Cooperative formation of porous silica and peptides on the prebiotic Earth.

Modern technology has perfected the synthesis of catalysts such as zeolites and mesoporous silicas using organic structure directing agents (SDA) and their industrial use to catalyze a large variety of organic reactions within their pores. We suggest that early in prebiotic evolution, synergistic interplay arose between organic species in aqueous solution and silica formed from rocks by dynamic dissolution-recrystallization. The natural organics, for example, amino acids, small peptides, and fatty acids, acted as SDA for assembly of functional porous silica structures that induced further polymerization of amino acids and peptides, as well as other organic reactions. Positive feedback between synthesis and catalysis in the silica-organic system may have accelerated the early stages of abiotic evolution by increasing the formation of polymerized species.

Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty.

Conservation decisions are often made in the face of uncertainty because the urgency to act can preclude delaying management while uncertainty is resolved. In this context, adaptive management is attractive, allowing simultaneous management and learning. An adaptive program design requires the identification of critical uncertainties that impede the choice of management action. Quantitative evaluation of critical uncertainty, using the expected value of information, may require more resources than are available in the early stages of conservation planning. Here, we demonstrate the use of a qualitative index to the value of information (QVoI) to prioritize which sources of uncertainty to reduce regarding the use of prescribed fire to benefit Eastern Black Rails (Laterallus jamaicensis jamaicensis), Yellow Rails (Coterminous noveboracensis), and Mottled Ducks (Anas fulvigula; hereafter, focal species) in high marshes of the U.S. Gulf of Mexico. Prescribed fire has been used as a management tool in Gulf of Mexico high marshes throughout the last 30+ years; however, effects of periodic burning on the focal species and the optimal conditions for burning marshes to improve habitat remain unknown. We followed a structured decision-making framework to develop conceptual models, which we then used to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes. We used QVoI to evaluate the sources of uncertainty based on their Magnitude, Relevance for decision-making, and Reducibility. We found that hypotheses related to the optimal fire return interval and season were the highest priorities for study, whereas hypotheses related to predation rates and interactions among management techniques were lowest. These results suggest that learning about the optimal fire frequency and season to benefit the focal species might produce the greatest management benefit. In this case study, we demonstrate that QVoI can help managers decide where to apply limited resources to learn which specific actions will result in a higher likelihood of achieving the desired management objectives. Further, we summarize the strengths and limitations of QVoI and outline recommendations for its future use for prioritizing research to reduce uncertainty about system dynamics and the effects of management actions.

Multicriteria decisions and portfolio analysis: land acquisition for biological and social objectives.

Resource allocation for land acquisition is a common multiobjective problem that involves complex trade-offs. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service currently uses the Targeted Resource Acquisition Comparison Tool (TRACT) to allocate funds from the Migratory Bird Conservation Fund (MBCF; established through the Migratory Bird Hunting and Conservation Act of 1934) for land acquisition based on cost-benefit analysis, regional priority rankings of candidate land parcels available for acquisition, and the overall biological contribution to duck population objectives. However, current policy encourages decision makers to consider societal and economic benefits of lands acquired, in addition to their biological benefits to waterfowl. These decisions about portfolio elements (i.e., individual land parcels) require an analysis of the difficult trade-offs among multiple objectives. In the last decade the application of multicriteria decision analysis (MCDA) methods has been instrumental in aiding decision makers with complex multiobjective decisions. In this study, we present an alternative approach to developing land-acquisition portfolios using MCDA and modern portfolio theory (MPT). We describe the development of a portfolio decision analysis tool using constrained optimization for land-acquisition decisions by the NWRS. We outline the decision framework, describe development of the prototype tool in Microsoft Excel, and test the results of the tool using land parcels submitted as candidates for MBCF funding in 2019. Our results indicate that the constrained optimization outperformed the traditional TRACT method and ad hoc portfolios developed using current NWRS criteria.

The multiple process model of goal-directed aiming/reaching: insights on limb control from various special populations.

Several years ago, our research group forwarded a model of goal-directed reaching and aiming that describes the processes involved in the optimization of speed, accuracy, and energy expenditure Elliott et al. (Psychol Bull 136:1023-1044, 2010). One of the main features of the model is the distinction between early impulse control, which is based on a comparison of expected to perceived sensory consequences, and late limb-target control that involves a spatial comparison of limb and target position. Our model also emphasizes the importance of strategic behaviors that limit the opportunity for worst-case or inefficient outcomes. In the 2010 paper, we included a section on how our model can be used to understand atypical aiming/reaching movements in a number of special populations. In light of a recent empirical and theoretical update of our model Elliott et al. (Neurosci Biobehav Rev 72:95-110, 2017), here we consider contemporary motor control work involving typical aging, Down syndrome, autism spectrum disorder, and tetraplegia with tendon-transfer surgery. We outline how atypical limb control can be viewed within the context of the multiple-process model of goal-directed reaching and aiming, and discuss the underlying perceptual-motor impairment that results in the adaptive solution developed by the specific group.

Characterization and spatial distribution of organic-contaminated sediment derived from historical industrial effluents.

Organic sediment contaminants [polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans (PCDD/Fs), and polycyclic aromatic hydrocarbons (PAHs)] were assessed using secondary monitoring data from a former tidal estuary (Boat Harbour) impacted by historical industrial effluents. Spatiotemporal characterization of PCDD/Fs and PAHs in sediments was conducted to inform a sediment remediation program designed to return this contaminated aquatic site back to a tidal lagoon. Spatiotemporal variations of sediment PCDD/F and PAH concentrations across Boat Harbour and off-site reference locations were assessed using secondary monitoring data collected between 1992 and 2015. Sediment PCDD/F toxic equivalency (TEQ) and PAH concentrations were compared to sediment quality guidelines. Sediment PCDD/F concentrations exceeded the highest effect thresholds posing severe ecological health risks. High sediment PCDD/F concentrations have persisted in Boat Harbour despite implementation of Pulp and Paper Mill Effluent Chlorinated Dioxins and Furans Regulations in 1992. PAH concentrations varied greatly. Five individual PAH compounds frequently exceeded severe effect thresholds, in contrast to total PAHs, which were below severe effect thresholds. Forensic analysis using PAH diagnostic ratios suggests pyrogenic PAHs derived from wood processes or coal combustion were likely sources. Twenty-five years of monitoring data revealed large data gaps in our understanding of sediment characteristics in Boat Harbour. Gaps included spatial (vertical and horizontal) and temporal variations, presenting challenges for remediation to accurately delineate sediment contaminants. Deeper horizons were poorly characterized compared to shallow sediments (0-15 cm). Historical secondary monitoring data showed that spatial coverage across Boat Harbour was inadequate. Due to severe ecological health risks associated with high sediment PCDD/F concentrations, remediation of the entire sediment inventory is recommended. Detailed vertical and horizontal sampling within Boat Harbour, establishment of local baseline concentrations, and additional sampling in down-gradient-receiving environments for a suite of contaminants are required to better characterize sediments prior to remediation.

SPIN2: Predicting sequence profiles from protein structures using deep neural networks.

Designing protein sequences that can fold into a given structure is a well-known inverse protein-folding problem. One important characteristic to attain for a protein design program is the ability to recover wild-type sequences given their native backbone structures. The highest average sequence identity accuracy achieved by current protein-design programs in this problem is around 30%, achieved by our previous system, SPIN. SPIN is a program that predicts sequences compatible with a provided structure using a neural network with fragment-based local and energy-based nonlocal profiles. Our new model, SPIN2, uses a deep neural network and additional structural features to improve on SPIN. SPIN2 achieves over 34% in sequence recovery in 10-fold cross-validation and independent tests, a 4% improvement over the previous version. The sequence profiles generated from SPIN2 are expected to be useful for improving existing fold recognition and protein design techniques. SPIN2 is available at http://sparks-lab.org.

Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning.

Predicting protein structure from sequence alone is challenging. Thus, the majority of methods for protein structure prediction rely on evolutionary information from multiple sequence alignments. In previous work we showed that Long Short-Term Bidirectional Recurrent Neural Networks (LSTM-BRNNs) improved over regular neural networks by better capturing intra-sequence dependencies. Here we show a single-sequence-based prediction method employing LSTM-BRNNs (SPIDER3-Single), that consistently achieves Q3 accuracy of 72.5%, and correlation coefficient of 0.67 between predicted and actual solvent accessible surface area. Moreover, it yields reasonably accurate prediction of eight-state secondary structure, main-chain angles (backbone ϕ and ψ torsion angles and C α-atom-based θ and τ angles), half-sphere exposure, and contact number. The method is more accurate than the corresponding evolutionary-based method for proteins with few sequence homologs, and computationally efficient for large-scale screening of protein-structural properties. It is available as an option in the SPIDER3 server, and a standalone version for download, at http://sparks-lab.org. © 2018 Wiley Periodicals, Inc.

Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins.

MOTIVATION: Solvent exposure of amino acid residues of proteins plays an important role in understanding and predicting protein structure, function and interactions. Solvent exposure can be characterized by several measures including solvent accessible surface area (ASA), residue depth (RD) and contact numbers (CN). More recently, an orientation-dependent contact number called half-sphere exposure (HSE) was introduced by separating the contacts within upper and down half spheres defined according to the Cα-Cß (HSEß) vector or neighboring Cα-Cα vectors (HSEα). HSEα calculated from protein structures was found to better describe the solvent exposure over ASA, CN and RD in many applications. Thus, a sequence-based prediction is desirable, as most proteins do not have experimentally determined structures. To our best knowledge, there is no method to predict HSEα and only one method to predict HSEß. RESULTS: This study developed a novel method for predicting both HSEα and HSEß (SPIDER-HSE) that achieved a consistent performance for 10-fold cross validation and two independent tests. The correlation coefficients between predicted and measured HSEß (0.73 for upper sphere, 0.69 for down sphere and 0.76 for contact numbers) for the independent test set of 1199 proteins are significantly higher than existing methods. Moreover, predicted HSEα has a higher correlation coefficient (0.46) to the stability change by residue mutants than predicted HSEß (0.37) and ASA (0.43). The results, together with its easy Cα-atom-based calculation, highlight the potential usefulness of predicted HSEα for protein structure prediction and refinement as well as function prediction. AVAILABILITY AND IMPLEMENTATION: The method is available at http://sparks-lab.org CONTACT: yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Early inner solar system origin for anomalous sulfur isotopes in differentiated protoplanets.

Achondrite meteorites have anomalous enrichments in (33)S, relative to chondrites, which have been attributed to photochemistry in the solar nebula. However, the putative photochemical reactions remain elusive, and predicted accompanying (33)S depletions have not previously been found, which could indicate an erroneous assumption regarding the origins of the (33)S anomalies, or of the bulk solar system S-isotope composition. Here, we report well-resolved anomalous (33)S depletions in IIIF iron meteorites (<-0.02 per mil), and (33)S enrichments in other magmatic iron meteorite groups. The (33)S depletions support the idea that differentiated planetesimals inherited sulfur that was photochemically derived from gases in the early inner solar system (<∼2 AU), and that bulk inner solar system S-isotope composition was chondritic (consistent with IAB iron meteorites, Earth, Moon, and Mars). The range of mass-independent sulfur isotope compositions may reflect spatial or temporal changes influenced by photochemical processes. A tentative correlation between S isotopes and Hf-W core segregation ages suggests that the two systems may be influenced by common factors, such as nebular location and volatile content.

Spatiotemporal assessment (quarter century) of pulp mill metal(loid) contaminated sediment to inform remediation decisions.

A bleached kraft pulp mill in Nova Scotia has discharged effluent wastewater into Boat Harbour, a former tidal estuary within Pictou Landing First Nation since 1967. Fifty years of effluent discharge into Boat Harbour has created >170,000 m3 of unconsolidated sediment, impacted by inorganic and organic contaminants, including metal[loid]s, polycyclic aromatic hydrocarbons (PAHs), dioxins, and furans. This study aimed to characterize metal(loid)-impacted sediments to inform decisions for a $89 million CAD sediment remediation program. The remediation goals are to return this impacted aquatic site to pre-mill tidal conditions. To understand historical sediment characteristics, spatiotemporal variation covering ~quarter century, of metal(loid) sediment concentrations across 103 Boat Harbour samples from 81 stations and four reference locations, were assessed by reviewing secondary data from 1992 to 2015. Metal(loid) sediment concentrations were compared to current Canadian freshwater and marine sediment quality guidelines (SQGs). Seven metal(loid)s, As, Cd, Cr, Cu, Pb, Hg, and Zn, exceeded low effect freshwater and marine SQGs; six, As, Cd, Cr, Pb, Hg, and Zn, exceeded severe effect freshwater SQGs; and four, Cd, Cu, Hg, and Zn, exceeded severe effect marine SQGs. Metal(loid) concentrations varied widely across three distinct temporal periods. Significantly higher Cd, Cu, Pb, Hg, and Zn concentrations were measured between 1998 and 2000, compared to earlier, 1992-1996 and more recent 2003-2015 data. Most samples, 69%, were shallow (0-15 cm), leaving deeper horizons under-characterized. Geographic information system (GIS) techniques also revealed inadequate spatial coverage, presenting challenges for remedy decisions regarding vertical and horizontal delineation of contaminants. Review of historical monitoring data revealed that gaps still exist in our understanding of sediment characteristics in Boat Harbour, including spatial, vertical and horizontal, and temporal variation of sediment contamination. To help return Boat Harbour to a tidal estuary, more detailed sampling is required to better characterize these sediments and to establish appropriate reference (background) concentrations to help develop cost-effective remediation approaches for this decades-old problem.

Protein fold recognition using HMM-HMM alignment and dynamic programming.

Detecting three dimensional structures of protein sequences is a challenging task in biological sciences. For this purpose, protein fold recognition has been utilized as an intermediate step which helps in classifying a novel protein sequence into one of its folds. The process of protein fold recognition encompasses feature extraction of protein sequences and feature identification through suitable classifiers. Several feature extractors are developed to retrieve useful information from protein sequences. These features are generally extracted by constituting protein's sequential, physicochemical and evolutionary properties. The performance in terms of recognition accuracy has also been gradually improved over the last decade. However, it is yet to reach a well reasonable and accepted level. In this work, we first applied HMM-HMM alignment of protein sequence from HHblits to extract profile HMM (PHMM) matrix. Then we computed the distance between respective PHMM matrices using kernalized dynamic programming. We have recorded significant improvement in fold recognition over the state-of-the-art feature extractors. The improvement of recognition accuracy is in the range of 2.7-11.6% when experimented on three benchmark datasets from Structural Classification of Proteins.

Population size and stopover duration estimation using mark-resight data and Bayesian analysis of a superpopulation model.

We present a novel formulation of a mark-recapture-resight model that allows estimation of population size, stopover duration, and arrival and departure schedules at migration areas. Estimation is based on encounter histories of uniquely marked individuals and relative counts of marked and unmarked animals. We use a Bayesian analysis of a state-space formulation of the Jolly-Seber mark-recapture model, integrated with a binomial model for counts of unmarked animals, to derive estimates of population size and arrival and departure probabilities. We also provide a novel estimator for stopover duration that is derived from the latent state variable representing the interim between arrival and departure in the state-space model. We conduct a simulation study of field sampling protocols to understand the impact of superpopulation size, proportion marked, and number of animals sampled on bias and precision of estimates. Simulation results indicate that relative bias of estimates of the proportion of the population with marks was low for all sampling scenarios and never exceeded 2%. Our approach does not require enumeration of all unmarked animals detected or direct knowledge of the number of marked animals in the population at the time of the study. This provides flexibility and potential application in a variety of sampling situations (e.g., migratory birds, breeding seabirds, sea turtles, fish, pinnipeds, etc.). Application of the methods is demonstrated with data from a study of migratory sandpipers.

A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation.

Conserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a Mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental-scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 d of flight with a mean seasonal survivorship of 90.5% (95% Cl = 89.2%, 91.9%), whereas spring migration took a mean of 23.5 d of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry, and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including the Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.

The violation of Fitts' Law: an examination of displacement biases and corrective submovements.

Fitts' Law holds that, to maintain accuracy, movement times of aiming movements must change as a result of varying degrees of movement difficulty. Recent evidence has emerged that aiming to a target located last in an array of placeholders results in a shorter movement time than would be expected by the Fitts' equation-a violation of Fitts' Law. It has been suggested that the violation emerges because the performer adopts an optimized movement strategy in which they partially pre-plan an action to the closest placeholder (undershoot the last placeholder) and rely on a secondary acceleration to propel the limb toward the last location when it is selected as the target (Glazebrook et al. in Hum Mov Sci 39:163-176, 2015). In the current study, we examine this proposal and further elucidate the processes underlying the violation by examining limb displacement and corrective submovements that occur when performers aim to different target locations. For our Main Study, participants executed discrete aiming movements in a five-placeholder array. We also reanalyzed data from a previously reported study in which participants aimed in placeholder and no-placeholder conditions (Blinch et al. in Exp Brain Res 223:505-515, 2012). The results showed the violation of Fitts' Law unfolded following peak velocity (online control). Further, the analysis showed that movements to the last target tended to overshoot and had a higher proportion of secondary submovements featuring a reversal than other categories of submovement (secondary accelerations, discontinuities). These findings indicate that the violation of Fitts' Law may, in fact, result from a strategic bias toward planning farther initial displacements of the limb which accommodates a shorter time in online control.

Oxygen isotope anomaly observed in water vapor from Alert, Canada and the implication for the stratosphere.

To identify the possible anomalous oxygen isotope signature in stratospheric water predicted by model studies, 25 water vapor samples were collected in 2003-2005 at Alert station, Canada (82°30'N), where there is downward transport of stratospheric air to the polar troposphere, and were analyzed for δ(17)O and δ(18)O relative to Chicago local precipitation (CLP). The latter was chosen as a reference because the relatively large evaporative moisture source should erase any possible oxygen isotope anomaly from the stratosphere. A mass-dependent fractionation coefficient for meteoric waters, λMDF(H2O) = 0.529 ± 0.003 [2σ standard error (SE)], was determined from 27 CLP samples collected in 2003-2005. An oxygen isotopic anomaly of Δ(17)O = 76 ± 16 ppm (2σ SE) was found in water vapor samples from Alert relative to CLP. We propose that the positive oxygen isotope anomalies observed at Alert originated from stratospheric ozone, were transferred to water in the stratosphere, and subsequently mixed with tropospheric water at high latitudes as the stratospheric air descended into the troposphere. On the basis of this ground signal, the average Δ(17)O in stratospheric water vapor predicted by a steady-state box model is ∼40‰. Seven ice core samples (1930-1991) from Dasuopu glacier (Himalayas, China) and Standard Light Antarctic Precipitation did not show an obvious oxygen isotope anomaly, and Vienna Standard Mean Ocean Water exhibited a negative Δ(17)O relative to CLP. Six Alert snow samples collected in March 2011 and measured at Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France, had (17)Oexcess of 45 ± 5 ppm (2σ SE) relative to Vienna Standard Mean Ocean Water.

Using a Manipulation Check to Uncover Age-Related Difference in Focus of Attention Instruction During a Balance Task.

BACKGROUND/STUDY CONTEXT: A manipulation check was used to investigate whether there is an age-related difference in the adherence to specific external- and internal-focus instructional constraints. METHODS: Participants stood on a force platform and were to maintain a feedback cursor (representing their center of pressure) along the horizontal direction, within a target on a computer monitor. Trials were conducted with either an external focus of attention (keeping the feedback cursor within the target) or an internal focus of attention (keeping the weight evenly distributed between both legs). RESULTS: The finding showed that younger adults followed the experimental instructions; however, older adults relied on external visual information when they were asked to focus on the body movements. CONCLUSION: Age-related declines may contribute to attention allocation differences. The authors propose that specific manipulation checks be used to ensure proper adherence to instructions when comparing age-related differences in postural control.

Gram-positive and Gram-negative subcellular localization using rotation forest and physicochemical-based features.

BACKGROUND: The functioning of a protein relies on its location in the cell. Therefore, predicting protein subcellular localization is an important step towards protein function prediction. Recent studies have shown that relying on Gene Ontology (GO) for feature extraction can improve the prediction performance. However, for newly sequenced proteins, the GO is not available. Therefore, for these cases, the prediction performance of GO based methods degrade significantly. RESULTS: In this study, we develop a method to effectively employ physicochemical and evolutionary-based information in the protein sequence. To do this, we propose segmentation based feature extraction method to explore potential discriminatory information based on physicochemical properties of the amino acids to tackle Gram-positive and Gram-negative subcellular localization. We explore our proposed feature extraction techniques using 10 attributes that have been experimentally selected among a wide range of physicochemical attributes. Finally by applying the Rotation Forest classification technique to our extracted features, we enhance Gram-positive and Gram-negative subcellular localization accuracies up to 3.4% better than previous studies which used GO for feature extraction. CONCLUSION: By proposing segmentation based feature extraction method to explore potential discriminatory information based on physicochemical properties of the amino acids as well as using Rotation Forest classification technique, we are able to enhance the Gram-positive and Gram-negative subcellular localization prediction accuracies, significantly.

Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC.

Protein subcellular localization is defined as predicting the functioning location of a given protein in the cell. It is considered an important step towards protein function prediction and drug design. Recent studies have shown that relying on Gene Ontology (GO) for feature extraction can improve protein subcellular localization prediction performance. However, relying solely on GO, this problem remains unsolved. At the same time, the impact of other sources of features especially evolutionary-based features has not been explored adequately for this task. In this study, we aim to extract discriminative evolutionary features to tackle this problem. To do this, we propose two segmentation based feature extraction methods to explore potential local evolutionary-based information for Gram-positive and Gram-negative subcellular localizations. We will show that by applying a Support Vector Machine (SVM) classifier to our extracted features, we are able to enhance Gram-positive and Gram-negative subcellular localization prediction accuracies by up to 6.4% better than previous studies including the studies that used GO for feature extraction.

Probabilistic expression of spatially varied amino acid dimers into general form of Chou׳s pseudo amino acid composition for protein fold recognition.

BACKGROUND: Identification of the tertiary structure (3D structure) of a protein is a fundamental problem in biology which helps in identifying its functions. Predicting a protein׳s fold is considered to be an intermediate step for identifying the tertiary structure of a protein. Computational methods have been applied to determine a protein׳s fold by assembling information from its structural, physicochemical and/or evolutionary properties. METHODS: In this study, we propose a scheme in which a feature extraction technique that extracts probabilistic expressions of amino acid dimers, which have varying degree of spatial separation in the primary sequences of proteins, from the Position Specific Scoring Matrix (PSSM). SVM classifier is used to create a model from extracted features for fold recognition. RESULTS: The performance of the proposed scheme is evaluated against three benchmarked datasets, namely the Ding and Dubchak, Extended Ding and Dubchak, and Taguchi and Gromiha datasets. CONCLUSIONS: The proposed scheme performed well in the experiments conducted, providing improvements over previously published results in literature.

Effector mass and trajectory optimization in the online regulation of goal-directed movement.

Goal-directed aiming movements are planned and executed so that they optimize speed, accuracy and energy expenditure. In particular, the primary submovements involved in manual aiming attempts typically undershoot targets in order to avoid costly time and energy overshoot errors. Furthermore, in aiming movements performed over a series of trials, the movement planning process considers the sensory information associated with the most recent aiming attempt. The goal of the current study was to gain further insight into how the sensory consequences associated with the recent and forthcoming aiming attempts impact performance. We first examined whether performers are more conservative in their aiming movements with a heavy, as opposed to a light, stylus by determining whether primary submovements undershot the target to a greater extent in the former due to an anticipated increase in spatial variability. Our results show that movements with the heavy stylus demonstrated greater undershoot biases in the primary submovements, as well as greater trial-to-trial spatial variability at specific trajectory kinematic landmarks. In addition, we also sought to determine whether the sensory information experienced on a previous aiming movement affected movement planning and/or online control on the subsequent aiming attempt. To vary the type sensory consequences experienced on a trial-to-trial basis, participants performed aiming movements with light and heavy styli in either blocked or random orderings of trials. In the random-order conditions, some participants were provided advance information about stylus mass for the upcoming trial, while others were not. The blocked and random trial orders had minimal impacts on end point aiming performance. Furthermore, similarities in the times to key kinematic landmarks in the trajectories of the random-order groups suggest that recent trial experience had a greater effect on the upcoming aiming movement compared with advance task knowledge.