Memory of past random wave conditions in submarine groundwater discharge

Submarine groundwater discharge (SGD) is an integral part of the hydrological cycle and represents an important aspect of land-ocean interactions. We used a numerical model to simulate flow and salt transport in a nearshore groundwater aquifer under varying wave conditions based on yearlong random wave data sets, including storm surge events. The results showed significant flow asymmetry with rapid response of influxes and retarded response of effluxes across the seabed to the irregular wave conditions. While a storm surge immediately intensified seawater influx to the aquifer, the subsequent return of intruded seawater to the sea, as part of an increased SGD, was gradual. Using functional data analysis, we revealed and quantified retarded, cumulative effects of past wave conditions on SGD including the fresh groundwater and recirculating seawater discharge components. The retardation was characterized well by a gamma distribution function regardless of wave conditions. The relationships between discharge rates and wave parameters were quantifiable by a regression model in a functional form independent of the actual irregular wave conditions. This statistical model provides a useful method for analyzing and predicting SGD from nearshore unconfined aquifers affected by random waves

Structural basis for the function of anti-idiotypic antibody in immune memory

We had earlier proposed a hypothesis to explain the mechanism of perpetuation of immunological memory based on the operation of idiotypic network in the complete absence of antigen. Experimental evidences were provided for memory maintenance through anti-idiotypic antibody (Ab(2)) carrying the internal image of the antigen. In the present work, we describe a structural basis for such memory perpetuation by molecular modeling and structural analysis studies. A three-dimensional model of Ab(2) was generated and the structure of the antigenic site on the hemagglutinin protein H of Rinderpest virus was modeled using the structural template of hemagglutinin protein of Measles virus. Our results show that a large portion of heavy chain containing the CDR regions of Ab(2) resembles the domain of the hemagglutinin housing the epitope regions. The similarity demonstrates that an internal image of the H antigen is formed in Ab(2), which provides a structural basis for functional mimicry demonstrated earlier. This work brings out the importance of the structural similarity between a domain of hemagglutinin protein to that of its corresponding Ab(2). It provides evidence that Ab(2) is indeed capable of functioning as surrogate antigen and provides support to earlier proposed relay hypothesis which has provided a mechanism for the maintenance of immunological memory.

Asymptotic behavior of a hierarchical system of learning automata

Learning automata arranged in a two-level hierarchy are considered. The automata operate in a stationary random environment and update their action probabilities according to the linear-reward- -penalty algorithm at each level. Unlike some hierarchical systems previously proposed, no information transfer exists from one level to another, and yet the hierarchy possesses good convergence properties. Using weak-convergence concepts it is shown that for large time and small values of parameters in the algorithm, the evolution of the optimal path probability can be represented by a diffusion whose parameters can be computed explicitly.

SHAMP: An experimental shared memory multimicroprocessor system for performance evaluation of parallel algorithms

In this paper, the design and implementation of a single shared bus, shared memory multiprocessing system using Intel's single board computers is presented. The hardware configuration and the operating system developed to execute the parallel algorithms are discussed. The performance evaluation studies carried out on Image are outlined.

Disease mapping using Bayesian hierarchical models

description and analysis of geographically indexed health data with respect to demographic, environmental, behavioural, socioeconomic, genetic, and infectious risk factors (Elliott andWartenberg 2004). Disease maps can be useful for estimating relative risk; ecological analyses, incorporating area and/or individual-level covariates; or cluster analyses (Lawson 2009). As aggregated data are often more readily available, one common method of mapping disease is to aggregate the counts of disease at some geographical areal level, and present them as choropleth maps (Devesa et al. 1999; Population Health Division 2006). Therefore, this chapter will focus exclusively on methods appropriate for areal data...

Predicting health programme participation: A gravity‐based, hierarchical modelling approach

Statistical analyses of health program participation seek to address a number of objectives compatible with the evaluation of demand for current resources. In this spirit, a spatial hierarchical model is developed for disentangling patterns in participation at the small area level, as a function of population-based demand and additional variation. For the former, a constrained gravity model is proposed to quantify factors associated with spatial choice and account for competition effects, for programs delivered by multiple clinics. The implications of gravity model misspecification within a mixed effects framework are also explored. The proposed model is applied to participation data from a no-fee mammography program in Brisbane, Australia. Attention is paid to the interpretation of various model outputs and their relevance for public health policy.

Comment on path integration of a quadratic action with a generalized memory

Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.

A hierarchical system of learning automata that can learn die globally optimal path

Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

Hierarchical Control of an Ammonia Reactor

An approach is presented for hierarchical control of an ammonia reactor, which is a key unit process in a nitrogen fertilizer complex. The aim of the control system is to ensure safe operation of the reactor around the optimal operating point in the face of process variable disturbances and parameter variations. The four different layers perform the functions of regulation, optimization, adaptation, and self-organization. The simulation for this proposed application is conducted on an AD511 hybrid computer in which the AD5 analog processor is used to represent the process and the PDP-11/ 35 digital computer is used for the implementation of control laws. Simulation results relating to the different layers have been presented.

Constitutive modeling of shape memory alloy wire with non-local rate kinetics

A constitutive modeling approach for shape memory alloy (SMA) wire by taking into account the microstructural phase inhomogeneity and the associated solid-solid phase transformation kinetics is reported in this paper. The approach is applicable to general thermomechanical loading. Characterization of various scales in the non-local rate sensitive kinetics is the main focus of this paper. Design of SMA materials and actuators not only involve an optimal exploitation of the hysteresis loops during loading-unloading, but also accounts for fatigue and training cycle identifications. For a successful design of SMA integrated actuator systems, it is essential to include the microstructural inhomogeneity effects and the loading rate dependence of the martensitic evolution, since these factors play predominant role in fatigue. In the proposed formulation, the evolution of new phase is assumed according to Weibull distribution. Fourier transformation and finite difference methods are applied to arrive at the analytical form of two important scaling parameters. The ratio of these scaling parameters is of the order of 10(6) for stress-free temperature-induced transformation and 10(4) for stress-induced transformation. These scaling parameters are used in order to study the effect of microstructural variation on the thermo-mechanical force and interface driving force. It is observed that the interface driving force is significant during the evolution. Increase in the slopes of the transformation start and end regions in the stress-strain hysteresis loop is observed for mechanical loading with higher rates.

Memory disorders in acute encephalitis : A neuropsychological study

Acute encephalitis is an inflammation of the brain, mostly caused by viral infection. A variety of cognitive symptoms may persist after the acute stage, and neuropsychological assessment is crucial in evaluation of the outcome. The most commonly reported sequelae are memory deficits. The main aims of this study were to investigate the types of memory impairment in various encephalitides, the frequency of global amnesia following encephalitis, and the changes in the deficits during follow-up. Between 1 January 1985 and 31 December 1994, 77 adult patients under the age of 75 with acute encephalitis but without alcohol abuse, or coexisting or previous neurological diseases were consecutively referred for neuropsychological examination at the Department of Neurology, Helsinki University Central Hospital. The aetiology was established in 44/77 (57%) patients; 17 had Herpes simplex virus encephalitis (HSVE). Transient amnesia (TENA) at the acute stage of the disease was found in 70% of patients. Furthermore, similarly to brain trauma, TENA was found to indicate cognitive outcome. The frequency of persisting global amnesia syndrome with both anterograde and retrograde amnesia in all encephalitic patients was 6%. One patient had isolated retrograde amnesia, which is very rare. In HSVE the frequency of global amnesia was 12.5%, which is lower than expected. As a group, HSVE patients were not found to have a homogeneous pattern of amnesia, instead subgroups among all encephalitic patients were observed: some patients had impaired semantic memory, some had difficulty predominantly with executive functions and some suffered from an increased forgetting rate. Herpes zoster encephalitis was found to result in mild memory impairment only, and the qualitative features indicated a subcortical dysfunction. On the whole, the cognitive deficits were predominantly found to diminish during follow-up. Progressive deterioration was often associated with intractable epilepsy. The frequency of dementia was 12.5%. In conclusion, the neuropsychological outcome, especially in HSVE, was more favourable than has previously been reported, possibly due to early acyclovir medication. Memory disorders after encephalitis should not be considered uniform, and the need for neuropsychological rehabilitation should be considered case-by-case

Oscillatory brain activity in memory disorders

Neuronal oscillations are thought to underlie interactions between distinct brain regions required for normal memory functioning. This study aimed at elucidating the neuronal basis of memory abnormalities in neurodegenerative disorders. Magnetoencephalography (MEG) was used to measure oscillatory brain signals in patients with Alzheimer s disease (AD), a neurodegenerative disease causing progressive cognitive decline, and mild cognitive impairment (MCI), a disorder characterized by mild but clinically significant complaints of memory loss without apparent impairment in other cognitive domains. Furthermore, to help interpret our AD/MCI results and to develop more powerful oscillatory MEG paradigms for clinical memory studies, oscillatory neuronal activity underlying declarative memory, the function which is afflicted first in both AD and MCI, was investigated in a group of healthy subjects. An increased temporal-lobe contribution coinciding with parieto-occipital deficits in oscillatory activity was observed in AD patients: sources in the 6 12.5 Hz range were significantly stronger in the parieto-occipital and significantly weaker in the right temporal region in AD patients, as compared to MCI patients and healthy elderly subjects. Further, the auditory steady-state response, thought to represent both evoked and induced activity, was enhanced in AD patients, as compared to controls, possibly reflecting decreased inhibition in auditory processing and deficits in adaptation to repetitive stimulation with low relevance. Finally, the methodological study revealed that successful declarative encoding and retrieval is associated with increases in occipital gamma and right hemisphere theta power in healthy unmedicated subjects. This result suggests that investigation of neuronal oscillations during cognitive performance could potentially be used to investigate declarative memory deficits in AD patients. Taken together, the present results provide an insight on the role of brain oscillatory activity in memory function and memory disorders.

Human brain networks of auditory attention and working memory

This thesis examines brain networks involved in auditory attention and auditory working memory using measures of task performance, brain activity, and neuroanatomical connectivity. Auditory orienting and maintenance of attention were compared with visual orienting and maintenance of attention, and top-down controlled attention was compared to bottom-up triggered attention in audition. Moreover, the effects of cognitive load on performance and brain activity were studied using an auditory working memory task. Corbetta and Shulman s (2002) model of visual attention suggests that what is known as the dorsal attention system (intraparietal sulcus/superior parietal lobule, IPS/SPL and frontal eye field, FEF) is involved in the control of top-down controlled attention, whereas what is known as the ventral attention system (temporo-parietal junction, TPJ and areas of the inferior/middle frontal gyrus, IFG/MFG) is involved in bottom-up triggered attention. The present results show that top-down controlled auditory attention also activates IPS/SPL and FEF. Furthermore, in audition, TPJ and IFG/MFG were activated not only by bottom-up triggered attention, but also by top-down controlled attention. In addition, the posterior cerebellum and thalamus were activated by top-down controlled attention shifts and the ventromedial prefrontal cortex (VMPFC) was activated by to-be-ignored, but attention-catching salient changes in auditory input streams. VMPFC may be involved in the evaluation of environmental events causing the bottom-up triggered engagement of attention. Auditory working memory activated a brain network that largely overlapped with the one activated by top-down controlled attention. The present results also provide further evidence of the role of the cerebellum in cognitive processing: During auditory working memory tasks, both activity in the posterior cerebellum (the crus I/II) and reaction speed increased when the cognitive load increased. Based on the present results and earlier theories on the role of the cerebellum in cognitive processing, the function of the posterior cerebellum in cognitive tasks may be related to the optimization of response speed.

Comment on “path integration of a quadratic action with a generalized memory

Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.

A multi-hierarchical strategy for on-ramp coordination

Ramp metering (RM) is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, RM algorithms fall into two categories by their effective scope: local control and coordinated control. Local control algorithm determines the metering rate based on the traffic condition on adjacent motorway mainline and the on-ramp. Conversely, coordinated RM strategies make use of measurements from the entire motorway network to operate individual ramp signals for optimal performance at the network level. This study proposes a multi-hierarchical strategy for on-ramp coordination. The strategy is structured in two layers. At the higher layer, a centralised, predictive controller plans the coordination control within a long update interval based on the location of high-risk breakdown flow. At the lower layer, reactive controllers determine the metering rates of those ramps involved in the ramp coordination with a short update interval. This strategy is modelled and applied to the northbound model of the Pacific Motorway in a micro-simulation platform (AIMSUN). The simulation results show that the proposed strategy effectively delays the onset of congestion and reduces total congestion with better managed on-ramp queues.