The effects of viscous loading of the human forearm flexors on the stability of coordination

This experiment investigated whether the stability of rhythmic unimanual movements is primarily a function of perceptual/spatial orientation or neuro-mechanical in nature. Eight participants performed rhythmic flexion and extension movements of the left wrist for 30 s at a frequency of 2.25 Hz paced by an auditory metronome. Each participant performed 8 flex-on-the-beat trials and 8 extend-on-the-beat trials in one of two load conditions, loaded and unload. In the loaded condition, a servo-controlled torque motor was used to apply a small viscous load that resisted the flexion phase of the movement only. Both the amplitude and frequency of the movement generated in the loaded and unloaded conditions were statistically equivalent. However, in the loaded condition movements in which participants were required to flex-on-the-beat became less stable (more variable) while extend-on-the-beat movements remained unchanged compared with the unload condition. The small alteration in required muscle force was sufficient to result in reliable changes in movement stability even a situation where the movement kinematics were identical. These findings support the notion that muscular constraints, independent of spatial dependencies, can be sufficiently strong to reliably influence coordination in a simple unimanual task.

Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

Quasi-birth-and-death (QBD) processes with infinite “phase spaces” can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase” giving the state of the first queue and the “level” giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts’s R-matrix and show that the decay rate of the stationary distribution of the “level” process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Capillary network models for transport in packed beds: Considerations of pore aspect ratio

The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Modification of the in vivo four-point loading model for studying mechanically induced bone adaptation

We modified the noninvasive, in vivo technique for strain application in the tibiae of rats (Turner et al,, Bone 12:73-79, 1991), The original model applies four-point bending to right tibiae via an open-loop, stepper-motor-driven spring linkage, Depending on the magnitude of applied load, the model produces new bone formation at periosteal (Ps) or endocortical surfaces (Ec.S). Due to the spring linkage, however, the range of frequencies at which loads can be applied is limited. The modified system replaces this design with an electromagnetic vibrator. A load transducer in series with the loading points allows calibration, the loaders' position to be adjusted, and cyclic loading completed under load central as a closed servo-loop. Two experiments were conducted to validate the modified system: (1) a strain gauge was applied to the lateral surface of the right tibia of 5 adult female rats and strains measured at applied loads from 10 to 60 N; and (2) the bone formation response was determined in 28 adult female Sprague-Dawley rats. Loading was applied as a haversine wave with a frequency of 2 Hz for 18 sec, every second day for 10 days. Peak bending loads mere applied at 33, 40, 52, and 64 N, and a sham-loading group tr as included at 64 N, Strains in the tibiae were linear between 10 and 60 N, and the average peak strain at the Ps.S at 60 N was 2664 +/- 250 microstrain, consistent with the results of Turner's group. Lamellar bone formation was stimulated at the Ec.S by applied bending, but not by sham loading. Bending strains above a loading threshold of 40 N increased Ec Lamellar hone formation rate, bone forming surface, and mineral apposition rate with a dose response similar to that reported by Turner et al, (J Bone Miner Res 9:87-97, 1994). We conclude that the modified loading system offers precision for applied loads of between 0 and 70 N, versatility in the selection of loading rates up to 20 Hz, and a reproducible bone formation response in the rat tibia, Adjustment of the loader also enables study of mechanical usage in murine tibia, an advantage with respect to the increasing variety of transgenic strains available in bone and mineral research. (Bone 23:307-310; 1998) (C) 1998 by Elsevier Science Inc. All rights reserved.

Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

Effects of beta-escin and saponin on the transverse-tubular system and sarcoplasmic reticulum membranes of rat and toad skeletal muscle

Mechanically skinned skeletal muscle fibres from rat and toad were exposed to the permeabilizing agents beta-escin and saponin. The effects of these agents on the sealed transverse tubular system (t-system) and sarcoplasmic reticulum (SR) were examined by looking at changes in the magnitude of the force responses to t-system depolarization, the time course of the fluorescence of fura-2 trapped in the sealed t-system, and changes in the magnitude of caffeine-induced contractures following SR loading with Ca2+ under defined conditions. In the presence of 2 mu g ml(-1) beta-escin and saponin, the response to t-system depolarization was not completely abolished, decreasing to a plateau, and a large proportion of fura-2 remained in the sealed t-system. At 10 mu g ml(-1), both agents abolished the ability of both rat and toad preparations to respond to t-system depolarization after 3 min of exposure, but a significant amount of fura-2 remained in sealed t-tubules even after exposure to 100 mu g ml(-1) beta-escin and saponin for 10 min. beta-Escin took longer than saponin to reduce the t-system depolarizations and fura-2 content of the sealed t-system to a similar level. The ability of the SR to load Ca2+ was reduced to a lower level after treatment with beta-escin than saponin. This direct effect on the SR occurred at much lower concentrations for rat (2 mu g ml(-1) beta-escin and 10 mu g ml(-1) saponin) than toad (10 mu g ml(-1) beta-escin and 150 mu g ml(-1) saponin). The reverse order in sensitivities to beta-escin and saponin of t-system and SR membranes indicates that the mechanisms of action of beta-escin and saponin are different in the two types of membrane. In conclusion, this study shows that: (1) beta-escin has a milder action on the surface membrane than saponin; (2) beta-escin is a more potent modifier of SR function; (3) simple permeabilization of membranes is not sufficient to explain the effects of beta-escin and saponin on muscle membranes; and (4) the t-system network within muscle fibres is not a homogeneous compartment.

A two-dimensional analytical solution of groundwater responses to tidal loading in an estuary and ocean

Previous studies on tidal dynamics of coastal aquifers have focussed on the inland propagation of oceanic tides in the cross-shore direction, a configuration that is essentially one-dimensional. Aquifers at natural coasts can also be influenced by tidal waves in nearby estuaries, resulting in a more complex behaviour of head fluctuations in the aquifers. We present an analytical solution to the two-dimensional depth-averaged groundwater flow equation for a semi-infinite aquifer subject to oscillating head conditions at the boundaries. The solution describes the tidal dynamics of a coastal aquifer that is adjacent to a cross-shore estuary. Both the effects of oceanic and estuarine tides on the aquifer are included in the solution. The analytical prediction of the head fluctuations is verified by comparison with numerical solutions computed using a standard finite-difference method. An essential feature of the present analytical solution is the interaction between the cross- and along-shore tidal waves in the aquifer area near the estuary's entry. As the distance from the estuary or coastline increases, the wave interaction is weakened and the aquifer response is reduced, respectively, to the one-dimensional solution for oceanic tides or the solution of Sun (Sun H. A two-dimensional analytical solution of groundwater response to tidal loading in an estuary, Water Resour Res 1997;33:1429-35) for two-dimensional non-interacting tidal waves. (C) 2000 Elsevier Science Ltd. All rights reserved.

An object-oriented neural network approach to short-term traffic forecasting

This paper discusses an object-oriented neural network model that was developed for predicting short-term traffic conditions on a section of the Pacific Highway between Brisbane and the Gold Coast in Queensland, Australia. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. The results obtained indicate that the TLRN is capable of predicting speed up to 5 minutes into the future with a high degree of accuracy (90-94%). Similar models, which were developed for predicting freeway travel times on the same facility, were successful in predicting travel times up to 15 minutes into the future with a similar degree of accuracy (93-95%). These results represent substantial improvements on conventional model performance and clearly demonstrate the feasibility of using the object-oriented approach for short-term traffic prediction. (C) 2001 Elsevier Science B.V. All rights reserved.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

Virtual models of the HLA class I antigen processing pathway

Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.

Mechanical loading modulates glutamate receptor subunit expression in bone

The cellular mechanisms coupling mechanical loading with bone remodeling remain unclear. In the CNS, the excitatory amino acid glutamate (Glu) serves as a potent neurotransmitter exerting its effects via various membrane Glu receptors (GluR). Nerves containing Glu exist close to bone cells expressing functional GluRs. Demonstration of a mechanically sensitive glutamate/aspartate transporter protein and the ability of glutamate to stimulate bone resorption in vitro suggest a role for glutamate linking mechanical load and bone remodeling. We used immunohistochemical techniques to identify the expression of N-methyl-D-aspartate acid (NMDA) and non-NMDA (AMPA or kainate) ionotropic GluR subunits on bone cells in vivo. In bone sections from young adult rats, osteoclasts expressed numerous GluR subunits including AMPA (GluR2/3 and GluR4), kainic acid (GluR567) and NMDA (NMDAR2A, NMDAR2B and NMDAR2C) receptor subtypes. Bone lining cells demonstrated immunoexpression for NMDAR2A, NMDAR2B, NMDAR2C, GluR567, GluR23, GuR2 and GluR4 subunits. Immunoexpression was not evident on osteocytes, chondrocytes or vascular channels. To investigate the effects of mechanical loading on GluR expression, we used a Materials Testing System (MTS) to apply 10 N sinusoidal axial compressive loads percutaneously to the right limbs (radius/ulna, tibia/fibula) of rats. Each limb underwent 300-load cycles/day (cycle rate, 1 Hz) for 4 consecutive days. Contralateral, non-loaded limbs served as controls. Mechanically loaded limbs revealed a load-induced loss of immunoexpression for GluR2/3, GluR4, GluR567 and NMDAR2A on osteoclasts and NMDAR2A, NMDAR2B, GluR2/3 and GluR4 on bone lining cells. Both neonatal rabbit and rat osteoclasts were cultured on bone slices to investigate the effect of the NMDA receptor antagonist, MK801, and the AMPA/kainic acid receptor antagonist, NBQX, on osteoclast resorptive activity in vitro. The inhibition of resorptive function seen suggested that both NMDAR and kainic acid receptor function are required for normal osteoclast function. While the exact role of ionotropic GluRs in skeletal tissue remains unclear, the modulation of GluR subunit expression by mechanical loading lends further support for participation of Glu as a mechanical loading effector. These ionotropic receptors appear to be functionally relevant to normal osteoclast resorptive activity. (C) 2005 Elsevier Inc. All rights reserved.