A neuro-adaptive augmented optimal dynamic inversion approach for effective and efficient treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.

Adaptive load control of the central processor in a distributed system with a star topology

The author presents adaptive control techniques for controlling the flow of real-time jobs from the peripheral processors (PPs) to the central processor (CP) of a distributed system with a star topology. He considers two classes of flow control mechanisms: (1) proportional control, where a certain proportion of the load offered to each PP is sent to the CP, and (2) threshold control, where there is a maximum rate at which each PP can send jobs to the CP. The problem is to obtain good algorithms for dynamically adjusting the control level at each PP in order to prevent overload of the CP, when the load offered by the PPs is unknown and varying. The author formulates the problem approximately as a standard system control problem in which the system has unknown parameters that are subject to change. Using well-known techniques (e.g., naive-feedback-controller and stochastic approximation techniques), he derives adaptive controls for the system control problem. He demonstrates the efficacy of these controls in the original problem by using the control algorithms in simulations of a queuing model of the CP and the load controls.

Optimal Blood Glucose Regulation using Single Network Adaptive Critics

Diabetes is a serious disease during which the body's production and use of insulin is impaired, causing glucose concentration level toincrease in the bloodstream. Regulating blood glucose levels as close to normal as possible, leads to a substantial decrease in long term complications of diabetes. In this paper, an intelligent neural network on-line optimal feedback treatment strategy based on nonlinear optimal control theory is presented for the disease using subcutaneous treatment strategy. A simple mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system is considered based on the Bergman's minimal model. A glucose infusion term representing the effect of glucose intake resulting from a meal is introduced into the model equations. The efficiency of the proposed controllers is shown taking random parameters and random initial conditions in presence of physical disturbances like food intake. A comparison study with linear quadratic regulator theory brings Out the advantages of the nonlinear control synthesis approach. Simulation results show that unlike linear optimal control, the proposed on-line continuous infusion strategy never leads to severe hypoglycemia problems.

New a posteriori error estimator and adaptive mesh refinement strategy for 2-D crack problems

A posteriori error estimation and adaptive refinement technique for fracture analysis of 2-D/3-D crack problems is the state-of-the-art. The objective of the present paper is to propose a new a posteriori error estimator based on strain energy release rate (SERR) or stress intensity factor (SIF) at the crack tip region and to use this along with the stress based error estimator available in the literature for the region away from the crack tip. The proposed a posteriori error estimator is called the K-S error estimator. Further, an adaptive mesh refinement (h-) strategy which can be used with K-S error estimator has been proposed for fracture analysis of 2-D crack problems. The performance of the proposed a posteriori error estimator and the h-adaptive refinement strategy have been demonstrated by employing the 4-noded, 8-noded and 9-noded plane stress finite elements. The proposed error estimator together with the h-adaptive refinement strategy will facilitate automation of fracture analysis process to provide reliable solutions.

Adaptive dendron: A bile acid oligomer behaving as both normal and inverse micellar mimic

The normal and inverse micellar property of a bile-acid-based dendritic structure was established through dye solubilization studies in both polar and nonpolar media.

Power System Stability Enhancement by Single Network Adaptive Critic Stabilizers

This paper proposes a Single Network Adaptive Critic (SNAC) based Power System Stabilizer (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a Single Machine Infinite Bus test system for various system and loading conditions. The proposed stabilizer, which is relatively easier to synthesize, consistently outperformed stabilizers based on conventional lead-lag and linear quadratic regulator designs.

Effects of Mean Luminance Changes on Human Contrast Perception

Background When we are viewing natural scenes, every saccade abruptly changes both the mean luminance and the contrast structure falling on any given retinal location. Thus it would be useful if the two were independently encoded by the visual system, even when they change simultaneously. Recordings from single neurons in the cat visual system have suggested that contrast information may be quite independently represented in neural responses to simultaneous changes in contrast and luminance. Here we test to what extent this is true in human perception. Methodology/Principal Findings Small contrast stimuli were presented together with a 7-fold upward or downward step of mean luminance (between 185 and 1295 Td, corresponding to 14 and 98 cd/m2), either simultaneously or with various delays (50–800 ms). The perceived contrast of the target under the different conditions was measured with an adaptive staircase method. Over the contrast range 0.1–0.45, mainly subtractive attenuation was found. Perceived contrast decreased by 0.052±0.021 (N = 3) when target onset was simultaneous with the luminance increase. The attenuation subsided within 400 ms, and even faster after luminance decreases, where the effect was also smaller. The main results were robust against differences in target types and the size of the field over which luminance changed. Conclusions/Significance Perceived contrast is attenuated mainly by a subtractive term when coincident with a luminance change. The effect is of ecologically relevant magnitude and duration; in other words, strict contrast constancy must often fail during normal human visual behaviour. Still, the relative robustness of the contrast signal is remarkable in view of the limited dynamic response range of retinal cones. We propose a conceptual model for how early retinal signalling may allow this.

Comparative study of adaptive frequency hopping with power control to avoid WLAN interference in WPAN systems like Bluetooth

Presently Bluetooth(BT) is one of the widely used device for personal communication. As BT devices are operating in the unlicensed ISM band, they are often subjected to the interference from WLAN. The band width of BT (1MHz) is narrower compare to the bandwidth of WLAN (22MHz). So for coexistence purpose it is important to observe the performance of narrow band signal BT in presence of wideband interference WLAN and vice versa. As there are many work on the performance of WLAN in presence BT interference 3]4]5]6], the main focus in this paper is on performance of BT in presence of WLAN interference in AWGN, Rayleigh fading channel. Then comparison of the performance using interference avoidance technique like adaptive frequency hopping, power control for BT system is given. Finally a conclusion is drawn observing the simulation results on the technique which is more suitable for WLAN interference mitigation in BT system.

Molecular Characterization of Viruses Causing the Cassava Brown Streak Disease Epidemic in Eastern Africa

Cassava brown streak disease (CBSD) was described for the first time in Tanganyika (now Tanzania) about seven decades ago. Tanganyika (now Tanzania) about seven decades ago. It was endemic in the lowland areas of East Africa and inland parts of Malawi and caused by Cassava brown streak virus (CBSV; genus Ipomovirus; Potyviridae). However, in 1990s CBSD was observed at high altitude areas in Uganda. The causes for spread to new locations were not known.The present work was thus initiated to generate information on genetic variability, clarify the taxonomy of the virus or viruses associated with CBSD in Eastern Africa as well as to understand the evolutionary forces acting on their genes. It also sought to develop a molecular based diagnostic tool for detection of CBSD-associated virus isolates. Comparison of the CP-encoding sequences of CBSD-associated virus isolates collected from Uganda and north-western Tanzania in 2007 and the partial sequences available in Genbank revealed occurrence of two genetically distinct groups of isolates. Two isolates were selected to represent the two groups. The complete genomes of isolates MLB3 (TZ:Mlb3:07) and Kor6 (TZ:Kor6:08) obtained from North-Western (Kagera) and North-Eastern (Tanga) Tanzania, respectively, were sequenced. The genomes were 9069 and 8995 nucleotides (nt), respectively. They translated into polyproteins that were predicted to yield ten mature proteins after cleavage. Nine proteins were typical in the family Potyviridae, namely P1, P3, 6K1, CI, 6K2, VPg, NIa-Pro, NIb and CP, but the viruses did not contain HC-Pro. Interestingly, genomes of both isolates contained a Maf/HAM1-like sequence (HAM1h; 678 nucleotides, 25 kDa) recombined between the NIb and CP domains in the 3’-proximal part of the genomes. HAM1h was also identified in Euphorbia ringspot virus (EuRSV) whose sequence was in GenBank. The HAM1 gene is widely spread in both prokaryotes and eukaryotes. In yeast (Saccharomyces cerevisiae) it is known to be a nucleoside triphosphate (NTP) pyrophosphatase. Novel information was obtained on the structural variation at the N-termini of polyproteins of viruses in the genus Ipomovirus. Cucumber vein yellowing virus (CVYV) and Squash vein yellowing virus (SqVYV) contain a duplicated P1 (P1a and P1b) but lack the HC-Pro. On the other hand, Sweet potato mild mottle virus (SPMMV), has a single but large P1 and has HC-Pro. Both virus isolates (TZ:Mlb3:07 & TZ:Kor6:08) characterized in this study contained a single P1 and lacked the HC-Pro which indicates unique evolution in the family Potyviridae. Comparison of 12 complete genomes of CBSD-associated viruses which included two genomes characterized in this study, revealed genetic identity of 69.0–70.3% (nt) and amino acid (aa) identities of 73.6–74.4% at polyprotein level. Comparison was also made among 68 complete CP sequences, which indicated 69.0-70.3 and 73.6-74.4 % identity at nt and aa levels, respectively. The genetic variation was large enough for dermacation of CBSD-associated virus isolates into two distinct species. The name CBSV was retained for isolates that were related to CBSV isolates available in database whereas the new virus described for the first time in this study was named Ugandan cassava brown streak virus (UCBSV) by the International Committee on Virus Taxonomy (ICTV). The isolates TZ:Mlb3:07 and TZ:Kor6:08 belong to UCBSV and CBSV, respectively. The isolates of CBSV and UCBSV were 79.3-95.5% and 86.3-99.3 % identitical at nt level, respectively, suggesting more variation amongst CBSV isolates. The main sources of variation in plant viruses are mutations and recombination. Signals for recombination events were detected in 50% of isolates of each virus. Recombination events were detected in coding and non-coding (3’-UTR) sequences except in the 5’UTR and P3. There was no evidence for recombination between isolates of CBSV and UCBSV. The non-synonomous (dN) to synonomous (dS) nucleotide substitution ratio (ω) for the HAM1h and CP domains of both viruses were ≤ 0.184 suggesting that most sites of these proteins were evolving under strong purifying selection. However, there were individual amino acid sites that were submitted to adaptive evolution. For instance, adaptive evolution was detected in the HAM1h of UCBSV (n=15) where 12 aa sites were under positive selection (P< 0.05) but not in CBSV (n=12). The CP of CBSV (n=23) contained 12 aa sites (p<0.01) while only 5 aa sites in the CP gene of UCBSV were predicted to be submitted to positive selection pressure (p<0.01). The advantages offered by the aa sites under positive selection could not be established but occurrence of such sites in the terminal ends of UCBSV-HAMIh, for example, was interpreted as a requirement for proteolysis during polyprotein processing. Two different primer pairs that simultaneously detect UCBSV and CBSV isolates were developed in this study. They were used successfully to study distribution of CBSV, UCBSV and their mixed infections in Tanzania and Uganda. It was established that the two viruses co-infect cassava and that incidences of co-infection could be as high as 50% around Lake Victoria on the Tanzanian side. Furthermore, it was revealed for the first time that both UCBSV and CBSV were widely distributed in Eastern Africa. The primer pair was also used to confirm infection in a close relative of cassava, Manihot glaziovii (Müller Arg.) with CBSV. DNA barcoding of M. glaziovii was done by sequencing the matK gene. Two out of seven M. glaziovii from the coastal areas of Korogwe and Kibaha in north eastern Tanzania were shown to be infected by CBSV but not UCBSV isolates. Detection in M. glaziovii has an implication in control and management of CBSD as it is likely to serve as virus reservoir. This study has contributed to the understanding of evolution of CBSV and UCBSV, which cause CBSD epidemic in Eastern Africa. The detection tools developed in this work will be useful in plant breeding, verification of the phytosanitary status of materials in regional and international movement of germplasm, and in all diagnostic activities related to management of CBSD. Whereas there are still many issues to be resolved such as the function and biological significance of HAM1h and its origin, this work has laid a foundation upon which the studies on these aspects can be based.

A structural principle for a class of adaptive systems

A feature common to many adaptive systems for identification and control is the adjustment.of gain parameters in a manner ensuring the stability of the overall system. This paper puts forward a principle which assures such a result for arbitrary systems which are linear and time invariant except for the adjustable parameters. The principle only demands that a transfer function be positive real. This transfer function dependent on the structure of the system with respect to the parameters. Several examples from adaptive identification, control and observer schemes are given as illustrations of the conceptual simplification provided by the structural principle.

Adaptive optimal load balancing in a nonhomogeneous multiserver system with a central job scheduler

A model comprising several servers, each equipped with its own queue and with possibly different service speeds, is considered. Each server receives a dedicated arrival stream of jobs; there is also a stream of generic jobs that arrive to a job scheduler and can be individually allocated to any of the servers. It is shown that if the arrival streams are all Poisson and all jobs have the same exponentially distributed service requirements, the probabilistic splitting of the generic stream that minimizes the average job response time is such that it balances the server idle times in a weighted least-squares sense, where the weighting coefficients are related to the service speeds of the servers. The corresponding result holds for nonexponentially distributed service times if the service speeds are all equal. This result is used to develop adaptive quasi-static algorithms for allocating jobs in the generic arrival stream when the load parameters are unknown. The algorithms utilize server idle-time measurements which are sent periodically to the central job scheduler. A model is developed for these measurements, and the result mentioned is used to cast the problem into one of finding a projection of the root of an affine function, when only noisy values of the function can be observed

Low frequency oscillations in power systems: A physical account and adaptive stabilizers

This paper presents a physical explanation of the phenomenon of low frequency oscillations experienced in power systems. A brief account of the present practice of providing fixed gain power system stabilizers (PSS) is followed by a summary of some of the recent design proposals for adaptive PSS. A novel PSS based on the effort of cancelling the negative damping torque produced by the automatic voltage regulator (AVR) is presented along with some recent studies on a multimachine system using a frequency identification technique.