Predictive Modes Research Articles

Integration of negative experiences: A neuropsychological framework for human resilience.

We propose that the fundamental mechanism underlying resilience is the integration of novel or negative experiences into internal schemata. This process requires a switch from reactive to predictive control modes, from the brain's salience network to the default mode network. Reappraisal, among other mechanisms, is suggested to facilitate this process.

Predictive modes of action of pesticides in uterine adenocarcinoma development in rats.

Endometrial adenocarcinoma in the uterine corpus is a malignant cancer that occurs in menopausal women and aged rodents. Because of the similarities in pathogenesis and morphology of endometrial adenocarcinoma in rodents and humans, prediction of the modes of action (MOA) in uterine carcinogenesis is important for extrapolation of rodent data to humans. Three MOAs have been accepted as major pathways for uterine carcinogenesis in rodents: 1) estrogenic activity, 2) increased serum 17beta-estradiiol (E2) to progesterone (P4) ratio and 3) modulation of estrogen metabolism to produce 4-hydroxyestradiol via P450 induction. Inhibition of estrogen excretion and increased aromatase in situ in the tumor are also a potential pathway. Here, chemicals showing uterine carcinogenicity were chosen from approximately 300 pesticides evaluated in Japan within the past decade, and their mechanisms were predicted using parameters from mechanistic and toxicity studies. Seven pesticides increased uterine tumor formation in rats, and the pathways of 4 pesticides could be predicted based on various mechanistic studies. The MOAs of cyenopyrafen and benthiavalicarb-isopropyl were predicted to be modulation of estrogen metabolism, while those of pyriminobac-methyl and spirodiclofen were predicted to be increased E2 to P4 ratio. The driven pathways of metazosulfuron and isopyrazam could not be predicted using several mechanistic studies. No mechanistic studies have been reported for sedaxane, which has a chemical structure and toxicological profile similar to isopyrazam. Our results indicated that appropriate mechanistic studies are useful for mechanism prediction in risk assessment. From this analysis, a flowchart showing a decision tree for predictive MOAs in uterine carcinogenesis was proposed.

Insight into the Predictive Binding Modes of the Influenza a Neuraminidase in Complexes with Avian and Human Receptor Analogues

The binding modes of the influenza A(H7N9) neuraminidase in complexes with avian-type (3′-SLN) and human-type (6&prime-SLN) receptor analogues are investigated by combined homology modelling, molecular docking and quantum mechanical/molecular mechanical (QM/MM) methods. The results reveal that these two analogues could be docked into the active site surrounding by residues of R118, T148, R152, E227, R276 and R371, and bind well in the receptor binding site. Comparing with the docking results, we find that the stabilities of the binding modes are all strengthened after optimisation. However, human-type 6′-SLN might be a preferable receptor analogue as it generates more HB interactions. Whether in the docking results or in the optimised structures, both of analogues (3′-SLN and 6′-SLN) bind in the receptor binding site mainly using their sialic acid groups of the analogues. This conclusion is consistent with most experimental results obtained from crystal structures. Our results give a good understanding on how the N9 interacts with host receptors from a structural perspective. They support the conclusion that the receptor binding mode might be changed from a avian-type to human-type receptor binding. This result might provide a theoretical guide for the study of the influenza A (H7N9) in the future.

Spontaneous Motor Tempo is the Easiest Pace to Act Upon for Both the Emergent and the Predictive Timing Modes

Spontaneous Motor Tempo is the Easiest Pace to Act Upon for Both the Emergent and the Predictive Timing Modes

Brain Systems for Probabilistic and Dynamic Prediction: Computational Specificity and Integration

Author SummaryTo interact effectively with the environment, brains must predict future events based on past and current experience. Predictions associated with different behavioural domains of the brain are often associated with different algorithmic forms. For example, whereas the motor system makes dynamic moment-by-moment predictions based on physical world models, the reward system is more typically associated with statistical predictions learned over discrete events. However, in perceptually rich natural environments, behaviour is not neatly segmented into tasks like “reward learning” and “motor control.” Instead, many different types of information are available in parallel. The brain must both select behaviourally relevant information and arbitrate between conflicting predictions. To investigate how the brain balances and integrates different types of predictive information, we set up a task in which humans predicted an object's flight trajectory by using one of two strategies: either a statistical model (based on where objects had often landed in the past) or dynamic calculation of the current flight trajectory. Using fMRI, we show that brain activity switches between different regions of the brain, depending on which predictive strategy was used, even though behavioural output remained the same. Furthermore, we found that brain regions involved in selecting actions took into account the predictions from both competing algorithms, weighting each algorithm optimally in terms of the precision with which it could predict the event of interest. Thus, these distinct brain systems compete to control predictive behaviour.

Motion sickness on tilting trains.

Trains that tilt on curves can go faster, but passengers complain of motion sickness. We studied the control signals and tilts to determine why this occurs and how to maintain speed while eliminating motion sickness. Accelerometers and gyros monitored train and passenger yaw and roll, and a survey evaluated motion sickness. The experimental train had 3 control configurations: an untilted mode, a reactive mode that detected curves from sensors on the front wheel set, and a predictive mode that determined curves from the train's position on the tracks. No motion sickness was induced in the untilted mode, but the train ran 21% slower than when it tilted 8° in either the reactive or predictive modes (113 vs. 137 km/h). Roll velocities rose and fell faster in the predictive than the reactive mode when entering and leaving turns (0.4 vs. 0.8 s for a 4°/s roll tilt, P<0.001). Concurrently, motion sickness was greater (P<0.001) in the reactive mode. We conclude that the slower rise in roll velocity during yaw rotations on entering and leaving curves had induced the motion sickness. Adequate synchronization of roll tilt with yaw velocity on curves will reduce motion sickness and improve passenger comfort on tilting trains.

Effective Subblock-Based and Pixel-Based Fast Direction Detections for H.264 Intra Prediction

In H.264/AVC intra-frame coding, the rate-distortion optimization (RDO) is employed to select the optimal coding mode to achieve the minimum rate-distortion cost. Due to a large number of combinations of coding modes, the computational burden becomes extremely high in intra-prediction. In this paper, we propose two fast, efficient but reliable direction detection algorithms by computing subblock and pixel direction differences. Both proposed methods effectively estimate the edge direction inside the block to narrow down the predictive modes to reduce the RDO computation. Experimental results show that the proposed methods can reduce the encoding time by about 60% with negligible loss of coding performance. For hardware realization, a fast mode decision VLSI circuit for intra-prediction with the silicon core size of 0.12 times 0.12 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> at 0.18-mum CMOS technology is implemented. The fast mode decision VLSI in three-stage pipelined architecture operated at 173 MHz can encode 30 fps real-time videos up to Level 5.

A Fast Mode Decision Algorithm and Its VLSI Design for H.264/AVC Intra-Prediction

In this paper, we present a fast mode decision algorithm and design its VLSI architecture for H.264 intra-prediction. A regular spatial domain filtering technique is proposed to compute the dominant edge strength (DES) to reduce the possible predictive modes. Experimental results revealed that the proposed fast intra-algorithm reduces 40% computation with slight peak signal-to-noise ratio (PSNR) degradation. The designed DES VLSI engine comprises a zigzag converter, a DES finite-state machine (FSM), and a DES core. The former two units handle memory allocation and control flow while the last performs pseudoblock computation, edge filtering, and dominant edge strength extraction. With semicustom design fabricated by 0.18 mum CMOS single-poly-six-metal technology, the realized die size is roughly 0.15 times 0.15 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and can be operated at 66 MHz.

Analysing the influence of upslope bedrock outcrops on shallow landsliding

A model for the prediction of topographic and climatic control on shallow landsliding in mountainous terrain is enhanced to analyse the impact of upslope rocky outcrops on downslope shallow landsliding. The model uses a ‘generalised quasi-dynamic wetness index’ to describe runoff propagation on bare rock surfaces connected to downslope soil-mantled topographic elements. This approach yields a simple enhanced model capable of describing the influence of upslope bedrock outcrops on the pattern of downslope soil saturation. The model is applied in both diagnostic and predictive modes to a small catchment in the eastern Italian Alps for which a detailed inventory of shallow landslides in areas dominated by rocky outcrops is available. In the diagnostic mode, the model is used with satisfactory results to reproduce the pattern of instability generated by an intense short-duration storm occurred on 14 September 1994, which triggered a large percentage of the surveyed landslides. In the predictive mode, the model is used for hazard assessment, and the return time of the critical rainfall needed to cause instability for each topographic element is determined. Modelling results obtained in the predictive mode are evaluated against all the surveyed landslides. It is revealed that the generalised quasi-dynamic model offers considerable improvement over the non-generalised quasi-dynamic model and the steady-state model in predicting existing landslides as represented in the considered landslide inventory.

Subdomain generation using emergent ant colony optimization

Finite elements mesh decomposition is a well known optimization problem and is used to split a computationally expensive finite elements mesh into smaller subdomains for parallel finite elements analysis. The ant colony optimization is a type of algorithm that seeks to model the emergent behaviour observed in ant colonies and utilize this behaviour to solve combinatorial problems. This technique has been applied to several problems, most of which are graph related because the ant colony metaphor can be most easily applied to such types of problems. This paper examines the application of ant colony optimization algorithm to the partitioning of unstructured adaptive meshes for parallel explicit time-stepping finite elements analysis. The concept of ant colony optimization technique in addition to the notion of swarm intelligence for finding approximate solutions to combinatorial optimization problems is described. This algorithm combines the features of the classical ant colony optimization technique with swarm intelligence to form a model which is an artificial system designed to perform a certain task. The application of the ant colony optimization for partitioning finite elements meshes based on triangular elements using the swarm intelligence concept is described. A recursive greedy algorithm optimization method is also presented as a local optimization technique to improve the quality of the solutions given by the ant colony optimization algorithm. The partitioning is based on the recursive bisection approach. The mesh partitioning is carried out using normal and predictive modes for which the predictive mode uses a trained multi-layered feedforward neural network that estimates the number of triangular elements that will be generated after finite elements mesh generation is carried out. The performance of the proposed hybrid approach for the recursive bisection of finite elements meshes is examined by decomposing two mesh examples and comparing them with a well known finite elements domain decomposer.

Predictive and reactive control of grasping forces: on the role of the basal ganglia and sensory feedback

We comparatively investigated predictive and reactive grip force behaviour in 12 subjects with basal ganglia dysfunction (six subjects with Parkinson's disease, six subjects with writer's cramp), two subjects chronically lacking all tactile and proprioceptive sensory feedback and 16 sex- and age-matched control subjects. Subjects held an instrumented receptacle between the index finger and thumb. A weight was dropped into the receptacle either unexpectedly from the experimenter's hand with the subject being blindfolded or expectedly from the subject's opposite hand. This paradigm allowed us to study predictive and reactive modes of grip force control. All patients generated an overshoot in grip force, irrespective of whether the weight was dropped expectedly or unexpectedly. When the weight was dropped from the experimenter's hand, a reactive grip force response lagged behind the load perturbation at impact in patients with basal ganglia dysfunction and healthy controls. When the weight was dropped expectedly from the subject's opposite hand, patients with basal ganglia dysfunction and healthy subjects started to increase grip force prior to the release of the weight, indicating a predictive mode of control. We interpret these data to support the notion that the motor dysfunction in basal ganglia disorders is associated with deficits of sensorimotor integration. Both deafferented subjects did not show a reactive mode of force control when the weight was dropped unexpectedly, underlining the importance of sensory feedback to initiate reactive force responses. Also in the predictive mode, grip force processing was severely impaired in deafferented subjects. Thus, at least intermittent sensory information is necessary to establish and update predictive modes of grasping force control.

Sequences of Predictive Saccades Are Correlated Over a Span of ∼2 s and Produce a Fractal Time Series

We previously demonstrated that there is an abrupt (rather than smooth) transition between reactive and predictive modes of eye-movement tracking of target lights (a phase transition). We also found evidence that the sequence of eye movements in the reactive mode was independent, whereas those in the predictive mode were correlated and possibly formed a random fractal sequence. Here we confirm the finding of fractal structure by quantifying the rate of decay of nonlinear forecasting when applied to these data. We also estimate the window over which consecutive trials are correlated and show that the duration of this window is fixed in time rather than number of trials. These results have implications for the neural mechanisms that drive predictive movements.

Phase transition between reactive and predictive eye movements is confirmed with nonlinear forecasting and surrogates

We previously demonstrated that there is an abrupt (rather than smooth) transition between reactive and predictive modes of eye-movement tracking of target lights (a phase transition). We also found evidence that the sequence of eye movements in the reactive mode was independent, while those in the predictive mode were correlated and possibly formed a random fractal sequence. Here, we confirm this finding by quantifying the rate of decay of nonlinear forecasting when applied to these data, and develop an extension to small data sets using surrogate data. Verification of these statistical properties in small data sets will be of great use in situations, such as the clinical testing of neurological patients, in which testing time is limited due to subject discomfort or other considerations.

Performance evaluation of a model describing the effects of temperature, water activity, pH and lactic acid concentration on the growth of Escherichia coli

A square root-type model for Escherichia coli growth in response to temperature, water activity, pH and lactic acid was developed by Ross et al. [Int. J. Food Microbiol. (2002).]. Predicted generation times from the model were compared to the literature data using bias and accuracy factors, graphical comparisons and plots of residuals for data obtained from both liquid growth media and foods. The model predicted well for 1025 growth rate estimates reported in the literature after poor quality or unrepresentative data ( n=215) was excluded, with a bias factor of 0.92, and an accuracy factor of 1.29. In a detailed comparison to two other predictive modes for E. coli growth, Pathogen Modeling Program (PMP) and Food MicroModel (FMM), the new model generally performed better. The new model consistently gave better predictions than the other models at generation times ≤5 h. Inclusion of the lactic acid term in the model is proposed to account for the consistently good performance of the model for comparisons to growth in meat, a parameter that is not explicitly included in the other models considered in the comparisons.

Physical Properties, Reactor Modeling, and Polymerization Kinetics in the Low-Density Polyethylene Tubular Reactor Process

In this investigation, we demonstrate our methodology in developing a comprehensive computer simulation model for the low-density polyethylene process in a tubular reactor using Polymers Plus. We use the perturbed-chain statistical associating fluid theory to describe the thermodynamic properties of the system. A comparison with literature data shows that the selected equation of state does a very good job in describing the physical properties and phase equilibria of the system. A detailed reactor model was proposed on the basis of transport literature that provides insight into the various resistances to heat transfer that arise during polymerization, and a comprehensive free-radical kinetic model was developed that describes the various individual mechanisms of the polymerization of ethylene and the properties of the polymer product. Results from the proposed simulation model were used in comparison with plant measurements from an Equistar Chemicals plant, in both correlative and predictive modes, for several polymer grades. In all cases considered, very good agreement was observed between simulation results and plant data on reactor temperature profiles, polymer properties, and production rates.

A comparison of 2 methods of measuring rectal temperatures with digital thermometers

Digital rectal thermometers typically have 2 distinct modes of operation: dwell or monitor, in which body temperature is displayed continuously, and predictive, in which body temperature is mathematically estimated on the basis of the curve of temperature rise that occurs after the thermometer is inserted. Although the dwell mode is generally considered more accurate, the predictive mode allows more rapid measurement. Direct comparisons of these 2 methods are lacking. To determine if measurements of rectal temperatures obtained with the predictive mode differ significantly from those obtained with the dwell mode. For each of 10 subjects, both dwell and predictive modes were used to measure early morning rectal temperature. For comparison of the 2 modes during states of temperature flux, 8 subjects had rectal temperatures measured after swimming in cold water. Initial predictive values were measured directly after each subject exited from the water. Initial dwell values were estimated by linear extrapolation of measured 3- and 6-minute dwell values. Paired-sample statistical methods were used to compare data. Measurements of early-morning temperatures obtained with the predictive mode did not differ significantly from those obtained with the dwell mode (P = .64). Predictive values also did not differ significantly from extrapolated dwell values for measurements obtained during mild temperature flux after immersion in cold water (P = .33). The predictive and dwell modes of digital rectal thermometers yield similar measurements of temperature during steady-state conditions and during states of mild temperature flux.

Neonatal Axillary Temperature Measurements: A Comparison of Electronic Thermometer Predictive and Monitor Modes

To determine whether predictive mode axillary temperature measurement is accurate in full-term newborns. Prospective, descriptive, comparative study. An acute-care community hospital in western Canada. A convenience sample of 72 healthy full-term newborns. Predictive and monitor mode axillary temperatures were measured once for each participant. Monitor mode axillary temperature served as the reference. Predictive and monitor mode axillary temperatures were compared using paired t tests and correlation analysis (Pearson's r). The time for monitor mode stabilization also was determined. A statistically but not clinically significant difference (.08 degrees C) between mean predictive and monitor mode axillary temperatures as well as a positive correlation were noted. Mean stabilization time for monitor mode axillary temperature was 3 minutes. The use of predictive mode temperature measurement at the axillary site in full-term healthy newborns is supported by this study. Although mean placement time for monitor mode temperature stabilization was 3 minutes, almost half of the sample did not achieve a stabilized temperature within this time. Further study is recommended in this area.

Modelling large urban drainage systems in real time

The interactions between rainfall and urban drainage systems (UDSs) are complex and must be considered as a whole in order to maximise control efficiency whilst at the same time achieving environmentally acceptable solutions. More rigorous standards, as a result of recent EU and UK legislation, are increasingly encouraging intervention in system management rather than more traditional passive procedures. To achieve these goals a global predictive real-time control (RTC) strategy is required, in which real-time flow prediction plays an important part in the provision of necessary first-hand information on system status in both current and predictive modes. This paper describes one such strategy, which differs from existing methods in the following ways: the novel way in which the UDS is represented; the algorithm used for model parameter identification; the strategies associated with the system output prediction; and the transfer function model used to represent the system. This transfer function model is a conceptually parameterised transfer function (CPTF) model, which by its nature falls into the category of lumped, dynamic, linear and conceptual although its structure takes the form of a non-conceptual transfer function model. The modelling approach is described as the RHINOS (Real-time urban Hydrological INfrastructure and Output modelling Strategy).

Modelling large urban drainage systems in real time

The interactions between rainfall and urban drainage systems (UDSs) are complex and must be considered as a whole in order to maximise control efficiency whilst at the same time achieving environmentally acceptable solutions. More rigorous standards, as a result of recent EU and UK legislation, are increasingly encouraging intervention in system management rather than more traditional passive procedures. To achieve these goals a global predictive real-time control (RTC) strategy is required, in which real-time flow prediction plays an important part in the provision of necessary first-hand information on system status in both current and predictive modes. This paper describes one such strategy, which differs from existing methods in the following ways: the novel way in which the UDS is represented; the algorithm used for model parameter identification; the strategies associated with the system output prediction; and the transfer function model used to represent the system. This transfer function model is a conceptually parameterised transfer function (CPTF) model, which by its nature falls into the category of lumped, dynamic, linear and conceptual although its structure takes the form of a non-conceptual transfer function model. The modelling approach is described as the RHINOS (Real-time urban Hydrological INfrastructure and Output modelling Strategy).

A method for biomolecular structural recognition and docking allowing conformational flexibility.

In this work, we present an algorithm developed to handle biomolecular structural recognition problems, as part of an interdisciplinary research endeavor of the Computer Vision and Molecular Biology fields. A key problem in rational drug design and in biomolecular structural recognition is the generation of binding modes between two molecules, also known as molecular docking. Geometrical fitness is a necessary condition for molecular interaction. Hence, docking a ligand (e.g., a drug molecule or a protein molecule), to a protein receptor (e.g., enzyme), involves recognition of molecular surfaces. Conformational transitions by "hinge-bending" involves rotational movements of relatively rigid parts with respect to each other. The generation of docked binding modes between two associating molecules depends on their three dimensional structures (3-D) and their conformational flexibility. In comparison to the particular case of rigid-body docking, the computational difficulty grows considerably when taking into account the additional degrees of freedom intrinsic to the flexible molecular docking problem. Previous docking techniques have enabled hinge movements only within small ligands. Partial flexibility in the receptor molecule is enabled by a few techniques. Hinge-bending motions of protein receptors domains are not addressed by these methods, although these types of transitions are significant, e.g., in enzymes activity. Our approach allows hinge induced motions to exist in either the receptor or the ligand molecules of diverse sizes. We allow domains/subdomains/group of atoms movements in either of the associating molecules. We achieve this by adapting a technique developed in Computer Vision and Robotics for the efficient recognition of partially occluded articulated objects. These types of objects consist of rigid parts which are connected by rotary joints (hinges). Our method is based on an extension and generalization of the Hough transform and the Geometric Hashing paradigms for rigid object recognition. We show experimental results obtained by the successful application of the algorithm to cases of bound and unbound molecular complexes, yielding fast matching times. While the "correct" molecular conformations of the known complexes are obtained with small RMS distances, additional, predictive good-fitting binding modes are generated as well. We conclude by discussing the algorithm's implications and extensions, as well as its application to investigations of protein structures in Molecular Biology and recognition problems in Computer Vision.