda, Sarifuddin; Indarti, Dina; Dewi Agushinta, R.; Ernastuti

2016-06-01

An object in an image when analyzed further will show the characteristics that distinguish one object with another object in an image. Characteristics that are used in object recognition in an image can be a color, shape, pattern, texture and spatial information that can be used to represent objects in the digital image. The method has recently been developed for image feature extraction on objects that share characteristics curve analysis (simple curve) and use the search feature of chain code object. This study will develop an algorithm analysis and the recognition of the type of curve as the basis for object recognition in images, with proposing addition of complex curve characteristics with maximum four branches that will be used for the process of object recognition in images. Definition of complex curve is the curve that has a point of intersection. By using some of the image of the edge detection, the algorithm was able to do the analysis and recognition of complex curve shape well.

Molecular basis for the wide range of affinity found in Csr/Rsm protein-RNA recognition.

PubMed

Duss, Olivier; Michel, Erich; Diarra dit Konté, Nana; Schubert, Mario; Allain, Frédéric H-T

2014-04-01

The carbon storage regulator/regulator of secondary metabolism (Csr/Rsm) type of small non-coding RNAs (sRNAs) is widespread throughout bacteria and acts by sequestering the global translation repressor protein CsrA/RsmE from the ribosome binding site of a subset of mRNAs. Although we have previously described the molecular basis of a high affinity RNA target bound to RsmE, it remains unknown how other lower affinity targets are recognized by the same protein. Here, we have determined the nuclear magnetic resonance solution structures of five separate GGA binding motifs of the sRNA RsmZ of Pseudomonas fluorescens in complex with RsmE. The structures explain how the variation of sequence and structural context of the GGA binding motifs modulate the binding affinity for RsmE by five orders of magnitude (∼10 nM to ∼3 mM, Kd). Furthermore, we see that conformational adaptation of protein side-chains and RNA enable recognition of different RNA sequences by the same protein contributing to binding affinity without conferring specificity. Overall, our findings illustrate how the variability in the Csr/Rsm protein-RNA recognition allows a fine-tuning of the competition between mRNAs and sRNAs for the CsrA/RsmE protein.

[Neural mechanisms of facial recognition].

PubMed

Nagai, Chiyoko

2007-01-01

We review recent researches in neural mechanisms of facial recognition in the light of three aspects: facial discrimination and identification, recognition of facial expressions, and face perception in itself. First, it has been demonstrated that the fusiform gyrus has a main role of facial discrimination and identification. However, whether the FFA (fusiform face area) is really a special area for facial processing or not is controversial; some researchers insist that the FFA is related to 'becoming an expert' for some kinds of visual objects, including faces. Neural mechanisms of prosopagnosia would be deeply concerned to this issue. Second, the amygdala seems to be very concerned to recognition of facial expressions, especially fear. The amygdala, connected with the superior temporal sulcus and the orbitofrontal cortex, appears to operate the cortical function. The amygdala and the superior temporal sulcus are related to gaze recognition, which explains why a patient with bilateral amygdala damage could not recognize only a fear expression; the information from eyes is necessary for fear recognition. Finally, even a newborn infant can recognize a face as a face, which is congruent with the innate hypothesis of facial recognition. Some researchers speculate that the neural basis of such face perception is the subcortical network, comprised of the amygdala, the superior colliculus, and the pulvinar. This network would relate to covert recognition that prosopagnosic patients have.

Probabilistic Open Set Recognition

NASA Astrophysics Data System (ADS)

Jain, Lalit Prithviraj

Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

Hemispheric lateralization of linguistic prosody recognition in comparison to speech and speaker recognition.

PubMed

Kreitewolf, Jens; Friederici, Angela D; von Kriegstein, Katharina

2014-11-15

Hemispheric specialization for linguistic prosody is a controversial issue. While it is commonly assumed that linguistic prosody and emotional prosody are preferentially processed in the right hemisphere, neuropsychological work directly comparing processes of linguistic prosody and emotional prosody suggests a predominant role of the left hemisphere for linguistic prosody processing. Here, we used two functional magnetic resonance imaging (fMRI) experiments to clarify the role of left and right hemispheres in the neural processing of linguistic prosody. In the first experiment, we sought to confirm previous findings showing that linguistic prosody processing compared to other speech-related processes predominantly involves the right hemisphere. Unlike previous studies, we controlled for stimulus influences by employing a prosody and speech task using the same speech material. The second experiment was designed to investigate whether a left-hemispheric involvement in linguistic prosody processing is specific to contrasts between linguistic prosody and emotional prosody or whether it also occurs when linguistic prosody is contrasted against other non-linguistic processes (i.e., speaker recognition). Prosody and speaker tasks were performed on the same stimulus material. In both experiments, linguistic prosody processing was associated with activity in temporal, frontal, parietal and cerebellar regions. Activation in temporo-frontal regions showed differential lateralization depending on whether the control task required recognition of speech or speaker: recognition of linguistic prosody predominantly involved right temporo-frontal areas when it was contrasted against speech recognition; when contrasted against speaker recognition, recognition of linguistic prosody predominantly involved left temporo-frontal areas. The results show that linguistic prosody processing involves functions of both hemispheres and suggest that recognition of linguistic prosody is based on

Recognition memory in developmental prosopagnosia: electrophysiological evidence for abnormal routes to face recognition

PubMed Central

Burns, Edwin J.; Tree, Jeremy J.; Weidemann, Christoph T.

2014-01-01

Dual process models of recognition memory propose two distinct routes for recognizing a face: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K) paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP) through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in eight individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG) data at the scalp. Those with DP were found to produce fewer correct “remember” responses and more false alarms than controls. EEG results showed that posterior “remember” old/new effects were delayed and restricted to the right posterior (RP) area in those with DP in comparison to the controls. A posterior “know” old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal “know” old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face-specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects. PMID:25177283

An Adaptive Method for Switching between Pedestrian/Car Indoor Positioning Algorithms based on Multilayer Time Sequences

PubMed Central

Gu, Zhining; Guo, Wei; Li, Chaoyang; Zhu, Xinyan; Guo, Tao

2018-01-01

Pedestrian dead reckoning (PDR) positioning algorithms can be used to obtain a target’s location only for movement with step features and not for driving, for which the trilateral Bluetooth indoor positioning method can be used. In this study, to obtain the precise locations of different states (pedestrian/car) using the corresponding positioning algorithms, we propose an adaptive method for switching between the PDR and car indoor positioning algorithms based on multilayer time sequences (MTSs). MTSs, which consider the behavior context, comprise two main aspects: filtering of noisy data in small-scale time sequences and using a state chain to reduce the time delay of algorithm switching in large-scale time sequences. The proposed method can be expected to realize the recognition of stationary, walking, driving, or other states; switch to the correct indoor positioning algorithm; and improve the accuracy of localization compared to using a single positioning algorithm. Our experiments show that the recognition of static, walking, driving, and other states improves by 5.5%, 45.47%, 26.23%, and 21% on average, respectively, compared with convolutional neural network (CNN) method. The time delay decreases by approximately 0.5–8.5 s for the transition between states and by approximately 24 s for the entire process. PMID:29495503

WD-repeat instability and diversification of the Podospora anserina hnwd non-self recognition gene family.

PubMed

Chevanne, Damien; Saupe, Sven J; Clavé, Corinne; Paoletti, Mathieu

2010-05-06

Genes involved in non-self recognition and host defence are typically capable of rapid diversification and exploit specialized genetic mechanism to that end. Fungi display a non-self recognition phenomenon termed heterokaryon incompatibility that operates when cells of unlike genotype fuse and leads to the cell death of the fusion cell. In the fungus Podospora anserina, three genes controlling this allorecognition process het-d, het-e and het-r are paralogs belonging to the same hnwd gene family. HNWD proteins are STAND proteins (signal transduction NTPase with multiple domains) that display a WD-repeat domain controlling recognition specificity. Based on genomic sequence analysis of different P. anserina isolates, it was established that repeat regions of all members of the gene family are extremely polymorphic and undergoing concerted evolution arguing for frequent recombination within and between family members. Herein, we directly analyzed the genetic instability and diversification of this allorecognition gene family. We have constituted a collection of 143 spontaneous mutants of the het-R (HNWD2) and het-E (hnwd5) genes with altered recognition specificities. The vast majority of the mutants present rearrangements in the repeat arrays with deletions, duplications and other modifications as well as creation of novel repeat unit variants. We investigate the extreme genetic instability of these genes and provide a direct illustration of the diversification strategy of this eukaryotic allorecognition gene family.

New approach for logo recognition

NASA Astrophysics Data System (ADS)

Chen, Jingying; Leung, Maylor K. H.; Gao, Yongsheng

2000-03-01

The problem of logo recognition is of great interest in the document domain, especially for document database. By recognizing the logo we obtain semantic information about the document which may be useful in deciding whether or not to analyze the textual components. In order to develop a logo recognition method that is efficient to compute and product intuitively reasonable results, we investigate the Line Segment Hausdorff Distance on logo recognition. Researchers apply Hausdorff Distance to measure the dissimilarity of two point sets. It has been extended to match two sets of line segments. The new approach has the advantage to incorporate structural and spatial information to compute the dissimilarity. The added information can conceptually provide more and better distinctive capability for recognition. The proposed technique has been applied on line segments of logos with encouraging results that support the concept experimentally. This might imply a new way for logo recognition.

Entity recognition in the biomedical domain using a hybrid approach.

PubMed

Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

Page Recognition: Quantum Leap In Recognition Technology

NASA Astrophysics Data System (ADS)

Miller, Larry

1989-07-01

No milestone has proven as elusive as the always-approaching "year of the LAN," but the "year of the scanner" might claim the silver medal. Desktop scanners have been around almost as long as personal computers. And everyone thinks they are used for obvious desktop-publishing and business tasks like scanning business documents, magazine articles and other pages, and translating those words into files your computer understands. But, until now, the reality fell far short of the promise. Because it's true that scanners deliver an accurate image of the page to your computer, but the software to recognize this text has been woefully disappointing. Old optical-character recognition (OCR) software recognized such a limited range of pages as to be virtually useless to real users. (For example, one OCR vendor specified 12-point Courier font from an IBM Selectric typewriter: the same font in 10-point, or from a Diablo printer, was unrecognizable!) Computer dealers have told me the chasm between OCR expectations and reality is so broad and deep that nine out of ten prospects leave their stores in disgust when they learn the limitations. And this is a very important, very unfortunate gap. Because the promise of recognition -- what people want it to do -- carries with it tremendous improvements in our productivity and ability to get tons of written documents into our computers where we can do real work with it. The good news is that a revolutionary new development effort has led to the new technology of "page recognition," which actually does deliver the promise we've always wanted from OCR. I'm sure every reader appreciates the breakthrough represented by the laser printer and page-makeup software, a combination so powerful it created new reasons for buying a computer. A similar breakthrough is happening right now in page recognition: the Macintosh (and, I must admit, other personal computers) equipped with a moderately priced scanner and OmniPage software (from Caere

Local Renyi entropic profiles of DNA sequences.

PubMed

Vinga, Susana; Almeida, Jonas S

2007-10-16

In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs. The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at http://kdbio.inesc-id.pt/~svinga/ep/. The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures.

Local Renyi entropic profiles of DNA sequences

PubMed Central

Vinga, Susana; Almeida, Jonas S

2007-01-01

Background In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs. Results The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at . Conclusion The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures. PMID:17939871

Image correlation method for DNA sequence alignment.

PubMed

Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

2012-01-01

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Bidirectional Modulation of Recognition Memory

PubMed Central

Ho, Jonathan W.; Poeta, Devon L.; Jacobson, Tara K.; Zolnik, Timothy A.; Neske, Garrett T.; Connors, Barry W.

2015-01-01

Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30–40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30–40 Hz was not effective in increasing exploration of novel images. Stimulation at 10–15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally. SIGNIFICANCE STATEMENT Recognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that

Recognition mechanism of p63 by the E3 ligase Itch

PubMed Central

Bellomaria, Alessia; Barbato, Gaetano; Melino, Gerry; Paci, Maurizio; Melino, Sonia

2012-01-01

The HECT-containing E3 ubiquitin ligase Itch mediates the degradation of several proteins, including p63 and p73, involved in cell specification and fate. Itch contains four WW domains, which are essential for recognition on the target substrate, which contains a short proline-rich sequence. Several signaling complexes containing these domains have been associated with human diseases such as muscular dystrophy, Alzheimer’s or Huntington’s diseases. To gain further insight into the structural determinants of the Itch-WW2 domain, we investigated its interaction with p63. We assigned, by 3D heteronuclear NMR experiments, the backbone and side chains of the uniformly ¹³C-¹⁵N-labeled Itch-WW2. In vitro interaction of Itch-WW2 domain with p63 was studied using its interactive p63 peptide, pep63. Pep63 is an 18-mer peptide corresponding to the region from 534–551 residue of p63, encompassing the PPxY motif that interacts with the Itch-WW domains, and we identified the residues involved in this molecular recognition. Moreover, here, a strategy of stabilization of the conformation of the PPxY peptide has been adopted, increasing the WW-ligand binding. We demonstrated that cyclization of pep63 leads to an increase of both the biological stability of the peptide and of the WW-ligand complex. Stable metal-binding complexes of the pep63 have been also obtained, and localized oxidative damage on Itch-WW2 domain has been induced, demonstrating the possibility of use of metal-pep63 complexes as models for the design of metal drugs to inhibit the Itch-WW-p63 recognition in vivo. Thus, our data suggest a novel strategy to study and inhibit the recognition mechanism of Itch E3-ligase. PMID:22935697

An iris recognition algorithm based on DCT and GLCM

NASA Astrophysics Data System (ADS)

Feng, G.; Wu, Ye-qing

2008-04-01

With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and more important. So many different techniques for person's status identity were proposed for this practical usage. Conventional person's status identity methods like password and identification card are not always reliable. A wide variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot research point in the past several years. This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that the algorithm is effective and feasible with iris recognition.

A new method to improve network topological similarity search: applied to fold recognition

PubMed Central

Lhota, John; Hauptman, Ruth; Hart, Thomas; Ng, Clara; Xie, Lei

2015-01-01

Motivation: Similarity search is the foundation of bioinformatics. It plays a key role in establishing structural, functional and evolutionary relationships between biological sequences. Although the power of the similarity search has increased steadily in recent years, a high percentage of sequences remain uncharacterized in the protein universe. Thus, new similarity search strategies are needed to efficiently and reliably infer the structure and function of new sequences. The existing paradigm for studying protein sequence, structure, function and evolution has been established based on the assumption that the protein universe is discrete and hierarchical. Cumulative evidence suggests that the protein universe is continuous. As a result, conventional sequence homology search methods may be not able to detect novel structural, functional and evolutionary relationships between proteins from weak and noisy sequence signals. To overcome the limitations in existing similarity search methods, we propose a new algorithmic framework—Enrichment of Network Topological Similarity (ENTS)—to improve the performance of large scale similarity searches in bioinformatics. Results: We apply ENTS to a challenging unsolved problem: protein fold recognition. Our rigorous benchmark studies demonstrate that ENTS considerably outperforms state-of-the-art methods. As the concept of ENTS can be applied to any similarity metric, it may provide a general framework for similarity search on any set of biological entities, given their representation as a network. Availability and implementation: Source code freely available upon request Contact: lxie@iscb.org PMID:25717198

Online handwritten mathematical expression recognition

NASA Astrophysics Data System (ADS)

Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

2007-01-01

We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

Deep Learning Improves Antimicrobial Peptide Recognition.

PubMed

Veltri, Daniel; Kamath, Uday; Shehu, Amarda

2018-03-24

Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides (AMPs), natural components of innate immunity, are popular targets for developing new drugs. Machine learning methods are now commonly adopted by wet-laboratory researchers to screen for promising candidates. In this work we utilize deep learning to recognize antimicrobial activity. We propose a neural network model with convolutional and recurrent layers that leverage primary sequence composition. Results show that the proposed model outperforms state-of-the-art classification models on a comprehensive data set. By utilizing the embedding weights, we also present a reduced-alphabet representation and show that reasonable AMP recognition can be maintained using nine amino-acid types. Models and data sets are made freely available through the Antimicrobial Peptide Scanner vr.2 web server at: www.ampscanner.com. amarda@gmu.edu for general inquiries and dan.veltri@gmail.com for web server information. Supplementary data are available at Bioinformatics online.

Using GOMS and Bayesian plan recognition to develop recognition models of operator behavior

NASA Astrophysics Data System (ADS)

Zaientz, Jack D.; DeKoven, Elyon; Piegdon, Nicholas; Wood, Scott D.; Huber, Marcus J.

2006-05-01

Trends in combat technology research point to an increasing role for uninhabited vehicles in modern warfare tactics. To support increased span of control over these vehicles human responsibilities need to be transformed from tedious, error-prone and cognition intensive operations into tasks that are more supervisory and manageable, even under intensely stressful conditions. The goal is to move away from only supporting human command of low-level system functions to intention-level human-system dialogue about the operator's tasks and situation. A critical element of this process is developing the means to identify when human operators need automated assistance and to identify what assistance they need. Toward this goal, we are developing an unmanned vehicle operator task recognition system that combines work in human behavior modeling and Bayesian plan recognition. Traditionally, human behavior models have been considered generative, meaning they describe all possible valid behaviors. Basing behavior recognition on models designed for behavior generation can offers advantages in improved model fidelity and reuse. It is not clear, however, how to reconcile the structural differences between behavior recognition and behavior modeling approaches. Our current work demonstrates that by pairing a cognitive psychology derived human behavior modeling approach, GOMS, with a Bayesian plan recognition engine, ASPRN, we can translate a behavior generation model into a recognition model. We will discuss the implications for using human performance models in this manner as well as suggest how this kind of modeling may be used to support the real-time control of multiple, uninhabited battlefield vehicles and other semi-autonomous systems.

[Neurological disease and facial recognition].

PubMed

Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

2012-07-01

To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

Face Recognition From One Example View.

DTIC Science & Technology

1995-09-01

Proceedings, International Workshop on Automatic Face- and Gesture-Recognition, pages 248{253, Zurich, 1995. [32] Yael Moses, Shimon Ullman, and Shimon...recognition. Journal of Cognitive Neuroscience, 3(1):71{86, 1991. [49] Shimon Ullman and Ronen Basri. Recognition by linear combinations of models

Automatic face recognition in HDR imaging

NASA Astrophysics Data System (ADS)

Pereira, Manuela; Moreno, Juan-Carlos; Proença, Hugo; Pinheiro, António M. G.

2014-05-01

The gaining popularity of the new High Dynamic Range (HDR) imaging systems is raising new privacy issues caused by the methods used for visualization. HDR images require tone mapping methods for an appropriate visualization on conventional and non-expensive LDR displays. These visualization methods might result in completely different visualization raising several issues on privacy intrusion. In fact, some visualization methods result in a perceptual recognition of the individuals, while others do not even show any identity. Although perceptual recognition might be possible, a natural question that can rise is how computer based recognition will perform using tone mapping generated images? In this paper, a study where automatic face recognition using sparse representation is tested with images that result from common tone mapping operators applied to HDR images. Its ability for the face identity recognition is described. Furthermore, typical LDR images are used for the face recognition training.

DNA sequence selectivity of hairpin polyamide turn units

PubMed Central

Farkas, Michelle E.; Li, Benjamin C.; Dose, Christian; Dervan, Peter B.

2011-01-01

A class of hairpin polyamides linked by 3,4-diaminobutyric acid, resulting in a β-amine residue at the turn unit, showed improved binding affinities relative to their α-amino-γ-turn analogs for particular sequences. We incorporated β-amino-γ-turns in six-ring polyamides and determined whether there are any sequence preferences under the turn unit by quantitative footprinting titrations. Although there was an energetic penalty for G·C and C·G base pairs, we found little preference for T·A over A·T at the β-amino-γ-turn position. Fluorine and hydroxyl substituted α-amino-γ-turns were synthesized for comparison. Their binding affinities and specificities in the context of six-ring polyamides demonstrated overall diminished affinity and no additional specificity at the turn position. We anticipate that this study will be a baseline for further investigation of the turn subunit as a recognition element for the DNA minor groove. PMID:19349175

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

PubMed

Yildirim, Özal

2018-05-01

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Learning of goal-relevant and -irrelevant complex visual sequences in human V1.

PubMed

Rosenthal, Clive R; Mallik, Indira; Caballero-Gaudes, Cesar; Sereno, Martin I; Soto, David

2018-06-12

Learning and memory are supported by a network involving the medial temporal lobe and linked neocortical regions. Emerging evidence indicates that primary visual cortex (i.e., V1) may contribute to recognition memory, but this has been tested only with a single visuospatial sequence as the target memorandum. The present study used functional magnetic resonance imaging to investigate whether human V1 can support the learning of multiple, concurrent complex visual sequences involving discontinous (second-order) associations. Two peripheral, goal-irrelevant but structured sequences of orientated gratings appeared simultaneously in fixed locations of the right and left visual fields alongside a central, goal-relevant sequence that was in the focus of spatial attention. Pseudorandom sequences were introduced at multiple intervals during the presentation of the three structured visual sequences to provide an online measure of sequence-specific knowledge at each retinotopic location. We found that a network involving the precuneus and V1 was involved in learning the structured sequence presented at central fixation, whereas right V1 was modulated by repeated exposure to the concurrent structured sequence presented in the left visual field. The same result was not found in left V1. These results indicate for the first time that human V1 can support the learning of multiple concurrent sequences involving complex discontinuous inter-item associations, even peripheral sequences that are goal-irrelevant. Copyright © 2018. Published by Elsevier Inc.

Function-based classification of carbohydrate-active enzymes by recognition of short, conserved peptide motifs.

PubMed

Busk, Peter Kamp; Lange, Lene

2013-06-01

Functional prediction of carbohydrate-active enzymes is difficult due to low sequence identity. However, similar enzymes often share a few short motifs, e.g., around the active site, even when the overall sequences are very different. To exploit this notion for functional prediction of carbohydrate-active enzymes, we developed a simple algorithm, peptide pattern recognition (PPR), that can divide proteins into groups of sequences that share a set of short conserved sequences. When this method was used on 118 glycoside hydrolase 5 proteins with 9% average pairwise identity and representing four characterized enzymatic functions, 97% of the proteins were sorted into groups correlating with their enzymatic activity. Furthermore, we analyzed 8,138 glycoside hydrolase 13 proteins including 204 experimentally characterized enzymes with 28 different functions. There was a 91% correlation between group and enzyme activity. These results indicate that the function of carbohydrate-active enzymes can be predicted with high precision by finding short, conserved motifs in their sequences. The glycoside hydrolase 61 family is important for fungal biomass conversion, but only a few proteins of this family have been functionally characterized. Interestingly, PPR divided 743 glycoside hydrolase 61 proteins into 16 subfamilies useful for targeted investigation of the function of these proteins and pinpointed three conserved motifs with putative importance for enzyme activity. Furthermore, the conserved sequences were useful for cloning of new, subfamily-specific glycoside hydrolase 61 proteins from 14 fungi. In conclusion, identification of conserved sequence motifs is a new approach to sequence analysis that can predict carbohydrate-active enzyme functions with high precision.

Diagnosis of twin-to-twin transfusion syndrome, selective fetal growth restriction, twin anaemia-polycythaemia sequence, and twin reversed arterial perfusion sequence.

PubMed

Sueters, Marieke; Oepkes, Dick

2014-02-01

Monochorionic twin pregnancies are well known to be at risk for a variety of severe complications, a true challenge for the maternal-fetal medicine specialist. With current standards of care, monochorionicity should be established in the first trimester. Subsequently, frequent monitoring using the appropriate diagnostic tools, and in-depth knowledge about the pathophysiology of all possible clinical presentations of monochorionic twin abnormalities, should lead to timely recognition, and appropriate management. Virtually all unique diseases found in monochorionic twins are directly related to placental angio-architecture. This, however, cannot be established reliably before birth. The clinician needs to be aware of the definitions and symptoms of twin-to twin transfusion syndrome, selective fetal growth restriction, twin anaemia-polycythaemia sequence, and twin reversed arterial perfusion sequence, to be able to recognise each disease and take the required action. In this chapter, we address current standards on correct and timely diagnoses of severe complications of monochorionic twin pregnancies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Document recognition serving people with disabilities

NASA Astrophysics Data System (ADS)

Fruchterman, James R.

2007-01-01

Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

Recognition of maximum flooding events in mixed siliciclastic-carbonate systems: Key to global chronostratigraphic correlation

USGS Publications Warehouse

Mancini, E.A.; Tew, B.H.

1997-01-01

The maximum flooding event within a depositional sequence is an important datum for correlation because it represents a virtually synchronous horizon. This event is typically recognized by a distinctive physical surface and/or a significant change in microfossil assemblages (relative fossil abundance peaks) in siliciclastic deposits from shoreline to continental slope environments in a passive margin setting. Recognition of maximum flooding events in mixed siliciclastic-carbonate sediments is more complicated because the entire section usually represents deposition in continental shelf environments with varying rates of biologic and carbonate productivity versus siliciclastic influx. Hence, this event cannot be consistently identified simply by relative fossil abundance peaks. Factors such as siliciclastic input, carbonate productivity, sediment accumulation rates, and paleoenvironmental conditions dramatically affect the relative abundances of microfossils. Failure to recognize these complications can lead to a sequence stratigraphic interpretation that substantially overestimates the number of depositional sequences of 1 to 10 m.y. duration.

Single-Stranded γPNAs for In Vivo Site-Specific Genome Editing via Watson-Crick Recognition

PubMed Central

Bahal, Raman; Quijano, Elias; McNeer, Nicole Ali; Liu, Yanfeng; Bhunia, Dinesh C.; López-Giráldez, Francesco; Fields, Rachel J.; Saltzman, W. Mark; Ly, Danith H.; Glazer, Peter M.

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction. PMID:25174576

Single-stranded γPNAs for in vivo site-specific genome editing via Watson-Crick recognition.

PubMed

Bahal, Raman; Quijano, Elias; McNeer, Nicole A; Liu, Yanfeng; Bhunia, Dinesh C; Lopez-Giraldez, Francesco; Fields, Rachel J; Saltzman, William M; Ly, Danith H; Glazer, Peter M

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction.

Infant Visual Recognition Memory

ERIC Educational Resources Information Center

Rose, Susan A.; Feldman, Judith F.; Jankowski, Jeffery J.

2004-01-01

Visual recognition memory is a robust form of memory that is evident from early infancy, shows pronounced developmental change, and is influenced by many of the same factors that affect adult memory; it is surprisingly resistant to decay and interference. Infant visual recognition memory shows (a) modest reliability, (b) good discriminant…

Unconstrained handwritten numeral recognition based on radial basis competitive and cooperative networks with spatio-temporal feature representation.

PubMed

Lee, S; Pan, J J

1996-01-01

This paper presents a new approach to representation and recognition of handwritten numerals. The approach first transforms a two-dimensional (2-D) spatial representation of a numeral into a three-dimensional (3-D) spatio-temporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. A multiresolution critical-point segmentation method is then proposed to extract local feature points, at varying degrees of scale and coarseness. A new neural network architecture, referred to as radial-basis competitive and cooperative network (RCCN), is presented especially for handwritten numeral recognition. RCCN is a globally competitive and locally cooperative network with the capability of self-organizing hidden units to progressively achieve desired network performance, and functions as a universal approximator of arbitrary input-output mappings. Three types of RCCNs are explored: input-space RCCN (IRCCN), output-space RCCN (ORCCN), and bidirectional RCCN (BRCCN). Experiments against handwritten zip code numerals acquired by the U.S. Postal Service indicated that the proposed method is robust in terms of variations, deformations, transformations, and corruption, achieving about 97% recognition rate.

A model of EcoRII restriction endonuclease action: the active complex is most likely formed by one protein subunit and one DNA recognition site

NASA Technical Reports Server (NTRS)

Karpova, E. A.; Kubareva, E. A.; Shabarova, Z. A.

1999-01-01

To elucidate the mechanism of interaction of restriction endonuclease EcoRII with DNA, we studied by native gel electrophoresis the binding of this endonuclease to a set of synthetic DNA-duplexes containing the modified or canonical recognition sequence 5'-d(CCA/TGG)-3'. All binding substrate or substrate analogues tested could be divided into two major groups: (i) duplexes that, at the interaction with endonuclease EcoRII, form two types of stable complexes on native gel in the absence of Mg2+ cofactor; (ii) duplexes that form only one type of complex, observed both in the presence and absence of Mg2+. Unlike the latter, duplexes under the first group can be hydrolyzed by endonuclease. Data obtained suggest that the active complex is most likely formed by one protein subunit and one DNA recognition sequence. A model of EcoRII endonuclease action is presented.

Sequence skill learning in persons who stutter: implications for cortico-striato-thalamo-cortical dysfunction.

PubMed

Smits-Bandstra, Sarah; De Nil, Luc F

2007-01-01

The basal ganglia and cortico-striato-thalamo-cortical connections are known to play a critical role in sequence skill learning and increasing automaticity over practice. The current paper reviews four studies comparing the sequence skill learning and the transition to automaticity of persons who stutter (PWS) and fluent speakers (PNS) over practice. Studies One and Two found PWS to have poor finger tap sequencing skill and nonsense syllable sequencing skill after practice, and on retention and transfer tests relative to PNS. Studies Three and Four found PWS to be significantly less accurate and/or significantly slower after practice on dual tasks requiring concurrent sequencing and colour recognition over practice relative to PNS. Evidence of PWS' deficits in sequence skill learning and automaticity development support the hypothesis that dysfunction in cortico-striato-thalamo-cortical connections may be one etiological component in the development and maintenance of stuttering. As a result of this activity, the reader will: (1) be able to articulate the research regarding the basal ganglia system relating to sequence skill learning; (2) be able to summarize the research on stuttering with indications of sequence skill learning deficits; and (3) be able to discuss basal ganglia mechanisms with relevance for theory of stuttering.

Experimental study on GMM-based speaker recognition

NASA Astrophysics Data System (ADS)

Ye, Wenxing; Wu, Dapeng; Nucci, Antonio

2010-04-01

Speaker recognition plays a very important role in the field of biometric security. In order to improve the recognition performance, many pattern recognition techniques have be explored in the literature. Among these techniques, the Gaussian Mixture Model (GMM) is proved to be an effective statistic model for speaker recognition and is used in most state-of-the-art speaker recognition systems. The GMM is used to represent the 'voice print' of a speaker through modeling the spectral characteristic of speech signals of the speaker. In this paper, we implement a speaker recognition system, which consists of preprocessing, Mel-Frequency Cepstrum Coefficients (MFCCs) based feature extraction, and GMM based classification. We test our system with TIDIGITS data set (325 speakers) and our own recordings of more than 200 speakers; our system achieves 100% correct recognition rate. Moreover, we also test our system under the scenario that training samples are from one language but test samples are from a different language; our system also achieves 100% correct recognition rate, which indicates that our system is language independent.

Quantum-Limited Image Recognition

DTIC Science & Technology

1989-12-01

J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 53. D. Barnea and H. Silverman...for Chapter 6 1. J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 2. D. Bamea and H

Cronobacter, the emergent bacterial pathogen Enterobacter sakazakii comes of age; MLST and whole genome sequence analysis.

PubMed

Forsythe, Stephen J; Dickins, Benjamin; Jolley, Keith A

2014-12-16

Following the association of Cronobacter spp. to several publicized fatal outbreaks in neonatal intensive care units of meningitis and necrotising enterocolitis, the World Health Organization (WHO) in 2004 requested the establishment of a molecular typing scheme to enable the international control of the organism. This paper presents the application of Next Generation Sequencing (NGS) to Cronobacter which has led to the establishment of the Cronobacter PubMLST genome and sequence definition database (http://pubmlst.org/cronobacter/) containing over 1000 isolates with metadata along with the recognition of specific clonal lineages linked to neonatal meningitis and adult infections Whole genome sequencing and multilocus sequence typing (MLST) has supports the formal recognition of the genus Cronobacter composed of seven species to replace the former single species Enterobacter sakazakii. Applying the 7-loci MLST scheme to 1007 strains revealed 298 definable sequence types, yet only C. sakazakii clonal complex 4 (CC4) was principally associated with neonatal meningitis. This clonal lineage has been confirmed using ribosomal-MLST (51-loci) and whole genome-MLST (1865 loci) to analyse 107 whole genomes via the Cronobacter PubMLST database. This database has enabled the retrospective analysis of historic cases and outbreaks following re-identification of those strains. The Cronobacter PubMLST database offers a central, open access, reliable sequence-based repository for researchers. It has the capacity to create new analysis schemes 'on the fly', and to integrate metadata (source, geographic distribution, clinical presentation). It is also expandable and adaptable to changes in taxonomy, and able to support the development of reliable detection methods of use to industry and regulatory authorities. Therefore it meets the WHO (2004) request for the establishment of a typing scheme for this emergent bacterial pathogen. Whole genome sequencing has additionally shown a range

Famous face recognition, face matching, and extraversion.

PubMed

Lander, Karen; Poyarekar, Siddhi

2015-01-01

It has been previously established that extraverts who are skilled at interpersonal interaction perform significantly better than introverts on a face-specific recognition memory task. In our experiment we further investigate the relationship between extraversion and face recognition, focusing on famous face recognition and face matching. Results indicate that more extraverted individuals perform significantly better on an upright famous face recognition task and show significantly larger face inversion effects. However, our results did not find an effect of extraversion on face matching or inverted famous face recognition.

Kazakh Traditional Dance Gesture Recognition

NASA Astrophysics Data System (ADS)

Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo

2014-04-01

Full body gesture recognition is an important and interdisciplinary research field which is widely used in many application spheres including dance gesture recognition. The rapid growth of technology in recent years brought a lot of contribution in this domain. However it is still challenging task. In this paper we implement Kazakh traditional dance gesture recognition. We use Microsoft Kinect camera to obtain human skeleton and depth information. Then we apply tree-structured Bayesian network and Expectation Maximization algorithm with K-means clustering to calculate conditional linear Gaussians for classifying poses. And finally we use Hidden Markov Model to detect dance gestures. Our main contribution is that we extend Kinect skeleton by adding headwear as a new skeleton joint which is calculated from depth image. This novelty allows us to significantly improve the accuracy of head gesture recognition of a dancer which in turn plays considerable role in whole body gesture recognition. Experimental results show the efficiency of the proposed method and that its performance is comparable to the state-of-the-art system performances.

Logo2PWM: a tool to convert sequence logo to position weight matrix.

PubMed

Gao, Zhen; Liu, Lu; Ruan, Jianhua

2017-10-03

position weight matrix (PWM) and sequence logo are the most widely used representations of transcription factor binding site (TFBS) in biological sequences. Sequence logo - a graphical representation of PWM, has been widely used in scientific publications and reports, due to its easiness of human perception, rich information, and simple format. Different from sequence logo, PWM works great as a precise and compact digitalized form, which can be easily used by a variety of motif analysis software. There are a few available tools to generate sequence logos from PWM; however, no tool does the reverse. Such tool to convert sequence logo back to PWM is needed to scan a TFBS represented in logo format in a publication where the PWM is not provided or hard to be acquired. A major difficulty in developing such tool to convert sequence logo to PWM is to deal with the diversity of sequence logo images. We propose logo2PWM for reconstructing PWM from a large variety of sequence logo images. Evaluation results on over one thousand logos from three sources of different logo format show that the correlation between the reconstructed PWMs and the original PWMs are constantly high, where median correlation is greater than 0.97. Because of the high recognition accuracy, the easiness of usage, and, the availability of both web-based service and stand-alone application, we believe that logo2PWM can readily benefit the study of transcription by filling the gap between sequence logo and PWM.

Fine-grained recognition of plants from images.

PubMed

Šulc, Milan; Matas, Jiří

2017-01-01

Fine-grained recognition of plants from images is a challenging computer vision task, due to the diverse appearance and complex structure of plants, high intra-class variability and small inter-class differences. We review the state-of-the-art and discuss plant recognition tasks, from identification of plants from specific plant organs to general plant recognition "in the wild". We propose texture analysis and deep learning methods for different plant recognition tasks. The methods are evaluated and compared them to the state-of-the-art. Texture analysis is only applied to images with unambiguous segmentation (bark and leaf recognition), whereas CNNs are only applied when sufficiently large datasets are available. The results provide an insight in the complexity of different plant recognition tasks. The proposed methods outperform the state-of-the-art in leaf and bark classification and achieve very competitive results in plant recognition "in the wild". The results suggest that recognition of segmented leaves is practically a solved problem, when high volumes of training data are available. The generality and higher capacity of state-of-the-art CNNs makes them suitable for plant recognition "in the wild" where the views on plant organs or plants vary significantly and the difficulty is increased by occlusions and background clutter.

Divided attention enhances the recognition of emotional stimuli: evidence from the attentional boost effect.

PubMed

Rossi-Arnaud, Clelia; Spataro, Pietro; Costanzi, Marco; Saraulli, Daniele; Cestari, Vincenzo

2018-01-01

The present study examined predictions of the early-phase-elevated-attention hypothesis of the attentional boost effect (ABE), which suggests that transient increases in attention at encoding, as instantiated in the ABE paradigm, should enhance the recognition of neutral and positive items (whose encoding is mostly based on controlled processes), while having small or null effects on the recognition of negative items (whose encoding is primarily based on automatic processes). Participants were presented a sequence of negative, neutral and positive stimuli (pictures in Experiment 1, words in Experiment 2) associated to target (red) squares, distractor (green) squares or no squares (baseline condition). They were told to attend to the pictures/words and simultaneously press the spacebar of the computer when a red square appeared. In a later recognition task, stimuli associated to target squares were recognised better than stimuli associated to distractor squares, replicating the standard ABE. More importantly, we also found that: (a) the memory enhancement following target detection occurred with all types of stimuli (neutral, negative and positive) and (b) the advantage of negative stimuli over neutral stimuli was intact in the DA condition. These findings suggest that the encoding of negative stimuli depends on both controlled (attention-dependent) and automatic (attention-independent) processes.

Transfer-Appropriate Processing in Recognition Memory: Perceptual and Conceptual Effects on Recognition Memory Depend on Task Demands

ERIC Educational Resources Information Center

Parks, Colleen M.

2013-01-01

Research examining the importance of surface-level information to familiarity in recognition memory tasks is mixed: Sometimes it affects recognition and sometimes it does not. One potential explanation of the inconsistent findings comes from the ideas of dual process theory of recognition and the transfer-appropriate processing framework, which…

Sequence Dependencies of DNA Deformability and Hydration in the Minor Groove

PubMed Central

Yonetani, Yoshiteru; Kono, Hidetoshi

2009-01-01

Abstract DNA deformability and hydration are both sequence-dependent and are essential in specific DNA sequence recognition by proteins. However, the relationship between the two is not well understood. Here, systematic molecular dynamics simulations of 136 DNA sequences that differ from each other in their central tetramer revealed that sequence dependence of hydration is clearly correlated with that of deformability. We show that this correlation can be illustrated by four typical cases. Most rigid basepair steps are highly likely to form an ordered hydration pattern composed of one water molecule forming a bridge between the bases of distinct strands, but a few exceptions favor another ordered hydration composed of two water molecules forming such a bridge. Steps with medium deformability can display both of these hydration patterns with frequent transition. Highly flexible steps do not have any stable hydration pattern. A detailed picture of this correlation demonstrates that motions of hydration water molecules and DNA bases are tightly coupled with each other at the atomic level. These results contribute to our understanding of the entropic contribution from water molecules in protein or drug binding and could be applied for the purpose of predicting binding sites. PMID:19686662

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition

PubMed Central

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-01-01

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates (F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware. PMID

A Public Database of Memory and Naive B-Cell Receptor Sequences.

PubMed

DeWitt, William S; Lindau, Paul; Snyder, Thomas M; Sherwood, Anna M; Vignali, Marissa; Carlson, Christopher S; Greenberg, Philip D; Duerkopp, Natalie; Emerson, Ryan O; Robins, Harlan S

2016-01-01

The vast diversity of B-cell receptors (BCR) and secreted antibodies enables the recognition of, and response to, a wide range of epitopes, but this diversity has also limited our understanding of humoral immunity. We present a public database of more than 37 million unique BCR sequences from three healthy adult donors that is many fold deeper than any existing resource, together with a set of online tools designed to facilitate the visualization and analysis of the annotated data. We estimate the clonal diversity of the naive and memory B-cell repertoires of healthy individuals, and provide a set of examples that illustrate the utility of the database, including several views of the basic properties of immunoglobulin heavy chain sequences, such as rearrangement length, subunit usage, and somatic hypermutation positions and dynamics.

Toward rules relating zinc finger protein sequences and DNA binding site preferences.

PubMed

Desjarlais, J R; Berg, J M

1992-08-15

Zinc finger proteins of the Cys2-His2 type consist of tandem arrays of domains, where each domain appears to contact three adjacent base pairs of DNA through three key residues. We have designed and prepared a series of variants of the central zinc finger within the DNA binding domain of Sp1 by using information from an analysis of a large data base of zinc finger protein sequences. Through systematic variations at two of the three contact positions (underlined), relatively specific recognition of sequences of the form 5'-GGGGN(G or T)GGG-3' has been achieved. These results provide the basis for rules that may develop into a code that will allow the design of zinc finger proteins with preselected DNA site specificity.

Relevance feedback-based building recognition

NASA Astrophysics Data System (ADS)

Li, Jing; Allinson, Nigel M.

2010-07-01

Building recognition is a nontrivial task in computer vision research which can be utilized in robot localization, mobile navigation, etc. However, existing building recognition systems usually encounter the following two problems: 1) extracted low level features cannot reveal the true semantic concepts; and 2) they usually involve high dimensional data which require heavy computational costs and memory. Relevance feedback (RF), widely applied in multimedia information retrieval, is able to bridge the gap between the low level visual features and high level concepts; while dimensionality reduction methods can mitigate the high-dimensional problem. In this paper, we propose a building recognition scheme which integrates the RF and subspace learning algorithms. Experimental results undertaken on our own building database show that the newly proposed scheme appreciably enhances the recognition accuracy.

Face Recognition in Humans and Machines

NASA Astrophysics Data System (ADS)

O'Toole, Alice; Tistarelli, Massimo

The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

[Screening specific recognition motif of RNA-binding proteins by SELEX in combination with next-generation sequencing technique].

PubMed

Zhang, Lu; Xu, Jinhao; Ma, Jinbiao

2016-07-25

RNA-binding protein exerts important biological function by specifically recognizing RNA motif. SELEX (Systematic evolution of ligands by exponential enrichment), an in vitro selection method, can obtain consensus motif with high-affinity and specificity for many target molecules from DNA or RNA libraries. Here, we combined SELEX with next-generation sequencing to study the protein-RNA interaction in vitro. A pool of RNAs with 20 bp random sequences were transcribed by T7 promoter, and target protein was inserted into plasmid containing SBP-tag, which can be captured by streptavidin beads. Through only one cycle, the specific RNA motif can be obtained, which dramatically improved the selection efficiency. Using this method, we found that human hnRNP A1 RRMs domain (UP1 domain) bound RNA motifs containing AGG and AG sequences. The EMSA experiment indicated that hnRNP A1 RRMs could bind the obtained RNA motif. Taken together, this method provides a rapid and effective method to study the RNA binding specificity of proteins.

Human fatigue expression recognition through image-based dynamic multi-information and bimodal deep learning

NASA Astrophysics Data System (ADS)

Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin

2016-09-01

Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.

The coevolution of recognition and social behavior.

PubMed

Smead, Rory; Forber, Patrick

2016-05-26

Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation.

The coevolution of recognition and social behavior

PubMed Central

Smead, Rory; Forber, Patrick

2016-01-01

Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation. PMID:27225673

Analyses of potential factors affecting survival of juvenile salmonids volitionally passing through turbines at McNary and John Day Dams, Columbia River

USGS Publications Warehouse

Beeman, John; Hansel, Hal; Perry, Russell; Hockersmith, Eric; Sandford, Ben

2011-01-01

This report describes analyses of data from radio- or acoustic-tagged juvenile salmonids passing through hydro-dam turbines to determine factors affecting fish survival. The data were collected during a series of studies designed to estimate passage and survival probabilities at McNary (2002-09) and John Day (2002-03) Dams on the Columbia River during controlled experiments of structures or operations at spillways. Relatively few tagged fish passed turbines in any single study, but sample sizes generally were adequate for our analyses when data were combined from studies using common methods over a series of years. We used information-theoretic methods to evaluate biological, operational, and group covariates by creating models fitting linear (all covariates) or curvilinear (operational covariates only) functions to the data. Biological covariates included tag burden, weight, and water temperature; operational covariates included spill percentage, total discharge, hydraulic head, and turbine unit discharge; and group covariates included year, treatment, and photoperiod. Several interactions between the variables also were considered. Support of covariates by the data was assessed by comparing the Akaike Information Criterion of competing models. The analyses were conducted because there was a lack of information about factors affecting survival of fish passing turbines volitionally and the data were available from past studies. The depth of acclimation, tag size relative to fish size (tag burden), turbine unit discharge, and area of entry into the turbine intake have been shown to affect turbine passage survival of juvenile salmonids in other studies. This study indicates that turbine passage survival of the study fish was primarily affected by biological covariates rather than operational covariates. A negative effect of tag burden was strongly supported in data from yearling Chinook salmon at John Day and McNary dams, but not for subyearling Chinook salmon or

Bilingual Language Switching: Production vs. Recognition

PubMed Central

Mosca, Michela; de Bot, Kees

2017-01-01

This study aims at assessing how bilinguals select words in the appropriate language in production and recognition while minimizing interference from the non-appropriate language. Two prominent models are considered which assume that when one language is in use, the other is suppressed. The Inhibitory Control (IC) model suggests that, in both production and recognition, the amount of inhibition on the non-target language is greater for the stronger compared to the weaker language. In contrast, the Bilingual Interactive Activation (BIA) model proposes that, in language recognition, the amount of inhibition on the weaker language is stronger than otherwise. To investigate whether bilingual language production and recognition can be accounted for by a single model of bilingual processing, we tested a group of native speakers of Dutch (L1), advanced speakers of English (L2) in a bilingual recognition and production task. Specifically, language switching costs were measured while participants performed a lexical decision (recognition) and a picture naming (production) task involving language switching. Results suggest that while in language recognition the amount of inhibition applied to the non-appropriate language increases along with its dominance as predicted by the IC model, in production the amount of inhibition applied to the non-relevant language is not related to language dominance, but rather it may be modulated by speakers' unconscious strategies to foster the weaker language. This difference indicates that bilingual language recognition and production might rely on different processing mechanisms and cannot be accounted within one of the existing models of bilingual language processing. PMID:28638361

Action Recognition in a Crowded Environment

PubMed Central

Nieuwenhuis, Judith; Bülthoff, Isabelle; Barraclough, Nick; de la Rosa, Stephan

2017-01-01

So far, action recognition has been mainly examined with small point-light human stimuli presented alone within a narrow central area of the observer’s visual field. Yet, we need to recognize the actions of life-size humans viewed alone or surrounded by bystanders, whether they are seen in central or peripheral vision. Here, we examined the mechanisms in central vision and far periphery (40° eccentricity) involved in the recognition of the actions of a life-size actor (target) and their sensitivity to the presence of a crowd surrounding the target. In Experiment 1, we used an action adaptation paradigm to probe whether static or idly moving crowds might interfere with the recognition of a target’s action (hug or clap). We found that this type of crowds whose movements were dissimilar to the target action hardly affected action recognition in central and peripheral vision. In Experiment 2, we examined whether crowd actions that were more similar to the target actions affected action recognition. Indeed, the presence of that crowd diminished adaptation aftereffects in central vision as wells as in the periphery. We replicated Experiment 2 using a recognition task instead of an adaptation paradigm. With this task, we found evidence of decreased action recognition accuracy, but this was significant in peripheral vision only. Our results suggest that the presence of a crowd carrying out actions similar to that of the target affects its recognition. We outline how these results can be understood in terms of high-level crowding effects that operate on action-sensitive perceptual channels. PMID:29308177

Bilingual Language Switching: Production vs. Recognition.