Continuous Time Quantum Monte Carlo method for fermions

We present numerically exact continuous-time Quantum Monte Carlo algorithm for fermions with a general non-local in space-time interaction. The new determinantal grand-canonical scheme is based on a stochastic series expansion for the partition function in the interaction representation. The method is particularly applicable for multi-band time-dependent correlations since it does not invoke the Hubbard-Stratonovich transformation. The test calculations for exactly solvable models as well results for the Green function and for the time-dependent susceptibility of the multi-band super-symmetric model with a spin-flip interaction are discussed.Comment: 10 pages, 7 Figure

Optimal H∞ insulin injection control for blood glucose regulation in diabetic patients

The theory of H/sup /spl infin// optimal control has the feature of minimizing the worst-case gain of an unknown disturbance input. When appropriately modified, the theory can be used to design a &quot;switching&quot; controller that can be applied to insulin injection for blood glucose (BG) regulation. The &quot;switching&quot; controller is defined by a collection of basic insulin rates and a rule that switches the insulin rates from one value to another. The rule employed an estimation of BG from noisy measurements, and the subsequent optimization of a performance index that involves the solution of a &quot;jump&quot; Riccati differential equation and a discrete-time dynamic programming equation. With an appropriate patient model, simulation studies have shown that the controller could correct BG deviation using clinically acceptable insulin delivery rates. <br /

Influence of soluble factors from the M2 phenotype macrophages on hematopoiesis in depression-like state

Chronic psychosocial stress provokes anxious behavior and depressive disorders. The longitudinal stress-induced neuroendocrine signals may alter functioning of immune (central and peripheral) organs. Increased myelopoiesis is observed in bone marrow, being detrimental to lympho- and erythropoiesis, with increased emigration of monocytic bone marrow cells to the periphery and their acquisition of “inflammatory” phenotype. The subsequent migration of such monocytes to the brain with differentiation into the M1 type macrophages which form inflammatory signals, and their effect upon endothelial cells and microglia leads to increased production of cytokines, chemokines, and adhesion molecules, thus accelerating accumulation of bone marrow-derived monocytes migrating to the brain. The signals from bone marrow monocytes and activated microglia promote neuroinflammatory condition which leads to behavioral changes. Current data on the presence of non-resident bone marrow macrophages in the brain of depressed patients require studies of hematopoiesis in depression-like states. Pronounced plasticity is a characteristic feature of macrophages, i.e., their ability to acquire M1 or M2 phenotype depending on the microenvironment signals. M1 exhibit high pro-inflammatory activity and have neurodestructive properties, whereas M2 cells are characterized by low pro-inflammatory activity and pronounced regenerative potential, due to the production of multiple soluble mediators and cytokines, including neurotrophic and immunoregulatory factors, anti-inflammatory substances that provide neuroprotection, stimulate neurogenesis, synaptogenesis, growth and myelinization of axons, thus theoretically substantiating an opportunity of using the potential of M2 macrophages in the treatment of depression. In this work, we studied the effect of soluble factors of human macrophages, polarized into cells with M2 phenotype under the conditions of serum deprivation, upon bone marrow hematopoiesis and peripheral blood cells in a model of stress-induced depression. We have shown enhanced differentiation of hematopoietic stem cells into the granulocyte-macrophage (CFU-GM) lineage, along with increased monocyte population in peripheral blood in the depressive-like murine model. Development of a depressive-like state in the animals was associated with reduced amounts of both erythroid precursors in bone marrow and erythrocytes/hemoglobin in peripheral blood. Intranasal administration of soluble M2 macrophage factors (M2-SFs) for 7 days was accompanied by a corrective effect on the above parameters, being significant for peripheral blood monocytes. The data obtained suggest effectiveness of the M2-SFS anti-inflammatory effects in correcting changes in hematopoiesis caused by social stress in depressive-like animals

Self-Control of Traffic Lights and Vehicle Flows in Urban Road Networks

Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks [D. Helbing and P. Moln\'ar, Phys. Eev. E 51 (1995) 4282--4286], we propose a self-organization approach to traffic light control. The problem can be treated as multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as ``green waves'' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes

About two classes of semantic correlation watched on the functional semantic networks

В работе рассмотрены два класса семантической корреляции, которые предложено использовать в процедурах пофрагментной верификации функциональных семантических сетей. В качестве первого класса выступает структурно-функциональная корреляция, основанная на анализе степени сходства орграфов, описывающих выделенные фрагменты сети. В качестве второго класса выступает референциальная корреляция, основанная на сопоставлении верхних (итоговых) семантических значений верифицируемых фрагментов. In operation two semantic correlation classes for fragmentary verification procedures using in the functional semantic networks are considered. As the first class structurally functional correlation based on the analysis of a level likeness digraphs describing in selected network fragments appears. As the second class referentsialny correlation based on comparison of the upper (total) semantic values of verifiable fragments appears

About the Big Graphs Arising when Forming the Diagnostic Models in a Reconfigurable Computing Field of Functional Monitoring and Diagnostics System of the Spacecraft Onboard Control Complex

One of the problems in implementation of the multipurpose complete systems based on the reconfigurable computing fields (RCF) is the problem of optimum redistribution of logicalarithmetic resources in growing scope of functional tasks. Irrespective of complexity, all of them are transformed into an orgraph, which functional and topological structure is appropriately imposed on the RCF based, as a rule, on the field programmable gate array (FPGA).Due to limitation of the hardware configurations and functions realized by means of the switched logical blocks (SLB), the abovementioned problem becomes even more critical when there is a need, within the strictly allocated RCF fragment, to realize even more complex challenge in comparison with the problem which was solved during the previous computing step. In such cases it is possible to speak about graphs of big dimensions with respect to allocated RCF fragment.The article considers this problem through development of diagnostic algorithms to implement diagnostics and control of an onboard control complex of the spacecraft using RCF. It gives examples of big graphs arising with respect to allocated RCF fragment when forming the hardware levels of a diagnostic model, which, in this case, is any hardware-based algorithm of diagnostics in RCF.The article reviews examples of arising big graphs when forming the complicated diagnostic models due to drastic difference in formation of hardware levels on closely located RCF fragments. It also pays attention to big graphs emerging when the multichannel diagnostic models are formed.Three main ways to solve the problem of big graphs with respect to allocated RCF fragment are given. These are: splitting the graph into fragments, use of pop-up windows with relocating and memorizing intermediate values of functions of high hardware levels of diagnostic models, and deep adaptive update of diagnostic model.It is shown that the last of three ways is the most efficient, but there is a demand to update a diagnostic model at all its hardware levels of RCF.</p

Estimation of Walking Energy Expenditure by Using Support Vector Regression

Abstract-This paper develops a new predictor of walking energy expenditure from wireless measurements of body movements using triaxial accelerometers. Reliable data were collected from repeated walking experiments in different conditions on a treadmill with simultaneous measurement of expired oxygen and carbon dioxide. Support vector regression, a powerful non-linear regression method, was used to process and model the data. This novel processing method sets this investigation apart from existing papers. Good results were achieved in the robust estimation of walking related energy expenditure from a number of variables derived from triaxial accelerometer and treadmill speed