Attentional load and implicit sequence learning.

Science.gov (United States)

Shanks, David R; Rowland, Lee A; Ranger, Mandeep S

2005-06-01

A widely employed conceptualization of implicit learning hypothesizes that it makes minimal demands on attentional resources. This conjecture was investigated by comparing learning under single-task and dual-task conditions in the sequential reaction time (SRT) task. Participants learned probabilistic sequences, with dual-task participants additionally having to perform a counting task using stimuli that were targets in the SRT display. Both groups were then tested for sequence knowledge under single-task (Experiments 1 and 2) or dual-task (Experiment 3) conditions. Participants also completed a free generation task (Experiments 2 and 3) under inclusion or exclusion conditions to determine if sequence knowledge was conscious or unconscious in terms of its access to intentional control. The experiments revealed that the secondary task impaired sequence learning and that sequence knowledge was consciously accessible. These findings disconfirm both the notion that implicit learning is able to proceed normally under conditions of divided attention, and that the acquired knowledge is inaccessible to consciousness. A unitary framework for conceptualizing implicit and explicit learning is proposed.

PLS and multicollinearity under conditions common in satisfaction studies

DEFF Research Database (Denmark)

Nielsen, Rikke; Kristensen, Kai; Eskildsen, Jacob Kjær

A number of studies have investigated the performance of the PLS path modelling algorithm in the presence of common empirical problems, such as model misspecification, skewness of manifest variables, missing values, and multicollinearity, and they have shown PLS to be quite robust (see e.g. Cassel...... et al., 1999; Kristensen, Eskildsen, 2005). However, most of the studies, including our own, have focused on somewhat simple models with very simple correlation structures. This paper extends the existing knowledge by investigating the effect of varying degrees of multicollinearity on the PLS model...

The effect of PLS regression in PLS path model estimation when multicollinearity is present

DEFF Research Database (Denmark)

Nielsen, Rikke; Kristensen, Kai; Eskildsen, Jacob

PLS path modelling has previously been found to be robust to multicollinearity both between latent variables and between manifest variables of a common latent variable (see e.g. Cassel et al. (1999), Kristensen, Eskildsen (2005), Westlund et al. (2008)). However, most of the studies investigate...... models with relatively few variables and very simple dependence structures compared to the models that are often estimated in practical settings. A recent study by Nielsen et al. (2009) found that when model structure is more complex, PLS path modelling is not as robust to multicollinearity between...... latent variables as previously assumed. A difference in the standard error of path coefficients of as much as 83% was found between moderate and severe levels of multicollinearity. Large differences were found not only for large path coefficients, but also for small path coefficients and in some cases...

Implicit sequence learning in people with Parkinson’s disease

Directory of Open Access Journals (Sweden)

Katherine R Gamble

2014-08-01

Full Text Available Implicit sequence learning involves learning about dependencies in sequences of events without intent to learn or awareness of what has been learned. Sequence learning is related to striatal dopamine levels, striatal activation, and integrity of white matter connections. People with Parkinson’s disease (PD have degeneration of dopamine-producing neurons, leading to dopamine deficiency and therefore striatal deficits, and they have difficulties with sequencing, including complex language comprehension and postural stability. Most research on implicit sequence learning in PD has used motor-based tasks. However, because PD presents with motor deficits, it is difficult to assess whether learning itself is impaired in these tasks. The present study used an implicit sequence learning task with a reduced motor component, the Triplets Learning Task (TLT. People with PD and age- and education-matched healthy older adults completed three sessions (each consisting of 10 blocks of 50 trials of the TLT. Results revealed that the PD group was able to learn the sequence, however, when learning was examined using a Half Blocks analysis (Nemeth et al., 2013, which compared learning in the 1st 25/50 trials of all blocks to that in the 2nd 25/50 trials, the PD group showed significantly less learning than Controls in the 2nd Half Blocks, but not in the 1st. Nemeth et al. hypothesized that the 1st Half Blocks involve recall and reactivation of the sequence learned, thus reflecting hippocampal-dependent learning, while the 2nd Half Blocks involve proceduralized behavior of learned sequences, reflecting striatal-based learning. The present results suggest that the PD group had intact hippocampal-dependent implicit sequence learning, but impaired striatal-dependent learning. Thus, sequencing deficits in PD are likely due to striatal impairments, but other brain systems, such as the hippocampus, may be able to partially compensate for striatal decline to improve

Mixture quantification using PLS in plastic scintillation measurements

Energy Technology Data Exchange (ETDEWEB)

Bagan, H.; Tarancon, A.; Rauret, G. [Departament de Quimica Analitica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain); Garcia, J.F., E-mail: jfgarcia@ub.ed [Departament de Quimica Analitica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain)

2011-06-15

This article reports the capability of plastic scintillation (PS) combined with multivariate calibration (Partial least squares; PLS) to detect and quantify alpha and beta emitters in mixtures. While several attempts have been made with this purpose in mind using liquid scintillation (LS), no attempt was done using PS that has the great advantage of not producing mixed waste after the measurements are performed. Following this objective, ternary mixtures of alpha and beta emitters ({sup 241}Am, {sup 137}Cs and {sup 90}Sr/{sup 90}Y) have been quantified. Procedure optimisation has evaluated the use of the net spectra or the sample spectra, the inclusion of different spectra obtained at different values of the Pulse Shape Analysis parameter and the application of the PLS1 or PLS2 algorithms. The conclusions show that the use of PS+PLS2 applied to the sample spectra, without the use of any pulse shape discrimination, allows quantification of the activities with relative errors less than 10% in most of the cases. This procedure not only allows quantification of mixtures but also reduces measurement time (no blanks are required) and the application of this procedure does not require detectors that include the pulse shape analysis parameter.

Pink line syndrome (PLS) in the scleractinian coral Porites lutea

Digital Repository Service at National Institute of Oceanography (India)

Ravindran, J.; Raghukumar, C.

Reef sites Pink line syndrome (PLS) in the scleractinian coral Porites lutea Accepted: 10 May 2002 / Published online: 5 July 2002 C211 Springer-Verlag 2002 We describe here an unreport- ed diseased state of Porites lutea (Milne-Edwards and Haime...)ontheKavarattireefof the Lakshadweep group of is- lands (11C176 N; 71C176E). Pink line syndrome (PLS) causes partial mortality of the coral P. lutea around Kavaratti Island (Fig. 1), and about 10% of colonies were found to be af- fected by PLS. The dead patches were colonized by a...

Collective effects of the PLS 2 GeV storage ring

International Nuclear Information System (INIS)

Yoon, M.; Choi, J.; Lee, T.

1993-01-01

Collective effects of the PLS storage ring are discussed. Evaluation of the PLS storage ring coupling impedances is presented. RF cavity Impedances are emphasized. Single-bunch threshold current is studied and longitudinal coupled-bunch instabilities caused by RF narrow-band resonances are analyzed

Fault detection in processes represented by PLS models using an EWMA control scheme

KAUST Repository

Harrou, Fouzi

2016-10-20

Fault detection is important for effective and safe process operation. Partial least squares (PLS) has been used successfully in fault detection for multivariate processes with highly correlated variables. However, the conventional PLS-based detection metrics, such as the Hotelling\\'s T and the Q statistics are not well suited to detect small faults because they only use information about the process in the most recent observation. Exponentially weighed moving average (EWMA), however, has been shown to be more sensitive to small shifts in the mean of process variables. In this paper, a PLS-based EWMA fault detection method is proposed for monitoring processes represented by PLS models. The performance of the proposed method is compared with that of the traditional PLS-based fault detection method through a simulated example involving various fault scenarios that could be encountered in real processes. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS method.

Continuous Online Sequence Learning with an Unsupervised Neural Network Model.

Science.gov (United States)

Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff

2016-09-14

The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.

Decrease in gamma-band activity tracks sequence learning

Science.gov (United States)

Madhavan, Radhika; Millman, Daniel; Tang, Hanlin; Crone, Nathan E.; Lenz, Fredrick A.; Tierney, Travis S.; Madsen, Joseph R.; Kreiman, Gabriel; Anderson, William S.

2015-01-01

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30–100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces. PMID:25653598

Enhanced Anomaly Detection Via PLS Regression Models and Information Entropy Theory

KAUST Repository

Harrou, Fouzi

2015-12-07

Accurate and effective fault detection and diagnosis of modern engineering systems is crucial for ensuring reliability, safety and maintaining the desired product quality. In this work, we propose an innovative method for detecting small faults in the highly correlated multivariate data. The developed method utilizes partial least square (PLS) method as a modelling framework, and the symmetrized Kullback-Leibler divergence (KLD) as a monitoring index, where it is used to quantify the dissimilarity between probability distributions of current PLS-based residual and reference one obtained using fault-free data. The performance of the PLS-based KLD fault detection algorithm is illustrated and compared to the conventional PLS-based fault detection methods. Using synthetic data, we have demonstrated the greater sensitivity and effectiveness of the developed method over the conventional methods, especially when data are highly correlated and small faults are of interest.

Enhanced Anomaly Detection Via PLS Regression Models and Information Entropy Theory

KAUST Repository

Harrou, Fouzi; Sun, Ying

2015-01-01

Accurate and effective fault detection and diagnosis of modern engineering systems is crucial for ensuring reliability, safety and maintaining the desired product quality. In this work, we propose an innovative method for detecting small faults in the highly correlated multivariate data. The developed method utilizes partial least square (PLS) method as a modelling framework, and the symmetrized Kullback-Leibler divergence (KLD) as a monitoring index, where it is used to quantify the dissimilarity between probability distributions of current PLS-based residual and reference one obtained using fault-free data. The performance of the PLS-based KLD fault detection algorithm is illustrated and compared to the conventional PLS-based fault detection methods. Using synthetic data, we have demonstrated the greater sensitivity and effectiveness of the developed method over the conventional methods, especially when data are highly correlated and small faults are of interest.

The Plasmin-Sensitive Protein Pls in Methicillin-Resistant Staphylococcus aureus (MRSA Is a Glycoprotein.

Directory of Open Access Journals (Sweden)

Isabelle Bleiziffer

2017-01-01

Full Text Available Most bacterial glycoproteins identified to date are virulence factors of pathogenic bacteria, i.e. adhesins and invasins. However, the impact of protein glycosylation on the major human pathogen Staphylococcus aureus remains incompletely understood. To study protein glycosylation in staphylococci, we analyzed lysostaphin lysates of methicillin-resistant Staphylococcus aureus (MRSA strains by SDS-PAGE and subsequent periodic acid-Schiff's staining. We detected four (>300, ∼250, ∼165, and ∼120 kDa and two (>300 and ∼175 kDa glycosylated surface proteins with strain COL and strain 1061, respectively. The ∼250, ∼165, and ∼175 kDa proteins were identified as plasmin-sensitive protein (Pls by mass spectrometry. Previously, Pls has been demonstrated to be a virulence factor in a mouse septic arthritis model. The pls gene is encoded by the staphylococcal cassette chromosome (SCCmec type I in MRSA that also encodes the methicillin resistance-conferring mecA and further genes. In a search for glycosyltransferases, we identified two open reading frames encoded downstream of pls on the SCCmec element, which we termed gtfC and gtfD. Expression and deletion analysis revealed that both gtfC and gtfD mediate glycosylation of Pls. Additionally, the recently reported glycosyltransferases SdgA and SdgB are involved in Pls glycosylation. Glycosylation occurs at serine residues in the Pls SD-repeat region and modifying carbohydrates are N-acetylhexosaminyl residues. Functional characterization revealed that Pls can confer increased biofilm formation, which seems to involve two distinct mechanisms. The first mechanism depends on glycosylation of the SD-repeat region by GtfC/GtfD and probably also involves eDNA, while the second seems to be independent of glycosylation as well as eDNA and may involve the centrally located G5 domains. Other previously known Pls properties are not related to the sugar modifications. In conclusion, Pls is a glycoprotein and

Offset Free Tracking Predictive Control Based on Dynamic PLS Framework

Directory of Open Access Journals (Sweden)

Jin Xin

2017-10-01

Full Text Available This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.

[MEG]PLS: A pipeline for MEG data analysis and partial least squares statistics.

Science.gov (United States)

Cheung, Michael J; Kovačević, Natasa; Fatima, Zainab; Mišić, Bratislav; McIntosh, Anthony R

2016-01-01

The emphasis of modern neurobiological theories has recently shifted from the independent function of brain areas to their interactions in the context of whole-brain networks. As a result, neuroimaging methods and analyses have also increasingly focused on network discovery. Magnetoencephalography (MEG) is a neuroimaging modality that captures neural activity with a high degree of temporal specificity, providing detailed, time varying maps of neural activity. Partial least squares (PLS) analysis is a multivariate framework that can be used to isolate distributed spatiotemporal patterns of neural activity that differentiate groups or cognitive tasks, to relate neural activity to behavior, and to capture large-scale network interactions. Here we introduce [MEG]PLS, a MATLAB-based platform that streamlines MEG data preprocessing, source reconstruction and PLS analysis in a single unified framework. [MEG]PLS facilitates MRI preprocessing, including segmentation and coregistration, MEG preprocessing, including filtering, epoching, and artifact correction, MEG sensor analysis, in both time and frequency domains, MEG source analysis, including multiple head models and beamforming algorithms, and combines these with a suite of PLS analyses. The pipeline is open-source and modular, utilizing functions from FieldTrip (Donders, NL), AFNI (NIMH, USA), SPM8 (UCL, UK) and PLScmd (Baycrest, CAN), which are extensively supported and continually developed by their respective communities. [MEG]PLS is flexible, providing both a graphical user interface and command-line options, depending on the needs of the user. A visualization suite allows multiple types of data and analyses to be displayed and includes 4-D montage functionality. [MEG]PLS is freely available under the GNU public license (http://meg-pls.weebly.com). Copyright © 2015 Elsevier Inc. All rights reserved.

The Effect of Nonnormality on CB-SEM and PLS-SEM Path Estimates

OpenAIRE

Z. Jannoo; B. W. Yap; N. Auchoybur; M. A. Lazim

2014-01-01

The two common approaches to Structural Equation Modeling (SEM) are the Covariance-Based SEM (CB-SEM) and Partial Least Squares SEM (PLS-SEM). There is much debate on the performance of CB-SEM and PLS-SEM for small sample size and when distributions are nonnormal. This study evaluates the performance of CB-SEM and PLS-SEM under normality and nonnormality conditions via a simulation. Monte Carlo Simulation in R programming language was employed to generate data based on the theoretical model w...

Timing system for PLS

International Nuclear Information System (INIS)

Chang, S.S.; Kim, M.S.; Won, S.C.; Choi, S.J.

1991-01-01

The PLS timing system consists of a master oscillator, a repetition rate pulse generator, a storage ring rf synchronizing system, and a rf driver and kicker trigger system composed of a fixed delay module and variable delay modules. All the timing modules are installed in the VME crates and controlled by the 32 bit microprocessors, and communicating with the Host computer via Ethernet. This paper describes the architectural design of this system as well as the requirements of performance

Helium Leak Test for the PLS Storage Ring Chamber

International Nuclear Information System (INIS)

Choi, M. H.; Kim, H. J.; Choi, W. C.

1993-01-01

The storage ring vacuum system for the Pohang Light Source (PLS) has been designed to maintain the vacuum pressure of 10 1 0 Torr which requires UHV welding to have helium leak rate less than 1x10 1 0 Torr·L/sec. In order to develop new technique (PLS) welding technique), a prototype vacuum chamber has been welded by using Tungsten Inert Gas welding method and all the welded joints have been tested with a non-destructive method, so called helium leak detection, to investigate the vacuum tightness of the weld joints. The test was performed with a detection limit of 1x10 1 0 Torr·L/sec for helium and no detectable leaks were found for all the welded joints. Thus the performance of welding technique is proven to meet the criteria of helium leak rate required in the PLS Storage Ring. Both the principle and the procedure for the helium leak detection are also discussed

Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data

Science.gov (United States)

Yin, Shen; Wang, Guang; Yang, Xu

2014-07-01

In practical industrial applications, the key performance indicator (KPI)-related prediction and diagnosis are quite important for the product quality and economic benefits. To meet these requirements, many advanced prediction and monitoring approaches have been developed which can be classified into model-based or data-driven techniques. Among these approaches, partial least squares (PLS) is one of the most popular data-driven methods due to its simplicity and easy implementation in large-scale industrial process. As PLS is totally based on the measured process data, the characteristics of the process data are critical for the success of PLS. Outliers and missing values are two common characteristics of the measured data which can severely affect the effectiveness of PLS. To ensure the applicability of PLS in practical industrial applications, this paper introduces a robust version of PLS to deal with outliers and missing values, simultaneously. The effectiveness of the proposed method is finally demonstrated by the application results of the KPI-related prediction and diagnosis on an industrial benchmark of Tennessee Eastman process.

Implicit sequence learning in deaf children with cochlear implants.

Science.gov (United States)

Conway, Christopher M; Pisoni, David B; Anaya, Esperanza M; Karpicke, Jennifer; Henning, Shirley C

2011-01-01

Deaf children with cochlear implants (CIs) represent an intriguing opportunity to study neurocognitive plasticity and reorganization when sound is introduced following a period of auditory deprivation early in development. Although it is common to consider deafness as affecting hearing alone, it may be the case that auditory deprivation leads to more global changes in neurocognitive function. In this paper, we investigate implicit sequence learning abilities in deaf children with CIs using a novel task that measured learning through improvement to immediate serial recall for statistically consistent visual sequences. The results demonstrated two key findings. First, the deaf children with CIs showed disturbances in their visual sequence learning abilities relative to the typically developing normal-hearing children. Second, sequence learning was significantly correlated with a standardized measure of language outcome in the CI children. These findings suggest that a period of auditory deprivation has secondary effects related to general sequencing deficits, and that disturbances in sequence learning may at least partially explain why some deaf children still struggle with language following cochlear implantation. © 2010 Blackwell Publishing Ltd.

First-order and higher order sequence learning in specific language impairment.

Science.gov (United States)

Clark, Gillian M; Lum, Jarrad A G

2017-02-01

A core claim of the procedural deficit hypothesis of specific language impairment (SLI) is that the disorder is associated with poor implicit sequence learning. This study investigated whether implicit sequence learning problems in SLI are present for first-order conditional (FOC) and higher order conditional (HOC) sequences. Twenty-five children with SLI and 27 age-matched, nonlanguage-impaired children completed 2 serial reaction time tasks. On 1 version, the sequence to be implicitly learnt comprised a FOC sequence and on the other a HOC sequence. Results showed that the SLI group learned the HOC sequence (η p ² = .285, p = .005) but not the FOC sequence (η p ² = .099, p = .118). The control group learned both sequences (FOC η p ² = .497, HOC η p 2= .465, ps < .001). The SLI group's difficulty learning the FOC sequence is consistent with the procedural deficit hypothesis. However, the study provides new evidence that multiple mechanisms may underpin the learning of FOC and HOC sequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Identification and characterization of a novel type of replication terminator with bidirectional activity on the Bacillus subtilis theta plasmid pLS20

NARCIS (Netherlands)

Meijer, WJJ; Smith, M; Wake, RG; deBoer, AL; Venema, G; Bron, S

We have sequenced and analysed a 3.1 kb fragment of the 55 kb endogenous Bacillus subtilis plasmid pLS20 containing its replication functions, Just outside the region required for autonomous replication, a segment of 18 bp was identified as being almost identical to part of the major B. subtilis

An Evolutionary Machine Learning Framework for Big Data Sequence Mining

Science.gov (United States)

Kamath, Uday Krishna

2014-01-01

Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…

Differentiating Visual from Response Sequencing during Long-term Skill Learning.

Science.gov (United States)

Lynch, Brighid; Beukema, Patrick; Verstynen, Timothy

2017-01-01

The dual-system model of sequence learning posits that during early learning there is an advantage for encoding sequences in sensory frames; however, it remains unclear whether this advantage extends to long-term consolidation. Using the serial RT task, we set out to distinguish the dynamics of learning sequential orders of visual cues from learning sequential responses. On each day, most participants learned a new mapping between a set of symbolic cues and responses made with one of four fingers, after which they were exposed to trial blocks of either randomly ordered cues or deterministic ordered cues (12-item sequence). Participants were randomly assigned to one of four groups (n = 15 per group): Visual sequences (same sequence of visual cues across training days), Response sequences (same order of key presses across training days), Combined (same serial order of cues and responses on all training days), and a Control group (a novel sequence each training day). Across 5 days of training, sequence-specific measures of response speed and accuracy improved faster in the Visual group than any of the other three groups, despite no group differences in explicit awareness of the sequence. The two groups that were exposed to the same visual sequence across days showed a marginal improvement in response binding that was not found in the other groups. These results indicate that there is an advantage, in terms of rate of consolidation across multiple days of training, for learning sequences of actions in a sensory representational space, rather than as motoric representations.

Construction of Network Management Information System of Agricultural Products Supply Chain Based on 3PLs

Institute of Scientific and Technical Information of China (English)

2010-01-01

The necessity to construct the network management information system of 3PLs agricultural supply chain is analyzed,showing that 3PLs can improve the overall competitive advantage of agricultural supply chain.3PLs changes the homogeneity management into specialized management of logistics service and achieves the alliance of the subjects at different nodes of agricultural products supply chain.Network management information system structure of agricultural products supply chain based on 3PLs is constructed,including the four layers (the network communication layer,the hardware and software environment layer,the database layer,and the application layer) and 7 function modules (centralized control,transportation process management,material and vehicle scheduling,customer relationship,storage management,customer inquiry,and financial management).Framework for the network management information system of agricultural products supply chain based on 3PLs is put forward.The management of 3PLs mainly includes purchasing management,supplier relationship management,planning management,customer relationship management,storage management and distribution management.Thus,a management system of internal and external integrated agricultural enterprises is obtained.The network management information system of agricultural products supply chain based on 3PLs has realized the effective sharing of enterprise information of agricultural products supply chain at different nodes,establishing a long-term partnership revolving around the 3PLs core enterprise,as well as a supply chain with stable relationship based on the supply chain network system,so as to improve the circulation efficiency of agricultural products,and to explore the sales market for agricultural products.

Motor sequence learning-induced neural efficiency in functional brain connectivity.

Science.gov (United States)

Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

2017-02-15

Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

The Picmonic(®) Learning System: enhancing memory retention of medical sciences, using an audiovisual mnemonic Web-based learning platform.

Science.gov (United States)

Yang, Adeel; Goel, Hersh; Bryan, Matthew; Robertson, Ron; Lim, Jane; Islam, Shehran; Speicher, Mark R

2014-01-01

Medical students are required to retain vast amounts of medical knowledge on the path to becoming physicians. To address this challenge, multimedia Web-based learning resources have been developed to supplement traditional text-based materials. The Picmonic(®) Learning System (PLS; Picmonic, Phoenix, AZ, USA) is a novel multimedia Web-based learning platform that delivers audiovisual mnemonics designed to improve memory retention of medical sciences. A single-center, randomized, subject-blinded, controlled study was conducted to compare the PLS with traditional text-based material for retention of medical science topics. Subjects were randomly assigned to use two different types of study materials covering several diseases. Subjects randomly assigned to the PLS group were given audiovisual mnemonics along with text-based materials, whereas subjects in the control group were given the same text-based materials with key terms highlighted. The primary endpoints were the differences in performance on immediate, 1 week, and 1 month delayed free-recall and paired-matching tests. The secondary endpoints were the difference in performance on a 1 week delayed multiple-choice test and self-reported satisfaction with the study materials. Differences were calculated using unpaired two-tailed t-tests. PLS group subjects demonstrated improvements of 65%, 161%, and 208% compared with control group subjects on free-recall tests conducted immediately, 1 week, and 1 month after study of materials, respectively. The results of performance on paired-matching tests showed an improvement of up to 331% for PLS group subjects. PLS group subjects also performed 55% greater than control group subjects on a 1 week delayed multiple choice test requiring higher-order thinking. The differences in test performance between the PLS group subjects and the control group subjects were statistically significant (P<0.001), and the PLS group subjects reported higher overall satisfaction with the

Fault detection in processes represented by PLS models using an EWMA control scheme

KAUST Repository

Harrou, Fouzi; Nounou, Mohamed N.; Nounou, Hazem N.

2016-01-01

with that of the traditional PLS-based fault detection method through a simulated example involving various fault scenarios that could be encountered in real processes. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS

Learning predictive statistics from temporal sequences: Dynamics and strategies.

Science.gov (United States)

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-10-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

Design of High Field Multipole Wiggler at PLS

International Nuclear Information System (INIS)

Kim, D. E.; Park, K. H.; Lee, H. G.; Suh, H. S.; Han, H. S.; Jung, Y. G.; Chung, C. W.

2007-01-01

Pohang Accelerator Laboratory (PAL) is developing a high field multipole wiggler for new EXAFS beamline. The beamline is planning to utilize very high photon energy (∼40keV) synchrotron radiation at Pohang Light Source (PLS). To achieve higher critical photon energy, the wiggler field need to be maximized. A magnetic structure with wedged pole and blocks with additional side blocks which are similar to asymmetric wiggler of ESRF are designed to achieve higher flux density. The end structures were designed to be asymmetric along the beam direction to ensure systematic zero 1st field integral. The thickness of the last magnets were adjusted to minimize the transition sequence to the fully developed periodic field. This approach is more convenient to control than adjusting the strength of the end magnets. The final design features 140mm period, 2.5 Tesla peak flux density at 12mm pole gap, 1205mm magnetic structure length with 16 full field poles. In this article, all the design, engineering efforts for the HFMSII wiggler will be described

Sparse kernel orthonormalized PLS for feature extraction in large datasets

DEFF Research Database (Denmark)

Arenas-García, Jerónimo; Petersen, Kaare Brandt; Hansen, Lars Kai

2006-01-01

In this paper we are presenting a novel multivariate analysis method for large scale problems. Our scheme is based on a novel kernel orthonormalized partial least squares (PLS) variant for feature extraction, imposing sparsity constrains in the solution to improve scalability. The algorithm...... is tested on a benchmark of UCI data sets, and on the analysis of integrated short-time music features for genre prediction. The upshot is that the method has strong expressive power even with rather few features, is clearly outperforming the ordinary kernel PLS, and therefore is an appealing method...

Memory and learning with rapid audiovisual sequences

Science.gov (United States)

Keller, Arielle S.; Sekuler, Robert

2015-01-01

We examined short-term memory for sequences of visual stimuli embedded in varying multisensory contexts. In two experiments, subjects judged the structure of the visual sequences while disregarding concurrent, but task-irrelevant auditory sequences. Stimuli were eight-item sequences in which varying luminances and frequencies were presented concurrently and rapidly (at 8 Hz). Subjects judged whether the final four items in a visual sequence identically replicated the first four items. Luminances and frequencies in each sequence were either perceptually correlated (Congruent) or were unrelated to one another (Incongruent). Experiment 1 showed that, despite encouragement to ignore the auditory stream, subjects' categorization of visual sequences was strongly influenced by the accompanying auditory sequences. Moreover, this influence tracked the similarity between a stimulus's separate audio and visual sequences, demonstrating that task-irrelevant auditory sequences underwent a considerable degree of processing. Using a variant of Hebb's repetition design, Experiment 2 compared musically trained subjects and subjects who had little or no musical training on the same task as used in Experiment 1. Test sequences included some that intermittently and randomly recurred, which produced better performance than sequences that were generated anew for each trial. The auditory component of a recurring audiovisual sequence influenced musically trained subjects more than it did other subjects. This result demonstrates that stimulus-selective, task-irrelevant learning of sequences can occur even when such learning is an incidental by-product of the task being performed. PMID:26575193

Memory and learning with rapid audiovisual sequences.

Science.gov (United States)

Keller, Arielle S; Sekuler, Robert

2015-01-01

We examined short-term memory for sequences of visual stimuli embedded in varying multisensory contexts. In two experiments, subjects judged the structure of the visual sequences while disregarding concurrent, but task-irrelevant auditory sequences. Stimuli were eight-item sequences in which varying luminances and frequencies were presented concurrently and rapidly (at 8 Hz). Subjects judged whether the final four items in a visual sequence identically replicated the first four items. Luminances and frequencies in each sequence were either perceptually correlated (Congruent) or were unrelated to one another (Incongruent). Experiment 1 showed that, despite encouragement to ignore the auditory stream, subjects' categorization of visual sequences was strongly influenced by the accompanying auditory sequences. Moreover, this influence tracked the similarity between a stimulus's separate audio and visual sequences, demonstrating that task-irrelevant auditory sequences underwent a considerable degree of processing. Using a variant of Hebb's repetition design, Experiment 2 compared musically trained subjects and subjects who had little or no musical training on the same task as used in Experiment 1. Test sequences included some that intermittently and randomly recurred, which produced better performance than sequences that were generated anew for each trial. The auditory component of a recurring audiovisual sequence influenced musically trained subjects more than it did other subjects. This result demonstrates that stimulus-selective, task-irrelevant learning of sequences can occur even when such learning is an incidental by-product of the task being performed.

The Picmonic® Learning System: enhancing memory retention of medical sciences, using an audiovisual mnemonic Web-based learning platform

Directory of Open Access Journals (Sweden)

Yang A

2014-05-01

Full Text Available Adeel Yang,1,* Hersh Goel,1,* Matthew Bryan,2 Ron Robertson,1 Jane Lim,1 Shehran Islam,1 Mark R Speicher2 1College of Medicine, The University of Arizona, Tucson, AZ, USA; 2Arizona College of Osteopathic Medicine, Midwestern University, Glendale, AZ, USA *These authors contributed equally to this work Background: Medical students are required to retain vast amounts of medical knowledge on the path to becoming physicians. To address this challenge, multimedia Web-based learning resources have been developed to supplement traditional text-based materials. The Picmonic® Learning System (PLS; Picmonic, Phoenix, AZ, USA is a novel multimedia Web-based learning platform that delivers audiovisual mnemonics designed to improve memory retention of medical sciences. Methods: A single-center, randomized, subject-blinded, controlled study was conducted to compare the PLS with traditional text-based material for retention of medical science topics. Subjects were randomly assigned to use two different types of study materials covering several diseases. Subjects randomly assigned to the PLS group were given audiovisual mnemonics along with text-based materials, whereas subjects in the control group were given the same text-based materials with key terms highlighted. The primary endpoints were the differences in performance on immediate, 1 week, and 1 month delayed free-recall and paired-matching tests. The secondary endpoints were the difference in performance on a 1 week delayed multiple-choice test and self-reported satisfaction with the study materials. Differences were calculated using unpaired two-tailed t-tests. Results: PLS group subjects demonstrated improvements of 65%, 161%, and 208% compared with control group subjects on free-recall tests conducted immediately, 1 week, and 1 month after study of materials, respectively. The results of performance on paired-matching tests showed an improvement of up to 331% for PLS group subjects. PLS group

The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression

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Chunxiao Zhang

2012-01-01

Full Text Available The prediction of the aero-engine performance parameters is very important for aero-engine condition monitoring and fault diagnosis. In this paper, the chaotic phase space of engine exhaust temperature (EGT time series which come from actual air-borne ACARS data is reconstructed through selecting some suitable nearby points. The partial least square (PLS based on the cubic spline function or the kernel function transformation is adopted to obtain chaotic predictive function of EGT series. The experiment results indicate that the proposed PLS chaotic prediction algorithm based on biweight kernel function transformation has significant advantage in overcoming multicollinearity of the independent variables and solve the stability of regression model. Our predictive NMSE is 16.5 percent less than that of the traditional linear least squares (OLS method and 10.38 percent less than that of the linear PLS approach. At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.

Draft genome sequence of Xylella fastidiosa pear leaf scorch strain in Taiwan

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The draft genome sequence of Xylella fastidiosa pear leaf scorch strain (PLS229) isolated from pear cultivar Hengshan (Pyrus pyrifolia) in Taiwan is reported. The bacterium has a genome size of 2,733,013 bp with a G+C content of 53.1%. The PLS229 strain genome was annotated to have 3,259 open readin...

A heuristic approach using multiple criteria for environmentally benign 3PLs selection

Science.gov (United States)

Kongar, Elif

2005-11-01

Maintaining competitiveness in an environment where price and quality differences between competing products are disappearing depends on the company's ability to reduce costs and supply time. Timely responses to rapidly changing market conditions require an efficient Supply Chain Management (SCM). Outsourcing logistics to third-party logistics service providers (3PLs) is one commonly used way of increasing the efficiency of logistics operations, while creating a more "core competency focused" business environment. However, this alone may not be sufficient. Due to recent environmental regulations and growing public awareness regarding environmental issues, 3PLs need to be not only efficient but also environmentally benign to maintain companies' competitiveness. Even though an efficient and environmentally benign combination of 3PLs can theoretically be obtained using exhaustive search algorithms, heuristics approaches to the selection process may be superior in terms of the computational complexity. In this paper, a hybrid approach that combines a multiple criteria Genetic Algorithm (GA) with Linear Physical Weighting Algorithm (LPPW) to be used in efficient and environmentally benign 3PLs is proposed. A numerical example is also provided to illustrate the method and the analyses.

Learning sequences on the subject of energy

International Nuclear Information System (INIS)

1986-01-01

The ten learning sequences follow on one another. Each picks on a particular aspect from the energy field. The subject notebooks are self-contained and can therefore be used independently. Apart from actual data and energy-related information, the information for the teacher contains: - proposals for teaching - suggestions for further activities - sample solutions for the pupil's sheets - references to the literature and media. The worksheets for the pupils are different; it should be possible to use the learning sequences in all classes of secondary school stage 1. The multicoloured foils for projectors should motivate, on the one hand, and on the other hand should help to check the results of learning. (orig./HP) [de

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

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Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the

Beam property studies in the PLS diagnostic beamline

CERN Document Server

Ko, I S; Seon, D K; Kim, C B; Lee, T Y

1999-01-01

A diagnostic beamline has been operated in the Pohang Light Source (PLS) storage ring for the diagnostics of electron and photon beam properties. It consists of two 1:1 imaging systems: a visible-light imaging system and a soft X-ray imaging system. We have measured the transverse and the longitudinal structures of beams by using a streak camera to obtain a visible image. Accurate transverse beam size have been measured to be 186 mu m horizontally and 43.1 mu m vertically by using soft X-ray images with minimum diffraction errors. The corresponding emittances are 11.7 nm-rad horizontally and 0.59 nm-rad vertically. By comparing the measured data with the design values, we confirmed that the PLS storage ring has reached its designed performance within an error of 3.3 % in the transverse direction.

An extension of PPLS-DA for classification and comparison to ordinary PLS-DA.

Directory of Open Access Journals (Sweden)

Anna Telaar

Full Text Available Classification studies are widely applied, e.g. in biomedical research to classify objects/patients into predefined groups. The goal is to find a classification function/rule which assigns each object/patient to a unique group with the greatest possible accuracy (classification error. Especially in gene expression experiments often a lot of variables (genes are measured for only few objects/patients. A suitable approach is the well-known method PLS-DA, which searches for a transformation to a lower dimensional space. Resulting new components are linear combinations of the original variables. An advancement of PLS-DA leads to PPLS-DA, introducing a so called 'power parameter', which is maximized towards the correlation between the components and the group-membership. We introduce an extension of PPLS-DA for optimizing this power parameter towards the final aim, namely towards a minimal classification error. We compare this new extension with the original PPLS-DA and also with the ordinary PLS-DA using simulated and experimental datasets. For the investigated data sets with weak linear dependency between features/variables, no improvement is shown for PPLS-DA and for the extensions compared to PLS-DA. A very weak linear dependency, a low proportion of differentially expressed genes for simulated data, does not lead to an improvement of PPLS-DA over PLS-DA, but our extension shows a lower prediction error. On the contrary, for the data set with strong between-feature collinearity and a low proportion of differentially expressed genes and a large total number of genes, the prediction error of PPLS-DA and the extensions is clearly lower than for PLS-DA. Moreover we compare these prediction results with results of support vector machines with linear kernel and linear discriminant analysis.

Combining pharmacophore fingerprints and PLS-discriminant analysis for virtual screening and SAR elucidation

DEFF Research Database (Denmark)

Askjær, Sune; Langgård, Morten

2008-01-01

The criterion of success for the initial stages of a ligand-based drug-discovery project is dual. First, a set of suitable lead compounds has to be identified. Second, a level of a preliminary structure-activity relationship (SAR) of the identified ligands has to be established in order to guide ...... by the protein-binding site known from X-ray complexes. The result of this analysis assists in explaining the efficiency of 2D pharmacophore fingerprints as descriptors in virtual screening....... the lead optimization toward a final drug candidate. This paper presents a combined approach to solving these two problems of ligand-based virtual screening and elucidation of SAR based on interplay between pharmacophore fingerprints and interpretation of PLS-discriminant analysis (PLS-DA) models....... The virtual screening capability of the PLS-DA method is compared to group fusion maximum similarity searching in a test using four graph-based pharmacophore fingerprints over a range of 10 diverse targets. The PLS-DA method was generally found to do better than the Smax method. The GpiDAPH3 and PCH...

Specific Deficit in Implicit Motor Sequence Learning following Spinal Cord Injury.

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Ayala Bloch

Full Text Available Physical and psychosocial rehabilitation following spinal cord injury (SCI leans heavily on learning and practicing new skills. However, despite research relating motor sequence learning to spinal cord activity and clinical observations of impeded skill-learning after SCI, implicit procedural learning following spinal cord damage has not been examined.To test the hypothesis that spinal cord injury (SCI in the absence of concomitant brain injury is associated with a specific implicit motor sequence learning deficit that cannot be explained by depression or impairments in other cognitive measures.Ten participants with SCI in T1-T11, unharmed upper limb motor and sensory functioning, and no concomitant brain injury were compared to ten matched control participants on measures derived from the serial reaction time (SRT task, which was used to assess implicit motor sequence learning. Explicit generation of the SRT sequence, depression, and additional measures of learning, memory, and intelligence were included to explore the source and specificity of potential learning deficits.There was no between-group difference in baseline reaction time, indicating that potential differences between the learning curves of the two groups could not be attributed to an overall reduction in response speed in the SCI group. Unlike controls, the SCI group showed no decline in reaction time over the first six blocks of the SRT task and no advantage for the initially presented sequence over the novel interference sequence. Meanwhile, no group differences were found in explicit learning, depression, or any additional cognitive measures.The dissociation between impaired implicit learning and intact declarative memory represents novel empirical evidence of a specific implicit procedural learning deficit following SCI, with broad implications for rehabilitation and adjustment.

Formulaic Sequences and the Implications for Second Language Learning

Science.gov (United States)

Xu, Qi

2016-01-01

The present paper is a review of literature in relation to formulaic sequences and the implications for second language learning. The formulaic sequence is a significant part of our language, and plays an essential role in both first and second language learning. The paper first introduces the definition, classifications, and major features of…

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

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Philip J Tully

2016-05-01

Full Text Available Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx. We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

Procedural learning in Tourette syndrome, ADHD, and comorbid Tourette-ADHD: Evidence from a probabilistic sequence learning task.

Science.gov (United States)

Takács, Ádám; Shilon, Yuval; Janacsek, Karolina; Kóbor, Andrea; Tremblay, Antoine; Németh, Dezső; Ullman, Michael T

2017-10-01

Procedural memory, which is rooted in the basal ganglia, plays an important role in the implicit learning of motor and cognitive skills. Few studies have examined procedural learning in either Tourette syndrome (TS) or Attention Deficit Hyperactivity Disorder (ADHD), despite basal ganglia abnormalities in both of these neurodevelopmental disorders. We aimed to assess procedural learning in children with TS (n=13), ADHD (n=22), and comorbid TS-ADHD (n=20), as well as in typically developing children (n=21). Procedural learning was measured with a well-studied implicit probabilistic sequence learning task, the alternating serial reaction time task. All four groups showed evidence of sequence learning, and moreover did not differ from each other in sequence learning. This result, from the first study to examine procedural memory across TS, ADHD and comorbid TS-ADHD, is consistent with previous findings of intact procedural learning of sequences in both TS and ADHD. In contrast, some studies have found impaired procedural learning of non-sequential probabilistic categories in TS. This suggests that sequence learning may be spared in TS and ADHD, while at least some other forms of learning in procedural memory are impaired, at least in TS. Our findings indicate that disorders associated with basal ganglia abnormalities do not necessarily show procedural learning deficits, and provide a possible path for more effective diagnostic tools, and educational and training programs. Copyright © 2017 Elsevier Inc. All rights reserved.

Learning multiple variable-speed sequences in striatum via cortical tutoring.

Science.gov (United States)

Murray, James M; Escola, G Sean

2017-05-08

Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.

On-line monitoring of extraction process of Flos Lonicerae Japonicae using near infrared spectroscopy combined with synergy interval PLS and genetic algorithm

Science.gov (United States)

Yang, Yue; Wang, Lei; Wu, Yongjiang; Liu, Xuesong; Bi, Yuan; Xiao, Wei; Chen, Yong

2017-07-01

There is a growing need for the effective on-line process monitoring during the manufacture of traditional Chinese medicine to ensure quality consistency. In this study, the potential of near infrared (NIR) spectroscopy technique to monitor the extraction process of Flos Lonicerae Japonicae was investigated. A new algorithm of synergy interval PLS with genetic algorithm (Si-GA-PLS) was proposed for modeling. Four different PLS models, namely Full-PLS, Si-PLS, GA-PLS, and Si-GA-PLS, were established, and their performances in predicting two quality parameters (viz. total acid and soluble solid contents) were compared. In conclusion, Si-GA-PLS model got the best results due to the combination of superiority of Si-PLS and GA. For Si-GA-PLS, the determination coefficient (Rp2) and root-mean-square error for the prediction set (RMSEP) were 0.9561 and 147.6544 μg/ml for total acid, 0.9062 and 0.1078% for soluble solid contents, correspondingly. The overall results demonstrated that the NIR spectroscopy technique combined with Si-GA-PLS calibration is a reliable and non-destructive alternative method for on-line monitoring of the extraction process of TCM on the production scale.

Klystron-modulator system availability of PLS 2 GeV electron linac

International Nuclear Information System (INIS)

Cho, M.H.; Park, S.S.; Oh, J.S.; Namkung, W.

1996-01-01

PLS Linac has been injecting 2 GeV electron beams to the Pohang Light Source (PLS) storage ring since September 1994. PLS 2 GeV linac employs 11 sets of high power klystron-modulator (K and M) system for the main RF source for the beam acceleration. The klystron has rated output peak power of 80 MW at 4 microsec pulse width and at 60 pps. The matching modulator has 200 MW peak output power. The total accumulated high voltage run time of the oldest unit has reached beyond 23,000 hour and the sum of all the high voltage run time is approximately 230,000 hour as of May 1996. In this paper, we review overall system performance of the high-power K and M system. A special attention is paid on the analysis of all failures and troubles of the K and M system which affected the linac high power RF operations as well as beam injection operations for the period of 1994 to May 1996. (author)

Sequence-specific procedural learning deficits in children with specific language impairment.

Science.gov (United States)

Hsu, Hsinjen Julie; Bishop, Dorothy V M

2014-05-01

This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children's performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7- to 11-year-old children with SLI (n = 48), typically developing age-matched children (n = 20) and younger typically developing children matched for receptive grammar (n = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar-matched children, but poorer than age-matched controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e. pursuit rotor), the children with SLI performed comparably with age-matched children and better than younger grammar-matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (the Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence-specific information, rather than generally weak procedural learning. © 2014 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

Enhanced learning of natural visual sequences in newborn chicks.

Science.gov (United States)

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.

COGNITIVE FATIGUE FACILITATES PROCEDURAL SEQUENCE LEARNING

Directory of Open Access Journals (Sweden)

Guillermo eBorragán

2016-03-01

Full Text Available Enhanced procedural learning has been evidenced in conditions where cognitive control is diminished, including hypnosis, disruption of prefrontal activity and non-optimal time of the day. Another condition depleting the availability of controlled resources is cognitive fatigue. We tested the hypothesis that cognitive fatigue, eventually leading to diminished cognitive control, facilitates procedural sequence learning. In a two-day experiment, twenty-three young healthy adults were administered a serial reaction time task (SRTT following the induction of high or low levels of cognitive fatigue, in a counterbalanced order. Cognitive fatigue was induced using the Time load Dual-back (TloadDback paradigm, a dual working memory task that allows tailoring cognitive load levels to the individual's optimal performance capacity. In line with our hypothesis, reaction times in the SRTT were faster in the high- than in the low-level fatigue condition, and performance improvement showed more of a benefit from the sequential components than from motor. Altogether, our results suggest a paradoxical, facilitating impact of cognitive fatigue on procedural motor sequence learning. We propose that facilitated learning in the high-level fatigue condition stems from a reduction in the cognitive resources devoted to cognitive control processes that normally oppose automatic procedural acquisition mechanisms.

Evaluating and Redesigning Teaching Learning Sequences at the Introductory Physics Level

Science.gov (United States)

Guisasola, Jenaro; Zuza, Kristina; Ametller, Jaume; Gutierrez-Berraondo, José

2017-01-01

In this paper we put forward a proposal for the design and evaluation of teaching and learning sequences in upper secondary school and university. We will connect our proposal with relevant contributions on the design of teaching sequences, ground it on the design-based research methodology, and discuss how teaching and learning sequences designed…

Synchronized tapping facilitates learning sound sequences as indexed by the P300.

Science.gov (United States)

Kamiyama, Keiko S; Okanoya, Kazuo

2014-01-01

The purpose of the present study was to determine whether and how single finger tapping in synchrony with sound sequences contributed to the auditory processing of them. The participants learned two unfamiliar sound sequences via different methods. In the tapping condition, they learned an auditory sequence while they tapped in synchrony with each sound onset. In the no tapping condition, they learned another sequence while they kept pressing a key until the sequence ended. After these learning sessions, we presented the two melodies again and recorded event-related potentials (ERPs). During the ERP recordings, 10% of the tones within each melody deviated from the original tones. An analysis of the grand average ERPs showed that deviant stimuli elicited a significant P300 in the tapping but not in the no-tapping condition. In addition, the significance of the P300 effect in the tapping condition increased as the participants showed highly synchronized tapping behavior during the learning sessions. These results indicated that single finger tapping promoted the conscious detection and evaluation of deviants within the learned sequences. The effect was related to individuals' musical ability to coordinate their finger movements along with external auditory events.

Learning of Grammar-Like Visual Sequences by Adults with and without Language-Learning Disabilities

Science.gov (United States)

Aguilar, Jessica M.; Plante, Elena

2014-01-01

Purpose: Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. Method: In Study 1,…

Visual Perceptual Echo Reflects Learning of Regularities in Rapid Luminance Sequences.

Science.gov (United States)

Chang, Acer Y-C; Schwartzman, David J; VanRullen, Rufin; Kanai, Ryota; Seth, Anil K

2017-08-30

A novel neural signature of active visual processing has recently been described in the form of the "perceptual echo", in which the cross-correlation between a sequence of randomly fluctuating luminance values and occipital electrophysiological signals exhibits a long-lasting periodic (∼100 ms cycle) reverberation of the input stimulus (VanRullen and Macdonald, 2012). As yet, however, the mechanisms underlying the perceptual echo and its function remain unknown. Reasoning that natural visual signals often contain temporally predictable, though nonperiodic features, we hypothesized that the perceptual echo may reflect a periodic process associated with regularity learning. To test this hypothesis, we presented subjects with successive repetitions of a rapid nonperiodic luminance sequence, and examined the effects on the perceptual echo, finding that echo amplitude linearly increased with the number of presentations of a given luminance sequence. These data suggest that the perceptual echo reflects a neural signature of regularity learning.Furthermore, when a set of repeated sequences was followed by a sequence with inverted luminance polarities, the echo amplitude decreased to the same level evoked by a novel stimulus sequence. Crucially, when the original stimulus sequence was re-presented, the echo amplitude returned to a level consistent with the number of presentations of this sequence, indicating that the visual system retained sequence-specific information, for many seconds, even in the presence of intervening visual input. Altogether, our results reveal a previously undiscovered regularity learning mechanism within the human visual system, reflected by the perceptual echo. SIGNIFICANCE STATEMENT How the brain encodes and learns fast-changing but nonperiodic visual input remains unknown, even though such visual input characterizes natural scenes. We investigated whether the phenomenon of "perceptual echo" might index such learning. The perceptual echo is a

Consolidating the effects of waking and sleep on motor-sequence learning.

Science.gov (United States)

Brawn, Timothy P; Fenn, Kimberly M; Nusbaum, Howard C; Margoliash, Daniel

2010-10-20

Sleep is widely believed to play a critical role in memory consolidation. Sleep-dependent consolidation has been studied extensively in humans using an explicit motor-sequence learning paradigm. In this task, performance has been reported to remain stable across wakefulness and improve significantly after sleep, making motor-sequence learning the definitive example of sleep-dependent enhancement. Recent work, however, has shown that enhancement disappears when the task is modified to reduce task-related inhibition that develops over a training session, thus questioning whether sleep actively consolidates motor learning. Here we use the same motor-sequence task to demonstrate sleep-dependent consolidation for motor-sequence learning and explain the discrepancies in results across studies. We show that when training begins in the morning, motor-sequence performance deteriorates across wakefulness and recovers after sleep, whereas performance remains stable across both sleep and subsequent waking with evening training. This pattern of results challenges an influential model of memory consolidation defined by a time-dependent stabilization phase and a sleep-dependent enhancement phase. Moreover, the present results support a new account of the behavioral effects of waking and sleep on explicit motor-sequence learning that is consistent across a wide range of tasks. These observations indicate that current theories of memory consolidation that have been formulated to explain sleep-dependent performance enhancements are insufficient to explain the range of behavioral changes associated with sleep.

Sleep and memory consolidation: motor performance and proactive interference effects in sequence learning.

Science.gov (United States)

Borragán, Guillermo; Urbain, Charline; Schmitz, Rémy; Mary, Alison; Peigneux, Philippe

2015-04-01

That post-training sleep supports the consolidation of sequential motor skills remains debated. Performance improvement and sensitivity to proactive interference are both putative measures of long-term memory consolidation. We tested sleep-dependent memory consolidation for visuo-motor sequence learning using a proactive interference paradigm. Thirty-three young adults were trained on sequence A on Day 1, then had Regular Sleep (RS) or were Sleep Deprived (SD) on the night after learning. After two recovery nights, they were tested on the same sequence A, then had to learn a novel, potentially competing sequence B. We hypothesized that proactive interference effects on sequence B due to the prior learning of sequence A would be higher in the RS condition, considering that proactive interference is an indirect marker of the robustness of sequence A, which should be better consolidated over post-training sleep. Results highlighted sleep-dependent improvement for sequence A, with faster RTs overnight for RS participants only. Moreover, the beneficial impact of sleep was specific to the consolidation of motor but not sequential skills. Proactive interference effects on learning a new material at Day 4 were similar between RS and SD participants. These results suggest that post-training sleep contributes to optimizing motor but not sequential components of performance in visuo-motor sequence learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Learning of grammar-like visual sequences by adults with and without language-learning disabilities.

Science.gov (United States)

Aguilar, Jessica M; Plante, Elena

2014-08-01

Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. In Study 1, adults with normal language (NL) or language-learning disability (LLD) were familiarized with the visual artificial grammar and then tested using items that conformed or deviated from the grammar. In Study 2, a 2nd sample of adults with NL and LLD were presented auditory word pairs with weak semantic associations (e.g., groom + clean) along with the visual learning task. Participants were instructed to attend to visual sequences and to ignore the auditory stimuli. Incidental encoding of these words would indicate reduced attention to the primary task. In Studies 1 and 2, both groups demonstrated learning and generalization of the artificial grammar. In Study 2, neither the NL nor the LLD group appeared to encode the words presented during the learning phase. The results argue against a general deficit in statistical learning for individuals with LLD and demonstrate that both NL and LLD learners can ignore extraneous auditory stimuli during visual learning.

Evaluating and redesigning teaching learning sequences at the introductory physics level

Science.gov (United States)

Guisasola, Jenaro; Zuza, Kristina; Ametller, Jaume; Gutierrez-Berraondo, José

2017-12-01

In this paper we put forward a proposal for the design and evaluation of teaching and learning sequences in upper secondary school and university. We will connect our proposal with relevant contributions on the design of teaching sequences, ground it on the design-based research methodology, and discuss how teaching and learning sequences designed according to our proposal relate to learning progressions. An iterative methodology for evaluating and redesigning the teaching and learning sequence (TLS) is presented. The proposed assessment strategy focuses on three aspects: (a) evaluation of the activities of the TLS, (b) evaluation of learning achieved by students in relation to the intended objectives, and (c) a document for gathering the difficulties found when implementing the TLS to serve as a guide to teachers. Discussion of this guide with external teachers provides feedback used for the TLS redesign. The context of our implementation and evaluation is an innovative calculus-based physics course for first-year engineering and science degree students at the University of the Basque Country.

Swarm-based Sequencing Recommendations in E-learning

NARCIS (Netherlands)

Van den Berg, Bert; Tattersall, Colin; Janssen, José; Brouns, Francis; Kurvers, Hub; Koper, Rob

2005-01-01

Van den Berg, B., Tattersall, C., Janssen, J., Brouns, F., Kurvers, H., & Koper, R. (2006). Swarm-based Sequencing Recommendations in E-learning. International Journal of Computer Science & Applications, III(III), 1-11.

Global classification of human facial healthy skin using PLS discriminant analysis and clustering analysis.

Science.gov (United States)

Guinot, C; Latreille, J; Tenenhaus, M; Malvy, D J

2001-04-01

Today's classifications of healthy skin are predominantly based on a very limited number of skin characteristics, such as skin oiliness or susceptibility to sun exposure. The aim of the present analysis was to set up a global classification of healthy facial skin, using mathematical models. This classification is based on clinical, biophysical skin characteristics and self-reported information related to the skin, as well as the results of a theoretical skin classification assessed separately for the frontal and the malar zones of the face. In order to maximize the predictive power of the models with a minimum of variables, the Partial Least Square (PLS) discriminant analysis method was used. The resulting PLS components were subjected to clustering analyses to identify the plausible number of clusters and to group the individuals according to their proximities. Using this approach, four PLS components could be constructed and six clusters were found relevant. So, from the 36 hypothetical combinations of the theoretical skin types classification, we tended to a strengthened six classes proposal. Our data suggest that the association of the PLS discriminant analysis and the clustering methods leads to a valid and simple way to classify healthy human skin and represents a potentially useful tool for cosmetic and dermatological research.

On-line monitoring the extract process of Fu-fang Shuanghua oral solution using near infrared spectroscopy and different PLS algorithms

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Kang, Qian; Ru, Qingguo; Liu, Yan; Xu, Lingyan; Liu, Jia; Wang, Yifei; Zhang, Yewen; Li, Hui; Zhang, Qing; Wu, Qing

2016-01-01

An on-line near infrared (NIR) spectroscopy monitoring method with an appropriate multivariate calibration method was developed for the extraction process of Fu-fang Shuanghua oral solution (FSOS). On-line NIR spectra were collected through two fiber optic probes, which were designed to transmit NIR radiation by a 2 mm flange. Partial least squares (PLS), interval PLS (iPLS) and synergy interval PLS (siPLS) algorithms were used comparatively for building the calibration regression models. During the extraction process, the feasibility of NIR spectroscopy was employed to determine the concentrations of chlorogenic acid (CA) content, total phenolic acids contents (TPC), total flavonoids contents (TFC) and soluble solid contents (SSC). High performance liquid chromatography (HPLC), ultraviolet spectrophotometric method (UV) and loss on drying methods were employed as reference methods. Experiment results showed that the performance of siPLS model is the best compared with PLS and iPLS. The calibration models for AC, TPC, TFC and SSC had high values of determination coefficients of (R2) (0.9948, 0.9992, 0.9950 and 0.9832) and low root mean square error of cross validation (RMSECV) (0.0113, 0.0341, 0.1787 and 1.2158), which indicate a good correlation between reference values and NIR predicted values. The overall results show that the on line detection method could be feasible in real application and would be of great value for monitoring the mixed decoction process of FSOS and other Chinese patent medicines.

Implicit motor sequence learning and working memory performance changes across the adult life span

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Sarah Nadine Meissner

2016-04-01

Full Text Available Although implicit motor sequence learning is rather well understood in young adults, effects of aging on this kind of learning are controversial. There is first evidence that working memory (WM might play a role in implicit motor sequence learning in young adults as well as in adults above the age of 65. However the knowledge about the development of these processes across the adult life span is rather limited. As the average age of our population continues to rise, a better understanding of age-related changes in motor sequence learning and potentially mediating cognitive processes takes on increasing significance. Therefore, we investigated aging effects on implicit motor sequence learning and WM. Sixty adults (18-71 years completed verbal and visuospatial n-back tasks and were trained on a serial reaction time task. Randomly varying trials served as control condition. To further assess consolidation indicated by off-line improvement and reduced susceptibility to interference, reaction times (RTs were determined 1 h after initial learning. Young and older but not middle-aged adults showed motor sequence learning. Nine out of 20 older adults (compared to one young/one middle-aged exhibited some evidence of sequence awareness. After 1 h, young and middle-aged adults showed off-line improvement. However, RT facilitation was not specific to sequence trials. Importantly, susceptibility to interference was reduced in young and older adults indicating the occurrence of consolidation. Although WM performance declined in older participants when load was high, it was not significantly related to sequence learning. The data reveal a decline in motor sequence learning in middle-aged but not in older adults. The use of explicit learning strategies in older adults might account for the latter result.

Association of Amine-Receptor DNA Sequence Variants with Associative Learning in the Honeybee.

Science.gov (United States)

Lagisz, Malgorzata; Mercer, Alison R; de Mouzon, Charlotte; Santos, Luana L S; Nakagawa, Shinichi

2016-03-01

Octopamine- and dopamine-based neuromodulatory systems play a critical role in learning and learning-related behaviour in insects. To further our understanding of these systems and resulting phenotypes, we quantified DNA sequence variations at six loci coding octopamine-and dopamine-receptors and their association with aversive and appetitive learning traits in a population of honeybees. We identified 79 polymorphic sequence markers (mostly SNPs and a few insertions/deletions) located within or close to six candidate genes. Intriguingly, we found that levels of sequence variation in the protein-coding regions studied were low, indicating that sequence variation in the coding regions of receptor genes critical to learning and memory is strongly selected against. Non-coding and upstream regions of the same genes, however, were less conserved and sequence variations in these regions were weakly associated with between-individual differences in learning-related traits. While these associations do not directly imply a specific molecular mechanism, they suggest that the cross-talk between dopamine and octopamine signalling pathways may influence olfactory learning and memory in the honeybee.

Who Learns More? Cultural Differences in Implicit Sequence Learning

Science.gov (United States)

Fu, Qiufang; Dienes, Zoltan; Shang, Junchen; Fu, Xiaolan

2013-01-01

Background It is well documented that East Asians differ from Westerners in conscious perception and attention. However, few studies have explored cultural differences in unconscious processes such as implicit learning. Methodology/Principal Findings The global-local Navon letters were adopted in the serial reaction time (SRT) task, during which Chinese and British participants were instructed to respond to global or local letters, to investigate whether culture influences what people acquire in implicit sequence learning. Our results showed that from the beginning British expressed a greater local bias in perception than Chinese, confirming a cultural difference in perception. Further, over extended exposure, the Chinese learned the target regularity better than the British when the targets were global, indicating a global advantage for Chinese in implicit learning. Moreover, Chinese participants acquired greater unconscious knowledge of an irrelevant regularity than British participants, indicating that the Chinese were more sensitive to contextual regularities than the British. Conclusions/Significance The results suggest that cultural biases can profoundly influence both what people consciously perceive and unconsciously learn. PMID:23940773

Interference effects in learning similar sequences of discrete movements

NARCIS (Netherlands)

Koedijker, J.M.; Oudejans, R.R.D.; Beek, P.J.

2010-01-01

Three experiments were conducted to examine proactive and retroactive interference effects in learning two similar sequences of discrete movements. In each experiment, the participants in the experimental group practiced two movement sequences on consecutive days (1 on each day, order

Perceived ambiguity as a barrier to intentions to learn genome sequencing results.

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Taber, Jennifer M; Klein, William M P; Ferrer, Rebecca A; Han, Paul K J; Lewis, Katie L; Biesecker, Leslie G; Biesecker, Barbara B

2015-10-01

Many variants that could be returned from genome sequencing may be perceived as ambiguous-lacking reliability, credibility, or adequacy. Little is known about how perceived ambiguity influences thoughts about sequencing results. Participants (n = 494) in an NIH genome sequencing study completed a baseline survey before sequencing results were available. We examined how perceived ambiguity regarding sequencing results and individual differences in medical ambiguity aversion and tolerance for uncertainty were associated with cognitions and intentions concerning sequencing results. Perceiving sequencing results as more ambiguous was associated with less favorable cognitions about results and lower intentions to learn and share results. Among participants low in tolerance for uncertainty or optimism, greater perceived ambiguity was associated with lower intentions to learn results for non-medically actionable diseases; medical ambiguity aversion did not moderate any associations. Results are consistent with the phenomenon of "ambiguity aversion" and may influence whether people learn and communicate genomic information.

Infants learn better from left to right: a directional bias in infants' sequence learning.

Science.gov (United States)

Bulf, Hermann; de Hevia, Maria Dolores; Gariboldi, Valeria; Macchi Cassia, Viola

2017-05-26

A wealth of studies show that human adults map ordered information onto a directional spatial continuum. We asked whether mapping ordinal information into a directional space constitutes an early predisposition, already functional prior to the acquisition of symbolic knowledge and language. While it is known that preverbal infants represent numerical order along a left-to-right spatial continuum, no studies have investigated yet whether infants, like adults, organize any kind of ordinal information onto a directional space. We investigated whether 7-month-olds' ability to learn high-order rule-like patterns from visual sequences of geometric shapes was affected by the spatial orientation of the sequences (left-to-right vs. right-to-left). Results showed that infants readily learn rule-like patterns when visual sequences were presented from left to right, but not when presented from right to left. This result provides evidence that spatial orientation critically determines preverbal infants' ability to perceive and learn ordered information in visual sequences, opening to the idea that a left-to-right spatially organized mental representation of ordered dimensions might be rooted in biologically-determined constraints on human brain development.

Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation

Science.gov (United States)

Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.

2016-01-01

Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation. PMID:26869075

Different frontal involvement in ALS and PLS revealed by Stroop event-related potentials and reaction times

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Ninfa eAmato

2013-12-01

Full Text Available BACKGROUND: A growing body of evidence suggests a link between cognitive and pathological changes in amyotrophic lateral sclerosis (ALS and in frontotemporal lobar dementia (FTLD. Cognitive deficits have been investigated much less extensively in primary lateral sclerosis (PLS than in ALS. OBJECTIVE: to investigate bioelectrical activity to Stroop test, assessing frontal function, in ALS, PLS and control groups. METHODS: 32 non-demented ALS patients, 10 non-demented PLS patients and 27 healthy subjects were included. Twenty-nine electroencephalography (EEG channels with binaural reference were recorded during covert Stroop task performance, involving mental discrimination of the stimuli and not vocal or motor response. Group effects on event related potentials (ERPs latency were analyzed using statistical multivariate analysis. Topographic analysis was performed using low resolution brain electromagnetic tomography (LORETA. RESULTS: ALS patients committed more errors in the execution of the task but they were not slower, whereas PLS patients did not show reduced accuracy, despite a slowing of reaction times (RTs. The main ERP components were delayed in ALS, but not in PLS, compared with controls. Moreover, RTs speed but not ERP latency correlated with clinical scores. ALS had decreased frontotemporal activity in the P2, P3 and N4 time windows compared to controls. CONCLUSION: These findings suggest a different pattern of psychophysiological involvement in ALS compared with PLS. The former is increasingly recognized to be a multisystems disorder, with a spectrum of executive and behavioural impairments reflecting frontotemporal dysfunction. The latter seems to mainly involve the motor system, with largely spared cognitive functions. Moreover, our results suggest that the covert version of the Stroop task used in the present study, may be useful to assess cognitive state in the very advanced stage of the disease, when other cognitive tasks are not

Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

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Qingyu Chen

Full Text Available First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases.We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.

Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

Science.gov (United States)

Chen, Qingyu; Zobel, Justin; Zhang, Xiuzhen; Verspoor, Karin

2016-01-01

First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases. We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.

A thioesterase bypasses the requirement for exogenous fatty acids in the plsX deletion of Streptococcus pneumoniae

NARCIS (Netherlands)

Parsons, J.B.; Frank, M.W.; Eleveld, M.J.; Schalkwijk, J.; Broussard, T.C.; Jonge, M.I. de; Rock, C.O.

2015-01-01

PlsX is an acyl-acyl carrier protein (ACP):phosphate transacylase that interconverts the two acyl donors in Gram-positive bacterial phospholipid synthesis. The deletion of plsX in Staphylococcus aureus results in a requirement for both exogenous fatty acids and de novo type II fatty acid

Neural correlates of skill acquisition: decreased cortical activity during a serial interception sequence learning task.

Science.gov (United States)

Gobel, Eric W; Parrish, Todd B; Reber, Paul J

2011-10-15

Learning of complex motor skills requires learning of component movements as well as the sequential structure of their order and timing. Using a Serial Interception Sequence Learning (SISL) task, participants learned a sequence of precisely timed interception responses through training with a repeating sequence. Following initial implicit learning of the repeating sequence, functional MRI data were collected during performance of that known sequence and compared with activity evoked during novel sequences of actions, novel timing patterns, or both. Reduced activity was observed during the practiced sequence in a distributed bilateral network including extrastriate occipital, parietal, and premotor cortical regions. These reductions in evoked activity likely reflect improved efficiency in visuospatial processing, spatio-motor integration, motor planning, and motor execution for the trained sequence, which is likely supported by nondeclarative skill learning. In addition, the practiced sequence evoked increased activity in the left ventral striatum and medial prefrontal cortex, while the posterior cingulate was more active during periods of better performance. Many prior studies of perceptual-motor skill learning have found increased activity in motor areas of the frontal cortex (e.g., motor and premotor cortex, SMA) and striatal areas (e.g., the putamen). The change in activity observed here (i.e., decreased activity across a cortical network) may reflect skill learning that is predominantly expressed through more accurate performance rather than decreased reaction time. Copyright © 2011 Elsevier Inc. All rights reserved.

Alpha-gamma phase amplitude coupling subserves information transfer during perceptual sequence learning.

Science.gov (United States)

Tzvi, Elinor; Bauhaus, Leon J; Kessler, Till U; Liebrand, Matthias; Wöstmann, Malte; Krämer, Ulrike M

2018-03-01

Cross-frequency coupling is suggested to serve transfer of information between wide-spread neuronal assemblies and has been shown to underlie many cognitive functions including learning and memory. In previous work, we found that alpha (8-13 Hz) - gamma (30-48 Hz) phase amplitude coupling (αγPAC) is decreased during sequence learning in bilateral frontal cortex and right parietal cortex. We interpreted this to reflect decreased demands for visuo-motor mapping once the sequence has been encoded. In the present study, we put this hypothesis to the test by adding a "simple" condition to the standard serial reaction time task (SRTT) with minimal needs for visuo-motor mapping. The standard SRTT in our paradigm entailed a perceptual sequence allowing for implicit learning of a sequence of colors with randomly assigned motor responses. Sequence learning in this case was thus not associated with reduced demands for visuo-motor mapping. Analysis of oscillatory power revealed a learning-related alpha decrease pointing to a stronger recruitment of occipito-parietal areas when encoding the perceptual sequence. Replicating our previous findings but in contrast to our hypothesis, αγPAC was decreased in sequence compared to random trials over right frontal and parietal cortex. It also tended to be smaller compared to trials requiring a simple motor sequence. We additionally analyzed αγPAC in resting-state data of a separate cohort. PAC in electrodes over right parietal cortex was significantly stronger compared to sequence trials and tended to be higher compared to simple and random trials of the SRTT data. We suggest that αγPAC in right parietal cortex reflects a "default-mode" brain state, which gets perturbed to allow for encoding of visual regularities into memory. Copyright © 2018 Elsevier Inc. All rights reserved.

Predicting effects of noncoding variants with deep learning-based sequence model.

Science.gov (United States)

Zhou, Jian; Troyanskaya, Olga G

2015-10-01

Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.

Improving sequence segmentation learning by predicting trigrams

NARCIS (Netherlands)

van den Bosch, A.; Daelemans, W.; Dagan, I.; Gildea, D.

2005-01-01

Symbolic machine-learning classifiers are known to suffer from near-sightedness when performing sequence segmentation (chunking) tasks in natural language processing: without special architectural additions they are oblivious of the decisions they made earlier when making new ones. We introduce a

Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS)

Science.gov (United States)

Krepper, Gabriela; Romeo, Florencia; Fernandes, David Douglas de Sousa; Diniz, Paulo Henrique Gonçalves Dias; de Araújo, Mário César Ugulino; Di Nezio, María Susana; Pistonesi, Marcelo Fabián; Centurión, María Eugenia

2018-01-01

Determining fat content in hamburgers is very important to minimize or control the negative effects of fat on human health, effects such as cardiovascular diseases and obesity, which are caused by the high consumption of saturated fatty acids and cholesterol. This study proposed an alternative analytical method based on Near Infrared Spectroscopy (NIR) and Successive Projections Algorithm for interval selection in Partial Least Squares regression (iSPA-PLS) for fat content determination in commercial chicken hamburgers. For this, 70 hamburger samples with a fat content ranging from 14.27 to 32.12 mg kg- 1 were prepared based on the upper limit recommended by the Argentinean Food Codex, which is 20% (w w- 1). NIR spectra were then recorded and then preprocessed by applying different approaches: base line correction, SNV, MSC, and Savitzky-Golay smoothing. For comparison, full-spectrum PLS and the Interval PLS are also used. The best performance for the prediction set was obtained for the first derivative Savitzky-Golay smoothing with a second-order polynomial and window size of 19 points, achieving a coefficient of correlation of 0.94, RMSEP of 1.59 mg kg- 1, REP of 7.69% and RPD of 3.02. The proposed methodology represents an excellent alternative to the conventional Soxhlet extraction method, since waste generation is avoided, yet without the use of either chemical reagents or solvents, which follows the primary principles of Green Chemistry. The new method was successfully applied to chicken hamburger analysis, and the results agreed with those with reference values at a 95% confidence level, making it very attractive for routine analysis.

Motor sequence learning occurs despite disrupted visual and proprioceptive feedback

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Boyd Lara A

2008-07-01

Full Text Available Abstract Background Recent work has demonstrated the importance of proprioception for the development of internal representations of the forces encountered during a task. Evidence also exists for a significant role for proprioception in the execution of sequential movements. However, little work has explored the role of proprioceptive sensation during the learning of continuous movement sequences. Here, we report that the repeated segment of a continuous tracking task can be learned despite peripherally altered arm proprioception and severely restricted visual feedback regarding motor output. Methods Healthy adults practiced a continuous tracking task over 2 days. Half of the participants experienced vibration that altered proprioception of shoulder flexion/extension of the active tracking arm (experimental condition and half experienced vibration of the passive resting arm (control condition. Visual feedback was restricted for all participants. Retention testing was conducted on a separate day to assess motor learning. Results Regardless of vibration condition, participants learned the repeated segment demonstrated by significant improvements in accuracy for tracking repeated as compared to random continuous movement sequences. Conclusion These results suggest that with practice, participants were able to use residual afferent information to overcome initial interference of tracking ability related to altered proprioception and restricted visual feedback to learn a continuous motor sequence. Motor learning occurred despite an initial interference of tracking noted during acquisition practice.

Sequence learning in differentially activated dendrites

DEFF Research Database (Denmark)

Nielsen, Bjørn Gilbert

2003-01-01

. It is proposed that the neural machinery required in such a learning/retrieval mechanism could involve the NMDA receptor, in conjunction with the ability of dendrites to maintain differentially activated regions. In particular, it is suggested that such a parcellation of the dendrite allows the neuron......Differentially activated areas of a dendrite permit the existence of zones with distinct rates of synaptic modification, and such areas can be individually accessed using a reference signal which localizes synaptic plasticity and memory trace retrieval to certain subregions of the dendrite...... to participate in multiple sequences, which can be learned without suffering from the 'wash-out' of synaptic efficacy associated with superimposition of training patterns. This is a biologically plausible solution to the stability-plasticity dilemma of learning in neural networks....

Visuospatial working memory training facilitates visually-aided explicit sequence learning.

Science.gov (United States)

Chan, John S Y; Wu, Qiaofeng; Liang, Danxia; Yan, Jin H

2015-10-01

Finger sequence learning requires visuospatial working memory (WM). However, the dynamics between age, WM training, and motor skill acquisition are unclear. Therefore, we examined how visuospatial WM training improves finger movement sequential accuracy in younger (n=26, 21.1±1.37years) and older adults (n=22, 70.6±4.01years). After performing a finger sequence learning exercise and numerical and spatial WM tasks, participants in each age group were randomly assigned to either the experimental (EX) or control (CO) groups. For one hour daily over a 10-day period, the EX group practiced an adaptive n-back spatial task while those in the CO group practiced a non-adaptive version. As a result of WM practice, the EX participants increased their accuracy in the spatial n-back tasks, while accuracy remained unimproved in the numerical n-back tasks. In all groups, reaction times (RT) became shorter in most numerical and spatial n-back tasks. The learners in the EX group - but not in the CO group - showed improvements in their retention of finger sequences. The findings support our hypothesis that computerized visuospatial WM training improves finger sequence learning both in younger and in older adults. We discuss the theoretical implications and clinical relevance of this research for motor learning and functional rehabilitation. Copyright © 2015 Elsevier B.V. All rights reserved.

The effect of cognitive aging on implicit sequence learning and dual tasking

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Jochen eVandenbossche

2014-02-01

Full Text Available We investigated the influence of attentional demands on sequence-specific learning by means of the serial reaction time (SRT task (Nissen & Bullemer, 1987 in young (age 18-25 and aged (age 55-75 adults. Participants had to respond as fast as possible to a stimulus presented in one of four horizontal locations by pressing a key corresponding to the spatial position of the stimulus. During the training phase sequential blocks were accompanied by (1 no secondary task (single, (2 a secondary tone counting task (dual tone, or (3 a secondary shape counting task (dual shape. Both secondary tasks were administered to investigate whether low and high interference tasks interact with implicit learning and age. The testing phase, under baseline single condition, was implemented to assess differences in sequence-specific learning between young and aged adults. Results indicate that (1 aged subjects show less sequence learning compared to young adults, (2 young participants show similar implicit learning effects under both single and dual task conditions when we account for explicit awareness, and (3 aged adults demonstrate reduced learning when the primary task is accompanied with a secondary task, even when explicit awareness is included as a covariate in the analysis. These findings point to implicit learning deficits under dual task conditions that can be related to cognitive aging, demonstrating the need for sufficient cognitive resources while performing a sequence learning task.

Parafac and PLS Applied to Determination of Captopril in Pharmaceutical Preparation and Biological Fluids by Ultraviolet Spectrophotometry

International Nuclear Information System (INIS)

Niazi, A.; Ghasemi, N.

2007-01-01

A new ultraviolet spectrophotometric method has been developed for the direct qualitative determination of captopril in pharmaceutical preparation and biological fluids such as human plasma and urine samples. The method was accomplished based on parallel factor analysis (PARAFAC) and partial least squares (PLS). The study was carried out in the pH range from 2.0 to 12.8 and with a concentration from 0.70 to 61.50 μg ml -1 of captopril. Multivariate calibration models PLS at various pH and PARAFAC were elaborated from ultraviolet spectra deconvolution and captopril determination. The best models for this system were obtained with PARAFAC and PLS at pH = 2.04 (PLS-PH2). The applications of the method for the determination of real samples were evaluated by analysis of captopril in pharmaceutical preparations and biological (human plasma and urine) fluids with satisfactory results. The accuracy of the method, evaluated through the root mean square error of prediction (RMSEP), was 0.58 for captopril with PARAFAC and 0.67 for captopril with PLS-PH2 model. Acidity constant of captopril at 25 0 C and ionic strength of 0.1 M have also been determined spectrophotometrically. The obtained pK a values of captopril are 3.90 ± 0.05 and 10.03 ± 0.08 for pK a1 and pK a2 , respectively

AO–MW–PLS method applied to rapid quantification of teicoplanin with near-infrared spectroscopy

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Jiemei Chen

2017-01-01

Full Text Available Teicoplanin (TCP is an important lipoglycopeptide antibiotic produced by fermenting Actinoplanes teichomyceticus. The change in TCP concentration is important to measure in the fermentation process. In this study, a reagent-free and rapid quantification method for TCP in the TCP–Tris–HCl mixture samples was developed using near-infrared (NIR spectroscopy by focusing our attention on the fermentation process for TCP. The absorbance optimization (AO partial least squares (PLS was proposed and integrated with the moving window (MW PLS, which is called AO–MW–PLS method, to select appropriate wavebands. A model set that includes various wavebands that were equivalent to the optimal AO–MW–PLS waveband was proposed based on statistical considerations. The public region of all equivalent wavebands was just one of the equivalent wavebands. The obtained public regions were 1540–1868nm for TCP and 1114–1310nm for Tris. The root-mean-square error and correlation coefficient for leave-one-out cross validation were 0.046mg mL−1 and 0.9998mg mL−1 for TCP, and 0.235mg mL−1 and 0.9986mg mL−1 for Tris, respectively. All the models achieved highly accurate prediction effects, and the selected wavebands provided valuable references for designing specialized spectrometers. This study provided a valuable reference for further application of the proposed methods to TCP fermentation broth and to other spectroscopic analysis fields.

Application of sequential and orthogonalised-partial least squares (SO-PLS) regression to predict sensory properties of Cabernet Sauvignon wines from grape chemical composition.

Science.gov (United States)

Niimi, Jun; Tomic, Oliver; Næs, Tormod; Jeffery, David W; Bastian, Susan E P; Boss, Paul K

2018-08-01

The current study determined the applicability of sequential and orthogonalised-partial least squares (SO-PLS) regression to relate Cabernet Sauvignon grape chemical composition to the sensory perception of the corresponding wines. Grape samples (n = 25) were harvested at a similar maturity and vinified identically in 2013. Twelve measures using various (bio)chemical methods were made on grapes. Wines were evaluated using descriptive analysis with a trained panel (n = 10) for sensory profiling. Data was analysed globally using SO-PLS for the entire sensory profiles (SO-PLS2), as well as for single sensory attributes (SO-PLS1). SO-PLS1 models were superior in validated explained variances than SO-PLS2. SO-PLS provided a structured approach in the selection of predictor chemical data sets that best contributed to the correlation of important sensory attributes. This new approach presents great potential for application in other explorative metabolomics studies of food and beverages to address factors such as quality and regional influences. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural Monkey: An Open-source Tool for Sequence Learning

Directory of Open Access Journals (Sweden)

Helcl Jindřich

2017-04-01

Full Text Available In this paper, we announce the development of Neural Monkey – an open-source neural machine translation (NMT and general sequence-to-sequence learning system built over the TensorFlow machine learning library. The system provides a high-level API tailored for fast prototyping of complex architectures with multiple sequence encoders and decoders. Models’ overall architecture is specified in easy-to-read configuration files. The long-term goal of the Neural Monkey project is to create and maintain a growing collection of implementations of recently proposed components or methods, and therefore it is designed to be easily extensible. Trained models can be deployed either for batch data processing or as a web service. In the presented paper, we describe the design of the system and introduce the reader to running experiments using Neural Monkey.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm

Science.gov (United States)

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV = 0.0776, Rc = 0.9777, RMSEP = 0.0963, and Rp = 0.9686 for pH model; RMSECV = 1.3544% w/w, Rc = 0.8871, RMSEP = 1.4946% w/w, and Rp = 0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry.

Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

KAUST Repository

Madakyaru, Muddu

2017-02-16

Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

KAUST Repository

Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

2017-01-01

Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

Motor Speech Sequence Learning in Adults Who Stutter

Directory of Open Access Journals (Sweden)

Mahsa Aghazamani

2018-04-01

Conclusion The results of this study showed that PWS show improvement in accuracy, reaction time and sequence duration variables from day 1 to day 3. Also, PWS show more substantial number of errors compared to PNS, but this difference was not significant between the two groups. Similar results were obtained for the reaction time. Results of this study demonstrated that PWS show slower sequence duration compared to PNS. Some studies suggested that this could be because people who stutter use a control strategy to reduce the number of errors, although many studies suggested that this may indicate motor learning. According to speech motor skills hypothesis, it can be concluded that people who stutter have limitations in motor speech learning abilities. The findings of the present study could have clinical implication for the treatment of stuttering.

Statistical process control of cocrystallization processes: A comparison between OPLS and PLS.

Science.gov (United States)

Silva, Ana F T; Sarraguça, Mafalda Cruz; Ribeiro, Paulo R; Santos, Adenilson O; De Beer, Thomas; Lopes, João Almeida

2017-03-30

Orthogonal partial least squares regression (OPLS) is being increasingly adopted as an alternative to partial least squares (PLS) regression due to the better generalization that can be achieved. Particularly in multivariate batch statistical process control (BSPC), the use of OPLS for estimating nominal trajectories is advantageous. In OPLS, the nominal process trajectories are expected to be captured in a single predictive principal component while uncorrelated variations are filtered out to orthogonal principal components. In theory, OPLS will yield a better estimation of the Hotelling's T 2 statistic and corresponding control limits thus lowering the number of false positives and false negatives when assessing the process disturbances. Although OPLS advantages have been demonstrated in the context of regression, its use on BSPC was seldom reported. This study proposes an OPLS-based approach for BSPC of a cocrystallization process between hydrochlorothiazide and p-aminobenzoic acid monitored on-line with near infrared spectroscopy and compares the fault detection performance with the same approach based on PLS. A series of cocrystallization batches with imposed disturbances were used to test the ability to detect abnormal situations by OPLS and PLS-based BSPC methods. Results demonstrated that OPLS was generally superior in terms of sensibility and specificity in most situations. In some abnormal batches, it was found that the imposed disturbances were only detected with OPLS. Copyright © 2017 Elsevier B.V. All rights reserved.

Domain-specific and domain-general constraints on word and sequence learning.

Science.gov (United States)

Archibald, Lisa M D; Joanisse, Marc F

2013-02-01

The relative influences of language-related and memory-related constraints on the learning of novel words and sequences were examined by comparing individual differences in performance of children with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists. The task involved presentation of pictures of common nouns followed immediately by equivalent presentations of the spoken names. The same participants also completed a paired-associate learning task involving word-picture and nonword-picture pairs. Hebbian learning was observed for all groups. Domain-general working memory constrained immediate recall, whereas language abilities impacted recall in the auditory modality only. In addition, working memory constrained paired-associate learning generally, whereas language abilities disproportionately impacted novel word learning. Overall, all of the learning tasks were highly correlated with domain-general working memory. The learning of nonwords was additionally related to general intelligence, phonological short-term memory, language abilities, and implicit learning. The results suggest that distinct associations between language- and memory-related mechanisms support learning of familiar and unfamiliar phonological forms and sequences.

No effects of transcranial DLPFC stimulation on implicit task sequence learning and consolidation.

Science.gov (United States)

Savic, Branislav; Cazzoli, Dario; Müri, René; Meier, Beat

2017-08-29

Neurostimulation of the dorsolateral prefrontal cortex (DLPFC) can modulate performance in cognitive tasks. In a recent study, however, transcranial direct current stimulation (tDCS) of the DLPFC did not affect implicit task sequence learning and consolidation in a paradigm that involved bimanual responses. Because bimanual performance increases the coupling between homologous cortical areas of the hemispheres and left and right DLPFC were stimulated separately the null findings may have been due to the bimanual setup. The aim of the present study was to test the effect of neuro-stimulation on sequence learning in a uni-manual setup. For this purpose two experiments were conducted. In Experiment 1, the DLPFC was stimulated with tDCS. In Experiment 2 the DLPFC was stimulated with transcranial magnetic stimulation (TMS). In both experiments, consolidation was measured 24 hours later. The results showed that sequence learning was present in all conditions and sessions, but it was not influenced by stimulation. Likewise, consolidation of sequence learning was robust across sessions, but it was not influenced by stimulation. These results replicate and extend previous findings. They indicate that established tDCS and TMS protocols on the DLPFC do not influence implicit task sequence learning and consolidation.

Application of GA-PLS and GA-KPLS calculations for the prediction of the retention indices of essential oils

Directory of Open Access Journals (Sweden)

Hadi Noorizadeh

2011-01-01

Full Text Available Genetic algorithm and partial least square (GA-PLS and kernel PLS (GA-KPLS techniques were used to investigate the correlation between retention indices (RI and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV (Q² between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR studies.

PLS2 regression as a tool for selection of optimal analytical modality

DEFF Research Database (Denmark)

Madsen, Michael; Esbensen, Kim

Intelligent use of modern process analysers allows process technicians and engineers to look deep into the dynamic behaviour of production systems. This opens up for a plurality of new possibilities with respect to process optimisation. Oftentimes, several instruments representing different...... technologies and price classes are able to decipher relevant process information simultaneously. The question then is: how to choose between available technologies without compromising the quality and usability of the data. We apply PLS2 modelling to quantify the relative merits of competing, or complementing......, analytical modalities. We here present results from a feasibility study, where Fourier Transform Near InfraRed (FT-NIR), Fourier Transform Mid InfraRed (FT-MIR), and Raman laser spectroscopy were applied on the same set of samples obtained from a pilot-scale beer brewing process. Quantitative PLS1 models...

Integrating knowledge representation/engineering, the multivariant PNN, and machine learning to improve breast cancer diagnosis

Science.gov (United States)

Land, Walker H., Jr.; Embrechts, Mark J.; Anderson, Frances R.; Smith, Tom; Wong, Lut; Fahlbusch, Steve; Choma, Robert

2005-03-01

Breast cancer is second only to lung cancer as a tumor-related cause of death in women. Currently, the method of choice for the early detection of breast cancer is mammography. While sensitive to the detection of breast cancer, its positive predictive value (PPV) is low. One of the main deterrents to achieving high computer aided diagnostic (CAD) accuracy is carelessly developed databases. These "noisy" data sets have always appeared to disrupt learning agents from learning correctly. A new statistical method for cleaning data sets was developed that improves the performance of CAD systems. Initial research efforts showed the following: PLS Az value improved by 8.79% and partial Az improved by 49.71%. The K-PLS Az value at Sigma 4.1 improved by 9.18% and the partial Az by 43.47%. The K-PLS at Sigma 3.6 (best fit sigma with this data set) Az value improved by 9.24% and the partial Az by 44.29%. With larger data sets, the ROC curves potentially could look much better than they do now. The Az value for K-PLS (0.892565) is better than PLS, PNN, and most SVMs. The SVM-rbf kernel was the only agent that out performed the K-PLS with an Az value of 0.895362. However, K-PLS runs much faster and appears to be just as accurate as the SVM-rbf kernel.

The impact of cerebellar transcranial direct current stimulation (tDCS) on learning fine-motor sequences.

Science.gov (United States)

Shimizu, Renee E; Wu, Allan D; Samra, Jasmine K; Knowlton, Barbara J

2017-01-05

The cerebellum has been shown to be important for skill learning, including the learning of motor sequences. We investigated whether cerebellar transcranial direct current stimulation (tDCS) would enhance learning of fine motor sequences. Because the ability to generalize or transfer to novel task variations or circumstances is a crucial goal of real world training, we also examined the effect of tDCS on performance of novel sequences after training. In Study 1, participants received either anodal, cathodal or sham stimulation while simultaneously practising three eight-element key press sequences in a non-repeating, interleaved order. Immediately after sequence practice with concurrent tDCS, a transfer session was given in which participants practised three interleaved novel sequences. No stimulation was given during transfer. An inhibitory effect of cathodal tDCS was found during practice, such that the rate of learning was slowed in comparison to the anodal and sham groups. In Study 2, participants received anodal or sham stimulation and a 24 h delay was added between the practice and transfer sessions to reduce mental fatigue. Although this consolidation period benefitted subsequent transfer for both tDCS groups, anodal tDCS enhanced transfer performance. Together, these studies demonstrate polarity-specific effects on fine motor sequence learning and generalization.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Kinetic microplate bioassays for relative potency of antibiotics improved by partial Least Square (PLS) regression.

Science.gov (United States)

Francisco, Fabiane Lacerda; Saviano, Alessandro Morais; Almeida, Túlia de Souza Botelho; Lourenço, Felipe Rebello

2016-05-01

Microbiological assays are widely used to estimate the relative potencies of antibiotics in order to guarantee the efficacy, safety, and quality of drug products. Despite of the advantages of turbidimetric bioassays when compared to other methods, it has limitations concerning the linearity and range of the dose-response curve determination. Here, we proposed to use partial least squares (PLS) regression to solve these limitations and to improve the prediction of relative potencies of antibiotics. Kinetic-reading microplate turbidimetric bioassays for apramacyin and vancomycin were performed using Escherichia coli (ATCC 8739) and Bacillus subtilis (ATCC 6633), respectively. Microbial growths were measured as absorbance up to 180 and 300min for apramycin and vancomycin turbidimetric bioassays, respectively. Conventional dose-response curves (absorbances or area under the microbial growth curve vs. log of antibiotic concentration) showed significant regression, however there were significant deviation of linearity. Thus, they could not be used for relative potency estimations. PLS regression allowed us to construct a predictive model for estimating the relative potencies of apramycin and vancomycin without over-fitting and it improved the linear range of turbidimetric bioassay. In addition, PLS regression provided predictions of relative potencies equivalent to those obtained from agar diffusion official methods. Therefore, we conclude that PLS regression may be used to estimate the relative potencies of antibiotics with significant advantages when compared to conventional dose-response curve determination. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and performance test of a new high power RF window in S-band PLS-II LINAC

Science.gov (United States)

Hwang, Woon-Ha; Joo, Young-Do; Kim, Seung-Hwan; Choi, Jae-Young; Noh, Sung-Ju; Ryu, Ji-Wan; Cho, Young-Ki

2017-12-01

A prototype of RF window was developed in collaboration with the Pohang Accelerator Laboratory (PAL) and domestic companies. High power performance tests of the single RF window were conducted at PAL to verify the operational characteristics for its application in the Pohang Light Source-II (PLS-II) linear accelerator (Linac). The tests were performed in the in-situ facility consisting of a modulator, klystron, waveguide network, vacuum system, cooling system, and RF analyzing equipment. The test results with Stanford linear accelerator energy doubler (SLED) have shown no breakdown up to 75 MW peak power with 4.5 μs RF pulse width at a repetition rate of 10 Hz. The test results with the current operation level of PLS-II Linac confirm that the RF window well satisfies the criteria for PLS-II Linac operation.

Interaction of PLS and PIN and hormonal crosstalk in Arabidopsis root developmentHormonal crosstalk in Arabidopsis

Directory of Open Access Journals (Sweden)

Junli eLiu

2013-04-01

Full Text Available Understanding how hormones and genes interact to coordinate plant growth is a major challenge in developmental biology. The activities of auxin, ethylene and cytokinin depend on cellular context and exhibit either synergistic or antagonistic interactions. Here we use experimentation and network construction to elucidate the role of the interaction of the POLARIS peptide (PLS and the auxin efflux carrier PIN proteins in the crosstalk of three hormones (auxin, ethylene and cytokinin in Arabidopsis root development. In ethylene hypersignalling mutants such as polaris (pls, we show experimentally that expression of both PIN1 and PIN2 significantly increases. This relationship is analysed in the context of the crosstalk between auxin, ethylene and cytokinin: in pls, endogenous auxin, ethylene and cytokinin concentration decreases, approximately remains unchanged and increases, respectively. Experimental data are integrated into a hormonal crosstalk network through combination with information in literature. Network construction reveals that the regulation of both PIN1 and PIN2 is predominantly via ethylene signalling. In addition, it is deduced that the relationship between cytokinin and PIN1 and PIN2 levels implies a regulatory role of cytokinin in addition to its regulation to auxin, ethylene and PLS levels. We discuss how the network of hormones and genes coordinates plant growth by simultaneously regulating the activities of auxin, ethylene and cytokinin signalling pathways.

A PLS-based extractive spectrophotometric method for simultaneous determination of carbamazepine and carbamazepine-10,11-epoxide in plasma and comparison with HPLC

Science.gov (United States)

Hemmateenejad, Bahram; Rezaei, Zahra; Khabnadideh, Soghra; Saffari, Maryam

2007-11-01

Carbamazepine (CBZ) undergoes enzyme biotransformation through epoxidation with the formation of its metabolite, carbamazepine-10,11-epoxide (CBZE). A simple chemometrics-assisted spectrophotometric method has been proposed for simultaneous determination of CBZ and CBZE in plasma. A liquid extraction procedure was operated to separate the analytes from plasma, and the UV absorbance spectra of the resultant solutions were subjected to partial least squares (PLS) regression. The optimum number of PLS latent variables was selected according to the PRESS values of leave-one-out cross-validation. A HPLC method was also employed for comparison. The respective mean recoveries for analysis of CBZ and CBZE in synthetic mixtures were 102.57 (±0.25)% and 103.00 (±0.09)% for PLS and 99.40 (±0.15)% and 102.20 (±0.02)%. The concentrations of CBZ and CBZE were also determined in five patients using the PLS and HPLC methods. The results showed that the data obtained by PLS were comparable with those obtained by HPLC method.

News Conference: Serbia hosts teachers' seminar Resources: Teachers TV website closes for business Festival: Science takes to the stage in Denmark Research: How noise affects learning in secondary schools CERN: CERN visit inspires new teaching ideas Education: PLS aims to improve perception of science for school students Conference: Scientix conference discusses challenges in science education

Science.gov (United States)

2011-07-01

Conference: Serbia hosts teachers' seminar Resources: Teachers TV website closes for business Festival: Science takes to the stage in Denmark Research: How noise affects learning in secondary schools CERN: CERN visit inspires new teaching ideas Education: PLS aims to improve perception of science for school students Conference: Scientix conference discusses challenges in science education

DEMAND FOR AND SUPPLY OF MARK-UP AND PLS FUNDS IN ISLAMIC BANKING: SOME ALTERNATIVE EXPLANATIONS

OpenAIRE

KHAN, TARIQULLAH

1995-01-01

Profit and loss-sharing (PLS) and bai’ al murabahah lil amir bil shira (mark-up) are the two parent principles of Islamic financing. The use of PLS is limited and that of mark-up overwhelming in the operations of the Islamic banks. Several studies provide different explanations for this phenomenon. The dominant among these is the moral hazard hypothesis. Some alternative explanations are given in the present paper. The discussion is based on both demand (user of funds) and supply (bank) side ...

Preliminary antifungal and cytotoxic evaluation of synthetic cycloalkyl[b]thiophene derivatives with PLS-DA analysis.

Science.gov (United States)

Souza, Beatriz C C; De Oliveira, Tiago B; Aquino, Thiago M; de Lima, Maria C A; Pitta, Ivan R; Galdino, Suely L; Lima, Edeltrudes O; Gonçalves-Silva, Teresinha; Militão, Gardênia C G; Scotti, Luciana; Scotti, Marcus T; Mendonça, Francisco J B

2012-06-01

A series of 2-[(arylidene)amino]-cycloalkyl[b]thiophene-3-carbonitriles (2a-x) was synthesized by incorporation of substituted aromatic aldehydes in Gewald adducts (1a-c). The title compounds were screened for their antifungal activity against Candida krusei and Criptococcus neoformans and for their antiproliferative activity against a panel of 3 human cancer cell lines (HT29, NCI H-292 and HEP). For antiproliferative activity, the partial least squares (PLS) methodology was applied. Some of the prepared compounds exhibited promising antifungal and proliferative properties. The most active compounds for antifungal activity were cyclohexyl[b]thiophene derivatives, and for antiproliferative activity cycloheptyl[b]thiophene derivatives, especially 2-[(1H-indol-2-yl-methylidene)amino]- 5,6,7,8-tetrahydro-4H-cyclohepta[b]thiophene-3-carbonitrile (2r), which inhibited more than 97 % growth of the three cell lines. The PLS discriminant analysis (PLS-DA) applied generated good exploratory and predictive results and showed that the descriptors having shape characteristics were strongly correlated with the biological data.

Unified Deep Learning Architecture for Modeling Biology Sequence.

Science.gov (United States)

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

Team-based learning to improve learning outcomes in a therapeutics course sequence.

Science.gov (United States)

Bleske, Barry E; Remington, Tami L; Wells, Trisha D; Dorsch, Michael P; Guthrie, Sally K; Stumpf, Janice L; Alaniz, Marissa C; Ellingrod, Vicki L; Tingen, Jeffrey M

2014-02-12

To compare the effectiveness of team-based learning (TBL) to that of traditional lectures on learning outcomes in a therapeutics course sequence. A revised TBL curriculum was implemented in a therapeutic course sequence. Multiple choice and essay questions identical to those used to test third-year students (P3) taught using a traditional lecture format were administered to the second-year pharmacy students (P2) taught using the new TBL format. One hundred thirty-one multiple-choice questions were evaluated; 79 tested recall of knowledge and 52 tested higher level, application of knowledge. For the recall questions, students taught through traditional lectures scored significantly higher compared to the TBL students (88%±12% vs. 82%±16%, p=0.01). For the questions assessing application of knowledge, no differences were seen between teaching pedagogies (81%±16% vs. 77%±20%, p=0.24). Scores on essay questions and the number of students who achieved 100% were also similar between groups. Transition to a TBL format from a traditional lecture-based pedagogy allowed P2 students to perform at a similar level as students with an additional year of pharmacy education on application of knowledge type questions. However, P3 students outperformed P2 students regarding recall type questions and overall. Further assessment of long-term learning outcomes is needed to determine if TBL produces more persistent learning and improved application in clinical settings.

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

Science.gov (United States)

Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

2015-05-01

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

DEFF Research Database (Denmark)

Tully, Philip J; Lindén, Henrik; Hennig, Matthias H

2016-01-01

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed...... in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods...

A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns

Science.gov (United States)

Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam

2013-01-01

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

Learning Sequences of Actions in Collectives of Autonomous Agents

Science.gov (United States)

Turner, Kagan; Agogino, Adrian K.; Wolpert, David H.; Clancy, Daniel (Technical Monitor)

2001-01-01

In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.

Exact estimation of biodiesel cetane number (CN) from its fatty acid methyl esters (FAMEs) profile using partial least square (PLS) adapted by artificial neural network (ANN)

International Nuclear Information System (INIS)

Hosseinpour, Soleiman; Aghbashlo, Mortaza; Tabatabaei, Meisam; Khalife, Esmail

2016-01-01

Highlights: • Estimating the biodiesel CN from its FAMEs profile using ANN-based PLS approach. • Comparing the capability of ANN-adapted PLS approach with the standard PLS model. • Exact prediction of biodiesel CN from it FAMEs profile using ANN-based PLS method. • Developing an easy-to-use software using ANN-PLS model for computing the biodiesel CN. - Abstract: Cetane number (CN) is among the most important properties of biodiesel because it quantifies combustion speed or in better words, ignition quality. Experimental measurement of biodiesel CN is rather laborious and expensive. However, the high proportionality of biodiesel fatty acid methyl esters (FAMEs) profile with its CN is very appealing to develop straightforward and inexpensive computerized tools for biodiesel CN estimation. Unfortunately, correlating the chemical structure of biodiesel to its CN using conventional statistical and mathematical approaches is very difficult. To solve this issue, partial least square (PLS) adapted by artificial neural network (ANN) was introduced and examined herein as an innovative approach for the exact estimation of biodiesel CN from its FAMEs profile. In the proposed approach, ANN paradigm was used for modeling the inner relation between the input and the output PLS score vectors. In addition, the capability of the developed method in predicting the biodiesel CN was compared with the basal PLS method. The accuracy of the developed approaches for computing the biodiesel CN was assessed using three statistical criteria, i.e., coefficient of determination (R"2), mean-squared error (MSE), and percentage error (PE). The ANN-adapted PLS method predicted the biodiesel CN with an R"2 value higher than 0.99 demonstrating the fidelity of the developed model over the classical PLS method with a markedly lower R"2 value of about 0.85. In order to facilitate the use of the proposed model, an easy-to-use computer program was also developed on the basis of ANN-adapted PLS

Auditory access, language access, and implicit sequence learning in deaf children.

Science.gov (United States)

Hall, Matthew L; Eigsti, Inge-Marie; Bortfeld, Heather; Lillo-Martin, Diane

2018-05-01

Developmental psychology plays a central role in shaping evidence-based best practices for prelingually deaf children. The Auditory Scaffolding Hypothesis (Conway et al., 2009) asserts that a lack of auditory stimulation in deaf children leads to impoverished implicit sequence learning abilities, measured via an artificial grammar learning (AGL) task. However, prior research is confounded by a lack of both auditory and language input. The current study examines implicit learning in deaf children who were (Deaf native signers) or were not (oral cochlear implant users) exposed to language from birth, and in hearing children, using both AGL and Serial Reaction Time (SRT) tasks. Neither deaf nor hearing children across the three groups show evidence of implicit learning on the AGL task, but all three groups show robust implicit learning on the SRT task. These findings argue against the Auditory Scaffolding Hypothesis, and suggest that implicit sequence learning may be resilient to both auditory and language deprivation, within the tested limits. A video abstract of this article can be viewed at: https://youtu.be/EeqfQqlVHLI [Correction added on 07 August 2017, after first online publication: The video abstract link was added.]. © 2017 John Wiley & Sons Ltd.

VG2 URA PLS DERIVED SUMMARY ION FIT 48SEC V1.0

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains the total ion density obtained from Voyager 2 PLS data (voltage range 10-5950 eV/Q) at Uranus by fitting the measured spectra with isotropic...

Senate Bill (PLS No. 200, de 2015, analysis versus the Principle of the Prohibition of Social Regression

Directory of Open Access Journals (Sweden)

Glaucia Ribeiro Lima

2016-12-01

Full Text Available The Senate Bill (PLS number 200, of 2015, proposes the edition of a law for the conduction of clinical trials involving human subjects. This study aimed to perform a critical analysis of the PLS 200/2015, based on the Principle of the Prohibition of Social Regression. Thus, a descriptive, documentary and normative research was conducted, with survey of the ethical and sanitary standards related to clinical research and findings related to the PL 200/2015. The PLS 200/2015 and the information regarding was also consulted on the website of the Senate. The regulation of the matter by law demonstrated not to be a problem in the research. The main conflicts were related to the creation of Independent Ethics Committee (IEC, that does not link the ethic review to an State Agency; the use of placebo, in which flexibility is contrary to all efforts to ensure that participants have the best treatment options; and post-study access, which restriction is contrary to the existing regulations that determine the free and unlimited access. The analysis of the main settings specified in the PLS 200/2015 did not identify social or scientific improvements. The Principle of the Prohibition of Social Regression can be used, thus, to ensure the constitutional provisions already undertake and accomplished, mainly the right to health, human dignity and the inviolability of the right to live.

VG2 URA PLS DERIVED RDR ION FIT 48SEC V1.0

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains the ion densities and temperatures along with formal 1 Sigma errors obtained from Voyager 2 PLS data (voltage range 10-5950 eV/Q) at Uranus by...

Music as a mnemonic to learn gesture sequences in normal aging and Alzheimer’s disease

OpenAIRE

Aline eMoussard; Emmanuel eBigand; Emmanuel eBigand; Isabelle ePeretz; Isabelle ePeretz; Isabelle ePeretz; Sylvie eBelleville; Sylvie eBelleville

2014-01-01

Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer's disease (AD) and healthy older adults (Controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning proce...

Music as a Mnemonic to Learn Gesture Sequences in Normal Aging and Alzheimer’s Disease

OpenAIRE

Moussard, Aline; Bigand, Emmanuel; Belleville, Sylvie; Peretz, Isabelle

2014-01-01

Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer’s disease (AD) and healthy older adults (controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning proce...

Music as a mnemonic to learn gesture sequences in normal aging and Alzheimer's disease.

Science.gov (United States)

Moussard, Aline; Bigand, Emmanuel; Belleville, Sylvie; Peretz, Isabelle

2014-01-01

Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer's disease (AD) and healthy older adults (controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning procedure such that participants had to imitate the gestures to-be-memorized in synchrony with the experimenter or after the experimenter during encoding. Results show different patterns of performance for the two groups. Overall, musical accompaniment had no impact on the controls' performance but improved those of AD participants. Conversely, synchronization of gestures during learning helped controls but seemed to interfere with retention in AD. We discuss these findings regarding their relevance for a better understanding of auditory-motor memory, and we propose recommendations to maximize the mnemonic effect of music for motor sequence learning for dementia care.

Statistical learning of music- and language-like sequences and tolerance for spectral shifts.

Science.gov (United States)

Daikoku, Tatsuya; Yatomi, Yutaka; Yumoto, Masato

2015-02-01

In our previous study (Daikoku, Yatomi, & Yumoto, 2014), we demonstrated that the N1m response could be a marker for the statistical learning process of pitch sequence, in which each tone was ordered by a Markov stochastic model. The aim of the present study was to investigate how the statistical learning of music- and language-like auditory sequences is reflected in the N1m responses based on the assumption that both language and music share domain generality. By using vowel sounds generated by a formant synthesizer, we devised music- and language-like auditory sequences in which higher-ordered transitional rules were embedded according to a Markov stochastic model by controlling fundamental (F0) and/or formant frequencies (F1-F2). In each sequence, F0 and/or F1-F2 were spectrally shifted in the last one-third of the tone sequence. Neuromagnetic responses to the tone sequences were recorded from 14 right-handed normal volunteers. In the music- and language-like sequences with pitch change, the N1m responses to the tones that appeared with higher transitional probability were significantly decreased compared with the responses to the tones that appeared with lower transitional probability within the first two-thirds of each sequence. Moreover, the amplitude difference was even retained within the last one-third of the sequence after the spectral shifts. However, in the language-like sequence without pitch change, no significant difference could be detected. The pitch change may facilitate the statistical learning in language and music. Statistically acquired knowledge may be appropriated to process altered auditory sequences with spectral shifts. The relative processing of spectral sequences may be a domain-general auditory mechanism that is innate to humans. Copyright © 2014 Elsevier Inc. All rights reserved.

Visual artificial grammar learning by rhesus macaques (Macaca mulatta): exploring the role of grammar complexity and sequence length.

Science.gov (United States)

Heimbauer, Lisa A; Conway, Christopher M; Christiansen, Morten H; Beran, Michael J; Owren, Michael J

2018-03-01

Humans and nonhuman primates can learn about the organization of stimuli in the environment using implicit sequential pattern learning capabilities. However, most previous artificial grammar learning studies with nonhuman primates have involved relatively simple grammars and short input sequences. The goal in the current experiments was to assess the learning capabilities of monkeys on an artificial grammar-learning task that was more complex than most others previously used with nonhumans. Three experiments were conducted using a joystick-based, symmetrical-response serial reaction time task in which two monkeys were exposed to grammar-generated sequences at sequence lengths of four in Experiment 1, six in Experiment 2, and eight in Experiment 3. Over time, the monkeys came to respond faster to the sequences generated from the artificial grammar compared to random versions. In a subsequent generalization phase, subjects generalized their knowledge to novel sequences, responding significantly faster to novel instances of sequences produced using the familiar grammar compared to those constructed using an unfamiliar grammar. These results reveal that rhesus monkeys can learn and generalize the statistical structure inherent in an artificial grammar that is as complex as some used with humans, for sequences up to eight items long. These findings are discussed in relation to whether or not rhesus macaques and other primate species possess implicit sequence learning abilities that are similar to those that humans draw upon to learn natural language grammar.

Negative affect reduces performance in implicit sequence learning.

Directory of Open Access Journals (Sweden)

Junchen Shang

Full Text Available BACKGROUND: It is well documented that positive rather than negative moods encourage integrative processing of conscious information. However, the extent to which implicit or unconscious learning can be influenced by affective states remains unclear. METHODOLOGY/PRINCIPAL FINDINGS: A Serial Reaction Time (SRT task with sequence structures requiring integration over past trials was adopted to examine the effect of affective states on implicit learning. Music was used to induce and maintain positive and negative affective states. The present study showed that participants in negative rather than positive states learned less of the regularity. Moreover, the knowledge was shown by a Bayesian analysis to be largely unconscious as participants were poor at recognizing the regularity. CONCLUSIONS/SIGNIFICANCE: The results demonstrated that negative rather than positive affect inhibited implicit learning of complex structures. Our findings help to understand the effects of affective states on unconscious or implicit processing.

A comparative QSAR study on the estrogenic activities of persistent organic pollutants by PLS and SVM

Directory of Open Access Journals (Sweden)

Fei Li

2015-11-01

Full Text Available Quantitative structure-activity relationships (QSARs were determined using partial least square (PLS and support vector machine (SVM. The predicted values by the final QSAR models were in good agreement with the corresponding experimental values. Chemical estrogenic activities are related to atomic properties (atomic Sanderson electronegativities, van der Waals volumes and polarizabilities. Comparison of the results obtained from two models, the SVM method exhibited better overall performances. Besides, three PLS models were constructed for some specific families based on their chemical structures. These predictive models should be useful to rapidly identify potential estrogenic endocrine disrupting chemicals.

Effects of aging and dopamine genotypes on the emergence of explicit memory during sequence learning.

Science.gov (United States)

Schuck, Nicolas W; Frensch, Peter A; Schjeide, Brit-Maren M; Schröder, Julia; Bertram, Lars; Li, Shu-Chen

2013-11-01

The striatum and medial temporal lobe play important roles in implicit and explicit memory, respectively. Furthermore, recent studies have linked striatal dopamine modulation to both implicit as well as explicit sequence learning and suggested a potential role of the striatum in the emergence of explicit memory during sequence learning. With respect to aging, previous findings indicated that implicit memory is less impaired than explicit memory in older adults and that genetic effects on cognition are magnified by aging. To understand the links between these findings, we investigated effects of aging and genotypes relevant for striatal dopamine on the implicit and explicit components of sequence learning. Reaction time (RT) and error data from 80 younger (20-30 years) and 70 older adults (60-71 years) during a serial reaction time task showed that age differences in learning-related reduction of RTs emerged gradually over the course of learning. Verbal recall and measures derived from the process-dissociation procedure revealed that younger adults acquired more explicit memory about the sequence than older adults, potentially causing age differences in RT gains in later stages of learning. Of specific interest, polymorphisms of the dopamine- and cAMP-regulated neuronal phosphoprotein (DARPP-32, rs907094) and dopamine transporter (DAT, VNTR) genes showed interactive effects on overall RTs and verbal recall of the sequence in older but not in younger adults. Together our findings show that variations in genotypes relevant for dopamine functions are associated more with aging-related impairments in the explicit than the implicit component of sequence learning, providing support for theories emphasizing the role of dopaminergic modulation in cognitive aging and the magnification of genetic effects in human aging. © 2013 Elsevier Ltd. All rights reserved.

Towards molecular design using 2D-molecular contour maps obtained from PLS regression coefficients

Science.gov (United States)

Borges, Cleber N.; Barigye, Stephen J.; Freitas, Matheus P.

2017-12-01

The multivariate image analysis descriptors used in quantitative structure-activity relationships are direct representations of chemical structures as they are simply numerical decodifications of pixels forming the 2D chemical images. These MDs have found great utility in the modeling of diverse properties of organic molecules. Given the multicollinearity and high dimensionality of the data matrices generated with the MIA-QSAR approach, modeling techniques that involve the projection of the data space onto orthogonal components e.g. Partial Least Squares (PLS) have been generally used. However, the chemical interpretation of the PLS-based MIA-QSAR models, in terms of the structural moieties affecting the modeled bioactivity has not been straightforward. This work describes the 2D-contour maps based on the PLS regression coefficients, as a means of assessing the relevance of single MIA predictors to the response variable, and thus allowing for the structural, electronic and physicochemical interpretation of the MIA-QSAR models. A sample study to demonstrate the utility of the 2D-contour maps to design novel drug-like molecules is performed using a dataset of some anti-HIV-1 2-amino-6-arylsulfonylbenzonitriles and derivatives, and the inferences obtained are consistent with other reports in the literature. In addition, the different schemes for encoding atomic properties in molecules are discussed and evaluated.

Effects of dopamine medication on sequence learning with stochastic feedback in Parkinson's disease

Directory of Open Access Journals (Sweden)

Moonsang Seo

2010-08-01

Full Text Available A growing body of evidence suggests that the midbrain dopamine system plays a key role in reinforcement learning and disruption of the midbrain dopamine system in Parkinson's disease (PD may lead to deficits on tasks that require learning from feedback. We examined how changes in dopamine levels (‘ON’ and ‘OFF’ their dopamine medication affect sequence learning from stochastic positive and negative feedback using Bayesian reinforcement learning models. We found deficits in sequence learning in patients with PD when they were ‘ON’ and ‘OFF’ medication relative to healthy controls, but smaller differences between patients ‘OFF’ and ‘ON’. The deficits were mainly due to decreased learning from positive feedback, although across all participant groups learning was more strongly associated with positive than negative feedback in our task. The learning in our task is likely mediated by the relatively depleted dorsal striatum and not the relatively intact ventral striatum. Therefore, the changes we see in our task may be due to a strong loss of phasic dopamine signals in the dorsal striatum in PD.

Effects of Dopamine Medication on Sequence Learning with Stochastic Feedback in Parkinson's Disease

Science.gov (United States)

Seo, Moonsang; Beigi, Mazda; Jahanshahi, Marjan; Averbeck, Bruno B.

2010-01-01

A growing body of evidence suggests that the midbrain dopamine system plays a key role in reinforcement learning and disruption of the midbrain dopamine system in Parkinson's disease (PD) may lead to deficits on tasks that require learning from feedback. We examined how changes in dopamine levels (“ON” and “OFF” their dopamine medication) affect sequence learning from stochastic positive and negative feedback using Bayesian reinforcement learning models. We found deficits in sequence learning in patients with PD when they were “ON” and “OFF” medication relative to healthy controls, but smaller differences between patients “OFF” and “ON”. The deficits were mainly due to decreased learning from positive feedback, although across all participant groups learning was more strongly associated with positive than negative feedback in our task. The learning in our task is likely mediated by the relatively depleted dorsal striatum and not the relatively intact ventral striatum. Therefore, the changes we see in our task may be due to a strong loss of phasic dopamine signals in the dorsal striatum in PD. PMID:20740077

Quantitative analysis of glycated albumin in serum based on ATR-FTIR spectrum combined with SiPLS and SVM.

Science.gov (United States)

Li, Yuanpeng; Li, Fucui; Yang, Xinhao; Guo, Liu; Huang, Furong; Chen, Zhenqiang; Chen, Xingdan; Zheng, Shifu

2018-08-05

A rapid quantitative analysis model for determining the glycated albumin (GA) content based on Attenuated total reflectance (ATR)-Fourier transform infrared spectroscopy (FTIR) combining with linear SiPLS and nonlinear SVM has been developed. Firstly, the real GA content in human serum was determined by GA enzymatic method, meanwhile, the ATR-FTIR spectra of serum samples from the population of health examination were obtained. The spectral data of the whole spectra mid-infrared region (4000-600 cm -1 ) and GA's characteristic region (1800-800 cm -1 ) were used as the research object of quantitative analysis. Secondly, several preprocessing steps including first derivative, second derivative, variable standardization and spectral normalization, were performed. Lastly, quantitative analysis regression models were established by using SiPLS and SVM respectively. The SiPLS modeling results are as follows: root mean square error of cross validation (RMSECV T ) = 0.523 g/L, calibration coefficient (R C ) = 0.937, Root Mean Square Error of Prediction (RMSEP T ) = 0.787 g/L, and prediction coefficient (R P ) = 0.938. The SVM modeling results are as follows: RMSECV T  = 0.0048 g/L, R C  = 0.998, RMSEP T  = 0.442 g/L, and R p  = 0.916. The results indicated that the model performance was improved significantly after preprocessing and optimization of characteristic regions. While modeling performance of nonlinear SVM was considerably better than that of linear SiPLS. Hence, the quantitative analysis model for GA in human serum based on ATR-FTIR combined with SiPLS and SVM is effective. And it does not need sample preprocessing while being characterized by simple operations and high time efficiency, providing a rapid and accurate method for GA content determination. Copyright © 2018 Elsevier B.V. All rights reserved.

A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity.

Directory of Open Access Journals (Sweden)

Quan Wang

2017-08-01

Full Text Available The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP and synaptic normalization (SN. When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network's changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network's sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that

Music as a mnemonic to learn gesture sequences in normal aging and Alzheimer’s disease

Directory of Open Access Journals (Sweden)

Aline eMoussard

2014-05-01

Full Text Available Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer's disease (AD and healthy older adults (Controls learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning procedure such that participants had to imitate the gestures to-be-memorized in synchrony with the experimenter or after the experimenter during encoding. Results show different patterns of performance for the two groups. Overall, musical accompaniment had no impact on the Controls' performance, but improved those of AD participants. Conversely, synchronization of gestures during learning helped Controls but seemed to interfere with retention in AD. We discuss these findings regarding their relevance for a better understanding of auditory-motor memory, and we propose recommendations to maximize the mnemonic effect of music for motor sequence learning for dementia care.

Music as a Mnemonic to Learn Gesture Sequences in Normal Aging and Alzheimer’s Disease

Science.gov (United States)

Moussard, Aline; Bigand, Emmanuel; Belleville, Sylvie; Peretz, Isabelle

2014-01-01

Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer’s disease (AD) and healthy older adults (controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning procedure such that participants had to imitate the gestures to-be-memorized in synchrony with the experimenter or after the experimenter during encoding. Results show different patterns of performance for the two groups. Overall, musical accompaniment had no impact on the controls’ performance but improved those of AD participants. Conversely, synchronization of gestures during learning helped controls but seemed to interfere with retention in AD. We discuss these findings regarding their relevance for a better understanding of auditory–motor memory, and we propose recommendations to maximize the mnemonic effect of music for motor sequence learning for dementia care. PMID:24860476

Infants' statistical learning: 2- and 5-month-olds' segmentation of continuous visual sequences.

Science.gov (United States)

Slone, Lauren Krogh; Johnson, Scott P

2015-05-01

Past research suggests that infants have powerful statistical learning abilities; however, studies of infants' visual statistical learning offer differing accounts of the developmental trajectory of and constraints on this learning. To elucidate this issue, the current study tested the hypothesis that young infants' segmentation of visual sequences depends on redundant statistical cues to segmentation. A sample of 20 2-month-olds and 20 5-month-olds observed a continuous sequence of looming shapes in which unit boundaries were defined by both transitional probability and co-occurrence frequency. Following habituation, only 5-month-olds showed evidence of statistically segmenting the sequence, looking longer to a statistically improbable shape pair than to a probable pair. These results reaffirm the power of statistical learning in infants as young as 5 months but also suggest considerable development of statistical segmentation ability between 2 and 5 months of age. Moreover, the results do not support the idea that infants' ability to segment visual sequences based on transitional probabilities and/or co-occurrence frequencies is functional at the onset of visual experience, as has been suggested previously. Rather, this type of statistical segmentation appears to be constrained by the developmental state of the learner. Factors contributing to the development of statistical segmentation ability during early infancy, including memory and attention, are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

Science.gov (United States)

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Determination of Trace Amounts of Gold in Environmental Samples by Adsorptive Stripping Voltammetry of Its Complex with Rhodamine Using Osc-Pls

Directory of Open Access Journals (Sweden)

A. Akrami

2012-11-01

Full Text Available The multivariate calibration method was applied for the determination of trace amounts of gold based on a hanging mercury drop electrode (HMDE in the presence of rhodanine, followed by reduction of adsorbed gold by voltammetric scan using differential pulse modulation The optimum experimental conditions are: rhodanine concentration of 0.20 mg mL-1, pH 5.0, accumulation potential of -600 mV versus Ag/AgCl, accumulation time of 100 sec, scan rate of 30 mV s-1 and pulse height of 100 mV. The calibration matrix for partial least squares (PLS regression was designed with 9 samples. Orthogonal signal correction (OSC is a preprocessing technique used for removing the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for PLS calibration without loss of prediction capacity using electrochemical method. The RMSEP for gold determination with PLS and OSC-PLS were 8.51 and 1.94, respectively. This procedure allows the determination of gold in synthetic and real samples with good reliability of the determination. 

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

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Stephen eGrossberg

2014-10-01

Full Text Available 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

Implicit Sequence Learning and Contextual Cueing Do Not Compete for Central Cognitive Resources

Science.gov (United States)

Jimenez, Luis; Vazquez, Gustavo A.

2011-01-01

Sequence learning and contextual cueing explore different forms of implicit learning, arising from practice with a structured serial task, or with a search task with informative contexts. We assess whether these two learning effects arise simultaneously when both remain implicit. Experiments 1 and 2 confirm that a cueing effect can be observed…

LTD windows of the STDP learning rule and synaptic connections having a large transmission delay enable robust sequence learning amid background noise.

Science.gov (United States)

Hayashi, Hatsuo; Igarashi, Jun

2009-06-01

Spike-timing-dependent synaptic plasticity (STDP) is a simple and effective learning rule for sequence learning. However, synapses being subject to STDP rules are readily influenced in noisy circumstances because synaptic conductances are modified by pre- and postsynaptic spikes elicited within a few tens of milliseconds, regardless of whether those spikes convey information or not. Noisy firing existing everywhere in the brain may induce irrelevant enhancement of synaptic connections through STDP rules and would result in uncertain memory encoding and obscure memory patterns. We will here show that the LTD windows of the STDP rules enable robust sequence learning amid background noise in cooperation with a large signal transmission delay between neurons and a theta rhythm, using a network model of the entorhinal cortex layer II with entorhinal-hippocampal loop connections. The important element of the present model for robust sequence learning amid background noise is the symmetric STDP rule having LTD windows on both sides of the LTP window, in addition to the loop connections having a large signal transmission delay and the theta rhythm pacing activities of stellate cells. Above all, the LTD window in the range of positive spike-timing is important to prevent influences of noise with the progress of sequence learning.

Semi-Supervised Learning for Classification of Protein Sequence Data

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Brian R. King

2008-01-01

Full Text Available Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.

A single session of prefrontal cortex transcranial direct current stimulation does not modulate implicit task sequence learning and consolidation.

Science.gov (United States)

Savic, Branislav; Müri, René; Meier, Beat

Transcranial direct current stimulation (tDCS) is assumed to affect cortical excitability and dependent on the specific stimulation conditions either to increase or decrease learning. The purpose of this study was to modulate implicit task sequence learning with tDCS. As cortico-striatal loops are critically involved in implicit task sequence learning, tDCS was applied above the dorsolateral prefrontal cortex (DLPFC). In Experiment 1, anodal, cathodal, or sham tDCS was applied before the start of the sequence learning task. In Experiment 2, stimulation was applied during the sequence learning task. Consolidation of learning was assessed after 24 h. The results of both experiments showed that implicit task sequence learning occurred consistently but it was not modulated by different tDCS conditions. Similarly, consolidation measured after a 24 h-interval including sleep was also not affected by stimulation. These results indicate that a single session of DLPFC tDCS is not sufficient to modulate implicit task sequence learning. This study adds to the accumulating evidence that tDCS may not be as effective as originally thought. Copyright © 2017 Elsevier Inc. All rights reserved.

A teaching-learning sequence about weather map reading

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Mandrikas, Achilleas; Stavrou, Dimitrios; Skordoulis, Constantine

2017-07-01

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 weather forecast. Sixty PET capabilities and difficulties in understanding weather maps were investigated, using inquiry-based learning activities. The results show that most PET became more capable of reading weather maps and assigning wind direction and speed on them. Our results also show that PET could be guided to understand meteorology concepts useful in everyday life and in teaching their future students.

Sequence Learning Under Uncertainty in Children: Self-Reflection vs. Self-Assertion.

Science.gov (United States)

Lange-Küttner, Christiane; Averbeck, Bruno B; Hirsch, Silvia V; Wießner, Isabel; Lamba, Nishtha

2012-01-01

We know that stochastic feedback impairs children's associative stimulus-response (S-R) learning (Crone et al., 2004a; Eppinger et al., 2009), but the impact of stochastic feedback on sequence learning that involves deductive reasoning has not been not tested so far. In the current study, 8- to 11-year-old children (N = 171) learned a sequence of four left and right button presses, LLRR, RRLL, LRLR, RLRL, LRRL, and RLLR, which needed to be deduced from feedback because no directional cues were given. One group of children experienced consistent feedback only (deterministic feedback, 100% correct). In this condition, green feedback on the screen indicated that the children had been right when they were right, and red feedback indicated that the children had been wrong when they were wrong. Another group of children experienced inconsistent feedback (stochastic feedback, 85% correct, 15% false), where in some trials, green feedback on the screen could signal that children were right when in fact they were wrong, and red feedback could indicate that they were wrong when in fact they had been right. Independently of age, children's sequence learning in the stochastic condition was initially much lower than in the deterministic condition, but increased gradually and improved with practice. Responses toward positive vs. negative feedback varied with age. Children were increasingly able to understand that they could have been wrong when feedback indicated they were right (self-reflection), but they remained unable to understand that they could have been right when feedback indicated they were wrong (self-assertion).

Sequence Learning Under Uncertainty in Children: Self-reflection vs. Self-Assertion

Directory of Open Access Journals (Sweden)

Christiane eLange-Küttner

2012-05-01

Full Text Available We know that stochastic feedback impairs children’s associative stimulus-response (S-R learning (Crone, Jennigs, & Van der Molen, 2004a; Eppinger, Mock, & Kray, 2009, but the impact of stochastic feedback on sequence learning that involves deductive reasoning has not been not tested so far. In the current study, 8- to 11-year-old children (N = 171 learned a sequence of four left and right button presses, LLRR, RRLL, LRLR, RLRL, LRRL and RLLR, that needed to be deduced from feedback because no directional cues were given. One group of children experienced consistent feedback only (deterministic feedback, 100% correct. In this condition, green feedback on the screen indicated that the children had been right when they were right, and red feedback indicated that the children had been wrong when they were wrong. Another group of children experienced inconsistent feedback (stochastic feedback, 85% correct, 15% false, where in some trials, green feedback on the screen could signal that children were right when in fact they were wrong, and red feedback could indicate that they were wrong when in fact they had been right. Independently of age, children’s sequence learning in the stochastic condition was initially much lower than in the deterministic condition, but increased gradually and improved with practice. Responses towards positive vs. negative feedback varied with age. Children were increasingly able to understand that they could have been wrong when feedback indicated they were right (self-reflection, but they remained unable to understand that they could have been right when feedback indicated they were wrong (self-assertion.

Nonlinear Synchronization for Automatic Learning of 3D Pose Variability in Human Motion Sequences

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Mozerov M

2010-01-01

Full Text Available A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.

Impacts of visuomotor sequence learning methods on speed and accuracy: Starting over from the beginning or from the point of error.

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Tanaka, Kanji; Watanabe, Katsumi

2016-02-01

The present study examined whether sequence learning led to more accurate and shorter performance time if people who are learning a sequence start over from the beginning when they make an error (i.e., practice the whole sequence) or only from the point of error (i.e., practice a part of the sequence). We used a visuomotor sequence learning paradigm with a trial-and-error procedure. In Experiment 1, we found fewer errors, and shorter performance time for those who restarted their performance from the beginning of the sequence as compared to those who restarted from the point at which an error occurred, indicating better learning of spatial and motor representations of the sequence. This might be because the learned elements were repeated when the next performance started over from the beginning. In subsequent experiments, we increased the occasions for the repetitions of learned elements by modulating the number of fresh start points in the sequence after errors. The results showed that fewer fresh start points were likely to lead to fewer errors and shorter performance time, indicating that the repetitions of learned elements enabled participants to develop stronger spatial and motor representations of the sequence. Thus, a single or two fresh start points in the sequence (i.e., starting over only from the beginning or from the beginning or midpoint of the sequence after errors) is likely to lead to more accurate and faster performance. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying Learning Behaviors by Contextualizing Differential Sequence Mining with Action Features and Performance Evolution

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Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Our learning-by-teaching environment, Betty's Brain, captures a wealth of data on students' learning interactions as they teach a virtual agent. This paper extends an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs sequence mining techniques to…

Sequenced Integration and the Identification of a Problem-Solving Approach through a Learning Process

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Cormas, Peter C.

2016-01-01

Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…

Observational learning of new movement sequences is reflected in fronto-parietal coherence.

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Jurjen van der Helden

Full Text Available Mankind is unique in her ability for observational learning, i.e. the transmission of acquired knowledge and behavioral repertoire through observation of others' actions. In the present study we used electrophysiological measures to investigate brain mechanisms of observational learning. Analysis investigated the possible functional coupling between occipital (alpha and motor (mu rhythms operating in the 10 Hz frequency range for translating "seeing" into "doing". Subjects observed movement sequences consisting of six consecutive left or right hand button presses directed at one of two target-buttons for subsequent imitation. Each movement sequence was presented four times, intervened by short pause intervals for sequence rehearsal. During a control task subjects observed the same movement sequences without a requirement for subsequent reproduction. Although both alpha and mu rhythms desynchronized during the imitation task relative to the control task, modulations in alpha and mu power were found to be largely independent from each other over time, arguing against a functional coupling of alpha and mu generators during observational learning. This independence was furthermore reflected in the absence of coherence between occipital and motor electrodes overlaying alpha and mu generators. Instead, coherence analysis revealed a pair of symmetric fronto-parietal networks, one over the left and one over the right hemisphere, reflecting stronger coherence during observation of movements than during pauses. Individual differences in fronto-parietal coherence were furthermore found to predict imitation accuracy. The properties of these networks, i.e. their fronto-parietal distribution, their ipsilateral organization and their sensitivity to the observation of movements, match closely with the known properties of the mirror neuron system (MNS as studied in the macaque brain. These results indicate a functional dissociation between higher order areas for

Fusion of neural computing and PLS techniques for load estimation

Energy Technology Data Exchange (ETDEWEB)

Lu, M.; Xue, H.; Cheng, X. [Northwestern Polytechnical Univ., Xi' an (China); Zhang, W. [Xi' an Inst. of Post and Telecommunication, Xi' an (China)

2007-07-01

A method to predict the electric load of a power system in real time was presented. The method is based on neurocomputing and partial least squares (PLS). Short-term load forecasts for power systems are generally determined by conventional statistical methods and Computational Intelligence (CI) techniques such as neural computing. However, statistical modeling methods often require the input of questionable distributional assumptions, and neural computing is weak, particularly in determining topology. In order to overcome the problems associated with conventional techniques, the authors developed a CI hybrid model based on neural computation and PLS techniques. The theoretical foundation for the designed CI hybrid model was presented along with its application in a power system. The hybrid model is suitable for nonlinear modeling and latent structure extracting. It can automatically determine the optimal topology to maximize the generalization. The CI hybrid model provides faster convergence and better prediction results compared to the abductive networks model because it incorporates a load conversion technique as well as new transfer functions. In order to demonstrate the effectiveness of the hybrid model, load forecasting was performed on a data set obtained from the Puget Sound Power and Light Company. Compared with the abductive networks model, the CI hybrid model reduced the forecast error by 32.37 per cent on workday, and by an average of 27.18 per cent on the weekend. It was concluded that the CI hybrid model has a more powerful predictive ability. 7 refs., 1 tab., 3 figs.

Online incidental statistical learning of audiovisual word sequences in adults: a registered report.

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Kuppuraj, Sengottuvel; Duta, Mihaela; Thompson, Paul; Bishop, Dorothy

2018-02-01

Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory-picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test-retest reliability ( r  = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process.

Scaffolding and interventions between students and teachers in a Learning Design Sequence

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Eva Edman Stålbrandt

Full Text Available The aims of this paper are to develop knowledge about scaffolding when students in Swedish schools use digital educational material and to investigate what the main focus is in teachers' interventions during a Learning Design Sequence (LDS, based on a socio-cultural perspective. The results indicate that scaffolding were most common in the primary transformation unit and the most frequent type was procedural scaffolding, although all types of scaffolds; conceptual, metacognitive, procedural, strategic, affective and technical scaffolding occurred in all parts of a learning design sequence. In this study most of the teachers and students, think that using digital educational material requires more and other forms of scaffolding and concerning teacher interventions teachers interact both supportively and restrictively according to students' learning process. Reasons for that are connected to the content of the intervention and whether teachers intervene together with the students or not.

Implicit sequence-specific motor learning after sub-cortical stroke is associated with increased prefrontal brain activations: An fMRI study

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Meehan, Sean K.; Randhawa, Bubblepreet; Wessel, Brenda; Boyd, Lara A.

2010-01-01

Implicit motor learning is preserved after stroke, but how the brain compensates for damage to facilitate learning is unclear. We used a random effects analysis to determine how stroke alters patterns of brain activity during implicit sequence-specific motor learning as compared to general improvements in motor control. Nine healthy participants and 9 individuals with chronic, right focal sub-cortical stroke performed a continuous joystick-based tracking task during an initial fMRI session, over 5 days of practice, and a retention test during a separate fMRI session. Sequence-specific implicit motor learning was differentiated from general improvements in motor control by comparing tracking performance on a novel, repeated tracking sequences during early practice and again at the retention test. Both groups demonstrated implicit sequence-specific motor learning at the retention test, yet substantial differences were apparent. At retention, healthy control participants demonstrated increased BOLD response in left dorsal premotor cortex (BA 6) but decreased BOLD response left dorsolateral prefrontal cortex (DLPFC; BA 9) during repeated sequence tracking. In contrast, at retention individuals with stroke did not show this reduction in DLPFC during repeated tracking. Instead implicit sequence-specific motor learning and general improvements in motor control were associated with increased BOLD response in the left middle frontal gyrus BA 8, regardless of sequence type after stroke. These data emphasize the potential importance of a prefrontal-based attentional network for implicit motor learning after stroke. The present study is the first to highlight the importance of the prefrontal cortex for implicit sequence-specific motor learning after stroke. PMID:20725908

Instrumentation and control system for PLS-IM-T 60 MeV LINAC

International Nuclear Information System (INIS)

Liu, D.K.; Yei, K.R.; Cheng, H.J.

1992-01-01

The PLSIMT is a 60 MeV LINAC as a preinjector for 2 GeV LINAC of PLS project. The instrumentation and control system have been designed under the institutional collaboration between the IHEP (Beijing, China) and POSTECH (Pohang, Korea). So far, the I and C system are being set up nowadays at the POSTECH of Pohang. This paper describes its major characteristics and present status. (author)

Visual Statistical Learning Works after Binding the Temporal Sequences of Shapes and Spatial Positions

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Osamu Watanabe

2011-05-01

Full Text Available The human visual system can acquire the statistical structures in temporal sequences of object feature changes, such as changes in shape, color, and its combination. Here we investigate whether the statistical learning for spatial position and shape changes operates separately or not. It is known that the visual system processes these two types of information separately; the spatial information is processed in the parietal cortex, whereas object shapes and colors are detected in the temporal pathway, and, after that, we perceive bound information in the two streams. We examined whether the statistical learning operates before or after binding the shape and the spatial information by using the “re-paired triplet” paradigm proposed by Turk-Browne, Isola, Scholl, and Treat (2008. The result showed that observers acquired combined sequences of shape and position changes, but no statistical information in individual sequence was obtained. This finding suggests that the visual statistical learning works after binding the temporal sequences of shapes and spatial structures and would operate in the higher-order visual system; this is consistent with recent ERP (Abla & Okanoya, 2009 and fMRI (Turk-Browne, Scholl, Chun, & Johnson, 2009 studies.

Isolating Visual and Proprioceptive Components of Motor Sequence Learning in ASD.

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Sharer, Elizabeth A; Mostofsky, Stewart H; Pascual-Leone, Alvaro; Oberman, Lindsay M

2016-05-01

In addition to defining impairments in social communication skills, individuals with autism spectrum disorder (ASD) also show impairments in more basic sensory and motor skills. Development of new skills involves integrating information from multiple sensory modalities. This input is then used to form internal models of action that can be accessed when both performing skilled movements, as well as understanding those actions performed by others. Learning skilled gestures is particularly reliant on integration of visual and proprioceptive input. We used a modified serial reaction time task (SRTT) to decompose proprioceptive and visual components and examine whether patterns of implicit motor skill learning differ in ASD participants as compared with healthy controls. While both groups learned the implicit motor sequence during training, healthy controls showed robust generalization whereas ASD participants demonstrated little generalization when visual input was constant. In contrast, no group differences in generalization were observed when proprioceptive input was constant, with both groups showing limited degrees of generalization. The findings suggest, when learning a motor sequence, individuals with ASD tend to rely less on visual feedback than do healthy controls. Visuomotor representations are considered to underlie imitative learning and action understanding and are thereby crucial to social skill and cognitive development. Thus, anomalous patterns of implicit motor learning, with a tendency to discount visual feedback, may be an important contributor in core social communication deficits that characterize ASD. Autism Res 2016, 9: 563-569. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Gift from statistical learning: Visual statistical learning enhances memory for sequence elements and impairs memory for items that disrupt regularities.

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Otsuka, Sachio; Saiki, Jun

2016-02-01

Prior studies have shown that visual statistical learning (VSL) enhances familiarity (a type of memory) of sequences. How do statistical regularities influence the processing of each triplet element and inserted distractors that disrupt the regularity? Given that increased attention to triplets induced by VSL and inhibition of unattended triplets, we predicted that VSL would promote memory for each triplet constituent, and degrade memory for inserted stimuli. Across the first two experiments, we found that objects from structured sequences were more likely to be remembered than objects from random sequences, and that letters (Experiment 1) or objects (Experiment 2) inserted into structured sequences were less likely to be remembered than those inserted into random sequences. In the subsequent two experiments, we examined an alternative account for our results, whereby the difference in memory for inserted items between structured and random conditions is due to individuation of items within random sequences. Our findings replicated even when control letters (Experiment 3A) or objects (Experiment 3B) were presented before or after, rather than inserted into, random sequences. Our findings suggest that statistical learning enhances memory for each item in a regular set and impairs memory for items that disrupt the regularity. Copyright © 2015 Elsevier B.V. All rights reserved.

The crucial role of the Pls1 tetraspanin during ascospore germination in Podospora anserina provides an example of the convergent evolution of morphogenetic processes in fungal plant pathogens and saprobes.

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Lambou, Karine; Malagnac, Fabienne; Barbisan, Crystel; Tharreau, Didier; Lebrun, Marc-Henri; Silar, Philippe

2008-10-01

Pls1 tetraspanins were shown for some pathogenic fungi to be essential for appressorium-mediated penetration into their host plants. We show here that Podospora anserina, a saprobic fungus lacking appressorium, contains PaPls1, a gene orthologous to known PLS1 genes. Inactivation of PaPls1 demonstrates that this gene is specifically required for the germination of ascospores in P. anserina. These ascospores are heavily melanized cells that germinate under inducing conditions through a specific pore. On the contrary, MgPLS1, which fully complements a DeltaPaPls1 ascospore germination defect, has no role in the germination of Magnaporthe grisea nonmelanized ascospores but is required for the formation of the penetration peg at the pore of its melanized appressorium. P. anserina mutants with mutation of PaNox2, which encodes the NADPH oxidase of the NOX2 family, display the same ascospore-specific germination defect as the DeltaPaPls1 mutant. Both mutant phenotypes are suppressed by the inhibition of melanin biosynthesis, suggesting that they are involved in the same cellular process required for the germination of P. anserina melanized ascospores. The analysis of the distribution of PLS1 and NOX2 genes in fungal genomes shows that they are either both present or both absent. These results indicate that the germination of P. anserina ascospores and the formation of the M. grisea appressorium penetration peg use the same molecular machinery that includes Pls1 and Nox2. This machinery is specifically required for the emergence of polarized hyphae from reinforced structures such as appressoria and ascospores. Its recurrent recruitment during fungal evolution may account for some of the morphogenetic convergence observed in fungi.

Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

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Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng

2017-05-25

Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.

Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

Science.gov (United States)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2018-04-01

External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

Speech Motor Sequence Learning: Acquisition and Retention in Parkinson Disease and Normal Aging

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Whitfield, Jason A.; Goberman, Alexander M.

2017-01-01

Purpose: The aim of the current investigation was to examine speech motor sequence learning in neurologically healthy younger adults, neurologically healthy older adults, and individuals with Parkinson disease (PD) over a 2-day period. Method: A sequential nonword repetition task was used to examine learning over 2 days. Participants practiced a…

Decoding sequence learning from single-trial intracranial EEG in humans.

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Marzia De Lucia

Full Text Available We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep or a later consolidated phase (day 2, after sleep, whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence. Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks.

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Panda, Priyadarshini; Roy, Kaushik

2017-01-01

Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations.

SOVEREIGN: An autonomous neural system for incrementally learning planned action sequences to navigate towards a rewarded goal.

Science.gov (United States)

Gnadt, William; Grossberg, Stephen

2008-06-01

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and size-invariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory

Experiments on Supervised Learning Algorithms for Text Categorization

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Namburu, Setu Madhavi; Tu, Haiying; Luo, Jianhui; Pattipati, Krishna R.

2005-01-01

Modern information society is facing the challenge of handling massive volume of online documents, news, intelligence reports, and so on. How to use the information accurately and in a timely manner becomes a major concern in many areas. While the general information may also include images and voice, we focus on the categorization of text data in this paper. We provide a brief overview of the information processing flow for text categorization, and discuss two supervised learning algorithms, viz., support vector machines (SVM) and partial least squares (PLS), which have been successfully applied in other domains, e.g., fault diagnosis [9]. While SVM has been well explored for binary classification and was reported as an efficient algorithm for text categorization, PLS has not yet been applied to text categorization. Our experiments are conducted on three data sets: Reuter's- 21578 dataset about corporate mergers and data acquisitions (ACQ), WebKB and the 20-Newsgroups. Results show that the performance of PLS is comparable to SVM in text categorization. A major drawback of SVM for multi-class categorization is that it requires a voting scheme based on the results of pair-wise classification. PLS does not have this drawback and could be a better candidate for multi-class text categorization.

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning

KAUST Repository

Teng, Haotian; Cao, Minh Duc; Hall, Michael B; Duarte, Tania; Wang, Sheng; Coin, Lachlan J M

2018-01-01

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning

KAUST Repository

Teng, Haotian

2018-04-10

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

Formal Learning Sequences and Progression in the Studio: A Framework for Digital Design Education

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Pontus Wärnestål

2016-02-01

Full Text Available This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a implements a theory of formal learning sequences as a user-centered design process in the studio; and (b describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.

Lateralized implicit sequence learning in uni- and bi-manual conditions.

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Schmitz, Rémy; Pasquali, Antoine; Cleeremans, Axel; Peigneux, Philippe

2013-02-01

It has been proposed that the right hemisphere (RH) is better suited to acquire novel material whereas the left hemisphere (LH) is more able to process well-routinized information. Here, we ask whether this potential dissociation also manifests itself in an implicit learning task. Using a lateralized version of the serial reaction time task (SRT), we tested whether participants trained in a divided visual field condition primarily stimulating the RH would learn the implicit regularities embedded in sequential material faster than participants in a condition favoring LH processing. In the first study, half of participants were presented sequences in the left (vs. right) visual field, and had to respond using their ipsilateral hand (unimanual condition), hence making visuo-motor processing possible within the same hemisphere. Results showed successful implicit sequence learning, as indicated by increased reaction time for a transfer sequence in both hemispheric conditions and lack of conscious knowledge in a generation task. There was, however, no evidence of interhemispheric differences. In the second study, we hypothesized that a bimanual response version of the lateralized SRT, which requires interhemispheric communication and increases computational and cognitive processing loads, would favor RH-dependent visuospatial/attentional processes. In this bimanual condition, our results revealed a much higher transfer effect in the RH than in the LH condition, suggesting higher RH sensitivity to the processing of novel sequential material. This LH/RH difference was interpreted within the framework of the Novelty-Routinization model [Goldberg, E., & Costa, L. D. (1981). Hemisphere differences in the acquisition and use of descriptive systems. Brain and Language, 14(1), 144-173] and interhemispheric interactions in attentional processing [Banich, M. T. (1998). The missing link: the role of interhemispheric interaction in attentional processing. Brain and Cognition, 36

MALDI-TOF-MS with PLS Modeling Enables Strain Typing of the Bacterial Plant Pathogen Xanthomonas axonopodis

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Sindt, Nathan M.; Robison, Faith; Brick, Mark A.; Schwartz, Howard F.; Heuberger, Adam L.; Prenni, Jessica E.

2018-02-01

Matrix-assisted desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) is a fast and effective tool for microbial species identification. However, current approaches are limited to species-level identification even when genetic differences are known. Here, we present a novel workflow that applies the statistical method of partial least squares discriminant analysis (PLS-DA) to MALDI-TOF-MS protein fingerprint data of Xanthomonas axonopodis, an important bacterial plant pathogen of fruit and vegetable crops. Mass spectra of 32 X. axonopodis strains were used to create a mass spectral library and PLS-DA was employed to model the closely related strains. A robust workflow was designed to optimize the PLS-DA model by assessing the model performance over a range of signal-to-noise ratios (s/n) and mass filter (MF) thresholds. The optimized parameters were observed to be s/n = 3 and MF = 0.7. The model correctly classified 83% of spectra withheld from the model as a test set. A new decision rule was developed, termed the rolled-up Maximum Decision Rule (ruMDR), and this method improved identification rates to 92%. These results demonstrate that MALDI-TOF-MS protein fingerprints of bacterial isolates can be utilized to enable identification at the strain level. Furthermore, the open-source framework of this workflow allows for broad implementation across various instrument platforms as well as integration with alternative modeling and classification algorithms.

Assessment of bitter taste of pharmaceuticals with multisensor system employing 3 way PLS regression

International Nuclear Information System (INIS)

Rudnitskaya, Alisa; Kirsanov, Dmitry; Blinova, Yulia; Legin, Evgeny; Seleznev, Boris; Clapham, David; Ives, Robert S.; Saunders, Kenneth A.; Legin, Andrey

2013-01-01

Highlights: ► Chemically diverse APIs are studied with potentiometric “electronic tongue”. ► Bitter taste of APIs can be predicted with 3wayPLS regression from ET data. ► High correlation of ET assessment with human panel and rat in vivo model. -- Abstract: The application of the potentiometric multisensor system (electronic tongue, ET) for quantification of the bitter taste of structurally diverse active pharmaceutical ingredients (API) is reported. The measurements were performed using a set of bitter substances that had been assessed by a professional human sensory panel and the in vivo rat brief access taste aversion (BATA) model to produce bitterness intensity scores for each substance at different concentrations. The set consisted of eight substances, both inorganic and organic – azelastine, caffeine, chlorhexidine, potassium nitrate, naratriptan, paracetamol, quinine, and sumatriptan. With the aim of enhancing the response of the sensors to the studied APIs, measurements were carried out at different pH levels ranging from 2 to 10, thus promoting ionization of the compounds. This experiment yielded a 3 way data array (samples × sensors × pH levels) from which 3wayPLS regression models were constructed with both human panel and rat model reference data. These models revealed that artificial assessment of bitter taste with ET in the chosen set of API's is possible with average relative errors of 16% in terms of human panel bitterness score and 25% in terms of inhibition values from in vivo rat model data. Furthermore, these 3wayPLS models were applied for prediction of the bitterness in blind test samples of a further set of API's. The results of the prediction were compared with the inhibition values obtained from the in vivo rat model

Assessment of bitter taste of pharmaceuticals with multisensor system employing 3 way PLS regression

Energy Technology Data Exchange (ETDEWEB)

Rudnitskaya, Alisa [CESAM and Chemistry Department, University of Aveiro, Aveiro (Portugal); Kirsanov, Dmitry, E-mail: d.kirsanov@gmail.com [Chemistry Department, St. Petersburg University, St. Petersburg (Russian Federation); Blinova, Yulia [Chemistry Department, St. Petersburg University, St. Petersburg (Russian Federation); Legin, Evgeny [Sensor Systems LLC, St. Petersburg (Russian Federation); Seleznev, Boris [Chemistry Department, St. Petersburg University, St. Petersburg (Russian Federation); Clapham, David; Ives, Robert S.; Saunders, Kenneth A. [GlaxoSmithKline Pharmaceuticals, Gunnels Wood Road, Stevenage (United Kingdom); Legin, Andrey [Chemistry Department, St. Petersburg University, St. Petersburg (Russian Federation)

2013-04-03

Highlights: ► Chemically diverse APIs are studied with potentiometric “electronic tongue”. ► Bitter taste of APIs can be predicted with 3wayPLS regression from ET data. ► High correlation of ET assessment with human panel and rat in vivo model. -- Abstract: The application of the potentiometric multisensor system (electronic tongue, ET) for quantification of the bitter taste of structurally diverse active pharmaceutical ingredients (API) is reported. The measurements were performed using a set of bitter substances that had been assessed by a professional human sensory panel and the in vivo rat brief access taste aversion (BATA) model to produce bitterness intensity scores for each substance at different concentrations. The set consisted of eight substances, both inorganic and organic – azelastine, caffeine, chlorhexidine, potassium nitrate, naratriptan, paracetamol, quinine, and sumatriptan. With the aim of enhancing the response of the sensors to the studied APIs, measurements were carried out at different pH levels ranging from 2 to 10, thus promoting ionization of the compounds. This experiment yielded a 3 way data array (samples × sensors × pH levels) from which 3wayPLS regression models were constructed with both human panel and rat model reference data. These models revealed that artificial assessment of bitter taste with ET in the chosen set of API's is possible with average relative errors of 16% in terms of human panel bitterness score and 25% in terms of inhibition values from in vivo rat model data. Furthermore, these 3wayPLS models were applied for prediction of the bitterness in blind test samples of a further set of API's. The results of the prediction were compared with the inhibition values obtained from the in vivo rat model.

Towards a user-friendly brain-computer interface: initial tests in ALS and PLS patients.

Science.gov (United States)

Bai, Ou; Lin, Peter; Huang, Dandan; Fei, Ding-Yu; Floeter, Mary Kay

2010-08-01

Patients usually require long-term training for effective EEG-based brain-computer interface (BCI) control due to fatigue caused by the demands for focused attention during prolonged BCI operation. We intended to develop a user-friendly BCI requiring minimal training and less mental load. Testing of BCI performance was investigated in three patients with amyotrophic lateral sclerosis (ALS) and three patients with primary lateral sclerosis (PLS), who had no previous BCI experience. All patients performed binary control of cursor movement. One ALS patient and one PLS patient performed four-directional cursor control in a two-dimensional domain under a BCI paradigm associated with human natural motor behavior using motor execution and motor imagery. Subjects practiced for 5-10min and then participated in a multi-session study of either binary control or four-directional control including online BCI game over 1.5-2h in a single visit. Event-related desynchronization and event-related synchronization in the beta band were observed in all patients during the production of voluntary movement either by motor execution or motor imagery. The online binary control of cursor movement was achieved with an average accuracy about 82.1+/-8.2% with motor execution and about 80% with motor imagery, whereas offline accuracy was achieved with 91.4+/-3.4% with motor execution and 83.3+/-8.9% with motor imagery after optimization. In addition, four-directional cursor control was achieved with an accuracy of 50-60% with motor execution and motor imagery. Patients with ALS or PLS may achieve BCI control without extended training, and fatigue might be reduced during operation of a BCI associated with human natural motor behavior. The development of a user-friendly BCI will promote practical BCI applications in paralyzed patients. Copyright 2010 International Federation of Clinical Neurophysiology. All rights reserved.

Dispositional optimism and perceived risk interact to predict intentions to learn genome sequencing results.

Science.gov (United States)

Taber, Jennifer M; Klein, William M P; Ferrer, Rebecca A; Lewis, Katie L; Biesecker, Leslie G; Biesecker, Barbara B

2015-07-01

Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. (c) 2015 APA, all rights reserved.

Data Mining of Chemogenomics Data Using Bi-Modal PLS Methods and Chemical Interpretation for Molecular Design.

Science.gov (United States)

Hasegawa, Kiyoshi; Funatsu, Kimito

2014-12-01

Chemogenomics is a new strategy in drug discovery for interrogating all molecules capable of interacting with all biological targets. Because of the almost infinite number of drug-like organic molecules, bench-based experimental chemogenomics methods are not generally feasible. Several in silico chemogenomics models have therefore been developed for high-throughput screening of large numbers of drug candidate compounds and target proteins. In previous studies, we described two novel bi-modal PLS approaches. These methods provide a significant advantage in that they enable direct connections to be made between biological activities and ligand and protein descriptors. In this special issue, we review these two PLS-based approaches using two different chemogenomics datasets for illustration. We then compare the predictive and interpretive performance of the two methods using the same congeneric data set. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Projects Delay Factors of Saudi Arabia Construction Industry Using PLS-SEM Path Modelling Approach

Directory of Open Access Journals (Sweden)

Abdul Rahman Ismail

2016-01-01

Full Text Available This paper presents the development of PLS-SEM Path Model of delay factors of Saudi Arabia construction industry focussing on Mecca City. The model was developed and assessed using SmartPLS v3.0 software and it consists of 37 factors/manifests in 7 groups/independent variables and one dependent variable which is delay of the construction projects. The model was rigorously assessed at measurement and structural components and the outcomes found that the model has achieved the required threshold values. At structural level of the model, among the seven groups, the client and consultant group has the highest impact on construction delay with path coefficient β-value of 0.452 and the project management and contract administration group is having the least impact to the construction delay with β-value of 0.016. The overall model has moderate explaining power ability with R2 value of 0.197 for Saudi Arabia construction industry representation. This model will able to assist practitioners in Mecca city to pay more attention in risk analysis for potential construction delay.

The Crucial Role of the Pls1 Tetraspanin during Ascospore Germination in Podospora anserina Provides an Example of the Convergent Evolution of Morphogenetic Processes in Fungal Plant Pathogens and Saprobes▿ †

Science.gov (United States)

Lambou, Karine; Malagnac, Fabienne; Barbisan, Crystel; Tharreau, Didier; Lebrun, Marc-Henri; Silar, Philippe

2008-01-01

Pls1 tetraspanins were shown for some pathogenic fungi to be essential for appressorium-mediated penetration into their host plants. We show here that Podospora anserina, a saprobic fungus lacking appressorium, contains PaPls1, a gene orthologous to known PLS1 genes. Inactivation of PaPls1 demonstrates that this gene is specifically required for the germination of ascospores in P. anserina. These ascospores are heavily melanized cells that germinate under inducing conditions through a specific pore. On the contrary, MgPLS1, which fully complements a ΔPaPls1 ascospore germination defect, has no role in the germination of Magnaporthe grisea nonmelanized ascospores but is required for the formation of the penetration peg at the pore of its melanized appressorium. P. anserina mutants with mutation of PaNox2, which encodes the NADPH oxidase of the NOX2 family, display the same ascospore-specific germination defect as the ΔPaPls1 mutant. Both mutant phenotypes are suppressed by the inhibition of melanin biosynthesis, suggesting that they are involved in the same cellular process required for the germination of P. anserina melanized ascospores. The analysis of the distribution of PLS1 and NOX2 genes in fungal genomes shows that they are either both present or both absent. These results indicate that the germination of P. anserina ascospores and the formation of the M. grisea appressorium penetration peg use the same molecular machinery that includes Pls1 and Nox2. This machinery is specifically required for the emergence of polarized hyphae from reinforced structures such as appressoria and ascospores. Its recurrent recruitment during fungal evolution may account for some of the morphogenetic convergence observed in fungi. PMID:18757568

Assessing a moderating effect and the global fit of a PLS model on online trading

Directory of Open Access Journals (Sweden)

Juan J. García-Machado

2017-12-01

Full Text Available This paper proposes a PLS Model for the study of Online Trading. Traditional investing has experienced a revolution due to the rise of e-trading services that enable investors to use Internet conduct secure trading. On the hand, model results show that there is a positive, direct and statistically significant relationship between personal outcome expectations, perceived relative advantage, shared vision and economy-based trust with the quality of knowledge. On the other hand, trading frequency and portfolio performance has also this relationship. After including the investor’s income and financial wealth (IFW as moderating effect, the PLS model was enhanced, and we found that the interaction term is negative and statistically significant, so, higher IFW levels entail a weaker relationship between trading frequency and portfolio performance and vice-versa. Finally, with regard to the goodness of overall model fit measures, they showed that the model is fit for SRMR and dG measures, so it is likely that the model is true.

Deficit in implicit motor sequence learning among children and adolescents with spastic cerebral palsy.

Science.gov (United States)

Gofer-Levi, Moran; Silberg, Tamar; Brezner, Amichai; Vakil, Eli

2013-11-01

Skill learning (SL) is learning as a result of repeated exposure and practice, which encompasses independent explicit (response to instructions) and implicit (response to hidden regularities) processes. Little is known about the effects of developmental disorders, such as Cerebral Palsy (CP), on the ability to acquire new skills. We compared performance of CP and typically developing (TD) children and adolescents in completing the serial reaction time (SRT) task, which is a motor sequence learning task, and examined the impact of various factors on this performance as indicative of the ability to acquire motor skills. While both groups improved in performance, participants with CP were significantly slower than TD controls and did not learn the implicit sequence. Our results indicate that SL in children and adolescents with CP is qualitatively and quantitatively different than that of their peers. Understanding the unique aspects of SL in children and adolescents with CP might help plan appropriate and efficient interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Determination of Cu in Shell of Preserved Egg by LIBS Coupled with PLS].

Science.gov (United States)

Hu, Hui-qin; Xu, Xue-hong; Liu, Mu-hua; Tu, Jian-ping; Huang, Le; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; Yang, Ping

2015-12-01

In this work, the content of copper in the shell of preserved eggs were determined directly by Laser induced breakdown spectroscopy (LIBS), and the characteristics lines of Cu was obtained. The samples of eggshell were pretreated by acid wet digestion, and the real content of Cu was obtained by atomic absorption spectrophotometer (AAS). Due to the test precision and accuracy of LIBS was influenced by a serious of factors, for example, the complex matrix effect of sample, the enviro nment noise, the system noise of the instrument, the stability of laser energy and so on. And the conventional unvariate linear calibration curve between LIBS intensity and content of element of sample, such as by use of Schiebe G-Lomakin equation, can not meet the requirement of quantitative analysis. In account of that, a kind of multivariate calibration method is needed. In this work, the data of LIBS spectra were processed by partial least squares (PLS), the precision and accuracy of PLS model were compared by different smoothing treatment and five pretreatment methods. The result showed that the correlation coefficient and the accuracy of the PLS model were improved, and the root mean square error and the average relative error were reduced effectively by 11 point smoothing with Multiplicative scatter correction (MSC) pretreatment. The results of the study show that, heavy metal Cu in preserved egg shells can be direct detected accurately by laser induced breakdown spectroscopy, and the next step batch tests will been conducted to find out the relationship of heavy metal Cu content in the preserved egg between the eggshell, egg white and egg yolk. And the goal of the contents of heavy metals in the egg white, egg yolk can be knew through determinate the eggshell by the LIBS can be achieved, to provide new method for rapid non-destructive testing technology for quality and satety of agricultural products.

PLS Torino: A way to discover semiconductors in a school lab

International Nuclear Information System (INIS)

Marzolla, F.

2015-01-01

In the wide range of PLS activities, one on semiconductors was realized with high-school 4th- and 5th-year students. After an introduction on semiconductor and electromagnetic radiation concepts, students assembled circuits, observed photoresistor and LED behavior and compared experimental and theoretical results. We especially paid attention to energy conversions and devices applications. An important point of the project is that it can be easily realized in our schools because low-cost devices are used. Moreover, discussing experimental results, it is possible to correct or complete students phenomena interpretation.

Analysis of designed experiments by stabilised PLS Regression and jack-knifing

DEFF Research Database (Denmark)

Martens, Harald; Høy, M.; Westad, F.

2001-01-01

Pragmatical, visually oriented methods for assessing and optimising bi-linear regression models are described, and applied to PLS Regression (PLSR) analysis of multi-response data from controlled experiments. The paper outlines some ways to stabilise the PLSR method to extend its range...... the reliability of the linear and bi-linear model parameter estimates. The paper illustrates how the obtained PLSR "significance" probabilities are similar to those from conventional factorial ANOVA, but the PLSR is shown to give important additional overview plots of the main relevant structures in the multi....... An Introduction, Wiley, Chichester, UK, 2001]....

A Teaching Sequence for Learning the Concept of Chemical Equilibrium in Secondary School Education

Science.gov (United States)

Ghirardi, Marco; Marchetti, Fabio; Pettinari, Claudio; Regis, Alberto; Roletto, Ezio

2014-01-01

A novel didactic sequence is proposed for the teaching of chemical equilibrium. This teaching sequence takes into account the historical and epistemological evolution of the concept, the alternative conceptions and learning difficulties highlighted by teaching science and research in education, and the need to focus on both the students'…

A study for lattice comparison for PLS 2 GeV storage ring

International Nuclear Information System (INIS)

Yoon, M.

1991-01-01

TBA and DBA lattices are compared for 1.5-2.5 GeV synchrotron light source, with particular attention to the PLS 2 GeV electron storage ring currently being developed in Pohang, Korea. For the comparison study, the optimum electron energy was chosen to be 2 GeV and the circumference of the ring is less than 280.56 m, the natural beam emittance no greater than 13 nm. Results from various linear and nonlinear optics comparison studies are presented

Preferences for learning different types of genome sequencing results among young breast cancer patients: Role of psychological and clinical factors.

Science.gov (United States)

Kaphingst, Kimberly A; Ivanovich, Jennifer; Lyons, Sarah; Biesecker, Barbara; Dresser, Rebecca; Elrick, Ashley; Matsen, Cindy; Goodman, Melody

2018-01-29

The growing importance of genome sequencing means that patients will increasingly face decisions regarding what results they would like to learn. The present study examined psychological and clinical factors that might affect these preferences. 1,080 women diagnosed with breast cancer at age 40 or younger completed an online survey. We assessed their interest in learning various types of genome sequencing results: risk of preventable disease or unpreventable disease, cancer treatment response, uncertain meaning, risk to relatives' health, and ancestry/physical traits. Multivariable logistic regression was used to examine whether being "very" interested in each result type was associated with clinical factors: BRCA1/2 mutation status, prior genetic testing, family history of breast cancer, and psychological factors: cancer recurrence worry, genetic risk worry, future orientation, health information orientation, and genome sequencing knowledge. The proportion of respondents who were very interested in learning each type of result ranged from 16% to 77%. In all multivariable models, those who were very interested in learning a result type had significantly higher knowledge about sequencing benefits, greater genetic risks worry, and stronger health information orientation compared to those with less interest (p-values psychological factors. Shared decision-making approaches that increase knowledge about genome sequencing and incorporate patient preferences for health information and learning about genetic risks may help support patients' informed choices about learning different types of sequencing results. © Society of Behavioral Medicine 2018.

Cognitive Control Structures in the Imitation Learning of Spatial Sequences and Rhythms-An fMRI Study.

Science.gov (United States)

Sakreida, Katrin; Higuchi, Satomi; Di Dio, Cinzia; Ziessler, Michael; Turgeon, Martine; Roberts, Neil; Vogt, Stefan

2018-03-01

Imitation learning involves the acquisition of novel motor patterns based on action observation (AO). We used event-related functional magnetic resonance imaging to study the imitation learning of spatial sequences and rhythms during AO, motor imagery (MI), and imitative execution in nonmusicians and musicians. While both tasks engaged the fronto-parietal mirror circuit, the spatial sequence task recruited posterior parietal and dorsal premotor regions more strongly. The rhythm task involved an additional network for auditory working memory. This partial dissociation supports the concept of task-specific mirror mechanisms. Two regions of cognitive control were identified: 1) dorsolateral prefrontal cortex (DLPFC) was found to be more strongly activated during MI of novel spatial sequences, which allowed us to extend the 2-level model of imitation learning by Buccino et al. (2004) to spatial sequences. 2) During imitative execution of both tasks, the posterior medial frontal cortex was robustly activated, along with the DLPFC, which suggests that both regions are involved in the cognitive control of imitation learning. The musicians' selective behavioral advantage for rhythm imitation was reflected cortically in enhanced sensory-motor processing during AO and by the absence of practice-related activation differences in DLPFC during rhythm execution. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Motor Sequence Learning Performance in Parkinson's Disease Patients Depends on the Stage of Disease

Science.gov (United States)

Stephan, Marianne A.; Meier, Beat; Zaugg, Sabine Weber; Kaelin-Lang, Alain

2011-01-01

It is still unclear, whether patients with Parkinson's disease (PD) are impaired in the incidental learning of different motor sequences in short succession, although such a deficit might greatly impact their daily life. The aim of this study was thus to clarify the relation between disease parameters of PD and incidental motor learning of two…

Middle school students' learning of mechanics concepts through engagement in different sequences of physical and virtual experiments

Science.gov (United States)

Sullivan, Sarah; Gnesdilow, Dana; Puntambekar, Sadhana; Kim, Jee-Seon

2017-08-01

Physical and virtual experimentation are thought to have different affordances for supporting students' learning. Research investigating the use of physical and virtual experiments to support students' learning has identified a variety of, sometimes conflicting, outcomes. Unanswered questions remain about how physical and virtual experiments may impact students' learning and for which contexts and content areas they may be most effective. Using a quasi-experimental design, we examined eighth grade students' (N = 100) learning of physics concepts related to pulleys depending on the sequence of physical and virtual labs they engaged in. Five classes of students were assigned to either the: physical first condition (PF) (n = 55), where students performed a physical pulley experiment and then performed the same experiment virtually, or virtual first condition (VF) (n = 45), with the opposite sequence. Repeated measures ANOVA's were conducted to examine how physical and virtual labs impacted students' learning of specific physics concepts. While we did not find clear-cut support that one sequence was better, we did find evidence that participating in virtual experiments may be more beneficial for learning certain physics concepts, such as work and mechanical advantage. Our findings support the idea that if time or physical materials are limited, using virtual experiments may help students understand work and mechanical advantage.

Does Sleep Facilitate the Consolidation of Allocentric or Egocentric Representations of Implicitly Learned Visual-Motor Sequence Learning?

Science.gov (United States)

Viczko, Jeremy; Sergeeva, Valya; Ray, Laura B.; Owen, Adrian M.; Fogel, Stuart M.

2018-01-01

Sleep facilitates the consolidation (i.e., enhancement) of simple, explicit (i.e., conscious) motor sequence learning (MSL). MSL can be dissociated into egocentric (i.e., motor) or allocentric (i.e., spatial) frames of reference. The consolidation of the allocentric memory representation is sleep-dependent, whereas the egocentric consolidation…

PLS-Prediction and Confirmation of Hydrojuglone Glucoside as the Antitrypanosomal Constituent of Juglans Spp.

Directory of Open Access Journals (Sweden)

Therese Ellendorff

2015-05-01

Full Text Available Naphthoquinones (NQs occur naturally in a large variety of plants. Several NQs are highly active against protozoans, amongst them the causative pathogens of neglected tropical diseases such as human African trypanosomiasis (sleeping sickness, Chagas disease and leishmaniasis. Prominent NQ-producing plants can be found among Juglans spp. (Juglandaceae with juglone derivatives as known constituents. In this study, 36 highly variable extracts were prepared from different plant parts of J. regia, J. cinerea and J. nigra. For all extracts, antiprotozoal activity was determined against the protozoans Trypanosoma cruzi, T. brucei rhodesiense and Leishmania donovani. In addition, an LC-MS fingerprint was recorded for each extract. With each extract’s fingerprint and the data on in vitro growth inhibitory activity against T. brucei rhodesiense a Partial Least Squares (PLS regression model was calculated in order to obtain an indication of compounds responsible for the differences in bioactivity between the 36 extracts. By means of PLS, hydrojuglone glucoside was predicted as an active compound against T. brucei and consequently isolated and tested in vitro. In fact, the pure compound showed activity against T. brucei at a significantly lower cytotoxicity towards mammalian cells than established antiprotozoal NQs such as lapachol.

[Transposition errors during learning to reproduce a sequence by the right- and the left-hand movements: simulation of positional and movement coding].

Science.gov (United States)

Liakhovetskiĭ, V A; Bobrova, E V; Skopin, G N

2012-01-01

Transposition errors during the reproduction of a hand movement sequence make it possible to receive important information on the internal representation of this sequence in the motor working memory. Analysis of such errors showed that learning to reproduce sequences of the left-hand movements improves the system of positional coding (coding ofpositions), while learning of the right-hand movements improves the system of vector coding (coding of movements). Learning of the right-hand movements after the left-hand performance involved the system of positional coding "imposed" by the left hand. Learning of the left-hand movements after the right-hand performance activated the system of vector coding. Transposition errors during learning to reproduce movement sequences can be explained by neural network using either vector coding or both vector and positional coding.

Examining the Effectiveness of a Semi-Self-Paced Flipped Learning Format in a College General Chemistry Sequence

Science.gov (United States)

Hibbard, Lisa; Sung, Shannon; Wells, Breche´

2016-01-01

Flipped learning has come to the forefront in education. It maximizes learning by moving content delivery online, where learning can be self-paced, allowing for class time to focus on student-centered active learning. This five-year cross-sectional study assessed student performance in a college general chemistry for majors sequence taught by a…

Insertion of Contemporary and Modern Physics in classroom: a teaching learning sequence on radioactivity

Directory of Open Access Journals (Sweden)

Carlos Alexandre dos Santos Batista

2017-12-01

Full Text Available After more than two decades of justifications on the insertion of Modern and Contemporary Physics in the high school Education, the current challenge regards to how this content can be inserted in the classroom in an interesting and innovative way. Recent research reveals that despite a significant accumulation of recent academic research, whose purpose is to assist teachers pedagogically, few are grounded and proposed theoretically seeking to investigate how this integration happens. In this sense, we present a teaching-learning sequence on the topic of radioactivity, forged in the theoretical and methodological assumptions of Design-Based Research and a Teaching-Learning Sequence that, when implemented in public schools in the south of Bahia, produced the relevant knowledge to be shared with the community on teaching physics. Forged in our assumptions, the proposal allows teachers and researchers to understand questions about how, when and why, in fact, the inclusion of Modern and Contemporary Physics can occur in a non-traditional way. Therefore, the importance of this proposal is revealed to the high school of physics as it translates its ability to transform the theoretical demands on the curriculum and methodological innovation in the practical interventions in the classroom. We add that the availability of the necessary sources to find lesson plans, quizzes, texts, videos of teaching-learning sequence, shows the contribution of this work for teachers and researchers, in particular, to improve the scientific learning of students in the Basic Education.

Sequencing learning experiences to engage different level learners in the workplace: An interview study with excellent clinical teachers.

Science.gov (United States)

Chen, H Carrie; O'Sullivan, Patricia; Teherani, Arianne; Fogh, Shannon; Kobashi, Brent; ten Cate, Olle

2015-01-01

Learning in the clinical workplace can appear to rely on opportunistic teaching. The cognitive apprenticeship model describes assigning tasks based on learner rather than just workplace needs. This study aimed to determine how excellent clinical teachers select clinical learning experiences to support the workplace participation and development of different level learners. Using a constructivist grounded theory approach, we conducted semi-structured interviews with medical school faculty identified as excellent clinical teachers teaching multiple levels of learners. We explored their approach to teach different level learners and their perceived role in promoting learner development. We performed thematic analysis of the interview transcripts using open and axial coding. We interviewed 19 clinical teachers and identified three themes related to their teaching approach: sequencing of learning experiences, selection of learning activities and teacher responsibilities. All teachers used sequencing as a teaching strategy by varying content, complexity and expectations by learner level. The teachers initially selected learning activities based on learner level and adjusted for individual competencies over time. They identified teacher responsibilities for learner education and patient safety, and used sequencing to promote both. Excellent clinical teachers described strategies for matching available learning opportunities to learners' developmental levels to safely engage learners and improve learning in the clinical workplace.

Learning Bounds of ERM Principle for Sequences of Time-Dependent Samples

Directory of Open Access Journals (Sweden)

Mingchen Yao

2015-01-01

Full Text Available Many generalization results in learning theory are established under the assumption that samples are independent and identically distributed (i.i.d.. However, numerous learning tasks in practical applications involve the time-dependent data. In this paper, we propose a theoretical framework to analyze the generalization performance of the empirical risk minimization (ERM principle for sequences of time-dependent samples (TDS. In particular, we first present the generalization bound of ERM principle for TDS. By introducing some auxiliary quantities, we also give a further analysis of the generalization properties and the asymptotical behaviors of ERM principle for TDS.

Detecting false positive sequence homology: a machine learning approach.

Science.gov (United States)

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Bybee, Seth M

2016-02-24

Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. There are many existing heuristic tools, most commonly based on bidirectional BLAST searches that are used to identify homologous genes and combine them into two fundamentally distinct classes: orthologs and paralogs. Due to only using heuristic filtering based on significance score cutoffs and having no cluster post-processing tools available, these methods can often produce multiple clusters constituting unrelated (non-homologous) sequences. Therefore sequencing data extracted from incomplete genome/transcriptome assemblies originated from low coverage sequencing or produced by de novo processes without a reference genome are susceptible to high false positive rates of homology detection. In this paper we develop biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes. We demonstrate that our machine learning method trained on both known homology clusters obtained from OrthoDB and randomly generated sequence alignments (non-homologs), successfully determines apparent false positives inferred by heuristic algorithms especially among proteomes recovered from low-coverage RNA-seq data. Almost ~42 % and ~25 % of predicted putative homologies by InParanoid and HaMStR respectively were classified as false positives on experimental data set. Our process increases the quality of output from other clustering algorithms by providing a novel post-processing method that is both fast and efficient at removing low quality clusters of putative homologous genes recovered by heuristic-based approaches.

Realtime control system for microprobe beamline at PLS

Energy Technology Data Exchange (ETDEWEB)

Yoon, J.C.; Lee, J.W.; Kim, K.H.; Ko, I.S. [Pohang Accelerator Laboratory, POSTECH, Pohang (Korea)

1998-11-01

The microprobe beamline of the Pohang Light Source (PLS) consists of main and second slits, a microprobe system, two ion chambers, a video-microscope, and a Si(Li) detector. These machine components must be controlled remodely through the computer system to make user's experiments precise and speedy. A real-time computer control system was developed to control and monitor these components. A VMEbus computer with an OS-9 real-time operating system was used for the low-level data acquisition and control. VME I/O modules were used for the step motor control and the scalar control. The software has a modular structure for the maximum performance and the easy maintenance. We developed the database, the I/O driver, and the control software. We used PC/Windows 95 for the data logging and the operator interface. Visual C{sup ++} was used for the graphical user interface programming. RS232C was used for the communication between the VME and the PC. (author)

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

Science.gov (United States)

Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping

2017-12-01

Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

Learning sequences on the subject of energy. Secondary school stage 1. Lernsequenzen zum Thema Energie. Sekundarstufe 1

Energy Technology Data Exchange (ETDEWEB)

1986-01-01

The ten learning sequences follow on one another. Each picks on a particular aspect from the energy field. The subject notebooks are self-contained and can therefore be used independently. Apart from actual data and energy-related information, the information for the teacher contains: - proposals for teaching - suggestions for further activities - sample solutions for the pupil's sheets - references to the literature and media. The worksheets for the pupils are different; it should be possible to use the learning sequences in all classes of secondary school stage 1. The multicoloured foils for projectors should motivate, on the one hand, and on the other hand should help to check the results of learning.

Definition and Analysis of a System for the Automated Comparison of Curriculum Sequencing Algorithms in Adaptive Distance Learning

Science.gov (United States)

Limongelli, Carla; Sciarrone, Filippo; Temperini, Marco; Vaste, Giulia

2011-01-01

LS-Lab provides automatic support to comparison/evaluation of the Learning Object Sequences produced by different Curriculum Sequencing Algorithms. Through this framework a teacher can verify the correspondence between the behaviour of different sequencing algorithms and her pedagogical preferences. In fact the teacher can compare algorithms…

Genetic algorithm-based wavelength selection in multicomponent spectrophotometric determination by PLS: Application on sulfamethoxazole and trimethoprim mixture in bovine milk

Directory of Open Access Journals (Sweden)

Givianrad Hadi Mohammad

2013-01-01

Full Text Available The simultaneous determination of sulfamethoxazole (SMX and trimethoprim (TMP mixtures in bovine milk by spectrophotometric method is a difficult problem in analytical chemistry, due to spectral interferences. By means of multivariate calibration methods, such as partial least square (PLS regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Genetic algorithm (GA is a suitable method for selecting wavelengths for PLS calibration of mixtures with almost identical spectra without loss of prediction capacity using the spectrophotometric method. In this study, the calibration model based on absorption spectra in the 200-400 nm range for 25 different mixtures of SMX and TMP Calibration matrices were formed form samples containing 0.25-20 and 0.3-21 μg mL-1 for SMX and TMP, at pH=10, respectively. The root mean squared error of deviation (RMSED for SMX and TMP with PLS and genetic algorithm partial least square (GAPLS were 0.242, 0.066 μgmL-1 and 0.074, 0.027 μg mL-1, respectively. This procedure was allowed the simultaneous determination of SMX and TMP in synthetic and real samples and good reliability of the determination was proved.

Mapping membrane activity in undiscovered peptide sequence space using machine learning.

Science.gov (United States)

Lee, Ernest Y; Fulan, Benjamin M; Wong, Gerard C L; Ferguson, Andrew L

2016-11-29

There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature of their functional commonality and sequence homology. SVM is used to search the undiscovered peptide sequence space and identify Pareto-optimal candidates that simultaneously maximize the distance σ from the SVM hyperplane (thus maximize its "antimicrobialness") and its ⍺-helicity, but minimize mutational distance to known AMPs. By calibrating SVM machine learning results with killing assays and small-angle X-ray scattering (SAXS), we find that the SVM metric σ correlates not with a peptide's minimum inhibitory concentration (MIC), but rather its ability to generate negative Gaussian membrane curvature. This surprising result provides a topological basis for membrane activity common to AMPs. Moreover, we highlight an important distinction between the maximal recognizability of a sequence to a trained AMP classifier (its ability to generate membrane curvature) and its maximal antimicrobial efficacy. As mutational distances are increased from known AMPs, we find AMP-like sequences that are increasingly difficult for nature to discover via simple mutation. Using the sequence map as a discovery tool, we find a unexpectedly diverse taxonomy of sequences that are just as membrane-active as known AMPs, but with a broad range of primary functions distinct from AMP functions, including endogenous neuropeptides, viral fusion proteins, topogenic peptides, and amyloids. The SVM classifier is useful as a general detector of membrane activity in peptide sequences.

An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.

Science.gov (United States)

Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin

2014-04-30

Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.

Application of NIRS coupled with PLS regression as a rapid, non-destructive alternative method for quantification of KBA in Boswellia sacra

Science.gov (United States)

Al-Harrasi, Ahmed; Rehman, Najeeb Ur; Mabood, Fazal; Albroumi, Muhammaed; Ali, Liaqat; Hussain, Javid; Hussain, Hidayat; Csuk, René; Khan, Abdul Latif; Alam, Tanveer; Alameri, Saif

2017-09-01

In the present study, for the first time, NIR spectroscopy coupled with PLS regression as a rapid and alternative method was developed to quantify the amount of Keto-β-Boswellic Acid (KBA) in different plant parts of Boswellia sacra and the resin exudates of the trunk. NIR spectroscopy was used for the measurement of KBA standards and B. sacra samples in absorption mode in the wavelength range from 700-2500 nm. PLS regression model was built from the obtained spectral data using 70% of KBA standards (training set) in the range from 0.1 ppm to 100 ppm. The PLS regression model obtained was having R-square value of 98% with 0.99 corelationship value and having good prediction with RMSEP value 3.2 and correlation of 0.99. It was then used to quantify the amount of KBA in the samples of B. sacra. The results indicated that the MeOH extract of resin has the highest concentration of KBA (0.6%) followed by essential oil (0.1%). However, no KBA was found in the aqueous extract. The MeOH extract of the resin was subjected to column chromatography to get various sub-fractions at different polarity of organic solvents. The sub-fraction at 4% MeOH/CHCl3 (4.1% of KBA) was found to contain the highest percentage of KBA followed by another sub-fraction at 2% MeOH/CHCl3 (2.2% of KBA). The present results also indicated that KBA is only present in the gum-resin of the trunk and not in all parts of the plant. These results were further confirmed through HPLC analysis and therefore it is concluded that NIRS coupled with PLS regression is a rapid and alternate method for quantification of KBA in Boswellia sacra. It is non-destructive, rapid, sensitive and uses simple methods of sample preparation.

Initial uncertainty impacts statistical learning in sound sequence processing.

Science.gov (United States)

Todd, Juanita; Provost, Alexander; Whitson, Lisa; Mullens, Daniel

2016-11-01

This paper features two studies confirming a lasting impact of first learning on how subsequent experience is weighted in early relevance-filtering processes. In both studies participants were exposed to sequences of sound that contained a regular pattern on two different timescales. Regular patterning in sound is readily detected by the auditory system and used to form "prediction models" that define the most likely properties of sound to be encountered in a given context. The presence and strength of these prediction models is inferred from changes in automatically elicited components of auditory evoked potentials. Both studies employed sound sequences that contained both a local and longer-term pattern. The local pattern was defined by a regular repeating pure tone occasionally interrupted by a rare deviating tone (p=0.125) that was physically different (a 30msvs. 60ms duration difference in one condition and a 1000Hz vs. 1500Hz frequency difference in the other). The longer-term pattern was defined by the rate at which the two tones alternated probabilities (i.e., the tone that was first rare became common and the tone that was first common became rare). There was no task related to the tones and participants were asked to ignore them while focussing attention on a movie with subtitles. Auditory-evoked potentials revealed long lasting modulatory influences based on whether the tone was initially encountered as rare and unpredictable or common and predictable. The results are interpreted as evidence that probability (or indeed predictability) assigns a differential information-value to the two tones that in turn affects the extent to which prediction models are updated and imposed. These effects are exposed for both common and rare occurrences of the tones. The studies contribute to a body of work that reveals that probabilistic information is not faithfully represented in these early evoked potentials and instead exposes that predictability (or conversely

Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

Science.gov (United States)

He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-03-01

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Prediction-oriented modeling in business research by means of PLS path modeling : Introduction to a JBR special section

NARCIS (Netherlands)

Cepeda Carrion, Gabriel; Henseler, Jörg; Ringle, Christian M.; Roldan, Jose Luis

2016-01-01

Under the main theme “prediction-oriented modeling in business research by means of partial least squares path modeling” (PLS), the special issue presents 17 papers. Most contributions include content from presentations at the 2nd International Symposium on Partial Least Squares Path Modeling: The

Dynamic sensorimotor planning during long-term sequence learning: the role of variability, response chunking and planning errors.

Science.gov (United States)

Verstynen, Timothy; Phillips, Jeff; Braun, Emily; Workman, Brett; Schunn, Christian; Schneider, Walter

2012-01-01

Many everyday skills are learned by binding otherwise independent actions into a unified sequence of responses across days or weeks of practice. Here we looked at how the dynamics of action planning and response binding change across such long timescales. Subjects (N = 23) were trained on a bimanual version of the serial reaction time task (32-item sequence) for two weeks (10 days total). Response times and accuracy both showed improvement with time, but appeared to be learned at different rates. Changes in response speed across training were associated with dynamic changes in response time variability, with faster learners expanding their variability during the early training days and then contracting response variability late in training. Using a novel measure of response chunking, we found that individual responses became temporally correlated across trials and asymptoted to set sizes of approximately 7 bound responses at the end of the first week of training. Finally, we used a state-space model of the response planning process to look at how predictive (i.e., response anticipation) and error-corrective (i.e., post-error slowing) processes correlated with learning rates for speed, accuracy and chunking. This analysis yielded non-monotonic association patterns between the state-space model parameters and learning rates, suggesting that different parts of the response planning process are relevant at different stages of long-term learning. These findings highlight the dynamic modulation of response speed, variability, accuracy and chunking as multiple movements become bound together into a larger set of responses during sequence learning.

Student learning and understanding of sequence stratigraphic principles

Science.gov (United States)

Herrera, Juan Sebastian

Research in geoscience education addressing students' conceptions of geological subjects has concentrated in topics such as geological time, plate tectonics, and problem solving in the field, mostly in K-12 and entry level college scenarios. Science education research addressing learning of sedimentary systems in advance undergraduates is rather limited. Therefore, this dissertation contributed to filling that research gap and explored students' narratives when explaining geological processes associated with the interaction between sediment deposition and sea level fluctuations. The purpose of the present study was to identify the common conceptions and alternative conceptions held by students when learning the basics of the sub discipline known as sequence stratigraphy - which concepts students were familiar and easily identified, and which ones they had more difficulty with. In addition, we mapped the cognitive models that underlie those conceptions by analyzing students' gestures and conceptual metaphors used in their explanations. This research also investigated the interaction between geoscientific visual displays and student gesturing in a specific learning context. In this research, an in-depth assessment of 27 students' ideas of the basic principles of sequence stratigraphy was completed. Participants were enrolled in advanced undergraduate stratigraphy courses at three research-intensive universities in Midwest U.S. Data collection methods included semi-structured interviews, spatial visualization tests, and lab assignments. Results indicated that students poorly integrated temporal and spatial scales in their sequence stratigraphic models, and that many alternative conceptions were more deeply rooted than others, especially those related to eustasy and base level. In order to better understand the depth of these conceptions, we aligned the analysis of gesture with the theory of conceptual metaphor to recognize the use of mental models known as image

Machine Learned Replacement of N-Labels for Basecalled Sequences in DNA Barcoding.

Science.gov (United States)

Ma, Eddie Y T; Ratnasingham, Sujeevan; Kremer, Stefan C

2018-01-01

This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to replace with basecalls (A,C,G,T). An N-label correction is defined given an additional read of the same sequence, and a human finished sequence. Corrections are added to the dataset when an alignment determines the additional read and human agree on the identity of the N-label. KB must also rate the replacement with quality value of in the additional read. Corrections are only available during system training. Developing the system, nearly 850,000 N-labels are obtained from Barcode of Life Datasystems, the premier database of genetic markers called DNA Barcodes. Increasing the number of correct bases improves reference sequence reliability, increases sequence identification accuracy, and assures analysis correctness. Keeping with barcoding standards, our system maintains an error rate of percent. Our system only applies corrections when it estimates low rate of error. Tested on this data, our automation selects and recovers: 79 percent of N-labels from COI (animal barcode); 80 percent from matK and rbcL (plant barcodes); and 58 percent from non-protein-coding sequences (across eukaryotes).

Constrained paths based on the Farey sequence in learning to juggle.

Science.gov (United States)

Yamamoto, Kota; Tsutsui, Seijiro; Yamamoto, Yuji

2015-12-01

In this article we report the results of a study conducted to investigate the learning dynamics of three-ball juggling from the perspective of frequency locking. Based on the Farey sequence, we predicted that four stable coordination patterns, corresponding to dwell ratios of 0.83, 0.75, 0.67, and 0.50, would appear in the learning process. We examined the learning process in terms of task performance, taking into account individual differences in the amount of learning. We observed that the participants acquired individual-specific coordination patterns in a relatively early stage of learning, and that those coordination patterns were preserved in subsequent learning, even though performance in terms of number of successful consecutive throws increased substantially. This increase appeared to be related to a reduction in spatial variability of the juggling movements. Finally, the observed coordination patterns were in agreement with the predicted patterns, with the proviso that the pattern corresponding to a dwell ratio of 0.50 was not realized and only a hint of evidence was found for the dwell ratio of 0.67. This implies that the dwell ratios of 0.83 and 0.75 in particular exhibited a stable coordination structure due to strong frequency locking between the temporal variables of juggling. Copyright © 2015 Elsevier B.V. All rights reserved.

More Than Words: The Role of Multiword Sequences in Language Learning and Use.

Science.gov (United States)

Christiansen, Morten H; Arnon, Inbal

2017-07-01

The ability to convey our thoughts using an infinite number of linguistic expressions is one of the hallmarks of human language. Understanding the nature of the psychological mechanisms and representations that give rise to this unique productivity is a fundamental goal for the cognitive sciences. A long-standing hypothesis is that single words and rules form the basic building blocks of linguistic productivity, with multiword sequences being treated as units only in peripheral cases such as idioms. The new millennium, however, has seen a shift toward construing multiword linguistic units not as linguistic rarities, but as important building blocks for language acquisition and processing. This shift-which originated within theoretical approaches that emphasize language learning and use-has far-reaching implications for theories of language representation, processing, and acquisition. Incorporating multiword units as integral building blocks blurs the distinction between grammar and lexicon; calls for models of production and comprehension that can accommodate and give rise to the effect of multiword information on processing; and highlights the importance of such units to learning. In this special topic, we bring together cutting-edge work on multiword sequences in theoretical linguistics, first-language acquisition, psycholinguistics, computational modeling, and second-language learning to present a comprehensive overview of the prominence and importance of such units in language, their possible role in explaining differences between first- and second-language learning, and the challenges the combined findings pose for theories of language. Copyright © 2017 Cognitive Science Society, Inc.

Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

KAUST Repository

Wong, Ka Chun

2011-02-05

Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.

Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

KAUST Repository

Wong, Ka Chun; Peng, Chengbin; Wong, Manhon; Leung, Kwongsak

2011-01-01

Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.

Sequence Learning with Stochastic Feedback in a Cross-Cultural Sample of Boys in the Autistic Spectrum

Science.gov (United States)

Hentschel, Maren; Lange-Kuttner, Christiane; Averbeck, Bruno B.

2016-01-01

The study investigated sequence learning from stochastic feedback in boys with Autistic Spectrum Disorder (ASD) and typically developed (TD) boys. We asked boys with ASD from Nigeria and the UK as well as age- and gender-matched controls (also males only) to deduce a sequence of four left and right button presses, LLRR, RRLL, LRLR, RLRL, LRRL and…

Data analysis of photon beam position at PLS-II

Energy Technology Data Exchange (ETDEWEB)

Ko, J.; Shin, S., E-mail: tlssh@postech.ac.kr; Huang, Jung-Yun; Kim, D.; Kim, C.; Kim, Ilyou; Lee, T.-Y.; Park, C.-D.; Kim, K. R. [Pohang Accelerator Laboratory, Pohang, Kyungbuk 790-834 (Korea, Republic of); Cho, Moohyun [Department of Physics, POSTECH, Pohang, Kyungbuk 790-834 (Korea, Republic of)

2016-07-27

In the third generation light source, photon beam position stability is critical issue on user experiment. Generally photon beam position monitors have been developed for the detection of the real photon beam position and the position is controlled by feedback system in order to keep the reference photon beam position. In the PLS-II, photon beam position stability for front end of particular beam line, in which photon beam position monitor is installed, has been obtained less than rms 1μm for user service period. Nevertheless, detail analysis for photon beam position data in order to demonstrate the performance of photon beam position monitor is necessary, since it can be suffers from various unknown noises. (for instance, a back ground contamination due to upstream or downstream dipole radiation, undulator gap dependence, etc.) In this paper, we will describe the start to end study for photon beam position stability and the Singular Value Decomposition (SVD) analysis to demonstrate the reliability on photon beam position data.

45 CFR 303.15 - Agreements to use the Federal Parent Locator Service (PLS) in parental kidnapping and child...

Science.gov (United States)

2010-10-01

... Service (PLS) in parental kidnapping and child custody or visitation cases. 303.15 Section 303.15 Public... parental kidnapping and child custody or visitation cases. (a) Definitions. The following definitions apply... responsibilities require access in connection with child custody and parental kidnapping cases; (ii) Store the...

Primary motor and premotor cortex in implicit sequence learning--evidence for competition between implicit and explicit human motor memory systems.

Science.gov (United States)

Kantak, Shailesh S; Mummidisetty, Chaithanya K; Stinear, James W

2012-09-01

Implicit and explicit memory systems for motor skills compete with each other during and after motor practice. Primary motor cortex (M1) is known to be engaged during implicit motor learning, while dorsal premotor cortex (PMd) is critical for explicit learning. To elucidate the neural substrates underlying the interaction between implicit and explicit memory systems, adults underwent a randomized crossover experiment of anodal transcranial direct current stimulation (AtDCS) applied over M1, PMd or sham stimulation during implicit motor sequence (serial reaction time task, SRTT) practice. We hypothesized that M1-AtDCS during practice will enhance online performance and offline learning of the implicit motor sequence. In contrast, we also hypothesized that PMd-AtDCS will attenuate performance and retention of the implicit motor sequence. Implicit sequence performance was assessed at baseline, at the end of acquisition (EoA), and 24 h after practice (retention test, RET). M1-AtDCS during practice significantly improved practice performance and supported offline stabilization compared with Sham tDCS. Performance change from EoA to RET revealed that PMd-AtDCS during practice attenuated offline stabilization compared with M1-AtDCS and sham stimulation. The results support the role of M1 in implementing online performance gains and offline stabilization for implicit motor sequence learning. In contrast, enhancing the activity within explicit motor memory network nodes such as the PMd during practice may be detrimental to offline stabilization of the learned implicit motor sequence. These results support the notion of competition between implicit and explicit motor memory systems and identify underlying neural substrates that are engaged in this competition. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Rapid classification of pharmaceutical ingredients with Raman spectroscopy using compressive detection strategy with PLS-DA multivariate filters.

Science.gov (United States)

Cebeci Maltaş, Derya; Kwok, Kaho; Wang, Ping; Taylor, Lynne S; Ben-Amotz, Dor

2013-06-01

Identifying pharmaceutical ingredients is a routine procedure required during industrial manufacturing. Here we show that a recently developed Raman compressive detection strategy can be employed to classify various widely used pharmaceutical materials using a hybrid supervised/unsupervised strategy in which only two ingredients are used for training and yet six other ingredients can also be distinguished. More specifically, our liquid crystal spatial light modulator (LC-SLM) based compressive detection instrument is trained using only the active ingredient, tadalafil, and the excipient, lactose, but is tested using these and various other excipients; microcrystalline cellulose, magnesium stearate, titanium (IV) oxide, talc, sodium lauryl sulfate and hydroxypropyl cellulose. Partial least squares discriminant analysis (PLS-DA) is used to generate the compressive detection filters necessary for fast chemical classification. Although the filters used in this study are trained on only lactose and tadalafil, we show that all the pharmaceutical ingredients mentioned above can be differentiated and classified using PLS-DA compressive detection filters with an accumulation time of 10ms per filter. Copyright © 2013 Elsevier B.V. All rights reserved.

Improving the robustness of a partial least squares (PLS) model based on pure component selectivity analysis and range optimization: Case study for the analysis of an etching solution containing hydrogen peroxide

Energy Technology Data Exchange (ETDEWEB)

Lee, Youngbok [Department of Chemistry, College of Natural Sciences, Hanyang University Haengdang-Dong, Seoul 133-791 (Korea, Republic of); Chung, Hoeil [Department of Chemistry, College of Natural Sciences, Hanyang University Haengdang-Dong, Seoul 133-791 (Korea, Republic of)]. E-mail: hoeil@hanyang.ac.kr; Arnold, Mark A. [Optical Science and Technology Center and Department of Chemistry, University of Iowa, Iowa City, IA 52242 (United States)

2006-07-14

Pure component selectivity analysis (PCSA) was successfully utilized to enhance the robustness of a partial least squares (PLS) model by examining the selectivity of a given component to other components. The samples used in this study were composed of NH{sub 4}OH, H{sub 2}O{sub 2} and H{sub 2}O, a popular etchant solution in the electronic industry. Corresponding near-infrared (NIR) spectra (9000-7500 cm{sup -1}) were used to build PLS models. The selective determination of H{sub 2}O{sub 2} without influences from NH{sub 4}OH and H{sub 2}O was a key issue since its molecular structure is similar to that of H{sub 2}O and NH{sub 4}OH also has a hydroxyl functional group. The best spectral ranges for the determination of NH{sub 4}OH and H{sub 2}O{sub 2} were found with the use of moving window PLS (MW-PLS) and corresponding selectivity was examined by pure component selectivity analysis. The PLS calibration for NH{sub 4}OH was free from interferences from the other components due to the presence of its unique NH absorption bands. Since the spectral variation from H{sub 2}O{sub 2} was broadly overlapping and much less distinct than that from NH{sub 4}OH, the selectivity and prediction performance for the H{sub 2}O{sub 2} calibration were sensitively varied depending on the spectral ranges and number of factors used. PCSA, based on the comparison between regression vectors from PLS and the net analyte signal (NAS), was an effective method to prevent over-fitting of the H{sub 2}O{sub 2} calibration. A robust H{sub 2}O{sub 2} calibration model with minimal interferences from other components was developed. PCSA should be included as a standard method in PLS calibrations where prediction error only is the usual measure of performance.

Robust Ultraviolet-Visible (UV-Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine.

Science.gov (United States)

Aleixandre-Tudo, José Luis; Nieuwoudt, Helené; Aleixandre, José Luis; Du Toit, Wessel J

2015-02-04

The validation of ultraviolet-visible (UV-vis) spectroscopy combined with partial least-squares (PLS) regression to quantify red wine tannins is reported. The methylcellulose precipitable (MCP) tannin assay and the bovine serum albumin (BSA) tannin assay were used as reference methods. To take the high variability of wine tannins into account when the calibration models were built, a diverse data set was collected from samples of South African red wines that consisted of 18 different cultivars, from regions spanning the wine grape-growing areas of South Africa with their various sites, climates, and soils, ranging in vintage from 2000 to 2012. A total of 240 wine samples were analyzed, and these were divided into a calibration set (n = 120) and a validation set (n = 120) to evaluate the predictive ability of the models. To test the robustness of the PLS calibration models, the predictive ability of the classifying variables cultivar, vintage year, and experimental versus commercial wines was also tested. In general, the statistics obtained when BSA was used as a reference method were slightly better than those obtained with MCP. Despite this, the MCP tannin assay should also be considered as a valid reference method for developing PLS calibrations. The best calibration statistics for the prediction of new samples were coefficient of correlation (R 2 val) = 0.89, root mean standard error of prediction (RMSEP) = 0.16, and residual predictive deviation (RPD) = 3.49 for MCP and R 2 val = 0.93, RMSEP = 0.08, and RPD = 4.07 for BSA, when only the UV region (260-310 nm) was selected, which also led to a faster analysis time. In addition, a difference in the results obtained when the predictive ability of the classifying variables vintage, cultivar, or commercial versus experimental wines was studied suggests that tannin composition is highly affected by many factors. This study also discusses the correlations in tannin values between the methylcellulose and protein

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

Science.gov (United States)

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.

Assessing the impacts of human activities and climate variations on grassland productivity by partial least squares structural equation modeling (PLS-SEM)

Institute of Scientific and Technical Information of China (English)

SHA Zongyao; XIE Yichun; TAN Xicheng; BAI Yongfei; LI Jonathan; LIU Xuefeng

2017-01-01

The cause-effect associations between geographical phenomena are an important focus in ecological research.Recent studies in structural equation modeling (SEM) demonstrated the potential for analyzing such associations.We applied the variance-based partial least squares SEM (PLS-SEM) and geographically-weighted regression (GWR) modeling to assess the human-climate impact on grassland productivity represented by above-ground biomass (AGB).The human and climate factors and their interaction were taken to explain the AGB variance by a PLS-SEM developed for the grassland ecosystem in Inner Mongolia,China.Results indicated that 65.5％ of the AGB variance could be explained by the human and climate factors and their interaction.The case study showed that the human and climate factors imposed a significant and negative impact on the AGB and that their interaction alleviated to some extent the threat from the intensified human-climate pressure.The alleviation may be attributable to vegetation adaptation to high human-climate stresses,to human adaptation to climate conditions or/and to recent vegetation restoration programs in the highly degraded areas.Furthermore,the AGB response to the human and climate factors modeled by GWR exhibited significant spatial variations.This study demonstrated that the combination of PLS-SEM and GWR model is feasible to investigate the cause-effect relation in socio-ecological systems.

A Teaching-Learning Sequence of Colour Informed by History and Philosophy of Science

Science.gov (United States)

Maurício, Paulo; Valente, Bianor; Chagas, Isabel

2017-01-01

In this work, we present a teaching-learning sequence on colour intended to a pre-service elementary teacher programme informed by History and Philosophy of Science. Working in a socio-constructivist framework, we made an excursion on the history of colour. Our excursion through history of colour, as well as the reported misconception on colour…

Rehearsal strategies during motor-sequence learning in old age : Execution vs motor imagery

NARCIS (Netherlands)

Stoter, Arjan J. R.; Scherder, Erik J. A.; Kamsma, Yvo P. T.; Mulder, Theo

Motor imagery and action-based rehearsal were compared during motor sequence-learning by young adults (M = 25 yr., SD = 3) and aged adults (M = 63 yr., SD = 7). General accuracy of aged adults was lower than that of young adults (F-1,F-28 = 7.37, p = .01) even though working-memory capacity was

The role of consolidation in learning context-dependent phonotactic patterns in speech and digital sequence production.

Science.gov (United States)

Anderson, Nathaniel D; Dell, Gary S

2018-04-03

Speakers implicitly learn novel phonotactic patterns by producing strings of syllables. The learning is revealed in their speech errors. First-order patterns, such as "/f/ must be a syllable onset," can be distinguished from contingent, or second-order, patterns, such as "/f/ must be an onset if the vowel is /a/, but a coda if the vowel is /o/." A metaanalysis of 19 experiments clearly demonstrated that first-order patterns affect speech errors to a very great extent in a single experimental session, but second-order vowel-contingent patterns only affect errors on the second day of testing, suggesting the need for a consolidation period. Two experiments tested an analogue to these studies involving sequences of button pushes, with fingers as "consonants" and thumbs as "vowels." The button-push errors revealed two of the key speech-error findings: first-order patterns are learned quickly, but second-order thumb-contingent patterns are only strongly revealed in the errors on the second day of testing. The influence of computational complexity on the implicit learning of phonotactic patterns in speech production may be a general feature of sequence production.

A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis

Science.gov (United States)

2013-01-01

Background Given the serious threats posed to terrestrial ecosystems by industrial contamination, environmental monitoring is a standard procedure used for assessing the current status of an environment or trends in environmental parameters. Measurement of metal concentrations at different trophic levels followed by their statistical analysis using exploratory multivariate methods can provide meaningful information on the status of environmental quality. In this context, the present paper proposes a novel chemometric approach to standard statistical methods by combining the Block clustering with Partial least square (PLS) analysis to investigate the accumulation patterns of metals in anthropized terrestrial ecosystems. The present study focused on copper, zinc, manganese, iron, cobalt, cadmium, nickel, and lead transfer along a soil-plant-snai food chain, and the hepatopancreas of the Roman snail (Helix pomatia) was used as a biological end-point of metal accumulation. Results Block clustering deliniates between the areas exposed to industrial and vehicular contamination. The toxic metals have similar distributions in the nettle leaves and snail hepatopancreas. PLS analysis showed that (1) zinc and copper concentrations at the lower trophic levels are the most important latent factors that contribute to metal accumulation in land snails; (2) cadmium and lead are the main determinants of pollution pattern in areas exposed to industrial contamination; (3) at the sites located near roads lead is the most threatfull metal for terrestrial ecosystems. Conclusion There were three major benefits by applying block clustering with PLS for processing the obtained data: firstly, it helped in grouping sites depending on the type of contamination. Secondly, it was valuable for identifying the latent factors that contribute the most to metal accumulation in land snails. Finally, it optimized the number and type of data that are best for monitoring the status of metallic

A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis.

Science.gov (United States)

Nica, Dragos V; Bordean, Despina Maria; Pet, Ioan; Pet, Elena; Alda, Simion; Gergen, Iosif

2013-08-30

Given the serious threats posed to terrestrial ecosystems by industrial contamination, environmental monitoring is a standard procedure used for assessing the current status of an environment or trends in environmental parameters. Measurement of metal concentrations at different trophic levels followed by their statistical analysis using exploratory multivariate methods can provide meaningful information on the status of environmental quality. In this context, the present paper proposes a novel chemometric approach to standard statistical methods by combining the Block clustering with Partial least square (PLS) analysis to investigate the accumulation patterns of metals in anthropized terrestrial ecosystems. The present study focused on copper, zinc, manganese, iron, cobalt, cadmium, nickel, and lead transfer along a soil-plant-snai food chain, and the hepatopancreas of the Roman snail (Helix pomatia) was used as a biological end-point of metal accumulation. Block clustering deliniates between the areas exposed to industrial and vehicular contamination. The toxic metals have similar distributions in the nettle leaves and snail hepatopancreas. PLS analysis showed that (1) zinc and copper concentrations at the lower trophic levels are the most important latent factors that contribute to metal accumulation in land snails; (2) cadmium and lead are the main determinants of pollution pattern in areas exposed to industrial contamination; (3) at the sites located near roads lead is the most threatfull metal for terrestrial ecosystems. There were three major benefits by applying block clustering with PLS for processing the obtained data: firstly, it helped in grouping sites depending on the type of contamination. Secondly, it was valuable for identifying the latent factors that contribute the most to metal accumulation in land snails. Finally, it optimized the number and type of data that are best for monitoring the status of metallic contamination in terrestrial ecosystems

Food Sauces to Understand Volcanoes: a Learning Sequence in Middle School

Science.gov (United States)

Pieraccioni, Fabio; Bonaccorsi, Elena; Gioncada, Anna

2017-04-01

Some volcanic processes occur at pressures and temperatures very different from daily experience. Such extreme conditions, unreproducible in the classroom, can lead children to build concepts about volcanic phenomena very different from the reality (Greca & Moreira, 2000; Dove, 1998). The didactic goals of this learning sequence concern the relationships between the viscosity of magmas and types of erupted materials and their consequences on volcano shapes, to favour pupils' comprehension of what a volcano is. Viscosity and its temperature dependence can be easily experimented in class with analogue materials at room temperature (Baker et al., 2004). Our research aims are to observe the development of the thought of pupils of middle schools on volcanic phenomena; this allowed to put in evidence the benefits of this approach and to give suggestions to avoid possible critical points. We have experimented a hands-on learning sequence about volcanoes in four third classes of Tuscan middle schools, for an amount of 95 pupils, 48 females and 47 males. Sharing the principles of constructivism, we think useful that pupils start from their own direct experience for understanding natural phenomena not directly observable. Therefore, we start from the experiences and knowledge of children to build a inquiry-based itinerary (Minner et al., 2010; Pieraccioni et al., 2016). The learning sequence begins with a practical activity in which we employ common and well-known materials to introduce the concept of viscosity in order to relate various kinds of magma to the shape of volcanoes. One of the benefits of this approach is to overcome the problems of introducing complex concepts such as acidity of magmas or silica content, far from the pupils' experience and knowledge. These concepts are often used in Italian middle school textbooks to describe and classify volcanoes. The result is a list of names to learn by heart. On the contrary, by using oil, ketchup, peanut butter or honey

Pengaruh Strategic Leadership pada Organizational Learning melalui Accounting Information System pada Perusahaan Non Manufaktur di Surabaya

OpenAIRE

Halim, Yessica Mardiana

2015-01-01

The purpose of this research was to identify the influence of Strategic Leadership Toward Organizational Learning with Accounting Information System as the mediating variable of Non Manufacturing Firms in Surabaya. The variables were: Strategic Leadership, Organization Learning, and Accounting Information System. The number of samples were 95 respondents. The data analysis technique used was Partial Least Square. The data then analyzed by SmartPLS software application. This research showed t...

"I know your name, but not your number"--Patients with verbal short-term memory deficits are impaired in learning sequences of digits.

Science.gov (United States)

Bormann, Tobias; Seyboth, Margret; Umarova, Roza; Weiller, Cornelius

2015-06-01

Studies on verbal learning in patients with impaired verbal short-term memory (vSTM) have revealed dissociations among types of verbal information. Patients with impaired vSTM are able to learn lists of known words but fail to acquire new word forms. This suggests that vSTM is involved in new word learning. The present study assessed both new word learning and the learning of digit sequences in two patients with impaired vSTM. In two experiments, participants were required to learn people's names, ages and professions, or their four digit 'phone numbers'. The STM patients were impaired on learning unknown family names and phone numbers, but managed to acquire other verbal information. In contrast, a patient with a severe verbal episodic memory impairment was impaired across information types. These results indicate verbal STM involvement in the learning of digit sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.

Impairment in explicit visuomotor sequence learning is related to loss of microstructural integrity of the corpus callosum in multiple sclerosis patients with minimal disability.

Science.gov (United States)

Bonzano, L; Tacchino, A; Roccatagliata, L; Sormani, M P; Mancardi, G L; Bove, M

2011-07-15

Sequence learning can be investigated by serial reaction-time (SRT) paradigms. Explicit learning occurs when subjects have to recognize a test sequence and has been shown to activate the frontoparietal network in both contralateral and ipsilateral hemispheres. Thus, the left and right superior longitudinal fasciculi (SLF), connecting the intra-hemispheric frontoparietal circuits, could have a role in explicit unimanual visuomotor learning. Also, as both hemispheres are involved, we could hypothesize that the corpus callosum (CC) has a role in this process. Pathological damage in both SLF and CC has been detected in patients with Multiple Sclerosis (PwMS), and microstructural alterations can be quantified by Diffusion Tensor Imaging (DTI). In light of these findings, we inquired whether PwMS with minimal disability showed impairments in explicit visuomotor sequence learning and whether this could be due to loss of white matter integrity in these intra- and inter-hemispheric white matter pathways. Thus, we combined DTI analysis with a modified version of SRT task based on finger opposition movements in a group of PwMS with minimal disability. We found that the performance in explicit sequence learning was significantly reduced in these patients with respect to healthy subjects; the amount of sequence-specific learning was found to be more strongly correlated with fractional anisotropy (FA) in the CC (r=0.93) than in the left (r=0.28) and right SLF (r=0.27) (p for interaction=0.005 and 0.04 respectively). This finding suggests that an inter-hemispheric information exchange between the homologous areas is required to successfully accomplish the task and indirectly supports the role of the right (ipsilateral) hemisphere in explicit visuomotor learning. On the other hand, we found no significant correlation of the FA in the CC and in the SLFs with nonspecific learning (assessed when stimuli are randomly presented), supporting the hypothesis that inter

Novel, customizable scoring functions, parameterized using N-PLS, for structure-based drug discovery.

Science.gov (United States)

Catana, Cornel; Stouten, Pieter F W

2007-01-01

The ability to accurately predict biological affinity on the basis of in silico docking to a protein target remains a challenging goal in the CADD arena. Typically, "standard" scoring functions have been employed that use the calculated docking result and a set of empirical parameters to calculate a predicted binding affinity. To improve on this, we are exploring novel strategies for rapidly developing and tuning "customized" scoring functions tailored to a specific need. In the present work, three such customized scoring functions were developed using a set of 129 high-resolution protein-ligand crystal structures with measured Ki values. The functions were parametrized using N-PLS (N-way partial least squares), a multivariate technique well-known in the 3D quantitative structure-activity relationship field. A modest correlation between observed and calculated pKi values using a standard scoring function (r2 = 0.5) could be improved to 0.8 when a customized scoring function was applied. To mimic a more realistic scenario, a second scoring function was developed, not based on crystal structures but exclusively on several binding poses generated with the Flo+ docking program. Finally, a validation study was conducted by generating a third scoring function with 99 randomly selected complexes from the 129 as a training set and predicting pKi values for a test set that comprised the remaining 30 complexes. Training and test set r2 values were 0.77 and 0.78, respectively. These results indicate that, even without direct structural information, predictive customized scoring functions can be developed using N-PLS, and this approach holds significant potential as a general procedure for predicting binding affinity on the basis of in silico docking.

Brain activation in motor sequence learning is related to the level of native cortical excitability.

Directory of Open Access Journals (Sweden)

Silke Lissek

Full Text Available Cortical excitability may be subject to changes through training and learning. Motor training can increase cortical excitability in motor cortex, and facilitation of motor cortical excitability has been shown to be positively correlated with improvements in performance in simple motor tasks. Thus cortical excitability may tentatively be considered as a marker of learning and use-dependent plasticity. Previous studies focused on changes in cortical excitability brought about by learning processes, however, the relation between native levels of cortical excitability on the one hand and brain activation and behavioral parameters on the other is as yet unknown. In the present study we investigated the role of differential native motor cortical excitability for learning a motor sequencing task with regard to post-training changes in excitability, behavioral performance and involvement of brain regions. Our motor task required our participants to reproduce and improvise over a pre-learned motor sequence. Over both task conditions, participants with low cortical excitability (CElo showed significantly higher BOLD activation in task-relevant brain regions than participants with high cortical excitability (CEhi. In contrast, CElo and CEhi groups did not exhibit differences in percentage of correct responses and improvisation level. Moreover, cortical excitability did not change significantly after learning and training in either group, with the exception of a significant decrease in facilitatory excitability in the CEhi group. The present data suggest that the native, unmanipulated level of cortical excitability is related to brain activation intensity, but not to performance quality. The higher BOLD mean signal intensity during the motor task might reflect a compensatory mechanism in CElo participants.

Substructural Regularization With Data-Sensitive Granularity for Sequence Transfer Learning.

Science.gov (United States)

Sun, Shichang; Liu, Hongbo; Meng, Jiana; Chen, C L Philip; Yang, Yu

2018-06-01

Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy. STLM can achieve the competing goals of preserving the target domain substructure and utilizing the observations from both the target and source domains simultaneously. The estimation of STLM is very efficient since an analytical solution can be derived as a necessary and sufficient condition. The relative usability of substructures to act as regularization parameters and the time complexity of STLM are also analyzed and discussed. Comprehensive experiments of part-of-speech tagging with both Brown and Twitter corpora fully justify that our model can make improvements on all the combinations of source and target domains.

Using the partial least squares (PLS) method to establish critical success factor interdependence in ERP implementation projects

OpenAIRE

Esteves, José; Pastor Collado, Juan Antonio; Casanovas Garcia, Josep

2002-01-01

This technical research report proposes the usage of a statistical approach named Partial Least squares (PLS) to define the relationships between critical success factors for ERP implementation projects. In previous research work, we developed a unified model of critical success factors for ERP implementation projects. Some researchers have evidenced the relationships between these critical success factors, however no one has defined in a form...

Implementing an Equilibrium Law Teaching Sequence for Secondary School Students to Learn Chemical Equilibrium

Science.gov (United States)

Ghirardi, Marco; Marchetti, Fabio; Pettinari, Claudio; Regis, Alberto; Roletto, Ezio

2015-01-01

A didactic sequence is proposed for the teaching of chemical equilibrium law. In this approach, we have avoided the kinetic derivation and the thermodynamic justification of the equilibrium constant. The equilibrium constant expression is established empirically by a trial-and-error approach. Additionally, students learn to use the criterion of…

Finishing and Special Motifs: Lessons Learned from CRISPR Analysis Using Next-Generation Draft Sequences (7th Annual SFAF Meeting, 2012)

Energy Technology Data Exchange (ETDEWEB)

Campbell, Catherine

2012-06-01

Catherine Campbell on "Finishing and Special Motifs: Lessons learned from CRISPR analysis using next-generation draft sequences" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.

Phantom and animal imaging studies using PLS synchrotron X-rays

CERN Document Server

Hee Joung Kim; Kyu Ho Lee; Hai Jo Jung; Eun Kyung Kim; Jung Ho Je; In Woo Kim; Yeukuang, Hwu; Wen Li Tsai; Je Kyung Seong; Seung Won Lee; Hyung Sik Yoo

2001-01-01

Ultra-high resolution radiographs can be obtained using synchrotron X-rays. A collaboration team consisting of K-JIST, POSTECH and YUMC has recently commissioned a new beamline (5C1) at Pohang Light Source (PLS) in Korea for medical applications using phase contrast radiology. Relatively simple image acquisition systems were set up on 5C1 beamline, and imaging studies were performed for resolution test patterns, mammographic phantom, and animals. Resolution test patterns and mammographic phantom images showed much better image resolution and quality with the 5C1 imaging system than the mammography system. Both fish and mouse images with 5C1 imaging system also showed much better image resolution with great details of organs and anatomy compared to those obtained with a conventional mammography system. A simple and inexpensive ultra-high resolution imaging system on 5C1 beamline was successfully implemented. The authors were able to acquire ultra-high resolution images for, resolution test patterns, mammograph...

The Relationship of the Learning of Tourism Marketing, Hard Skills, Soft Skills and Working Quality of the Graduates of Tourism Academy in Medan

Directory of Open Access Journals (Sweden)

Sumihar Sebastiana Sitompul

2017-06-01

Full Text Available The quality of human resources originated from the field of education, especially the graduates should be able to compete with other nations. Research design uses Partial Least Square (PLS with smart PLS 2.0 program. The subjects were the graduates of tourism academy who have been working at tourism offices in North Sumatera namely Medan, Samosir, Dairi, Humbang Hasundutan, North Tapanuli, Toba Samosir, Karo, Serdang Bedagai, Deli Serdang. Respondents are 97 officers. Data collected by using instrument of questionnaire and analyzed by statistic with significant ≤ 0,05. The result of the research demonstrated that (1 the learning of tourism marketing significantly affected the hard skills. (2 The learning of tourism marketing significantly affected the soft skills (3 Hard skills significantly affected working quality of the graduates (4 Soft skills significantly affected working quality of the graduates (5 The learning of tourism marketing significantly affected working quality of the graduates.

An Improved Incremental Learning Approach for KPI Prognosis of Dynamic Fuel Cell System.

Science.gov (United States)

Yin, Shen; Xie, Xiaochen; Lam, James; Cheung, Kie Chung; Gao, Huijun

2016-12-01

The key performance indicator (KPI) has an important practical value with respect to the product quality and economic benefits for modern industry. To cope with the KPI prognosis issue under nonlinear conditions, this paper presents an improved incremental learning approach based on available process measurements. The proposed approach takes advantage of the algorithm overlapping of locally weighted projection regression (LWPR) and partial least squares (PLS), implementing the PLS-based prognosis in each locally linear model produced by the incremental learning process of LWPR. The global prognosis results including KPI prediction and process monitoring are obtained from the corresponding normalized weighted means of all the local models. The statistical indicators for prognosis are enhanced as well by the design of novel KPI-related and KPI-unrelated statistics with suitable control limits for non-Gaussian data. For application-oriented purpose, the process measurements from real datasets of a proton exchange membrane fuel cell system are employed to demonstrate the effectiveness of KPI prognosis. The proposed approach is finally extended to a long-term voltage prediction for potential reference of further fuel cell applications.

Unsupervised Learning of Word-Sequence Representations from Scratch via Convolutional Tensor Decomposition

OpenAIRE

Huang, Furong; Anandkumar, Animashree

2016-01-01

Unsupervised text embeddings extraction is crucial for text understanding in machine learning. Word2Vec and its variants have received substantial success in mapping words with similar syntactic or semantic meaning to vectors close to each other. However, extracting context-aware word-sequence embedding remains a challenging task. Training over large corpus is difficult as labels are difficult to get. More importantly, it is challenging for pre-trained models to obtain word-...

A Teaching and Learning Sequence about the Interplay of Chance and Determinism in Nonlinear Systems

Science.gov (United States)

Stavrou, D.; Duit, R.; Komorek, M.

2008-01-01

A teaching and learning sequence aimed at introducing upper secondary school students to the interplay between chance and determinism in nonlinear systems is presented. Three experiments concerning nonlinear systems (deterministic chaos, self-organization and fractals) and one experiment concerning linear systems are introduced. Thirty upper…

The Effect of Using a Visual Representation Tool in a Teaching-Learning Sequence for Teaching Newton's Third Law

Science.gov (United States)

Savinainen, Antti; Mäkynen, Asko; Nieminen, Pasi; Viiri, Jouni

2017-01-01

This paper presents a research-based teaching-learning sequence (TLS) that focuses on the notion of interaction in teaching Newton's third law (N3 law) which is, as earlier studies have shown, a challenging topic for students to learn. The TLS made systematic use of a visual representation tool--an interaction diagram (ID)--highlighting…

Simultaneous measurement of two enzyme activities using infrared spectroscopy: A comparative evaluation of PARAFAC, TUCKER and N-PLS modeling.

Science.gov (United States)

Baum, Andreas; Hansen, Per Waaben; Meyer, Anne S; Mikkelsen, Jørn Dalgaard

2013-08-06

Enzymes are used in many processes to release fermentable sugars for green production of biofuel, or the refinery of biomass for extraction of functional food ingredients such as pectin or prebiotic oligosaccharides. The complex biomasses may, however, require a multitude of specific enzymes which are active on specific substrates generating a multitude of products. In this paper we use the plant polymer, pectin, to present a method to quantify enzyme activity of two pectolytic enzymes by monitoring their superimposed spectral evolutions simultaneously. The data is analyzed by three chemometric multiway methods, namely PARAFAC, TUCKER3 and N-PLS, to establish simultaneous enzyme activity assays for pectin lyase and pectin methyl esterase. Correlation coefficients Rpred(2) for prediction test sets are 0.48, 0.96 and 0.96 for pectin lyase and 0.70, 0.89 and 0.89 for pectin methyl esterase, respectively. The retrieved models are compared and prediction test sets show that especially TUCKER3 performs well, even in comparison to the supervised regression method N-PLS. Copyright © 2013 Elsevier B.V. All rights reserved.

Influencia del Género en la Percepción y Adopción de e-Learning en Alumnos de Educación Superior en Chile

Directory of Open Access Journals (Sweden)

Patricio Esteban Ramírez-Correa

2010-11-01

El objetivo principal de este estudio es examinar las diferencias de género en la adopción de la tecnología en los estudiantes de educación superior en Chile. El modelo TAM es la herramienta utilizada para medir la aceptación y el uso de e-learning de los encuestados. Se utilizo Partial Least Squares (PLS, específicamente, el análisis multigrupo de PLS se usó para comparar las diferencias entre grupos. En resumen, podemos afirmar que en una muestra de estudiantes chilenos de educación superior su conducta de aceptación de la tecnología de e-learning coincide con el modelo TAM y los resultados no muestran diferencias estadísticamente significativas entre mujeres y hombres.

Prediction of Caffeine Content in Java Preanger Coffee Beans by NIR Spectroscopy Using PLS and MLR Method

Science.gov (United States)

Budiastra, I. W.; Sutrisno; Widyotomo, S.; Ayu, P. C.

2018-05-01

Caffeine is one of important components in coffee that contributes to the coffee beverages flavor. Caffeine concentration in coffee bean is usually determined by chemical method which is time consuming and destructive method. A nondestructive method using NIR spectroscopy was successfully applied to determine the caffeine concentration of Arabica gayo coffee bean. In this study, NIR Spectroscopy was assessed to determine the caffeine concentration of java preanger coffee bean. A hundred samples, each consist of 96 g coffee beans were prepared for reflectance and chemical measurement. Reflectance of the sample was measured by FT-NIR spectrometer in the wavelength of 1000-2500 nm (10000-4000 cm-1) followed by determination of caffeine content using LCMS method. Calibration of NIR spectra and the caffeine content was carried out using PLS and MLR methods. Several spectra data processing was conducted to increase the accuracy of prediction. The result of the study showed that caffeine content could be determined by PLS model using 7 factors and spectra data processing of combination of the first derivative and MSC of spectra absorbance (r = 0.946; CV = 1.54 %; RPD = 2.28). A lower accuracy was obtained by MLR model consisted of three caffeine and other four absorption wavelengths (r = 0.683; CV = 3.31%; RPD = 1.18).

Foundations of Sequence-to-Sequence Modeling for Time Series

OpenAIRE

Kuznetsov, Vitaly; Mariet, Zelda

2018-01-01

The availability of large amounts of time series data, paired with the performance of deep-learning algorithms on a broad class of problems, has recently led to significant interest in the use of sequence-to-sequence models for time series forecasting. We provide the first theoretical analysis of this time series forecasting framework. We include a comparison of sequence-to-sequence modeling to classical time series models, and as such our theory can serve as a quantitative guide for practiti...

The role of culture in perceptual learning styles

OpenAIRE

حسینی فاطمی ، پیشقدم حسینی فاطمی ، پیشقدم

2009-01-01

The major aim of this article is to determine the role of culture in perceptual learning style (PLS) preferences of Iranian English learners, in order to minimize teacher-student style conflict in the classroom. To do this, 400 university students from different fields of study were selected from Allameh Tabatabaee University in Tehran, Ferdowsi University of Mashhad and Mashhad University of Medical Sciences. The subjects were asked to answer Reid’s questionnaire (1987) which was designed to...

Implementing the Fundamental Principle of Islamic Finance PLS in Order to Reduce Moral Hazard on the Financial Services Market

OpenAIRE

Dariusz Piotrowski

2014-01-01

Moral hazard is a situation where agent takes a risky actions, knowing that potential costs will be born by principal. In finance, moral hazard arises when advisers take risky decisions come to believe that they will not have to carry the full burden of potential loses. Implementing the fundamental principle of Islamic finance PLS could reduce moral hazard on financial services market.

Implicit motor sequence learning in schizophrenia and in old age: reduced performance only in the third session

NARCIS (Netherlands)

Cornelis, Claudia; de Picker, Livia J.; de Boer, Peter; Dumont, Glenn; Coppens, Violette; Morsel, Anne; Janssens, Luc; Timmers, Maarten; Sabbe, Bernard G. C.; Morrens, Manuel; Hulstijn, Wouter

2016-01-01

Although there still is conflicting evidence whether schizophrenia is a neurodegenerative disease, cognitive changes in schizophrenia resemble those observed during normal aging. In contrast to extensively demonstrated deficits in explicit learning, it remains unclear whether implicit sequence

Solving the Curriculum Sequencing Problem with DNA Computing Approach

Science.gov (United States)

Debbah, Amina; Ben Ali, Yamina Mohamed

2014-01-01

In the e-learning systems, a learning path is known as a sequence of learning materials linked to each others to help learners achieving their learning goals. As it is impossible to have the same learning path that suits different learners, the Curriculum Sequencing problem (CS) consists of the generation of a personalized learning path for each…

COMPARISON OF PARTIAL LEAST SQUARES REGRESSION METHOD ALGORITHMS: NIPALS AND PLS-KERNEL AND AN APPLICATION

Directory of Open Access Journals (Sweden)

ELİF BULUT

2013-06-01

Full Text Available Partial Least Squares Regression (PLSR is a multivariate statistical method that consists of partial least squares and multiple linear regression analysis. Explanatory variables, X, having multicollinearity are reduced to components which explain the great amount of covariance between explanatory and response variable. These components are few in number and they don’t have multicollinearity problem. Then multiple linear regression analysis is applied to those components to model the response variable Y. There are various PLSR algorithms. In this study NIPALS and PLS-Kernel algorithms will be studied and illustrated on a real data set.

The Analysis of Electronic Journal Utilization In Learning Process: Technology Acceptance Model And Information System Success

Directory of Open Access Journals (Sweden)

Achmad Zaky

2017-12-01

Full Text Available This study aims to observe the behavior of electronic journal (e-journal among bachelor students of the Universitas Brawijaya by Technology Acceptance Model (TAM and Information System Success (ISS as theoretical framework. The research samples are all bachelor students who have used e-journal in their learning process. The respondents are selected by convenience sampling method. The data are collected through survey and analyzed by Partial Least Square (PLS with SmartPLS 3. The result of the study reveals that user satisfaction and intention to use have significant effect on actual use of e-journal among bachelor students at the Universitas Brawijaya. Those variables affect the actual use because they have been formed by other variables such as information quality, perceived easiness, perceived usefulness, and attitude towards behavior. Furthermore, information quality has significant influence on user satisfaction, while perceived usefulness and perceived usefulness do not have direct effect on the intention to use. The implication of this study is relevant for educators to recognize the reason factors to use e-journal in the learning process.

Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device.

Science.gov (United States)

McKinstry, Jeffrey L; Edelman, Gerald M

2013-01-01

Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.

Sequence Matters but How Exactly? A Method for Evaluating Activity Sequences from Data

Science.gov (United States)

Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma

2016-01-01

How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

Science.gov (United States)

van den Akker, Jeroen; Mishne, Gilad; Zimmer, Anjali D; Zhou, Alicia Y

2018-04-17

Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software tools, the majority of variants called using NGS alone are in fact accurate and reliable. However, a small subset of difficult-to-call variants that still do require orthogonal confirmation exist. For this reason, many clinical laboratories confirm NGS results using orthogonal technologies such as Sanger sequencing. Here, we report the development of a deterministic machine-learning-based model to differentiate between these two types of variant calls: those that do not require confirmation using an orthogonal technology (high confidence), and those that require additional quality testing (low confidence). This approach allows reliable NGS-based calling in a clinical setting by identifying the few important variant calls that require orthogonal confirmation. We developed and tested the model using a set of 7179 variants identified by a targeted NGS panel and re-tested by Sanger sequencing. The model incorporated several signals of sequence characteristics and call quality to determine if a variant was identified at high or low confidence. The model was tuned to eliminate false positives, defined as variants that were called by NGS but not confirmed by Sanger sequencing. The model achieved very high accuracy: 99.4% (95% confidence interval: +/- 0.03%). It categorized 92.2% (6622/7179) of the variants as high confidence, and 100% of these were confirmed to be present by Sanger sequencing. Among the variants that were categorized as low confidence, defined as NGS calls of low quality that are likely to be artifacts, 92.1% (513/557) were found to be not present by Sanger sequencing. This work shows that NGS data contains sufficient characteristics for a machine-learning-based model to

Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

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Vasiliki eFolia

2014-02-01

Full Text Available In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45 and the medial prefrontal regions (centered on BA 8/32. Importantly, and central to this study, the inclusion of a naive preference FMRI baseline measurement allowed us to conclude that these FMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax in unsupervised AGL paradigms with proper learning designs.

The consolidation of implicit sequence memory in obstructive sleep apnea.

Directory of Open Access Journals (Sweden)

Eszter Csabi

Full Text Available Obstructive Sleep Apnea (OSA Syndrome is a relatively frequent sleep disorder characterized by disrupted sleep patterns. It is a well-established fact that sleep has beneficial effect on memory consolidation by enhancing neural plasticity. Implicit sequence learning is a prominent component of skill learning. However, the formation and consolidation of this fundamental learning mechanism remains poorly understood in OSA. In the present study we examined the consolidation of different aspects of implicit sequence learning in patients with OSA. We used the Alternating Serial Reaction Time task to measure general skill learning and sequence-specific learning. There were two sessions: a learning phase and a testing phase, separated by a 10-hour offline period with sleep. Our data showed differences in offline changes of general skill learning between the OSA and control group. The control group demonstrated offline improvement from evening to morning, while the OSA group did not. In contrast, we did not observe differences between the groups in offline changes in sequence-specific learning. Our findings suggest that disrupted sleep in OSA differently affects neural circuits involved in the consolidation of sequence learning.

Variable selection methods in PLS regression - a comparison study on metabolomics data

DEFF Research Database (Denmark)

Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need to be related. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...

Physical structure and genetic expression of the sulfonamide-resistance plasmid pLS80 and its derivatives in Streptococcus pneumoniae and Bacillus subtilis

Energy Technology Data Exchange (ETDEWEB)

Lopez, P.; Espinosa, M.; Lacks, S.A.

1984-01-01

The 10-kb chromosomal fragment of Streptococcus pneumoniae cloned in pLS80 contains the sul-d allele of the pneumococcal gene for dihydropteroate synthase. As a single copy in the chromosome this allele confers resistance to sulfanilamide at 0.2 mg/ml; in the multicopy plasmid it confers resistance to 2.0 mg/ml. The sul-d mutation was mapped by restriction analysis to a 0.4-kb region. A spontaneous deletion beginning approx. 1.5 kb to the right of the sul-d mutation prevented gene function, possibly by removing a promoter. This region could be restored by chromosomal facilitation and be demonstrated in the plasmid by selection for sulfonamide resistance. Under selection for a vector marker, tetracycline resistance, only the deleted plasmid was detectable, apparently as a result of plasmid segregation and the advantageous growth rates of cells with smaller plasmids. When such cells were selected for sulfonamide resistance, the deleted region returned to the plasmid, presumably by equilibration between the chromosome and the plasmid pool, to give a low frequency (approx. 10/sup -3/) of cells resistant to sulfanilamide at 2.0 mg/ml. Models for the mechanisms of chromosomal facilitation and equilibration are proposed. Several derivatives of pLS80 could be transferred to Bacillus subtilis, where they conferred resistance to sulfanilamide at 2 mg/ml, thereby demonstrating cross-species expression of the pneumococcal gene. Transfer of the plasmids to B. subtilis gave rise to large deletions to the left of the sul-d marker, but these deletions did not interfere with the sul-d gene function. Restriction maps of pLS80 and its variously deleted derivatives are presented.

Transferring a Teaching Learning Sequence between Two Different Educational Contexts: The Case of Greece and Finland

Science.gov (United States)

Spyrtou, Anna; Lavonen, Jari; Zoupidis, Anastasios; Loukomies, Anni; Pnevmatikos, Dimitris; Juuti, Kalle; Kariotoglou, Petros

2018-01-01

In the present paper, we report on the idea of exchanging educational innovations across European countries aiming to shed light on the following question: how feasible and useful is it to transfer an innovation across different national educational settings? The innovation, in this case, Inquiry-Based Teaching Learning Sequences, is recognized as…

Classification of cassava starch films by physicochemical properties and water vapor permeability quantification by FTIR and PLS.

Science.gov (United States)

Henrique, C M; Teófilo, R F; Sabino, L; Ferreira, M M C; Cereda, M P

2007-05-01

Cassava starches are widely used in the production of biodegradable films, but their resistance to humidity migration is very low. In this work, commercial cassava starch films were studied and classified according to their physicochemical properties. A nondestructive method for water vapor permeability determination, which combines with infrared spectroscopy and multivariate calibration, is also presented. The following commercial cassava starches were studied: pregelatinized (amidomax 3550), carboxymethylated starch (CMA) of low and high viscosities, and esterified starches. To make the films, 2 different starch concentrations were evaluated, consisting of water suspensions with 3% and 5% starch. The filmogenic solutions were dried and characterized for their thickness, grammage, water vapor permeability, water activity, tensile strength (deformation force), water solubility, and puncture strength (deformation). The minimum thicknesses were 0.5 to 0.6 mm in pregelatinized starch films. The results were treated by means of the following chemometric methods: principal component analysis (PCA) and partial least squares (PLS) regression. PCA analysis on the physicochemical properties of the films showed that the differences in concentration of the dried material (3% and 5% starch) and also in the type of starch modification were mainly related to the following properties: permeability, solubility, and thickness. IR spectra collected in the region of 4000 to 600 cm(-1) were used to build a PLS model with good predictive power for water vapor permeability determination, with mean relative errors of 10.0% for cross-validation and 7.8% for the prediction set.

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

Science.gov (United States)

Yu, Peigen; Low, Mei Yin; Zhou, Weibiao

2018-01-01

In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R 2 ) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R 2 (0.875) and RMSE (2.41%). Copyright © 2017 Elsevier Ltd. All rights reserved.

Screening method for rapid classification of psychoactive substances in illicit tablets using mid infrared spectroscopy and PLS-DA.

Science.gov (United States)

Pereira, Leandro S A; Lisboa, Fernanda L C; Coelho Neto, José; Valladão, Frederico N; Sena, Marcelo M

2018-05-09

Several new psychoactive substances (NPS) have reached the illegal drug market in recent years, and ecstasy-like tablets are one of the forms affected by this change. Cathinones and tryptamines have increasingly been found in ecstasy-like seized samples as well as other amphetamine type stimulants. A presumptive method for identifying different drugs in seized ecstasy tablets (n=92) using ATR-FTIR (attenuated total reflectance - Fourier transform infrared spectroscopy) and PLS-DA (partial least squares discriminant analysis) was developed. A hierarchical strategy of sequential modeling was performed with PLS-DA. The main model discriminated four classes: 5-MeO-MIPT, methylenedioxyamphetamines (MDMA and MDA), methamphetamine, and cathinones. Two submodels were built to identify drugs present in MDs and cathinones classes. Models were validated through the estimate of figures of merit. The average reliability rate (RLR) of the main model was 96.8% and accordance (ACC) was 100%. For the submodels, RLR and ACC were 100%. The reliability of the models was corroborated through their spectral interpretation. Thus, spectral assignments were performed by associating informative vectors of each specific modeled class to the respective drugs. The developed method is simple, fast, and can be applied to the forensic laboratory routine, leading to objective results reports useful for forensic scientists and law enforcement. Copyright © 2018 Elsevier B.V. All rights reserved.

Metode PLS: Analisis Kinerja Karyawan melalui Kepuasan Kerja dan Komitmen Karyawan

Directory of Open Access Journals (Sweden)

Saskia Yuanita

2012-11-01

Full Text Available Global challenges of the current causes increasing competition among national and international businesses. Under these conditions, the company realizes the importance of quality and efforts to enhance competitiveness by doing improvements consistently and continuously in order to meet customer and market needs. This study aims to examine the effect of the implementation of ISO 9001 quality management system onemployee performance, and the moderating effects of job satisfaction and employee commitment to the relationship between the application of ISO 9001:2008 quality management system on employee performance. The method used to analyze is Partial Least Square (PLS. The results show that the application of ISO 9001:2008 quality management system affects performance of employees with employee satisfaction and commitment as moderating variable that affect the relationship between the application of ISO 9001:2008quality management system on employee performance. Both variables, moderating employee satisfaction and commitment have positive parameter estimation, so that when the satisfaction and commitment of employees increase, it will give effect to the improvement of the implementation of the ISO 9001:2008 quality management system on employee performance.

The Local Territory as a Resource for Learning Science: A Proposal for the Design of Teaching-learning Sequences in Science Education

OpenAIRE

González-Weil, C.; Merino-Rubilar, C.; Ahumada, G.; Arenas, A.; Salinas, V.; Bravo, P.

2014-01-01

The present work arises from the need to reform Science Education, particularly through the contextualization of teaching. It is proposed to achieve this through the use of local territory as a resource for the design of teaching-learning-sequences (TLS). To do this, an interdisciplinary group of researchers and teachers from a Secondary School created a Professional Circle for Reflection on Teaching, which constructed an emerging conceptualization of Territory, analyzed the possibil...

Dissecting Sequences of Regulation and Cognition: Statistical Discourse Analysis of Primary School Children's Collaborative Learning

Science.gov (United States)

Molenaar, Inge; Chiu, Ming Ming

2014-01-01

Extending past research showing that regulative activities (metacognitive and relational) can aid learning, this study tests whether sequences of cognitive, metacognitive and relational activities affect subsequent cognition. Scaffolded by a computer avatar, 54 primary school students (working in 18 groups of 3) discussed writing a report about a…

New approach to breast cancer CAD using partial least squares and kernel-partial least squares

Science.gov (United States)

Land, Walker H., Jr.; Heine, John; Embrechts, Mark; Smith, Tom; Choma, Robert; Wong, Lut

2005-04-01

Breast cancer is second only to lung cancer as a tumor-related cause of death in women. Currently, the method of choice for the early detection of breast cancer is mammography. While sensitive to the detection of breast cancer, its positive predictive value (PPV) is low, resulting in biopsies that are only 15-34% likely to reveal malignancy. This paper explores the use of two novel approaches called Partial Least Squares (PLS) and Kernel-PLS (K-PLS) to the diagnosis of breast cancer. The approach is based on optimization for the partial least squares (PLS) algorithm for linear regression and the K-PLS algorithm for non-linear regression. Preliminary results show that both the PLS and K-PLS paradigms achieved comparable results with three separate support vector learning machines (SVLMs), where these SVLMs were known to have been trained to a global minimum. That is, the average performance of the three separate SVLMs were Az = 0.9167927, with an average partial Az (Az90) = 0.5684283. These results compare favorably with the K-PLS paradigm, which obtained an Az = 0.907 and partial Az = 0.6123. The PLS paradigm provided comparable results. Secondly, both the K-PLS and PLS paradigms out performed the ANN in that the Az index improved by about 14% (Az ~ 0.907 compared to the ANN Az of ~ 0.8). The "Press R squared" value for the PLS and K-PLS machine learning algorithms were 0.89 and 0.9, respectively, which is in good agreement with the other MOP values.

Consumption-based cross-brand learning : Are private labels really private?

NARCIS (Netherlands)

Gijsbrechts, E.; Szymanowski, M.G.

2012-01-01

While some researchers view private labels (PLs) as a key tool for retailer differentiation, others imply that consumers do not distinguish between PLs of different chains. This debate raises the question: Do a retail chain's PL investments subsidize rival PLs? In addition, how does this affect

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

Science.gov (United States)

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.

Classification and authentication of unknown water samples using machine learning algorithms.

Science.gov (United States)

Kundu, Palash K; Panchariya, P C; Kundu, Madhusree

2011-07-01

This paper proposes the development of water sample classification and authentication, in real life which is based on machine learning algorithms. The proposed techniques used experimental measurements from a pulse voltametry method which is based on an electronic tongue (E-tongue) instrumentation system with silver and platinum electrodes. E-tongue include arrays of solid state ion sensors, transducers even of different types, data collectors and data analysis tools, all oriented to the classification of liquid samples and authentication of unknown liquid samples. The time series signal and the corresponding raw data represent the measurement from a multi-sensor system. The E-tongue system, implemented in a laboratory environment for 6 numbers of different ISI (Bureau of Indian standard) certified water samples (Aquafina, Bisleri, Kingfisher, Oasis, Dolphin, and McDowell) was the data source for developing two types of machine learning algorithms like classification and regression. A water data set consisting of 6 numbers of sample classes containing 4402 numbers of features were considered. A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system. A proposed partial least squares (PLS) based classifier, which was dedicated as well; to authenticate a specific category of water sample evolved out as an integral part of the E-tongue instrumentation system. The developed PCA and PLS based E-tongue system emancipated an overall encouraging authentication percentage accuracy with their excellent performances for the aforesaid categories of water samples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Influence of the nature of soil organic matter on the sorption behaviour of pentadecane as determined by PLS analysis of mid-infrared DRIFT and solid-state {sup 13}C NMR spectra

Energy Technology Data Exchange (ETDEWEB)

Clark Ehlers, G.A. [Institute of Environmental Biotechnology, Department IFA-Tulln, University of Natural Resources and Applied Life Sciences, Vienna, Konrad Lorenz Str. 20, Tulln A-3430 (Austria); Forrester, Sean T. [CSIRO Land and Water, Waite Rd, Urrbrae SA 5064 (Australia); Scherr, Kerstin E. [Institute of Environmental Biotechnology, Department IFA-Tulln, University of Natural Resources and Applied Life Sciences, Vienna, Konrad Lorenz Str. 20, Tulln A-3430 (Austria); Loibner, Andreas P., E-mail: andreas.loibner@boku.ac.a [Institute of Environmental Biotechnology, Department IFA-Tulln, The University of Natural Resources and Applied Life Sciences, Vienna, Konrad Lorenz Str. 20, Tulln A-3430 (Austria); Janik, Les J. [CSIRO Land and Water, Waite Rd, Urrbrae SA 5064 (Australia)

2010-01-15

The nature of soil organic matter (SOM) functional groups associated with sorption processes was determined by correlating partitioning coefficients with solid-state {sup 13}C nuclear magnetic resonance (NMR) and diffuse reflectance mid-infrared (DRIFT) spectral features using partial least squares (PLS) regression analysis. Partitioning sorption coefficients for n-pentadecane (n-C{sub 15}) were determined for three alternative models: the Langmuir model, the dual distributed reactive domain model (DRDM) and the Freundlich model, where the latter was found to be the most appropriate. NMR-derived constitutional descriptors did not correlate with Freundlich model parameters. By contrast, PLS analysis revealed the most likely nature of the functional groups in SOM associated with n-C{sub 15} sorption coefficients (K{sub F}) to be aromatic, possibly porous soil char, rather than aliphatic organic components for the presently investigated soils. High PLS cross-validation correlation suggested that the model was robust for the purpose of characterising the functional group chemistry important for n-C{sub 15} sorption. - NMR/IR spectroscopy and chemometrics reveal the aromatic fraction of soil organic matter being responsible for alkane sorption.

Modelling the Success of Learning Management Systems: Application of Latent Class Segmentation Using FIMIX-PLS

Science.gov (United States)

Arenas-Gaitán, Jorge; Rondán-Cataluña, Francisco Javier; Ramírez-Correa, Patricio E.

2018-01-01

There is not a unique attitude towards the implementation of digital technology in educational sceneries. This paper aims to validate an adaptation of the DeLone and McLean information systems success model in the context of a learning management system. Furthermore, this study means to prove (1) the necessity of segmenting students in order to…

Teaching Task Sequencing via Verbal Mediation.

Science.gov (United States)

Rusch, Frank R.; And Others

1987-01-01

Verbal sequence training was used to teach a moderately mentally retarded woman to sequence job-related tasks. Learning to say the tasks in the proper sequence resulted in the employee performing her tasks in that sequence, and the employee was capable of mediating her own work behavior when scheduled changes occurred. (Author/JDD)

An introduction to deep learning on biological sequence data: examples and solutions.

Science.gov (United States)

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae

2017-11-15

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. skaaesonderby@gmail.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A Teaching-Learning Sequence for the Special Relativity Theory at High School Level Historically and Epistemologically Contextualized

Science.gov (United States)

Arriassecq, Irene; Greca, Ileana Maria

2012-01-01

This paper discusses some topics that stem from recent contributions made by the History, the Philosophy, and the Didactics of Science. We consider these topics relevant to the introduction of the Special Relativity Theory (SRT) in high school within a contextualized approach. We offer an outline of a teaching-learning sequence dealing with the…

The feasibility of using explicit method for linear correction of the particle size variation using NIR Spectroscopy combined with PLS2regression method

Science.gov (United States)

Yulia, M.; Suhandy, D.

2018-03-01

NIR spectra obtained from spectral data acquisition system contains both chemical information of samples as well as physical information of the samples, such as particle size and bulk density. Several methods have been established for developing calibration models that can compensate for sample physical information variations. One common approach is to include physical information variation in the calibration model both explicitly and implicitly. The objective of this study was to evaluate the feasibility of using explicit method to compensate the influence of different particle size of coffee powder in NIR calibration model performance. A number of 220 coffee powder samples with two different types of coffee (civet and non-civet) and two different particle sizes (212 and 500 µm) were prepared. Spectral data was acquired using NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement. A discrimination method based on PLS-DA was conducted and the influence of different particle size on the performance of PLS-DA was investigated. In explicit method, we add directly the particle size as predicted variable results in an X block containing only the NIR spectra and a Y block containing the particle size and type of coffee. The explicit inclusion of the particle size into the calibration model is expected to improve the accuracy of type of coffee determination. The result shows that using explicit method the quality of the developed calibration model for type of coffee determination is a little bit superior with coefficient of determination (R2) = 0.99 and root mean square error of cross-validation (RMSECV) = 0.041. The performance of the PLS2 calibration model for type of coffee determination with particle size compensation was quite good and able to predict the type of coffee in two different particle sizes with relatively high R2 pred values. The prediction also resulted in low bias and RMSEP values.

Calibration sets selection strategy for the construction of robust PLS models for prediction of biodiesel/diesel blends physico-chemical properties using NIR spectroscopy

Science.gov (United States)

Palou, Anna; Miró, Aira; Blanco, Marcelo; Larraz, Rafael; Gómez, José Francisco; Martínez, Teresa; González, Josep Maria; Alcalà, Manel

2017-06-01

Even when the feasibility of using near infrared (NIR) spectroscopy combined with partial least squares (PLS) regression for prediction of physico-chemical properties of biodiesel/diesel blends has been widely demonstrated, inclusion in the calibration sets of the whole variability of diesel samples from diverse production origins still remains as an important challenge when constructing the models. This work presents a useful strategy for the systematic selection of calibration sets of samples of biodiesel/diesel blends from diverse origins, based on a binary code, principal components analysis (PCA) and the Kennard-Stones algorithm. Results show that using this methodology the models can keep their robustness over time. PLS calculations have been done using a specialized chemometric software as well as the software of the NIR instrument installed in plant, and both produced RMSEP under reproducibility values of the reference methods. The models have been proved for on-line simultaneous determination of seven properties: density, cetane index, fatty acid methyl esters (FAME) content, cloud point, boiling point at 95% of recovery, flash point and sulphur.

Development and validation of a Partial Least Squares-Discriminant Analysis (PLS-DA) model based on the determination of ethyl glucuronide (EtG) and fatty acid ethyl esters (FAEEs) in hair for the diagnosis of chronic alcohol abuse.

Science.gov (United States)

Alladio, E; Giacomelli, L; Biosa, G; Corcia, D Di; Gerace, E; Salomone, A; Vincenti, M

2018-01-01

The chronic intake of an excessive amount of alcohol is currently ascertained by determining the concentration of direct alcohol metabolites in the hair samples of the alleged abusers, including ethyl glucuronide (EtG) and, less frequently, fatty acid ethyl esters (FAEEs). Indirect blood biomarkers of alcohol abuse are still determined to support hair EtG results and diagnose a consequent liver impairment. In the present study, the supporting role of hair FAEEs is compared with indirect blood biomarkers with respect to the contexts in which hair EtG interpretation is uncertain. Receiver Operating Characteristics (ROC) curves and multivariate Principal Component Analysis (PCA) demonstrated much stronger correlation of EtG results with FAEEs than with any single indirect biomarker or their combinations. Partial Least Squares Discriminant Analysis (PLS-DA) models based on hair EtG and FAEEs were developed to maximize the biomarkers information content on a multivariate background. The final PLS-DA model yielded 100% correct classification on a training/evaluation dataset of 155 subjects, including both chronic alcohol abusers and social drinkers. Then, the PLS-DA model was validated on an external dataset of 81 individual providing optimal discrimination ability between chronic alcohol abusers and social drinkers, in terms of specificity and sensitivity. The PLS-DA scores obtained for each subject, with respect to the PLS-DA model threshold that separates the probabilistic distributions for the two classes, furnished a likelihood ratio value, which in turn conveys the strength of the experimental data support to the classification decision, within a Bayesian logic. Typical boundary real cases from daily work are discussed, too. Copyright © 2017 Elsevier B.V. All rights reserved.

Brain activation during anticipation of sound sequences.

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Leaver, Amber M; Van Lare, Jennifer; Zielinski, Brandon; Halpern, Andrea R; Rauschecker, Josef P

2009-02-25

Music consists of sound sequences that require integration over time. As we become familiar with music, associations between notes, melodies, and entire symphonic movements become stronger and more complex. These associations can become so tight that, for example, hearing the end of one album track can elicit a robust image of the upcoming track while anticipating it in total silence. Here, we study this predictive "anticipatory imagery" at various stages throughout learning and investigate activity changes in corresponding neural structures using functional magnetic resonance imaging. Anticipatory imagery (in silence) for highly familiar naturalistic music was accompanied by pronounced activity in rostral prefrontal cortex (PFC) and premotor areas. Examining changes in the neural bases of anticipatory imagery during two stages of learning conditional associations between simple melodies, however, demonstrates the importance of fronto-striatal connections, consistent with a role of the basal ganglia in "training" frontal cortex (Pasupathy and Miller, 2005). Another striking change in neural resources during learning was a shift between caudal PFC earlier to rostral PFC later in learning. Our findings regarding musical anticipation and sound sequence learning are highly compatible with studies of motor sequence learning, suggesting common predictive mechanisms in both domains.

Application of Genetic Algorithm (GA) Assisted Partial Least Square (PLS) Analysis on Trilinear and Non-trilinear Fluorescence Data Sets to Quantify the Fluorophores in Multifluorophoric Mixtures: Improving Quantification Accuracy of Fluorimetric Estimations of Dilute Aqueous Mixtures.

Science.gov (United States)

Kumar, Keshav

2018-03-29

Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence spectroscopy (TSFS) are the 2 fluorescence techniques that are commonly used for the analysis of multifluorophoric mixtures. These 2 fluorescence techniques are conceptually different and provide certain advantages over each other. The manual analysis of such highly correlated large volume of EEMF and TSFS towards developing a calibration model is difficult. Partial least square (PLS) analysis can analyze the large volume of EEMF and TSFS data sets by finding important factors that maximize the correlation between the spectral and concentration information for each fluorophore. However, often the application of PLS analysis on entire data sets does not provide a robust calibration model and requires application of suitable pre-processing step. The present work evaluates the application of genetic algorithm (GA) analysis prior to PLS analysis on EEMF and TSFS data sets towards improving the precision and accuracy of the calibration model. The GA algorithm essentially combines the advantages provided by stochastic methods with those provided by deterministic approaches and can find the set of EEMF and TSFS variables that perfectly correlate well with the concentration of each of the fluorophores present in the multifluorophoric mixtures. The utility of the GA assisted PLS analysis is successfully validated using (i) EEMF data sets acquired for dilute aqueous mixture of four biomolecules and (ii) TSFS data sets acquired for dilute aqueous mixtures of four carcinogenic polycyclic aromatic hydrocarbons (PAHs) mixtures. In the present work, it is shown that by using the GA it is possible to significantly improve the accuracy and precision of the PLS calibration model developed for both EEMF and TSFS data set. Hence, GA must be considered as a useful pre-processing technique while developing an EEMF and TSFS calibration model.

Nursing Student Perceptions Regarding Simulation Experience Sequencing.

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Woda, Aimee A; Gruenke, Theresa; Alt-Gehrman, Penny; Hansen, Jamie

2016-09-01

The use of simulated learning experiences (SLEs) have increased within nursing curricula with positive learning outcomes for nursing students. The purpose of this study is to explore nursing students' perceptions of their clinical decision making (CDM) related to the block sequencing of different patient care experiences, SLEs versus hospital-based learning experiences (HLEs). A qualitative descriptive design used open-ended survey questions to generate information about the block sequencing of SLEs and its impact on nursing students' perceived CDM. Three themes emerged from the data: Preexperience Anxiety, Real-Time Decision Making, and Increased Patient Care Experiences. Nursing students identified that having SLEs prior to HLEs provided several benefits. Even when students preferred SLEs prior to HLEs, the sequence did not impact their CDM. This suggests that alternating block sequencing can be used without impacting the students' perceptions of their ability to make decisions. [J Nurs Educ. 2016;55(9):528-532.]. Copyright 2016, SLACK Incorporated.

IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform.

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N Lance Hepler

2014-09-01

Full Text Available Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals--a cure and a vaccine--remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab, determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license, documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.

Relating What Is To Be Learned To What Is Known: Subsumptive Sequencing, Co-ordination and Cognitive Skills Activation.

Science.gov (United States)

Stein, Faith S.; And Others

Recent advances have been made in facilitating implementation of Ausubel's advance organizer strategy. One reason Ausubel's approach has not been widely adopted is its lack of specificity about how to relate what is to be learned to what has already been assimilated within the cognitive structure. The use of subsumptive sequencing, coordinate…

The Bacillus subtilis Conjugative Plasmid pLS20 Encodes Two Ribbon-Helix-Helix Type Auxiliary Relaxosome Proteins That Are Essential for Conjugation

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Andrés Miguel-Arribas

2017-11-01

Full Text Available Bacterial conjugation is the process by which a conjugative element (CE is transferred horizontally from a donor to a recipient cell via a connecting pore. One of the first steps in the conjugation process is the formation of a nucleoprotein complex at the origin of transfer (oriT, where one of the components of the nucleoprotein complex, the relaxase, introduces a site- and strand specific nick to initiate the transfer of a single DNA strand into the recipient cell. In most cases, the nucleoprotein complex involves, besides the relaxase, one or more additional proteins, named auxiliary proteins, which are encoded by the CE and/or the host. The conjugative plasmid pLS20 replicates in the Gram-positive Firmicute bacterium Bacillus subtilis. We have recently identified the relaxase gene and the oriT of pLS20, which are separated by a region of almost 1 kb. Here we show that this region contains two auxiliary genes that we name aux1LS20 and aux2LS20, and which we show are essential for conjugation. Both Aux1LS20 and Aux2LS20 are predicted to contain a Ribbon-Helix-Helix DNA binding motif near their N-terminus. Analyses of the purified proteins show that Aux1LS20 and Aux2LS20 form tetramers and hexamers in solution, respectively, and that they both bind preferentially to oriTLS20, although with different characteristics and specificities. In silico analyses revealed that genes encoding homologs of Aux1LS20 and/or Aux2LS20 are located upstream of almost 400 relaxase genes of the RelLS20 family (MOBL of relaxases. Thus, Aux1LS20 and Aux2LS20 of pLS20 constitute the founding member of the first two families of auxiliary proteins described for CEs of Gram-positive origin.

The Bacillus subtilis Conjugative Plasmid pLS20 Encodes Two Ribbon-Helix-Helix Type Auxiliary Relaxosome Proteins That Are Essential for Conjugation.

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Miguel-Arribas, Andrés; Hao, Jian-An; Luque-Ortega, Juan R; Ramachandran, Gayetri; Val-Calvo, Jorge; Gago-Córdoba, César; González-Álvarez, Daniel; Abia, David; Alfonso, Carlos; Wu, Ling J; Meijer, Wilfried J J

2017-01-01

Bacterial conjugation is the process by which a conjugative element (CE) is transferred horizontally from a donor to a recipient cell via a connecting pore. One of the first steps in the conjugation process is the formation of a nucleoprotein complex at the origin of transfer ( oriT ), where one of the components of the nucleoprotein complex, the relaxase, introduces a site- and strand specific nick to initiate the transfer of a single DNA strand into the recipient cell. In most cases, the nucleoprotein complex involves, besides the relaxase, one or more additional proteins, named auxiliary proteins, which are encoded by the CE and/or the host. The conjugative plasmid pLS20 replicates in the Gram-positive Firmicute bacterium Bacillus subtilis . We have recently identified the relaxase gene and the oriT of pLS20, which are separated by a region of almost 1 kb. Here we show that this region contains two auxiliary genes that we name aux1 LS20 and aux2 LS20 , and which we show are essential for conjugation. Both Aux1 LS20 and Aux2 LS20 are predicted to contain a Ribbon-Helix-Helix DNA binding motif near their N-terminus. Analyses of the purified proteins show that Aux1 LS20 and Aux2 LS20 form tetramers and hexamers in solution, respectively, and that they both bind preferentially to oriT LS20 , although with different characteristics and specificities. In silico analyses revealed that genes encoding homologs of Aux1 LS20 and/or Aux2 LS20 are located upstream of almost 400 relaxase genes of the Rel LS20 family (MOB L ) of relaxases. Thus, Aux1 LS20 and Aux2 LS20 of pLS20 constitute the founding member of the first two families of auxiliary proteins described for CEs of Gram-positive origin.

Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

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Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

Learning of Sensory Sequences in Cerebellar Patients

Science.gov (United States)

Frings, Markus; Boenisch, Raoul; Gerwig, Marcus; Diener, Hans-Christoph; Timmann, Dagmar

2004-01-01

A possible role of the cerebellum in detecting and recognizing event sequences has been proposed. The present study sought to determine whether patients with cerebellar lesions are impaired in the acquisition and discrimination of sequences of sensory stimuli of different modalities. A group of 26 cerebellar patients and 26 controls matched for…

Propiedades psicométricas de la Escala de lenguaje para preescolares (PLS-3 colombianos

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Rita Flórez Romero

2013-01-01

Full Text Available Objetivo.El presente estudio buscó caracterizar las propiedades psicométricas del instrumento Preschool Language Scale – 3(PLS-3, en una muestra de 477 niños colombianos de cuatro a siete años de la ciudad de Bogotá D. C. Método. Para lograr este propósito, se realizaron análisis de coeficientes de discriminación, dificultad y matriz de relaciones tetracóricas. Resultados. Se encontraron apropiados niveles de confiabilidad, alta sensibilidad a la evolución de la comprensión y producción lingüística de los niños, así como un bajo índice de dificultad en algunos reactivos. Conclusión. Estos resultados se discuten a la luz de índices de discriminación en pruebas de desarrollo lingüístico típico y atípico.

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

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Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

Developing renal nurses' buttonhole cannulation skills using e-learning.

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Blackman, Ian R; Mannix, Trudi; Sinclair, Peter M

2014-03-01

It has previously been shown that nurses can learn clinical nursing skills by e-learning (online), and that many variables will influence how well nurses adopt learned clinical skills using distance education. This study aimed to identify and measure the strength of those factors which would simultaneously influence registered nurses' (RNs') beliefs about their own learning about buttonhole cannulation, using e-learning. An online Likert style survey consisting of a list of statements related to knowledge and skill domains considered crucial in the area of buttonhole cannulation was distributed to 101 RNs before and after completing an e-learning programme. Participants were required to identify their current level of self-confidence in relationship to each of the statements. Measures of RNs' self-rated abilities to assess and implement buttonhole cannulation after completing a related e-learning program were tested using a Partial Least Squares Analysis (PLS-PATH) programme. The study's results strongly identify that the nurses' ability to meet both clinical and educational outcomes of the renal e-learning module can be predicted by six variables, none of which are directly related to the participants' demographic or clinical backgrounds. These findings support the use of e-learning to teach clinical skills to RNs, and demonstrate the value of Partial Least Squares Analysis in determining influential learning factors. © 2014 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Ego Depletion Impairs Implicit Learning

Science.gov (United States)

Thompson, Kelsey R.; Sanchez, Daniel J.; Wesley, Abigail H.; Reber, Paul J.

2014-01-01

Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent. PMID:25275517

Ego depletion impairs implicit learning.

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Kelsey R Thompson

Full Text Available Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent.

Ego depletion impairs implicit learning.

Science.gov (United States)

Thompson, Kelsey R; Sanchez, Daniel J; Wesley, Abigail H; Reber, Paul J

2014-01-01

Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent.

The Effects of CBI Lesson Sequence Type and Field Dependence on Learning from Computer-Based Cooperative Instruction in Web

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Ipek, Ismail

2010-01-01

The purpose of this study was to investigate the effects of CBI lesson sequence type and cognitive style of field dependence on learning from Computer-Based Cooperative Instruction (CBCI) in WEB on the dependent measures, achievement, reading comprehension and reading rate. Eighty-seven college undergraduate students were randomly assigned to…

A teaching and learning sequence about the interplay of chance and determinism in nonlinear systems

International Nuclear Information System (INIS)

Stavrou, D; Duit, R; Komorek, M

2008-01-01

A teaching and learning sequence aimed at introducing upper secondary school students to the interplay between chance and determinism in nonlinear systems is presented. Three experiments concerning nonlinear systems (deterministic chaos, self-organization and fractals) and one experiment concerning linear systems are introduced. Thirty upper secondary students' capabilities and difficulties in understanding the scientific point of view were investigated, using a teaching experiment design. The results show that most students were capable of sound explanations concerning the interplay of chance and determinism in nonlinear systems

A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.

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Benjamin G Schultz

Full Text Available Implicit learning (IL occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigated in temporal pattern learning. Two experiments by Schultz, Stevens, Keller, and Tillmann demonstrated the IL of auditory temporal patterns using a serial reaction-time task and a generation task based on the process dissociation procedure. The generation task demonstrated that learning was implicit in both experiments via motor fluency, that is, the inability to suppress learned information. With the aim to disentangle conscious and unconscious processes, we analyze unreported recognition data associated with the Schultz et al. experiments using the sequence identification measurement model. The model assumes that perceptual fluency reflects unconscious processes and IL. For Experiment 1, the model indicated that conscious and unconscious processes contributed to recognition of temporal patterns, but that unconscious processes had a greater influence on recognition than conscious processes. In the model implementation of Experiment 2, there was equal contribution of conscious and unconscious processes in the recognition of temporal patterns. As Schultz et al. demonstrated IL in both experiments using a generation task, and the conditions reported here in Experiments 1 and 2 were identical, two explanations are offered for the discrepancy in model and behavioral results based on the two tasks: 1 perceptual fluency may not be necessary to infer IL, or 2 conscious control over implicitly learned information may vary as a function of perceptual fluency and motor fluency.

Housing Value Forecasting Based on Machine Learning Methods

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Jingyi Mu

2014-01-01

Full Text Available In the era of big data, many urgent issues to tackle in all walks of life all can be solved via big data technique. Compared with the Internet, economy, industry, and aerospace fields, the application of big data in the area of architecture is relatively few. In this paper, on the basis of the actual data, the values of Boston suburb houses are forecast by several machine learning methods. According to the predictions, the government and developers can make decisions about whether developing the real estate on corresponding regions or not. In this paper, support vector machine (SVM, least squares support vector machine (LSSVM, and partial least squares (PLS methods are used to forecast the home values. And these algorithms are compared according to the predicted results. Experiment shows that although the data set exists serious nonlinearity, the experiment result also show SVM and LSSVM methods are superior to PLS on dealing with the problem of nonlinearity. The global optimal solution can be found and best forecasting effect can be achieved by SVM because of solving a quadratic programming problem. In this paper, the different computation efficiencies of the algorithms are compared according to the computing times of relevant algorithms.

Students' Learning of a Generalized Theory of Sound Transmission from a Teaching-Learning Sequence about Sound, Hearing and Health

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West, Eva; Wallin, Anita

2013-04-01

Learning abstract concepts such as sound often involves an ontological shift because to conceptualize sound transmission as a process of motion demands abandoning sound transmission as a transfer of matter. Thus, for students to be able to grasp and use a generalized model of sound transmission poses great challenges for them. This study involved 199 students aged 10-14. Their views about sound transmission were investigated before and after teaching by comparing their written answers about sound transfer in different media. The teaching was built on a research-based teaching-learning sequence (TLS), which was developed within a framework of design research. The analysis involved interpreting students' underlying theories of sound transmission, including the different conceptual categories that were found in their answers. The results indicated a shift in students' understandings from the use of a theory of matter before the intervention to embracing a theory of process afterwards. The described pattern was found in all groups of students irrespective of age. Thus, teaching about sound and sound transmission is fruitful already at the ages of 10-11. However, the older the students, the more advanced is their understanding of the process of motion. In conclusion, the use of a TLS about sound, hearing and auditory health promotes students' conceptualization of sound transmission as a process in all grades. The results also imply some crucial points in teaching and learning about the scientific content of sound.

Comparison of Machine Learning Techniques in Inferring Phytoplankton Size Classes

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Shuibo Hu

2018-03-01

Full Text Available The size of phytoplankton not only influences its physiology, metabolic rates and marine food web, but also serves as an indicator of phytoplankton functional roles in ecological and biogeochemical processes. Therefore, some algorithms have been developed to infer the synoptic distribution of phytoplankton cell size, denoted as phytoplankton size classes (PSCs, in surface ocean waters, by the means of remotely sensed variables. This study, using the NASA bio-Optical Marine Algorithm Data set (NOMAD high performance liquid chromatography (HPLC database, and satellite match-ups, aimed to compare the effectiveness of modeling techniques, including partial least square (PLS, artificial neural networks (ANN, support vector machine (SVM and random forests (RF, and feature selection techniques, including genetic algorithm (GA, successive projection algorithm (SPA and recursive feature elimination based on support vector machine (SVM-RFE, for inferring PSCs from remote sensing data. Results showed that: (1 SVM-RFE worked better in selecting sensitive features; (2 RF performed better than PLS, ANN and SVM in calibrating PSCs retrieval models; (3 machine learning techniques produced better performance than the chlorophyll-a based three-component method; (4 sea surface temperature, wind stress, and spectral curvature derived from the remote sensing reflectance at 490, 510, and 555 nm were among the most sensitive features to PSCs; and (5 the combination of SVM-RFE feature selection techniques and random forests regression was recommended for inferring PSCs. This study demonstrated the effectiveness of machine learning techniques in selecting sensitive features and calibrating models for PSCs estimations with remote sensing.

Improved ability of biological and previous caries multimarkers to predict caries disease as revealed by multivariate PLS modelling

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Ericson Thorild

2009-11-01

Full Text Available Abstract Background Dental caries is a chronic disease with plaque bacteria, diet and saliva modifying disease activity. Here we have used the PLS method to evaluate a multiplicity of such biological variables (n = 88 for ability to predict caries in a cross-sectional (baseline caries and prospective (2-year caries development setting. Methods Multivariate PLS modelling was used to associate the many biological variables with caries recorded in thirty 14-year-old children by measuring the numbers of incipient and manifest caries lesions at all surfaces. Results A wide but shallow gliding scale of one fifth caries promoting or protecting, and four fifths non-influential, variables occurred. The influential markers behaved in the order of plaque bacteria > diet > saliva, with previously known plaque bacteria/diet markers and a set of new protective diet markers. A differential variable patterning appeared for new versus progressing lesions. The influential biological multimarkers (n = 18 predicted baseline caries better (ROC area 0.96 than five markers (0.92 and a single lactobacilli marker (0.7 with sensitivity/specificity of 1.87, 1.78 and 1.13 at 1/3 of the subjects diagnosed sick, respectively. Moreover, biological multimarkers (n = 18 explained 2-year caries increment slightly better than reported before but predicted it poorly (ROC area 0.76. By contrast, multimarkers based on previous caries predicted alone (ROC area 0.88, or together with biological multimarkers (0.94, increment well with a sensitivity/specificity of 1.74 at 1/3 of the subjects diagnosed sick. Conclusion Multimarkers behave better than single-to-five markers but future multimarker strategies will require systematic searches for improved saliva and plaque bacteria markers.

Intentional Learning Vs Incidental Learning

OpenAIRE

Shahbaz Ahmed

2017-01-01

This study is conducted to demonstrate the knowledge of intentional learning and incidental learning. Hypothesis of this experiment is intentional learning is better than incidental learning, participants were demonstrated and were asked to learn the 10 non sense syllables in a specific sequence from the colored cards in the end they were asked to recall the background color of each card instead of non-sense syllables. Independent variables of the experiment are the colored cards containing n...

Evaluation of in-line Raman data for end-point determination of a coating process: Comparison of Science-Based Calibration, PLS-regression and univariate data analysis.

Science.gov (United States)

Barimani, Shirin; Kleinebudde, Peter

2017-10-01

A multivariate analysis method, Science-Based Calibration (SBC), was used for the first time for endpoint determination of a tablet coating process using Raman data. Two types of tablet cores, placebo and caffeine cores, received a coating suspension comprising a polyvinyl alcohol-polyethylene glycol graft-copolymer and titanium dioxide to a maximum coating thickness of 80µm. Raman spectroscopy was used as in-line PAT tool. The spectra were acquired every minute and correlated to the amount of applied aqueous coating suspension. SBC was compared to another well-known multivariate analysis method, Partial Least Squares-regression (PLS) and a simpler approach, Univariate Data Analysis (UVDA). All developed calibration models had coefficient of determination values (R 2 ) higher than 0.99. The coating endpoints could be predicted with root mean square errors (RMSEP) less than 3.1% of the applied coating suspensions. Compared to PLS and UVDA, SBC proved to be an alternative multivariate calibration method with high predictive power. Copyright © 2017 Elsevier B.V. All rights reserved.

Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data.

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Manal Helal

Full Text Available BACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52% corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra

Implicit visual learning and the expression of learning.

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Haider, Hilde; Eberhardt, Katharina; Kunde, Alexander; Rose, Michael

2013-03-01

Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response devices (keyboard vs. mouse) in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes. Copyright © 2012 Elsevier Inc. All rights reserved.

Metabolic Profiling and Classification of Propolis Samples from Southern Brazil: An NMR-Based Platform Coupled with Machine Learning.

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Maraschin, Marcelo; Somensi-Zeggio, Amélia; Oliveira, Simone K; Kuhnen, Shirley; Tomazzoli, Maíra M; Raguzzoni, Josiane C; Zeri, Ana C M; Carreira, Rafael; Correia, Sara; Costa, Christopher; Rocha, Miguel

2016-01-22

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching ∼90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Exploring the Moderating Role of Perceived Flexibility Advantages in Mobile Learning Continuance Intention (MLCI

Directory of Open Access Journals (Sweden)

Rui-Ting Huang

2014-07-01

Full Text Available The primary purpose of this study was to explore the key factors that could affect mobile learning continuance intention (MLCI, and examine the moderating effect of perceived flexibility advantages (PFA on the relationship between key mobile learning elements and continuance intention. Five hundred undergraduate students who had previously adopted mobile devices to learn English took part in this study. Partial least squares (PLS analysis was utilized to test the hypotheses in this study. It has been found that the perceived usefulness of mobile technology, subjective norm, and self-management of learning could be closely linked to mobile learning continuance intention. With particular respect to the moderating role of perceived flexibility advantages, it has been demonstrated that PFA could moderate the relationship between perceived usefulness of mobile technology and mobile learning continuance intention, as well as the association between subjective norm and mobile learning continuance intention, whereas PFA did not moderate the link between self-management of learning and mobile learning continuance intention.This report has further added to the body of knowledge in the field of mobile learning through empirical examination.

New PLS analysis approach to wine volatile compounds characterization by near infrared spectroscopy (NIR).

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Genisheva, Z; Quintelas, C; Mesquita, D P; Ferreira, E C; Oliveira, J M; Amaral, A L

2018-04-25

This work aims to explore the potential of near infrared (NIR) spectroscopy to quantify volatile compounds in Vinho Verde wines, commonly determined by gas chromatography. For this purpose, 105 Vinho Verde wine samples were analyzed using Fourier transform near infrared (FT-NIR) transmission spectroscopy in the range of 5435 cm -1 to 6357 cm -1 . Boxplot and principal components analysis (PCA) were performed for clusters identification and outliers removal. A partial least square (PLS) regression was then applied to develop the calibration models, by a new iterative approach. The predictive ability of the models was confirmed by an external validation procedure with an independent sample set. The obtained results could be considered as quite good with coefficients of determination (R 2 ) varying from 0.94 to 0.97. The current methodology, using NIR spectroscopy and chemometrics, can be seen as a promising rapid tool to determine volatile compounds in Vinho Verde wines. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

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Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

2017-05-01

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture

OpenAIRE

Park, Seong Hyeon; Kim, ByeongDo; Kang, Chang Mook; Chung, Chung Choo; Choi, Jun Won

2018-01-01

In this paper, we propose a deep learning based vehicle trajectory prediction technique which can generate the future trajectory sequence of surrounding vehicles in real time. We employ the encoder-decoder architecture which analyzes the pattern underlying in the past trajectory using the long short-term memory (LSTM) based encoder and generates the future trajectory sequence using the LSTM based decoder. This structure produces the $K$ most likely trajectory candidates over occupancy grid ma...

Intelligent Web-Based Learning System with Personalized Learning Path Guidance

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Chen, C. M.

2008-01-01

Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…

Continued usage of e-learning: Expectations and performance

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Fernando Antonio de Melo Pereira

2015-10-01

Full Text Available The present study aims to investigate the determinants of satisfaction and the resulting continuance intention use in e-learning context. The constructs of decomposed expectancy disconfirmation theory (DEDT are evaluated from the perspective of users of a virtual learning environment (VLE in relation to expectations and perceived performance. An online survey collected responses from 197 students of a public management course in distance mode. Structural equation modeling was operationalized by the method of partial least squares in Smart PLS software. The results showed that there is a relationship between quality, usability, value and value disconfirmation with satisfaction. Likewise, satisfaction proved to be decisive for the continuance intention use. However, there were no significant relationships between quality disconfirmation and usability disconfirmation with satisfaction. Based on the results, is discussed the theoretical and practical implications of the structural model found by the search.

Improvement of the thermo-mechanical position stability of the beam position monitor in the PLS-II

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Ha, Taekyun; Hong, Mansu; Kwon, Hyuckchae; Han, Hongsik; Park, Chongdo

2016-09-01

In the storage ring of the Pohang Light Source-II (PLS-II), we reduced the mechanical displacement of the electron-beam position monitors (e-BPMs) that is caused by heating during e-beam storage. The BPM pickup itself must be kept stable to sub-micrometer precision in order for a stable photon beam to be provided to beamlines because the orbit feedback system is programmed to make the electron beam pass through the center of the BPM. Thermal deformation of the vacuum chambers on which the BPM pickups are mounted is inevitable when the electron beam current is changed by an unintended beam abort. We reduced this deformation by improving the vacuum chamber support and by enhancing the water cooling. We report a thermo-mechanical analysis and displacement measurements for the BPM pickups after improvements.

[Genome-wide identification and bioinformatic analysis of PPR gene family in tomato].

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Ding, Anming; Li, Ling; Qu, Xu; Sun, Tingting; Chen, Yaqiong; Zong, Peng; Li, Zunqiang; Gong, Daping; Sun, Yuhe

2014-01-01

Pentatricopeptide repeats (PPRs) genes constitute one of the largest gene families in plants, which play a broad and essential role in plant growth and development. In this study, the protein sequences annotated by the tomato (S. lycopersicum L.) genome project were screened with the Pfam PPR sequences. A total of 471 putative PPR-encoding genes were identified. Based on the motifs defined in A. thaliana L., protein structure and conserved sequences for each tomato motif were analyzed. We also analyzed phylogenetic relationship, subcellular localization, expression and GO analysis of the identified gene sequences. Our results demonstrate that tomato PPR gene family contains two subfamilies, P and PLS, each accounting for half of the family. PLS subfamily can be divided into four subclasses i.e., PLS, E, E+ and DYW. Each subclass of sequences forms a clade in the phylogenetic tree. The PPR motifs were found highly conserved among plants. The tomato PPR genes were distributed over 12 chromosomes and most of them lack introns. The majority of PPR proteins harbor mitochondrial or chloroplast localization sequences, whereas GO analysis showed that most PPR proteins participate in RNA-related biological processes.

Examining the Role of Childhood Experiences in Developing Altruistic and Knowledge Sharing Behaviors among Children in Their Later Life: A Partial Least Squares (PLS Path Modeling Approach

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Imran Ali

2018-01-01

Full Text Available Previous research on child development advocates that motivating children to make a choice to forfeit their own toys with others develop sharing behavior in later life. Borrowing the conceptual background from the child development theory, this study proposes a model of knowledge sharing behavior among individuals at the workplace. The study proposes a unique conceptual model that integrates the cognitive/behavioral, and other childhood theories to explain the knowledge sharing behavior among individuals. The study uses psychological, cognitive, behavioral and social learning theories to explain the development of altruistic behavior in childhood as a determinant of knowledge sharing behavior. This study develops and empirically tests a research framework which explains the role of childhood experiences in developing altruistic behavior among children and the translation of this altruistic behavior into knowledge sharing behavior later in their professional life. This study explores those relationships using PLS-SEM with data from 310 individuals from Pakistan. The study concludes the role of parents and child-rearing practices as central in developing children’s altruistic attitude that leads to knowledge sharing behavior in their later life. The implications and future research directions are discussed in details.

Prediction of SOC content by Vis-NIR spectroscopy at European scale using a modified local PLS algorithm

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Nocita, M.; Stevens, A.; Toth, G.; van Wesemael, B.; Montanarella, L.

2012-12-01

In the context of global environmental change, the estimation of carbon fluxes between soils and the atmosphere has been the object of a growing number of studies. This has been motivated notably by the possibility to sequester CO2 into soils by increasing the soil organic carbon (SOC) stocks and by the role of SOC in maintaining soil quality. Spatial variability of SOC masks its slow accumulation or depletion, and the sampling density required to detect a change in SOC content is often very high and thus very expensive and labour intensive. Visible near infrared diffuse reflectance spectroscopy (Vis-NIR DRS) has been shown to be a fast, cheap and efficient tool for the prediction of SOC at fine scales. However, when applied to regional or country scales, Vis-NIR DRS did not provide sufficient accuracy as an alternative to standard laboratory soil analysis for SOC monitoring. Under the framework of Land Use/Cover Area Frame Statistical Survey (LUCAS) project of the European Commission's Joint Research Centre (JRC), about 20,000 samples were collected all over European Union. Soil samples were analyzed for several physical and chemical parameters, and scanned with a Vis-NIR spectrometer in the same laboratory. The scope of our research was to predict SOC content at European scale using LUCAS spectral library. We implemented a modified local partial least square regression (l-PLS) including, in addition to spectral distance, other potentially useful covariates (geography, texture, etc.) to select for each unknown sample a group of predicting neighbours. The dataset was split in mineral soils under cropland, mineral soils under grassland, mineral soils under woodland, and organic soils due to the extremely diverse spectral response of the four classes. Four every class training (70%) and test (30%) sets were created to calibrate and validate the SOC prediction models. The results showed very good prediction ability for mineral soils under cropland and mineral soils

Sensitivity to structure in action sequences: An infant event-related potential study.

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Monroy, Claire D; Gerson, Sarah A; Domínguez-Martínez, Estefanía; Kaduk, Katharina; Hunnius, Sabine; Reid, Vincent

2017-05-06

Infants are sensitive to structure and patterns within continuous streams of sensory input. This sensitivity relies on statistical learning, the ability to detect predictable regularities in spatial and temporal sequences. Recent evidence has shown that infants can detect statistical regularities in action sequences they observe, but little is known about the neural process that give rise to this ability. In the current experiment, we combined electroencephalography (EEG) with eye-tracking to identify electrophysiological markers that indicate whether 8-11-month-old infants detect violations to learned regularities in action sequences, and to relate these markers to behavioral measures of anticipation during learning. In a learning phase, infants observed an actor performing a sequence featuring two deterministic pairs embedded within an otherwise random sequence. Thus, the first action of each pair was predictive of what would occur next. One of the pairs caused an action-effect, whereas the second did not. In a subsequent test phase, infants observed another sequence that included deviant pairs, violating the previously observed action pairs. Event-related potential (ERP) responses were analyzed and compared between the deviant and the original action pairs. Findings reveal that infants demonstrated a greater Negative central (Nc) ERP response to the deviant actions for the pair that caused the action-effect, which was consistent with their visual anticipations during the learning phase. Findings are discussed in terms of the neural and behavioral processes underlying perception and learning of structured action sequences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detecting Scareware by Mining Variable Length Instruction Sequences

OpenAIRE

Shahzad, Raja Khurram; Lavesson, Niklas

2011-01-01

Scareware is a recent type of malicious software that may pose financial and privacy-related threats to novice users. Traditional countermeasures, such as anti-virus software, require regular updates and often lack the capability of detecting novel (unseen) instances. This paper presents a scareware detection method that is based on the application of machine learning algorithms to learn patterns in extracted variable length opcode sequences derived from instruction sequences of binary files....

A comprehensive account of sound sequence imitation in the songbird.

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Maren Westkott

2016-07-01

Full Text Available The amazing imitation capabilities of songbirds show that they can memorize sensory sequences and transform them into motor activities which in turn generate the original sound sequences. This suggests that the bird's brain can learn 1. to reliably reproduce spatio-temporal sensory representations and 2. to transform them into corresponding spatio-temporal motor activations by using an inverse mapping. Neither the synaptic mechanisms nor the network architecture enabling these two fundamental aspects of imitation learning are known. We propose an architecture of coupled neuronal modules that mimick areas in the song bird and show that a unique synaptic plasticity mechanism can serve to learn both, sensory sequences in a recurrent neuronal network, as well as an inverse model that transforms the sensory memories into the corresponding motor activations. The proposed membrane potential dependent learning rule together with the architecture that includes basic features of the bird's brain represents the first comprehensive account of bird imitation learning based on spiking neurons.

PLS models for determination of SARA analysis of Colombian vacuum residues and molecular distillation fractions using MIR-ATR

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Jorge A. Orrego-Ruiz

2014-06-01

Full Text Available In this work, prediction models of Saturates, Aromatics, Resins and Asphaltenes fractions (SARA from thirty-seven vacuum residues of representative Colombian crudes and eighteen fractions of molecular distillation process were obtained. Mid-Infrared (MIR Attenuated Total Reflection (ATR spectroscopy in combination with partial least squares (PLS regression analysis was used to estimate accurately SARA analysis in these kind of samples. Calibration coefficients of prediction models were for saturates, aromatics, resins and asphaltenes fractions, 0.99, 0.96, 0.97 and 0.99, respectively. This methodology permits to control the molecular distillation process since small differences in chemical composition can be detected. Total time elapsed to give the SARA analysis per sample is 10 minutes.

Draft genome sequence of Actinotignum schaalii DSM 15541T: Genetic insights into the lifestyle, cell fitness and virulence.

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Atteyet F Yassin

Full Text Available The permanent draft genome sequence of Actinotignum schaalii DSM 15541T is presented. The annotated genome includes 2,130,987 bp, with 1777 protein-coding and 58 rRNA-coding genes. Genome sequence analysis revealed absence of genes encoding for: components of the PTS systems, enzymes of the TCA cycle, glyoxylate shunt and gluconeogensis. Genomic data revealed that A. schaalii is able to oxidize carbohydrates via glycolysis, the nonoxidative pentose phosphate and the Entner-Doudoroff pathways. Besides, the genome harbors genes encoding for enzymes involved in the conversion of pyruvate to lactate, acetate and ethanol, which are found to be the end products of carbohydrate fermentation. The genome contained the gene encoding Type I fatty acid synthase required for de novo FAS biosynthesis. The plsY and plsX genes encoding the acyltransferases necessary for phosphatidic acid biosynthesis were absent from the genome. The genome harbors genes encoding enzymes responsible for isoprene biosynthesis via the mevalonate (MVA pathway. Genes encoding enzymes that confer resistance to reactive oxygen species (ROS were identified. In addition, A. schaalii harbors genes that protect the genome against viral infections. These include restriction-modification (RM systems, type II toxin-antitoxin (TA, CRISPR-Cas and abortive infection system. A. schaalii genome also encodes several virulence factors that contribute to adhesion and internalization of this pathogen such as the tad genes encoding proteins required for pili assembly, the nanI gene encoding exo-alpha-sialidase, genes encoding heat shock proteins and genes encoding type VII secretion system. These features are consistent with anaerobic and pathogenic lifestyles. Finally, resistance to ciprofloxacin occurs by mutation in chromosomal genes that encode the subunits of DNA-gyrase (GyrA and topisomerase IV (ParC enzymes, while resistant to metronidazole was due to the frxA gene, which encodes NADPH

Interference-free acquisition of overlapping sequences in explicit spatial memory.

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Eggert, Thomas; Drever, Johannes; Straube, Andreas

2014-04-01

Some types of human sequential memory, e.g. the acquisition of a new composition by a trained musician, seem to be very efficient in extending the length of a memorized sequence and in flexible reuse of known subsequences in a newly acquired sequential context. This implies that interference between known and newly acquired subsequences can be avoided even when learning a sequence which is a partial mutation of a known sequence. It is known that established motor sequences do not have such flexibility. Using learning of deferred imitation, the current study investigates the flexibility of explicit spatial memory by quantifying the interferences between successively acquired, partially overlapping sequences. After learning a spatial sequence on day 1, this sequence was progressively modified on day 2. On day 3, a retention test was performed with both the initial and the modified sequence. The results show that subjects performed very well on day 1 and day 2. No spatial interference between changed and unchanged targets was observed during the stepwise progressive modification of the reproduced sequence. Surprisingly, subjects performed well on both sequences on day 3. Comparison with a control experiment without intermediate mutation training showed that the initial training on day 1 did not proactively interfere with the retention of the modified sequence on day 3. Vice versa, the mutation training on day 2 did not interfere retroactively with the retention of the original sequence as tested on day 3. The results underline the flexibility in acquiring explicit spatial memory. Copyright © 2014 Elsevier B.V. All rights reserved.

Predicting Post-Translational Modifications from Local Sequence Fragments Using Machine Learning Algorithms: Overview and Best Practices.

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Tatjewski, Marcin; Kierczak, Marcin; Plewczynski, Dariusz

2017-01-01

Here, we present two perspectives on the task of predicting post translational modifications (PTMs) from local sequence fragments using machine learning algorithms. The first is the description of the fundamental steps required to construct a PTM predictor from the very beginning. These steps include data gathering, feature extraction, or machine-learning classifier selection. The second part of our work contains the detailed discussion of more advanced problems which are encountered in PTM prediction task. Probably the most challenging issues which we have covered here are: (1) how to address the training data class imbalance problem (we also present statistics describing the problem); (2) how to properly set up cross-validation folds with an approach which takes into account the homology of protein data records, to address this problem we present our folds-over-clusters algorithm; and (3) how to efficiently reach for new sources of learning features. Presented techniques and notes resulted from intense studies in the field, performed by our and other groups, and can be useful both for researchers beginning in the field of PTM prediction and for those who want to extend the repertoire of their research techniques.

Supervised Sequence Labelling with Recurrent Neural Networks

CERN Document Server

Graves, Alex

2012-01-01

Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary.    The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional...

Constraint Satisfaction Inference : Non-probabilistic Global Inference for Sequence Labelling

NARCIS (Netherlands)

Canisius, S.V.M.; van den Bosch, A.; Daelemans, W.; Basili, R.; Moschitti, A.

2006-01-01

We present a new method for performing sequence labelling based on the idea of using a machine-learning classifier to generate several possible output sequences, and then applying an inference procedure to select the best sequence among those. Most sequence labelling methods following a similar

Beta band transcranial alternating (tACS and direct current stimulation (tDCS applied after initial learning facilitate retrieval of a motor sequence

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Vanessa eKrause

2016-01-01

Full Text Available The primary motor cortex (M1 contributes to the acquisition and early consolidation of a motor sequence. Although the relevance of M1 excitability for motor learning has been supported, the significance of M1 oscillations remains an open issue. This study aims at investigating to what extent retrieval of a newly learned motor sequence can be differentially affected by motor-cortical transcranial alternating (tACS and direct current stimulation (tDCS. Alpha (10 Hz, beta (20 Hz or sham tACS was applied in 36 right-handers. Anodal or cathodal tDCS was applied in 30 right-handers. Participants learned an eight-digit serial reaction time task (SRTT; sequential vs. random with the right hand. Stimulation was applied to the left M1 after SRTT acquisition at rest for ten minutes. Reaction times were analyzed at baseline, end of acquisition, retrieval immediately after stimulation and reacquisition after eight further sequence repetitions.Reaction times during retrieval were significantly faster following 20 Hz tACS as compared to 10 Hz and sham tACS indicating a facilitation of early consolidation. TDCS yielded faster reaction times, too, independent of polarity. No significant differences between 20 Hz tACS and tDCS effects on retrieval were found suggesting that 20 Hz effects might be associated with altered motor-cortical excitability. Based on the behavioural modulation yielded by tACS and tDCS one might speculate that altered motor-cortical beta oscillations support early motor consolidation possibly associated with neuroplastic reorganization.

Using a Learning Activity Sequence in Large-Enrollment Physical Geology Classes: Supporting the Needs of Underserved Students While Motivating Interest, Learning, and Success

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Pun, A.; Smith, G. A.

2011-12-01

The learning activity sequence (LAS) strategy is a student-focused pedagogy that emphasizes active classroom learning to promote learning among all students, and in particular, those with diverse backgrounds. Online assessments both set the stage for active learning and help students synthesize material during their learning. UNM is one of only two Carnegie Research University Very High institutions also designated as Hispanic-serving and the only state flagship university that is also a majority-minority undergraduate institution. In 2010 Hispanics comprised 40% of 20,655 undergraduates (and 49% of freshmen), 37% of undergraduates were Pell Grant recipients (the largest proportion of any public flagship research university; J. Blacks Higher Ed., 2009) and 44% of incoming freshmen were first-generation students. To maximize student learning in this environment rich in traditionally underserved students, we designed a LAS for nonmajor physical geology (enrollments 100-160) that integrates in-class instruction with structured out-of-class learning. The LAS has 3 essential parts: Students read before class to acquire knowledge used during in-class collaborative, active-learning activities that build conceptual understanding. Lastly, students review notes and synthesize what they've learned before moving on to the next topic. The model combines online and in-class learning and assessment: Online reading assessments before class; active-learning experiences during class; online learning assessments after class. Class sessions include short lectures, peer instruction "clickers", and small-group problem solving (lecture tutorials). Undergraduate Peer-Learning Facilitators are available during class time to help students with problem solving. Effectiveness of the LAS approach is reflected in three types of measurements. (1) Using the LAS strategy, the overall rate of students earning a grade of C or higher is higher than compared to the average for all large

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

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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…

Magnifying visual target information and the role of eye movements in motor sequence learning.

Science.gov (United States)

Massing, Matthias; Blandin, Yannick; Panzer, Stefan

2016-01-01

An experiment investigated the influence of eye movements on learning a simple motor sequence task when the visual display was magnified. The task was to reproduce a 1300 ms spatial-temporal pattern of elbow flexions and extensions. The spatial-temporal pattern was displayed in front of the participants. Participants were randomly assigned to four groups differing on eye movements (free to use their eyes/instructed to fixate) and the visual display (small/magnified). All participants had to perform a pre-test, an acquisition phase, a delayed retention test, and a transfer test. The results indicated that participants in each practice condition increased their performance during acquisition. The participants who were permitted to use their eyes in the magnified visual display outperformed those who were instructed to fixate on the magnified visual display. When a small visual display was used, the instruction to fixate induced no performance decrements compared to participants who were permitted to use their eyes during acquisition. The findings demonstrated that a spatial-temporal pattern can be learned without eye movements, but being permitting to use eye movements facilitates the response production when the visual angle is increased. Copyright © 2015 Elsevier B.V. All rights reserved.

Analyzing State Sequences with Probabilistic Suffix Trees: The PST R Package

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Alexis Gabadinho

2016-08-01

Full Text Available This article presents the PST R package for categorical sequence analysis with probabilistic suffix trees (PSTs, i.e., structures that store variable-length Markov chains (VLMCs. VLMCs allow to model high-order dependencies in categorical sequences with parsimonious models based on simple estimation procedures. The package is specifically adapted to the field of social sciences, as it allows for VLMC models to be learned from sets of individual sequences possibly containing missing values; in addition, the package is extended to account for case weights. This article describes how a VLMC model is learned from one or more categorical sequences and stored in a PST. The PST can then be used for sequence prediction, i.e., to assign a probability to whole observed or artificial sequences. This feature supports data mining applications such as the extraction of typical patterns and outliers. This article also introduces original visualization tools for both the model and the outcomes of sequence prediction. Other features such as functions for pattern mining and artificial sequence generation are described as well. The PST package also allows for the computation of probabilistic divergence between two models and the fitting of segmented VLMCs, where sub-models fitted to distinct strata of the learning sample are stored in a single PST.

Determinação simultânea dos teores de cinza e proteína em farinha de trigo empregando NIRR-PLS e DRIFT-PLS Simultaneous determination of ash content and protein in wheat flour using infrared reflection techniques and partial least-squares regression (PLS

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Marco Flôres Ferrão

2004-09-01

Full Text Available As técnicas de espectroscopia por reflexão no infravermelho próximo (NIRRS e por reflexão difusa no infravermelho médio com transformada de Fourier (DRIFTS foram empregadas com o método de regressão multivariado por mínimos quadrados parciais (PLS para a determinação simultânea dos teores de proteína e cinza em amostras de farinha de trigo da variedade Triticum aestivum L. Foram coletados espectros no infravermelho em duplicata de 100 amostras, empregando-se acessórios de reflexão difusa. Os teores de proteína (8,85-13,23% e cinza (0,330-1,287%, empregados como referência, foram determinados pelo método Kjeldhal e método gravimétrico, respectivamente. Os dados espectrais foram utilizados no formato log(1/R, bem como suas derivadas de primeira e segunda ordem, sendo pré-processados usando-se os dados centrados na média (MC ou escalados pela variância (VS ou ambos. Cinqüenta e cinco amostras foram usadas para calibração e 45 para validação dos modelos, adotando-se como critério de construção os valores mínimos do erro padrão de calibração (SEC e do erro padrão de validação (SEV. Estes valores foram inferiores a 0,33% para proteína e a 0,07% para cinza. Os métodos desenvolvidos apresentam como vantagens a não agressão ao ambiente, bem como permitem uma determinação direta, simultânea, rápida e não destrutiva dos teores de proteína e cinza em amostras de farinha de trigo.Partial Least Square (PLS multivariate calibration associated to Near Infrared Reflection Spectroscopy (NIRRS or Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS were used to establish methods for simultaneous determination of protein and ash content on commercial wheat flour samples of Triticum aestivum L. Duplicate spectra of 100 samples with protein content between 8.85-13.23% (Kjeldahl method and ash content between 0.330-1.287% (gravimetric method were employed to build calibration methods. The spectra were used

Time-of-flight secondary ion mass spectrometry of a range of coal samples: a chemometrics (PCA, cluster, and PLS) analysis

Energy Technology Data Exchange (ETDEWEB)

Lei Pei; Guilin Jiang; Bonnie J. Tyler; Larry L. Baxter; Matthew R. Linford [Brigham Young University, Provo, UT (United States). Department of Chemistry and Biochemistry

2008-03-15

This paper documents time-of-flight secondary ion mass spectrometry (ToF-SIMS) analyses of 34 different coal samples. In many cases, the inorganic Na{sup +}, Al{sup +}, Si{sup +}, and K{sup +} ions dominate the spectra, eclipsing the organic peaks. A scores plot of principal component 1 (PC1) versus principal component 2 (PC2) in a principal components analysis (PCA) effectively separates the coal spectra into a triangular pattern, where the different vertices of this pattern come from (I) spectra that have a strong inorganic signature that is dominated by Na{sup +}, (ii) spectra that have a strong inorganic signature that is dominated by Al{sup +}, Si{sup +}, and K{sup +}, and (iii) spectra that have a strong organic signature. Loadings plots of PC1 and PC2 confirm these observations. The spectra with the more prominent inorganic signatures come from samples with higher ash contents. Cluster analysis with the K-means algorithm was also applied to the data. The progressive clustering revealed in the dendrogram correlates extremely well with the clustering of the data points found in the scores plot of PC1 versus PC2 from the PCA. In addition, this clustering often correlates with properties of the coal samples, as measured by traditional analyses. Partial least-squares (PLS), which included the use of interval PLS and a genetic algorithm for variable selection, shows a good correlation between ToF-SIMS spectra and some of the properties measured by traditional means. Thus, ToF-SIMS appears to be a promising technique for the analysis of this important fuel. 33 refs., 9 figs., 5 tabs.

A Three-Dimensional Approach and Open Source Structure for the Design and Experimentation of Teaching-Learning Sequences: The Case of Friction

Science.gov (United States)

Besson, Ugo; Borghi, Lidia; De Ambrosis, Anna; Mascheretti, Paolo

2010-01-01

We have developed a teaching-learning sequence (TLS) on friction based on a preliminary study involving three dimensions: an analysis of didactic research on the topic, an overview of usual approaches, and a critical analysis of the subject, considered also in its historical development. We found that mostly the usual presentations do not take…

Occupational Sequences: Auto Engines 1. AT 121.

Science.gov (United States)

Korb, A. W.; And Others

In an attempt to individualize an automotive course, the Vocational-Technical Division of Northern Montana College has developed Occupational Sequences for an engine rebuilding course. Occupational Sequences, a learning or teaching aid, is an analysis of numbered operations involved in engine rebuilding. Job sheets, included in the book, provide a…

Development of a state machine sequencer for the Keck Interferometer: evolution, development, and lessons learned using a CASE tool approach

Science.gov (United States)

Reder, Leonard J.; Booth, Andrew; Hsieh, Jonathan; Summers, Kellee R.

2004-09-01

This paper presents a discussion of the evolution of a sequencer from a simple Experimental Physics and Industrial Control System (EPICS) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a Computer Aided Software Engineering (CASE) tool approach. The main purpose of the Interferometer Sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations to be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Harel finite state machine software program designed to orchestrate several lower-level hardware and software hard real-time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORBA, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

Implicit perceptual-motor skill learning in mild cognitive impairment and Parkinson's disease.

Science.gov (United States)

Gobel, Eric W; Blomeke, Kelsey; Zadikoff, Cindy; Simuni, Tanya; Weintraub, Sandra; Reber, Paul J

2013-05-01

Implicit skill learning is hypothesized to depend on nondeclarative memory that operates independent of the medial temporal lobe (MTL) memory system and instead depends on cortico striatal circuits between the basal ganglia and cortical areas supporting motor function and planning. Research with the Serial Reaction Time (SRT) task suggests that patients with memory disorders due to MTL damage exhibit normal implicit sequence learning. However, reports of intact learning rely on observations of no group differences, leading to speculation as to whether implicit sequence learning is fully intact in these patients. Patients with Parkinson's disease (PD) often exhibit impaired sequence learning, but this impairment is not universally observed. Implicit perceptual-motor sequence learning was examined using the Serial Interception Sequence Learning (SISL) task in patients with amnestic Mild Cognitive Impairment (MCI; n = 11) and patients with PD (n = 15). Sequence learning in SISL is resistant to explicit learning and individually adapted task difficulty controls for baseline performance differences. Patients with MCI exhibited robust sequence learning, equivalent to healthy older adults (n = 20), supporting the hypothesis that the MTL does not contribute to learning in this task. In contrast, the majority of patients with PD exhibited no sequence-specific learning in spite of matched overall task performance. Two patients with PD exhibited performance indicative of an explicit compensatory strategy suggesting that impaired implicit learning may lead to greater reliance on explicit memory in some individuals. The differences in learning between patient groups provides strong evidence in favor of implicit sequence learning depending solely on intact basal ganglia function with no contribution from the MTL memory system.

Protecting genomic sequence anonymity with generalization lattices.

Science.gov (United States)

Malin, B A

2005-01-01

Current genomic privacy technologies assume the identity of genomic sequence data is protected if personal information, such as demographics, are obscured, removed, or encrypted. While demographic features can directly compromise an individual's identity, recent research demonstrates such protections are insufficient because sequence data itself is susceptible to re-identification. To counteract this problem, we introduce an algorithm for anonymizing a collection of person-specific DNA sequences. The technique is termed DNA lattice anonymization (DNALA), and is based upon the formal privacy protection schema of k -anonymity. Under this model, it is impossible to observe or learn features that distinguish one genetic sequence from k-1 other entries in a collection. To maximize information retained in protected sequences, we incorporate a concept generalization lattice to learn the distance between two residues in a single nucleotide region. The lattice provides the most similar generalized concept for two residues (e.g. adenine and guanine are both purines). The method is tested and evaluated with several publicly available human population datasets ranging in size from 30 to 400 sequences. Our findings imply the anonymization schema is feasible for the protection of sequences privacy. The DNALA method is the first computational disclosure control technique for general DNA sequences. Given the computational nature of the method, guarantees of anonymity can be formally proven. There is room for improvement and validation, though this research provides the groundwork from which future researchers can construct genomics anonymization schemas tailored to specific datasharing scenarios.

Learning Recursion: Multiple Nested and Crossed Dependencies

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Meinou de Vries

2011-06-01

Full Text Available Language acquisition in both natural and artificial language learning settings crucially depends on extracting information from ordered sequences. A shared sequence learning mechanism is thus assumed to underlie both natural and artificial language learning. A growing body of empirical evidence is consistent with this hypothesis. By means of artificial language learning experiments, we may therefore gain more insight in this shared mechanism. In this paper, we review empirical evidence from artificial language learning and computational modeling studies, as well as natural language data, and suggest that there are two key factors that help deter-mine processing complexity in sequence learning, and thus in natural language processing. We propose that the specific ordering of non-adjacent dependencies (i.e. nested or crossed, as well as the number of non-adjacent dependencies to be resolved simultaneously (i.e. two or three are important factors in gaining more insight into the boundaries of human sequence learning; and thus, also in natural language processing. The implications for theories of linguistic competence are discussed.

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

Science.gov (United States)

Li, Ying Hong; Xu, Jing Yu; Tao, Lin; Li, Xiao Feng; Li, Shuang; Zeng, Xian; Chen, Shang Ying; Zhang, Peng; Qin, Chu; Zhang, Cheng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong

2016-01-01

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

Learning by observation: insights from Williams syndrome.

Science.gov (United States)

Foti, Francesca; Menghini, Deny; Mandolesi, Laura; Federico, Francesca; Vicari, Stefano; Petrosini, Laura

2013-01-01

Observing another person performing a complex action accelerates the observer's acquisition of the same action and limits the time-consuming process of learning by trial and error. Observational learning makes an interesting and potentially important topic in the developmental domain, especially when disorders are considered. The implications of studies aimed at clarifying whether and how this form of learning is spared by pathology are manifold. We focused on a specific population with learning and intellectual disabilities, the individuals with Williams syndrome. The performance of twenty-eight individuals with Williams syndrome was compared with that of mental age- and gender-matched thirty-two typically developing children on tasks of learning of a visuo-motor sequence by observation or by trial and error. Regardless of the learning modality, acquiring the correct sequence involved three main phases: a detection phase, in which participants discovered the correct sequence and learned how to perform the task; an exercise phase, in which they reproduced the sequence until performance was error-free; an automatization phase, in which by repeating the error-free sequence they became accurate and speedy. Participants with Williams syndrome beneficiated of observational training (in which they observed an actor detecting the visuo-motor sequence) in the detection phase, while they performed worse than typically developing children in the exercise and automatization phases. Thus, by exploiting competencies learned by observation, individuals with Williams syndrome detected the visuo-motor sequence, putting into action the appropriate procedural strategies. Conversely, their impaired performances in the exercise phases appeared linked to impaired spatial working memory, while their deficits in automatization phases to deficits in processes increasing efficiency and speed of the response. Overall, observational experience was advantageous for acquiring competencies

Learning by observation: insights from Williams syndrome.

Directory of Open Access Journals (Sweden)

Francesca Foti

Full Text Available Observing another person performing a complex action accelerates the observer's acquisition of the same action and limits the time-consuming process of learning by trial and error. Observational learning makes an interesting and potentially important topic in the developmental domain, especially when disorders are considered. The implications of studies aimed at clarifying whether and how this form of learning is spared by pathology are manifold. We focused on a specific population with learning and intellectual disabilities, the individuals with Williams syndrome. The performance of twenty-eight individuals with Williams syndrome was compared with that of mental age- and gender-matched thirty-two typically developing children on tasks of learning of a visuo-motor sequence by observation or by trial and error. Regardless of the learning modality, acquiring the correct sequence involved three main phases: a detection phase, in which participants discovered the correct sequence and learned how to perform the task; an exercise phase, in which they reproduced the sequence until performance was error-free; an automatization phase, in which by repeating the error-free sequence they became accurate and speedy. Participants with Williams syndrome beneficiated of observational training (in which they observed an actor detecting the visuo-motor sequence in the detection phase, while they performed worse than typically developing children in the exercise and automatization phases. Thus, by exploiting competencies learned by observation, individuals with Williams syndrome detected the visuo-motor sequence, putting into action the appropriate procedural strategies. Conversely, their impaired performances in the exercise phases appeared linked to impaired spatial working memory, while their deficits in automatization phases to deficits in processes increasing efficiency and speed of the response. Overall, observational experience was advantageous for

What can we learn about lyssavirus genomes using 454 sequencing?

Science.gov (United States)

Höper, Dirk; Finke, Stefan; Freuling, Conrad M; Hoffmann, Bernd; Beer, Martin

2012-01-01

The main task of the individual project number four"Whole genome sequencing, virus-host adaptation, and molecular epidemiological analyses of lyssaviruses "within the network" Lyssaviruses--a potential re-emerging public health threat" is to provide high quality complete genome sequences from lyssaviruses. These sequences are analysed in-depth with regard to the diversity of the viral populations as to both quasi-species and so-called defective interfering RNAs. Moreover, the sequence data will facilitate further epidemiological analyses, will provide insight into the evolution of lyssaviruses and will be the basis for the design of novel nucleic acid based diagnostics. The first results presented here indicate that not only high quality full-length lyssavirus genome sequences can be generated, but indeed efficient analysis of the viral population gets feasible.

Three children with autism spectrum disorder learn to perform a three-step communication sequence using an iPad®-based speech-generating device.

Science.gov (United States)

Waddington, Hannah; Sigafoos, Jeff; Lancioni, Giulio E; O'Reilly, Mark F; van der Meer, Larah; Carnett, Amarie; Stevens, Michelle; Roche, Laura; Hodis, Flaviu; Green, Vanessa A; Sutherland, Dean; Lang, Russell; Marschik, Peter B

2014-12-01

Many children with autism spectrum disorder (ASD) have limited or absent speech and might therefore benefit from learning to use a speech-generating device (SGD). The purpose of this study was to evaluate a procedure aimed at teaching three children with ASD to use an iPad(®)-based SGD to make a general request for access to toys, then make a specific request for one of two toys, and then communicate a thank-you response after receiving the requested toy. A multiple-baseline across participants design was used to determine whether systematic instruction involving least-to-most-prompting, time delay, error correction, and reinforcement was effective in teaching the three children to engage in this requesting and social communication sequence. Generalization and follow-up probes were conducted for two of the three participants. With intervention, all three children showed improvement in performing the communication sequence. This improvement was maintained with an unfamiliar communication partner and during the follow-up sessions. With systematic instruction, children with ASD and severe communication impairment can learn to use an iPad-based SGD to complete multi-step communication sequences that involve requesting and social communication functions. Copyright © 2014 ISDN. Published by Elsevier Ltd. All rights reserved.

Analisa Pengaruh Leadership Style terhadap Organization Performance melalui Learning Organization dan Employee Satisfaction (Studi Kasus pada Akuntan Publik di Kantor Akuntan Publik di Surabaya)

OpenAIRE

Nathania, Stephanie Yunita

2015-01-01

This study aimsed to know the direct and significant influence of leadership style to organizational performance through learning organization and employee's satisfaction in the public accounting firm in Surabaya. This was a of quantitative research by obtaining primary data. The data obtained by distributing questionnaires to 150 auditors in the public accounting firm's in Surabaya. The data obtained were processed by using data PLS.The results indicated the existency of a significant relati...

Age-related changes in consolidation of perceptual and muscle-based learning of motor skills

Directory of Open Access Journals (Sweden)

Rebecca M. C. Spencer

2013-11-01

Full Text Available Improvements in motor sequence learning come about via goal-based learning of the sequence of visual stimuli and muscle-based learning of the sequence of movement responses. In young adults, consolidation of goal-based learning is observed after intervals of sleep but not following wake, whereas consolidation of muscle-based learning is greater following intervals with wake compared to sleep. While the benefit of sleep on motor sequence learning has been shown to decline with age, how sleep contributes to consolidation of goal-based versus muscle-based learning in older adults has not been disentangled. We trained young (n=62 and older (n=50 adults on a motor sequence learning task and re-tested learning following 12 hr intervals containing overnight sleep or daytime wake. To probe consolidation of goal-based learning of the sequence, half of the participants were re-tested in a configuration in which the stimulus sequence was the same but, due to a shift in stimulus-response mapping, the movement response sequence differed. To probe consolidation of muscle-based learning, the remaining participants were tested in a configuration in which the stimulus sequence was novel, but now the sequence of movements used for responding was unchanged. In young adults, there was a significant condition (goal-based v. muscle-based learning by interval (sleep v. wake interaction, F(1,58=6.58, p=.013: Goal-based learning tended to be greater following sleep compared to wake, t(29=1.47, p=.072. Conversely, muscle-based learning was greater following wake than sleep, t(29=2.11, p=.021. Unlike young adults, this interaction was not significant in older adults, F(1,46=.04, p=.84, nor was there a main effect of interval, F(1,46=1.14, p=.29. Thus, older adults do not preferentially consolidate sequence learning over wake or sleep.

A Unified Theoretical Framework for Cognitive Sequencing.

Science.gov (United States)

Savalia, Tejas; Shukla, Anuj; Bapi, Raju S

2016-01-01

The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks.

A Unified Theoretical Framework for Cognitive Sequencing

Directory of Open Access Journals (Sweden)

Tejas Savalia

2016-11-01

Full Text Available The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit versus explicit and goal-directed versus habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops ─ basal ganglia-frontal cortex and hippocampus-frontal cortex loops ─ mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI on developing awareness in implicit learning tasks.

PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

Directory of Open Access Journals (Sweden)

Renata Bujak

2016-07-01

Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

AVALIAÇÃO DE ESPECTRÔMETRO NIR PORTÁTIL E PLS-DA PARA A DISCRIMINAÇÃO DE SEIS ESPÉCIES SIMILARES DE MADEIRAS AMAZÔNICAS

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Liz F. Soares

Full Text Available Supervising wood exploitation can be very challenging due to the existence of many similar species and the reduced number of wood identification experts to meet the demand. There is evidence that valuable endangered wood species are being smuggled disguised as other species. Near infrared spectroscopy (NIRS and chemometrics has been successfully used to discriminate between Amazonian wood species using high resolution instruments. In this study, a handheld spectrometer was evaluated for the discrimination of six visually similar tropical wood species using PLS-DA. Woods of mahogany (Swietenia macrophylla and cedar (Cedrela odorata, both high value tropical timber species included in Appendixes II and III of the CITES, respectively; crabwood (Carapa guianensis; cedrinho (Erisma uncinatum; curupixá (Micropholis melinoniana; and jatobá (Hymenea coubaril. The data for model development and validation take into account both laboratory and field measurements. Outlier exclusion was performed based on Hotelling T2, residuals Q and errors in the estimated class values. The efficiency rates were higher than 90% for all species, showing that the handheld NIR combined with PLS-DA succeeded in discriminate between these species. These results stimulate the application of handheld NIR spectrometers in the supervision of wood exploitation, which can contribute to the species preservation.

Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification

Science.gov (United States)

Emond, Bruno; Buffett, Scott

2015-01-01

This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

Evaluating the Effect of Arabic Engineering Students’ Learning Styles in Blended Programming Courses

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Ahmed Al-Azawei

2016-04-01

Full Text Available This study investigated the complex relationship among learning styles, gender, perceived satisfaction, and academic performance across four programming courses supported by an e-learning platform. A total of 219 undergraduate students from a public Iraqi university who recently experienced e-learning voluntarily took place in the study. The integrated courses adopted a blended learning mode and all learners were provided the same learning content and pathway irrespective of their individual styles. Data were gathered using the Index of Learning Styles (ILS, three closed-ended questions, and the academic record. Traditional statistics and partial least squares structural equation modelling (PLS-SEM were performed to examine the proposed hypotheses. The findings of this research suggested that, overall, learning style dimensions are uncorrelated with either academic performance or perceived satisfaction, except for the processing dimension (active/reflective that has a significant effect on the latter. Furthermore, gender is unassociated with any of the proposed model’s constructs. Finally, there is no significant correlation between academic performance and perceived satisfaction. These results led to the conclusion that even though Arabic engineering students prefer active, sensing, visual, and sequential learning as do other engineering students from different backgrounds, they can adapt to a learning context even if their preferences are not met. The research contributes empirically to the existing debate regarding the potential implications of learning styles and for the Arabic context in particular, since respective research remains rare.

Towards Statistical Unsupervised Online Learning for Music Listening with Hearing Devices

DEFF Research Database (Denmark)

Purwins, Hendrik; Marchini, Marco; Marxer, Richard

of sounds into phonetic/instrument categories and learning of instrument event sequences is performed jointly using a Hierarchical Dirichlet Process Hidden Markov Model. Whereas machines often learn by processing a large data base and subsequently updating parameters of the algorithm, humans learn...... and their respective transition counts. We propose to use online learning for the co-evolution of both CI user and machine in (re-)learning musical language. [1] Marco Marchini and Hendrik Purwins. Unsupervised analysis and generation of audio percussion sequences. In International Symposium on Computer Music Modeling...... categories) as well as the temporal context horizon (e.g. storing up to 2-note sequences or up to 10-note sequences) is adaptable. The framework in [1] is based on two cognitively plausible principles: unsupervised learning and statistical learning. Opposed to supervised learning in primary school children...

Mutation analysis of the cathepsin C gene in Indian families with Papillon-Lefèvre syndrome

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Srivastava Satish

2003-07-01

Full Text Available Abstract Background PLS is a rare autosomal recessive disorder characterized by early onset periodontopathia and palmar plantar keratosis. PLS is caused by mutations in the cathepsin C (CTSC gene. Dipeptidyl-peptidase I encoded by the CTSC gene removes dipeptides from the amino-terminus of protein substrates and mainly plays an immune and inflammatory role. Several mutations have been reported in this gene in patients from several ethnic groups. We report here mutation analysis of the CTSC gene in three Indian families with PLS. Methods Peripheral blood samples were obtained from individuals belonging to three Indian families with PLS for genomic DNA isolation. Exon-specific intronic primers were used to amplify DNA samples from individuals. PCR products were subsequently sequenced to detect mutations. PCR-SCCP and ASOH analyses were used to determine if mutations were present in normal control individuals. Results All patients from three families had a classic PLS phenotype, which included palmoplantar keratosis and early-onset severe periodontitis. Sequence analysis of the CTSC gene showed three novel nonsense mutations (viz., p.Q49X, p.Q69X and p.Y304X in homozygous state in affected individuals from these Indian families. Conclusions This study reported three novel nonsense mutations in three Indian families. These novel nonsense mutations are predicted to produce truncated dipeptidyl-peptidase I causing PLS phenotype in these families. A review of the literature along with three novel mutations reported here showed that the total number of mutations in the CTSC gene described to date is 41 with 17 mutations being located in exon 7.

Probabilistic learning and inference in schizophrenia.

Science.gov (United States)

Averbeck, Bruno B; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S

2011-04-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behavior remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behavior, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving a noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. Published by Elsevier B.V.

Probabilistic learning and inference in schizophrenia

Science.gov (United States)

Averbeck, Bruno B.; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S.

2010-01-01

Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behaviour remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behaviour, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. PMID:20810252

Comparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms.

Science.gov (United States)

Malegori, Cristina; Nascimento Marques, Emanuel José; de Freitas, Sergio Tonetto; Pimentel, Maria Fernanda; Pasquini, Celio; Casiraghi, Ernestina

2017-04-01

The main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer in the evaluation of the prediction accuracy. In particular, the aim of this study was to estimate in a non-destructive manner, titratable acidity and ascorbic acid content in acerola fruit during ripening, in a view of direct applicability in field of this new miniaturised handheld device. Acerola (Malpighia emarginata DC.) is a super-fruit characterised by a considerable amount of ascorbic acid, ranging from 1.0% to 4.5%. However, during ripening, acerola colour changes and the fruit may lose as much as half of its ascorbic acid content. Because the variability of chemical parameters followed a non-strictly linear profile, two different regression algorithms were compared: PLS and SVM. Regression models obtained with Micro-NIR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-NIR data give comparable results using both SVM and PLS algorithms, with lower errors for SVM regression. The prediction ability of the two instruments was statistically compared using the Passing-Bablok regression algorithm; the outcomes are critically discussed together with the regression models, showing the suitability of the portable Micro-NIR for in field monitoring of chemical parameters of interest in acerola fruits. Copyright © 2016 Elsevier B.V. All rights reserved.

Learning of pitch and time structures in an artificial grammar setting.

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Prince, Jon B; Stevens, Catherine J; Jones, Mari Riess; Tillmann, Barbara

2018-04-12

Despite the empirical evidence for the power of the cognitive capacity of implicit learning of structures and regularities in several modalities and materials, it remains controversial whether implicit learning extends to the learning of temporal structures and regularities. We investigated whether (a) an artificial grammar can be learned equally well when expressed in duration sequences as when expressed in pitch sequences, (b) learning of the artificial grammar in either duration or pitch (as the primary dimension) sequences can be influenced by the properties of the secondary dimension (invariant vs. randomized), and (c) learning can be boosted when the artificial grammar is expressed in both pitch and duration. After an exposure phase with grammatical sequences, learning in a subsequent test phase was assessed in a grammaticality judgment task. Participants in both the pitch and duration conditions showed incidental (not fully implicit) learning of the artificial grammar when the secondary dimension was invariant, but randomizing the pitch sequence prevented learning of the artificial grammar in duration sequences. Expressing the artificial grammar in both pitch and duration resulted in disproportionately better performance, suggesting an interaction between the learning of pitch and temporal structure. The findings are relevant to research investigating the learning of temporal structures and the learning of structures presented simultaneously in 2 dimensions (e.g., space and time, space and objects). By investigating learning, the findings provide further insight into the potential specificity of pitch and time processing, and their integrated versus independent processing, as previously debated in music cognition research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification

OpenAIRE

Hwang, Kyuyeon; Sung, Wonyong

2015-01-01

Connectionist temporal classification (CTC) based supervised sequence training of recurrent neural networks (RNNs) has shown great success in many machine learning areas including end-to-end speech and handwritten character recognition. For the CTC training, however, it is required to unroll (or unfold) the RNN by the length of an input sequence. This unrolling requires a lot of memory and hinders a small footprint implementation of online learning or adaptation. Furthermore, the length of tr...

Scalable Kernel Methods and Algorithms for General Sequence Analysis

Science.gov (United States)

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…

Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

Directory of Open Access Journals (Sweden)

Radhika M. Pai

2016-03-01

Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

Directory of Open Access Journals (Sweden)

Radhika M. Pai

2016-04-01

Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

cTBS disruption of the supplementary motor area perturbs cortical sequence representation but not behavioural performance.

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Solopchuk, Oleg; Alamia, Andrea; Dricot, Laurence; Duque, Julie; Zénon, Alexandre

2017-12-01

Neuroimaging studies have repeatedly emphasized the role of the supplementary motor area (SMA) in motor sequence learning, but interferential approaches have led to inconsistent findings. Here, we aimed to test the role of the SMA in motor skill learning by combining interferential and neuroimaging techniques. Sixteen subjects were trained on simple finger movement sequences for 4 days. Afterwards, they underwent two neuroimaging sessions, in which they executed both trained and novel sequences. Prior to entering the scanner, the subjects received inhibitory transcranial magnetic stimulation (TMS) over the SMA or a control site. Using multivariate fMRI analysis, we confirmed that motor training enhances the neural representation of motor sequences in the SMA, in accordance with previous findings. However, although SMA inhibition altered sequence representation (i.e. between-sequence decoding accuracy) in this area, behavioural performance remained unimpaired. Our findings question the causal link between the neuroimaging correlate of elementary motor sequence representation in the SMA and sequence generation, calling for a more thorough investigation of the role of this region in performance of learned motor sequences. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative analyses of two Geraniaceae transcriptomes using next-generation sequencing.

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Zhang, Jin; Ruhlman, Tracey A; Mower, Jeffrey P; Jansen, Robert K

2013-12-29

Organelle genomes of Geraniaceae exhibit several unusual evolutionary phenomena compared to other angiosperm families including accelerated nucleotide substitution rates, widespread gene loss, reduced RNA editing, and extensive genomic rearrangements. Since most organelle-encoded proteins function in multi-subunit complexes that also contain nuclear-encoded proteins, it is likely that the atypical organellar phenomena affect the evolution of nuclear genes encoding organellar proteins. To begin to unravel the complex co-evolutionary interplay between organellar and nuclear genomes in this family, we sequenced nuclear transcriptomes of two species, Geranium maderense and Pelargonium x hortorum. Normalized cDNA libraries of G. maderense and P. x hortorum were used for transcriptome sequencing. Five assemblers (MIRA, Newbler, SOAPdenovo, SOAPdenovo-trans [SOAPtrans], Trinity) and two next-generation technologies (454 and Illumina) were compared to determine the optimal transcriptome sequencing approach. Trinity provided the highest quality assembly of Illumina data with the deepest transcriptome coverage. An analysis to determine the amount of sequencing needed for de novo assembly revealed diminishing returns of coverage and quality with data sets larger than sixty million Illumina paired end reads for both species. The G. maderense and P. x hortorum transcriptomes contained fewer transcripts encoding the PLS subclass of PPR proteins relative to other angiosperms, consistent with reduced mitochondrial RNA editing activity in Geraniaceae. In addition, transcripts for all six plastid targeted sigma factors were identified in both transcriptomes, suggesting that one of the highly divergent rpoA-like ORFs in the P. x hortorum plastid genome is functional. The findings support the use of the Illumina platform and assemblers optimized for transcriptome assembly, such as Trinity or SOAPtrans, to generate high-quality de novo transcriptomes with broad coverage. In addition

Teacher learning through reciprocal peer coaching :an analysis of activity sequences

NARCIS (Netherlands)

Zwart, R.C.; Wubbels, Th.; Bolhuis, S.M; Bergen, T.C.M.

2008-01-01

Just what and how eight experienced teachers in four coaching dyads learned during a 1-year reciprocal peer coaching trajectory was examined in the present study. The learning processes were mapped by providing a detailed description of reported learning activities, reported learning outcomes, and

Simultaneous measurement of two enzyme activities using infrared spectroscopy: A comparative evaluation of PARAFAC, TUCKER and N-PLS modeling

DEFF Research Database (Denmark)

Baum, Andreas; Hansen, Per Waaben; Meyer, Anne S.

2013-01-01

multiway methods, namely PARAFAC, TUCKER3 and N-PLS, to establish simultaneous enzyme activity assays for pectin lyase and pectin methyl esterase. Correlation coefficients Rpred2 for prediction test sets are 0.48, 0.96 and 0.96 for pectin lyase and 0.70, 0.89 and 0.89 for pectin methyl esterase......Enzymes are used in many processes to release fermentable sugars for green production of biofuel, or the refinery of biomass for extraction of functional food ingredients such as pectin or prebiotic oligosaccharides. The complex biomasses may, however, require a multitude of specific enzymes which...... are active on specific substrates generating a multitude of products. In this paper we use the plant polymer, pectin, to present a method to quantify enzyme activity of two pectolytic enzymes by monitoring their superimposed spectral evolutions simultaneously. The data is analyzed by three chemometric...

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding

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Yun Xu

2016-10-01

Full Text Available Partial least squares (PLS is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R or a classification model (PLS-DA. However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a “pure” regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

ROBOT LEARNING OF OBJECT MANIPULATION TASK ACTIONS FROM HUMAN DEMONSTRATIONS

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Maria Kyrarini

2017-08-01

Full Text Available Robot learning from demonstration is a method which enables robots to learn in a similar way as humans. In this paper, a framework that enables robots to learn from multiple human demonstrations via kinesthetic teaching is presented. The subject of learning is a high-level sequence of actions, as well as the low-level trajectories necessary to be followed by the robot to perform the object manipulation task. The multiple human demonstrations are recorded and only the most similar demonstrations are selected for robot learning. The high-level learning module identifies the sequence of actions of the demonstrated task. Using Dynamic Time Warping (DTW and Gaussian Mixture Model (GMM, the model of demonstrated trajectories is learned. The learned trajectory is generated by Gaussian mixture regression (GMR from the learned Gaussian mixture model.  In online working phase, the sequence of actions is identified and experimental results show that the robot performs the learned task successfully.

KARATE WITH CONSTRUCTIVE LEARNING

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Srikrishna Karanam

2012-02-01

Full Text Available Any conventional learning process involves the traditional hierarchy of garnering of information and then recall gathered information. Constructive learning is an important research area having wide impact on teaching methods in education, learning theories, and plays a major role in many education reform movements. It is observed that constructive learning advocates the interconnection between emotions and learning. Human teachers identify the emotions of students with varying degrees of accuracy and can improve the learning rate of the students by motivating them. In learning with computers, computers also should be given the capability to recognize emotions so as to optimize the learning process. Image Processing is a very popular tool used in the process of establishing the theory of Constructive Learning. In this paper we use the Optical Flow computation in image sequences to analyze the accuracy of the moves of a karate player. We have used the Lucas-Kanade method for computing the optical flow in image sequences. A database consisting of optical flow images by a group of persons learning karate is formed and the learning rates are analyzed in order to main constructive learning. The contours of flow images are compared with the standard images and the error graphs are plotted. Analysis of the emotion of the amateur karate player is made by observing the error plots.

Does consolidation of visuospatial sequence knowledge depend on eye movements?

Directory of Open Access Journals (Sweden)

Daphné Coomans

Full Text Available In the current study, we assessed whether visuospatial sequence knowledge is retained over 24 hours and whether this retention is dependent on the occurrence of eye movements. Participants performed two sessions of a serial reaction time (SRT task in which they had to manually react to the identity of a target letter pair presented in one of four locations around a fixation cross. When the letter pair 'XO' was presented, a left response had to be given, when the letter pair 'OX' was presented, a right response was required. In the Eye Movements (EM condition, eye movements were necessary to perform the task since the fixation cross and the target were separated by at least 9° visual angle. In the No Eye Movements (NEM condition, on the other hand, eye movements were minimized by keeping the distance from the fixation cross to the target below 1° visual angle and by limiting the stimulus presentation to 100 ms. Since the target identity changed randomly in both conditions, no manual response sequence was present in the task. However, target location was structured according to a deterministic sequence in both the EM and NEM condition. Learning of the target location sequence was determined at the end of the first session and 24 hours after initial learning. Results indicated that the sequence learning effect in the SRT task diminished, yet remained significant, over the 24 hour interval in both conditions. Importantly, the difference in eye movements had no impact on the transfer of sequence knowledge. These results suggest that the retention of visuospatial sequence knowledge occurs alike, irrespective of whether this knowledge is supported by eye movements or not.

Improved motor sequence retention by motionless listening.

Science.gov (United States)

Lahav, Amir; Katz, Tal; Chess, Roxanne; Saltzman, Elliot

2013-05-01

This study examined the effect of listening to a newly learned musical piece on subsequent motor retention of the piece. Thirty-six non-musicians were trained to play an unfamiliar melody on a piano keyboard. Next, they were randomly assigned to participate in three follow-up listening sessions over 1 week. Subjects who, during their listening sessions, listened to the same initial piece showed significant improvements in motor memory and retention of the piece despite the absence of physical practice. These improvements included increased pitch accuracy, time accuracy, and dynamic intensity of key pressing. Similar improvements, though to a lesser degree, were observed in subjects who, during their listening sessions, were distracted by another task. Control subjects, who after learning the piece had listened to nonmusical sounds, showed impaired motoric retention of the piece at 1 week from the initial acquisition day. These results imply that motor sequences can be established in motor memory without direct access to motor-related information. In addition, the study revealed that the listening-induced improvements did not generalize to the learning of a new musical piece composed of the same notes as the initial piece learned, limiting the effects to musical motor sequences that are already part of the individual's motor repertoire.

Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence

NARCIS (Netherlands)

Al-Shahib, A.; Breitling, R.; Gilbert, D.

2005-01-01

Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence

Phonological learning in semantic dementia.

Science.gov (United States)

Jefferies, Elizabeth; Bott, Samantha; Ehsan, Sheeba; Lambon Ralph, Matthew A

2011-04-01

Patients with semantic dementia (SD) have anterior temporal lobe (ATL) atrophy that gives rise to a highly selective deterioration of semantic knowledge. Despite pronounced anomia and poor comprehension of words and pictures, SD patients have well-formed, fluent speech and normal digit span. Given the intimate connection between phonological STM and word learning revealed by both neuropsychological and developmental studies, SD patients might be expected to show good acquisition of new phonological forms, even though their ability to map these onto meanings is impaired. In contradiction of these predictions, a limited amount of previous research has found poor learning of new phonological forms in SD. In a series of experiments, we examined whether SD patient, GE, could learn novel phonological sequences and, if so, under which circumstances. GE showed normal benefits of phonological knowledge in STM (i.e., normal phonotactic frequency and phonological similarity effects) but reduced support from semantic memory (i.e., poor immediate serial recall for semantically degraded words, characterised by frequent item errors). Next, we demonstrated normal learning of serial order information for repeated lists of single-digit number words using the Hebb paradigm: these items were well-understood allowing them to be repeated without frequent item errors. In contrast, patient GE showed little learning of nonsense syllable sequences using the same Hebb paradigm. Detailed analysis revealed that both GE and the controls showed a tendency to learn their own errors as opposed to the target items. Finally, we showed normal learning of phonological sequences for GE when he was prevented from repeating his errors. These findings confirm that the ATL atrophy in SD disrupts phonological processing for semantically degraded words but leaves the phonological architecture intact. Consequently, when item errors are minimised, phonological STM can support the acquisition of new phoneme

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

Science.gov (United States)

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations

Context-dependent motor skill: perceptual processing in memory-based sequence production

NARCIS (Netherlands)

Ruitenberg, M.F.L.; Abrahamse, E.L.; de Kleine, Elian; Verwey, Willem B.

2012-01-01

Previous studies have shown that motor sequencing skill can benefit from the reinstatement of the learning context—even with respect to features that are formally not required for appropriate task performance. The present study explored whether such context-dependence develops when sequence

Pharmacist work stress and learning from quality related events.

Science.gov (United States)

Boyle, Todd A; Bishop, Andrea; Morrison, Bobbi; Murphy, Andrea; Barker, James; Ashcroft, Darren M; Phipps, Denham; Mahaffey, Thomas; MacKinnon, Neil J

2016-01-01

Among the many stresses faced by pharmacy staff, quality related event (QRE) learning can be among the most significant. In the absence of a supportive organizational culture, the potential for blaming individuals, versus identifying key process flaws, is significant and can be very intimidating to those involved in such discussions and may increase an already stressful work environment. This research develops and tests a model of the relationship between the work stress faced by pharmacists and the extent of QRE learning in community pharmacies. Building upon recent research models that explore job characteristics and safety climate, the model proposes that work stress captured by the effort that the pharmacist invests into job performance, the extent to which the pharmacist is rewarded for such efforts, and the extent of pharmacist work-related commitment to their job, influence pharmacist assessment of the working conditions within their community pharmacy. It is further proposed that working conditions influence the extent of a blame culture and safety focus in the pharmacy, which, in turn, influences organizational learning from QREs. This research formed part of a larger study focused on QRE reporting in community pharmacies. As part of the larger study, a total of 1035 questionnaires were mailed to community pharmacists, pharmacy managers, and pharmacy owners in the Canadian province of Saskatchewan during the fall of 2013 and winter and spring of 2014. Partial least squares (PLS) using SmartPLS was selected to test and further develop the proposed model. An examination of the statistical significance of latent variable paths, convergent validity, construct reliability, discriminant validity, and variance explained was used to assess the overall quality of the model. Of the 1035 questionnaire sent, a total of 432 questionnaires were returned for an initial response rate of approximately 42%. However, for this research, only questionnaires from staff

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

Science.gov (United States)

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

Dysgraphia in Patients with Primary Lateral Sclerosis: A Speech-Based Rehearsal Deficit?

Science.gov (United States)

Zago, S.; Poletti, B.; Corbo, M.; Adobbati, L.; Silani, V.

2008-01-01

The present study aims to demonstrate that errors when writing are more common than expected in patients affected by primary lateral sclerosis (PLS) with severe dysarthria or complete mutism, independent of spasticity. Sixteen patients meeting Pringle’s et al. [34] criteria for PLS underwent standard neuropsychological tasks and evaluation of writing. We assessed writing abilities in spelling through dictation in which a set of words, non-words and short phrases were presented orally and by composing words using a set of preformed letters. Finally, a written copying task was performed with the same words. Relative to controls, PLS patients made a greater number of spelling errors in all writing conditions, but not in copy task. The error types included: omissions, transpositions, insertions and letter substitutions. These were equally distributed on the writing task and the composition of words with a set of preformed letters. This pattern of performance is consistent with a spelling impairment. The results are consistent with the concept that written production is critically dependent on the subvocal articulatory mechanism of rehearsal, perhaps at the level of retaining the sequence of graphemes in a graphemic buffer. In PLS patients a disturbance in rehearsal opportunity may affect the correct sequencing/assembly of an orthographic representation in the written process. PMID:19096141

Learning Orthographic Structure with Sequential Generative Neural Networks

Science.gov (United States)

Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

2016-01-01

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in…

Generation of novel motor sequences: the neural correlates of musical improvisation.

Science.gov (United States)

Berkowitz, Aaron L; Ansari, Daniel

2008-06-01

While some motor behavior is instinctive and stereotyped or learned and re-executed, much action is a spontaneous response to a novel set of environmental conditions. The neural correlates of both pre-learned and cued motor sequences have been previously studied, but novel motor behavior has thus far not been examined through brain imaging. In this paper, we report a study of musical improvisation in trained pianists with functional magnetic resonance imaging (fMRI), using improvisation as a case study of novel action generation. We demonstrate that both rhythmic (temporal) and melodic (ordinal) motor sequence creation modulate activity in a network of brain regions comprised of the dorsal premotor cortex, the rostral cingulate zone of the anterior cingulate cortex, and the inferior frontal gyrus. These findings are consistent with a role for the dorsal premotor cortex in movement coordination, the rostral cingulate zone in voluntary selection, and the inferior frontal gyrus in sequence generation. Thus, the invention of novel motor sequences in musical improvisation recruits a network of brain regions coordinated to generate possible sequences, select among them, and execute the decided-upon sequence.

Learning Markov models for stationary system behaviors

DEFF Research Database (Denmark)

Chen, Yingke; Mao, Hua; Jaeger, Manfred

2012-01-01

to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....

Effect of Subjective Norms Mediation to Entrepreneurship Intention at Entrepreneurship Learning in School

Directory of Open Access Journals (Sweden)

Achmad Mustofa

2018-04-01

Full Text Available This type of research is quantitative research with the help of Smart PLS 3.0 application. The population in this study are all students of marketing program of SMK Negeri Boyolali on entrepreneuship learning. Through the sampling formula Issac and Michael obtained as many as 175 student samples. Sampling technique used proportionate stratified random sampling. Technical analysis used is structural equation model analysis. Testing hypothesis with significant level 5% obtained by coefficient of beta (original sample at specific indirect effects equal to 0,105. It shows that entrepreneuship learning has positive predictive properties of entrepreneurship intention (EI through students' subjective norms. The value of t-count is 2,844, the value of t-table is 1.96 then t-count > t-table (2,844> 1,96. It shows that student EI is significantly influenced by entrepreneuship learning through students' subjective norms. While the value of coefficient of determination (r-square obtained coefficient of determination for subjective norms (SN variable shows that the amount of contribution, contribution given by entrepreneurship learning (EL variables 9.3% and the value of coefficient of determination for EI variable shows that the amount of contribution, contribution given by variable SN 37.8%. So this research is well used in the development of economic learning innovation, especially entrepreneurship subjects.

Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning

Science.gov (United States)

2013-01-01

Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction

Deep Learning and Its Applications in Biomedicine.

Science.gov (United States)

Cao, Chensi; Liu, Feng; Tan, Hai; Song, Deshou; Shu, Wenjie; Li, Weizhong; Zhou, Yiming; Bo, Xiaochen; Xie, Zhi

2018-02-01

Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning applications, including medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. Finally, we offer our perspectives for the future directions in the field of deep learning. Copyright © 2018. Production and hosting by Elsevier B.V.

Abstract feature codes: The building blocks of the implicit learning system.

Science.gov (United States)

Eberhardt, Katharina; Esser, Sarah; Haider, Hilde

2017-07-01

According to the Theory of Event Coding (TEC; Hommel, Müsseler, Aschersleben, & Prinz, 2001), action and perception are represented in a shared format in the cognitive system by means of feature codes. In implicit sequence learning research, it is still common to make a conceptual difference between independent motor and perceptual sequences. This supposedly independent learning takes place in encapsulated modules (Keele, Ivry, Mayr, Hazeltine, & Heuer 2003) that process information along single dimensions. These dimensions have remained underspecified so far. It is especially not clear whether stimulus and response characteristics are processed in separate modules. Here, we suggest that feature dimensions as they are described in the TEC should be viewed as the basic content of modules of implicit learning. This means that the modules process all stimulus and response information related to certain feature dimensions of the perceptual environment. In 3 experiments, we investigated by means of a serial reaction time task the nature of the basic units of implicit learning. As a test case, we used stimulus location sequence learning. The results show that a stimulus location sequence and a response location sequence cannot be learned without interference (Experiment 2) unless one of the sequences can be coded via an alternative, nonspatial dimension (Experiment 3). These results support the notion that spatial location is one module of the implicit learning system and, consequently, that there are no separate processing units for stimulus versus response locations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Living laboratory: whole-genome sequencing as a learning healthcare enterprise.

Science.gov (United States)

Angrist, M; Jamal, L

2015-04-01

With the proliferation of affordable large-scale human genomic data come profound and vexing questions about management of such data and their clinical uncertainty. These issues challenge the view that genomic research on human beings can (or should) be fully segregated from clinical genomics, either conceptually or practically. Here, we argue that the sharp distinction between clinical care and research is especially problematic in the context of large-scale genomic sequencing of people with suspected genetic conditions. Core goals of both enterprises (e.g. understanding genotype-phenotype relationships; generating an evidence base for genomic medicine) are more likely to be realized at a population scale if both those ordering and those undergoing sequencing for diagnostic reasons are routinely and longitudinally studied. Rather than relying on expensive and lengthy randomized clinical trials and meta-analyses, we propose leveraging nascent clinical-research hybrid frameworks into a broader, more permanent instantiation of exploratory medical sequencing. Such an investment could enlighten stakeholders about the real-life challenges posed by whole-genome sequencing, such as establishing the clinical actionability of genetic variants, returning 'off-target' results to families, developing effective service delivery models and monitoring long-term outcomes. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Real time flaw detection and characterization in tube through partial least squares and SVR: Application to eddy current testing

Science.gov (United States)

Ahmed, Shamim; Miorelli, Roberto; Calmon, Pierre; Anselmi, Nicola; Salucci, Marco

2018-04-01

This paper describes Learning-By-Examples (LBE) technique for performing quasi real time flaw localization and characterization within a conductive tube based on Eddy Current Testing (ECT) signals. Within the framework of LBE, the combination of full-factorial (i.e., GRID) sampling and Partial Least Squares (PLS) feature extraction (i.e., GRID-PLS) techniques are applied for generating a suitable training set in offine phase. Support Vector Regression (SVR) is utilized for model development and inversion during offine and online phases, respectively. The performance and robustness of the proposed GIRD-PLS/SVR strategy on noisy test set is evaluated and compared with standard GRID/SVR approach.

FACTORS INFLUENCING THE LEARNING SUCCESS OF MASTER STUDENTS AT IPB BUSINESS SCHOOL (SB-IPB

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Maya Wulan Arini

2017-05-01

Full Text Available Business School of IPB (SB-IPB has a low level of completing of study for its master program students on-time. Based on the report of SB-IPB 2015, only 0.8% of students graduating in 2014/2015 successfully completed their study in the normal time of thesis writing. This study aims to identify what factors cause the students unable to complete their thesis on time, thus affecting their learning success. The primary data in this study came from interviews to the students of year 2011/2012, while the secondary data were obtained from the academic section of SB-IPB. Determination of the number of samples was done using slovin formula obtaining 80 students as the respondents. The data analysis method used was SEM with PLS method. The results of the research indicate that the indicator that has a dominant role on the student characteristics is employment status while the dominant role indicators on the process of thesis writing are the suitability of area of interest and the administrative process. The value of the characteristics of students significantly affecting the process of their thesis writing is-0.283, and this indicates that students who are full time workers have a number of constraints in their thesis writing process. Likewise, the process of the thesis writing has a significant influence on the success of the study i.e. 0.346, and it means that the easier the process of thesis writing, the greater the success of their study. The academic division is expected to be more active in controlling the students who are in the process of writing their thesis, especially for the class whose students work full time so that it can well support the learning success of the students.Keywords: business school, master program, success of the study, PLS, SEMABSTRAKMahasiswa program magister di sekolah bisnis IPB (SB-IPB memiliki tingkat ketepatan penyelesaian studi yang masih rendah. Berdasarkan laporan SB IPB 2015, hanya 0.8% mahasiswa yang lulus tahun

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM in advanced metering infrastructure of smart grid.

Directory of Open Access Journals (Sweden)

Yuancheng Li

Full Text Available Advanced Metering Infrastructure (AMI realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

The rupture in the physics teacher’s pedagogical sequence

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Anne Louise Scarinci

2013-12-01

Full Text Available This is the result of an observational research, carried out with a group of high school physics teachers in professional development. We departed from the recognition of the incipient learning in courses, as identified from the few changes resultant in teachers’ practices. While studying their attempts to take into classroom the proposals learned in the courses, we’ve observed that such attempts frequently originated a rupture in the pedagogical sequence. This caused a great distress and a tendency to return to the “old” practice. Of what does this rupture consist? Which obstacles may be causing them? This question lead us to study the characteristics of teachers’ practices and their evolution/oscillation, motivated by the professional development course. We’ve related the ruptures in their pedagogical sequence with the incoherence in teachers' strategies and attitudes when applying the teaching theory being learned, whereas still maintaining aspects of their practice founded into the old theory. We’ve concluded that the learning of a new teaching theory requires a ground attitudinal change, more fundamental than possible changes in the teaching strategies, these ones capable of planning.

DeepSimulator: a deep simulator for Nanopore sequencing

KAUST Repository

Li, Yu; Han, Renmin; Bi, Chongwei; Li, Mo; Wang, Sheng; Gao, Xin

2017-01-01

or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments

Imaging of glia activation in people with primary lateral sclerosis.

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Paganoni, Sabrina; Alshikho, Mohamad J; Zürcher, Nicole R; Cernasov, Paul; Babu, Suma; Loggia, Marco L; Chan, James; Chonde, Daniel B; Garcia, David Izquierdo; Catana, Ciprian; Mainero, Caterina; Rosen, Bruce R; Cudkowicz, Merit E; Hooker, Jacob M; Atassi, Nazem

2018-01-01

Glia activation is thought to contribute to neuronal damage in several neurodegenerative diseases based on preclinical and human post - mortem studies, but its role in primary lateral sclerosis (PLS) is unknown. To localize and measure glia activation in people with PLS compared to healthy controls (HC). Ten participants with PLS and ten age-matched HCs underwent simultaneous magnetic resonance (MR) and proton emission tomography (PET). The radiotracer [ 11 C]-PBR28 was used to obtain PET-based measures of 18 kDa translocator protein (TSPO) expression, a marker of activated glial cells. MR techniques included a structural sequence to measure cortical thickness and diffusion tensor imaging (DTI) to assess white matter integrity. PET data showed increased [ 11 C]-PBR28 uptake in anatomically-relevant motor regions which co-localized with areas of regional gray matter atrophy and decreased subcortical fractional anisotropy. This study supports a link between glia activation and neuronal degeneration in PLS, and suggests that these disease mechanisms can be measured in vivo in PLS. Future studies are needed to determine the longitudinal changes of these imaging measures and to clarify if MR-PET with [ 11 C]-PBR28 can be used as a biomarker for drug development in the context of clinical trials for PLS.

DeepSimulator: a deep simulator for Nanopore sequencing

KAUST Repository

Li, Yu

2017-12-23

Motivation: Oxford Nanopore sequencing is a rapidly developed sequencing technology in recent years. To keep pace with the explosion of the downstream data analytical tools, a versatile Nanopore sequencing simulator is needed to complement the experimental data as well as to benchmark those newly developed tools. However, all the currently available simulators are based on simple statistics of the produced reads, which have difficulty in capturing the complex nature of the Nanopore sequencing procedure, the main task of which is the generation of raw electrical current signals. Results: Here we propose a deep learning based simulator, DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83% to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection. Availability: The software can be accessed freely at: https://github.com/lykaust15/DeepSimulator.

An Integrated Mixed Methods Research Design: Example of the Project Foreign Language Learning Strategies and Achievement: Analysis of Strategy Clusters and Sequences

OpenAIRE

Vlčková Kateřina

2014-01-01

The presentation focused on an so called integrated mixed method research design example on a basis of a Czech Science Foundation Project Nr. GAP407/12/0432 "Foreign Language Learning Strategies and Achievement: Analysis of Strategy Clusters and Sequences". All main integrated parts of the mixed methods research design were discussed: the aim, theoretical framework, research question, methods and validity threats. Prezentace se zaměřovala na tzv. integrovaný vícemetodový výzkumný design na...

Neural mechanisms of sequence generation in songbirds

Science.gov (United States)

Langford, Bruce

Animal models in research are useful for studying more complex behavior. For example, motor sequence generation of actions requiring good muscle coordination such as writing with a pen, playing an instrument, or speaking, may involve the interaction of many areas in the brain, each a complex system in itself; thus it can be difficult to determine causal relationships between neural behavior and the behavior being studied. Birdsong, however, provides an excellent model behavior for motor sequence learning, memory, and generation. The song consists of learned sequences of notes that are spectrographically stereotyped over multiple renditions of the song, similar to syllables in human speech. The main areas of the songbird brain involve in singing are known, however, the mechanisms by which these systems store and produce song are not well understood. We used a custom built, head-mounted, miniature motorized microdrive to chronically record the neural firing patterns of identified neurons in HVC, a pre-motor cortical nucleus which has been shown to be important in song timing. These were done in Bengalese finch which generate a song made up of stereotyped notes but variable note sequences. We observed song related bursting in neurons projecting to Area X, a homologue to basal ganglia, and tonic firing in HVC interneurons. Interneuron had firing rate patterns that were consistent over multiple renditions of the same note sequence. We also designed and built a light-weight, low-powered wireless programmable neural stimulator using Bluetooth Low Energy Protocol. It was able to generate perturbations in the song when current pulses were administered to RA, which projects to the brainstem nucleus responsible for syringeal muscle control.

Learning resistance mutation pathways of HIV

OpenAIRE

Ramon, Jan; Dubrovskaya, Snezhana; Blockeel, Hendrik

2007-01-01

We propose a novel machine learning algorithm for learning mutation pathways of viruses from a population of viral DNA strands. More specifically, given a number of sequences, the algorithm constructs a phylogenetic tree that expresses the ancestry of the sequences, and at the same time builds a model describing dependencies between mutations that is consistent with the data as well as the phylogenetic tree. Our approach extends existing approaches for phylogenetic tree construction by not as...

A teaching-learning sequence on a socio-scientific issue: analysis and evaluation of its implementation in the classroom*

Science.gov (United States)

Vázquez-Alonso, Ángel; Aponte, Abdiel; Manassero-Mas, María-Antonia; Montesano, Marisa

2016-07-01

This study examines the effectiveness of a teaching-learning sequence (TLS) to improve the understanding of the influences and interactions between a technology (mining) and society. The aim of the study is also to show the possibility of both teaching and assessing the most innovative issues and aspects of scientific competence and their impact on the understanding of the nature of science. The methodology used a quasi-experimental, pre-post-test design with a control group, with pre-post-test differences as the empirical indicators of improved understanding. Improvements were modest, as the empirical differences (pre-post and experimental-control group) were not large, but the experimental group scored more highly than the control group. The areas that showed improvement were identified. The paper includes the TLS itself and the standardized assessment tools that are functional and transferable to other researchers and teachers. This paper first appeared in Educ. Quim (2014), 25(1), 190-202, a journal in Spanish. It appears by kind permission of the Editor, Professor Jose Chamizo. It was chosen because it illustrates the value of studies that use a standard procedure to address learning in a novel context.

Machine learning applications in genetics and genomics.

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Libbrecht, Maxwell W; Noble, William Stafford

2015-06-01

The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning applications for the analysis of genome sequencing data sets, including the annotation of sequence elements and epigenetic, proteomic or metabolomic data. We present considerations and recurrent challenges in the application of supervised, semi-supervised and unsupervised machine learning methods, as well as of generative and discriminative modelling approaches. We provide general guidelines to assist in the selection of these machine learning methods and their practical application for the analysis of genetic and genomic data sets.

Designing E-learning Model to Learn About Transportation Management System to Support Supply Chain Management with Simulation Problems

OpenAIRE

Wiyono, Didiek Sri; Pribadi, Sidigdoyo; Permana, Ryan

2011-01-01

Focus of this research is designing Transportation Management System (TMS) as e-learning media for logistic education. E-learning is the use of Internet technologies to enhance knowledge and performance. E-learning technologies offer learners control over content, learning sequence, pace of learning, time, and often media, allowing them to tailor their experiences to meet their personal learning objectives. E-learning appears to be at least as effective as classical lectures. Students do not ...

Deep learning

CERN Document Server

Goodfellow, Ian; Courville, Aaron

2016-01-01

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

Supervised Learning for Dynamical System Learning.

Science.gov (United States)

Hefny, Ahmed; Downey, Carlton; Gordon, Geoffrey J

2015-01-01

Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computational and statistical efficiency. Unfortunately, they can be difficult to use and extend in practice: e.g., they can make it difficult to incorporate prior information such as sparsity or structure. To address this problem, we present a new view of dynamical system learning: we show how to learn dynamical systems by solving a sequence of ordinary supervised learning problems, thereby allowing users to incorporate prior knowledge via standard techniques such as L 1 regularization. Many existing spectral methods are special cases of this new framework, using linear regression as the supervised learner. We demonstrate the effectiveness of our framework by showing examples where nonlinear regression or lasso let us learn better state representations than plain linear regression does; the correctness of these instances follows directly from our general analysis.

PLS-NIR determination of five parameters in different types of Chinese rice wine

Science.gov (United States)

Yu, Haiyan; Ying, Yibin; Fu, Xiaping; Lu, Huishan

2005-11-01

To evaluate the applicability of near infrared spectroscopy for determination of the five enological parameters (alcoholic degree, pH value, total acid and amino acid nitrogen, °Brix) of Chinese rice wine, transmission spectra were collected in the spectral range from 12500 to 3800 cm-1 in a 1 mm path length rectangular quartz cuvette with air as reference at room temperature. Five calibration equations for the five parameters were established between the reference data and spectra by partial least squares (PLS) regression, separately. The best calibration results were achieved for the determination of alcoholic degree and °Brix. The RPD (ration of the standard deviation of the samples to the SECV) values of the calibration for both alcoholic degree and °Brix were higher than 3 (4.30 and 7.94, respectively), which demonstrated the robustness and power of the calibration models. The determination coefficients (R2) for alcoholic degree and °Brix were 0.987 and 0.991, respectively. The performance of pH, total acid and amino acid nitrogen was not as good as that of alcoholic degree and °Brix. The RPD values for the three parameters were 1.48, 1.85 and 1.82, respectively, and R2 values were 0.964, 0.970 and 0.971, respectively. In validation step, R2 value of the five parameters are all higher than 0.7, especially for alcoholic degree and °Brix (0.968 and 0.956, respectively). The results demonstrated that NIR spectroscopy could be used to predict the concentration of the five enological parameters in Chinese rice wine.

Strategic Cognitive Sequencing: A Computational Cognitive Neuroscience Approach

Directory of Open Access Journals (Sweden)

Seth A. Herd