Characterization of Sirt2 using conditional RNAi in mice

Within the past eight years, RNA interference (RNAi) has emerged as a powerful experimental tool for gene function analysis in mice. Reversible control of shRNA mediated RNAi has been achieved by using a tetracycline (tet)-inducible promoter. In the presence of the inductor doxycycline (dox), shRNA mediated gene silencing is initiated, whereas RNAi mechanism is blocked in the absence of dox. To achieve spatially and temporally regulated RNAi, the tet inducible system was combined with a Cre/loxP based strategy for tissue specific activation of shRNA constructs. To this end, a loxP-flanked "promoter inhibitory element" (PIE) was placed between the proximal (PSE) and distal sequence element (DSE) of a dox inducible promoter such that promoter function is completely blocked. Re-activation can be achieved through Cre mediated excision of PIE. To allow for gene silencing in a selected tissue, Cre expression can be regulated by a tissue-specific promoter. In mouse ES cells, the system mediated tight regulation of shRNA expression upon Cre mediated activation and dox administration, reaching knockdown efficiencies of >80%. Unexpectedly, the system showed a limited activity in transgenic mice when applied for conditional silencing of two different targets, LacZ and Sirt2. Sirt2 is a member of the sirtuin family which has considerably gained attention in vitro for its possible role in many physiological processes, including adipogenesis and neurodegenerative diseases. To investigate the function of Sirt2 in vivo, the unmodified dox-responsive and tet-inducible promoter was further used for conditional RNAi in transgenic mice. Inducible shRNA expression resulted in efficient silencing of Sirt2 (>90%) in all tissues which have been analyzed. Suppression of Sirt2 during embryogenesis resulted in offspring consisting of equal ratios of wild type and transgenic pups, indicating that Sirt2 is not indispensable for development. In adult animals, glucose metabolism, insulin sensitivity and energy balance appeared to be unaffected by Sirt2 deficiency. Likewise, expression of PPARγ, a downstream target of Sirt2, was not found to be altered upon Sirt2 inhibition. Finally, Sirt2 silencing was induced in an experimental model of Parkinson disease (PD). Data from Rotarod performances to study motor behaviour did not provide any evidence for a role of Sirt2 in PD pathogenesis as suggested by previous in vitro studies. Taken together, conditional Sirt2 silencing in vivo does not support speculation concerning a central role of Sirt2 in physiological processes, embryogenesis and in a mouse model of Parkinson disease

The application of quadratic optimal cooperative control synthesis to a CH-47 helicopter

A control-system design method, Quadratic Optimal Cooperative Control Synthesis (CCS), is applied to the design of a Stability and Control Augmentation Systems (SCAS). The CCS design method is different from other design methods in that it does not require detailed a priori design criteria, but instead relies on an explicit optimal pilot-model to create desired performance. The design model, which was developed previously for fixed-wing aircraft, is simplified and modified for application to a Boeing Vertol CH-47 helicopter. Two SCAS designs are developed using the CCS design methodology. The resulting CCS designs are then compared with designs obtained using classical/frequency-domain methods and Linear Quadratic Regulator (LQR) theory in a piloted fixed-base simulation. Results indicate that the CCS method, with slight modifications, can be used to produce controller designs which compare favorably with the frequency-domain approach

A Simplified Speed Control of Induction Motor based on a Low Cost FPGA

This paper investigates the development of a simplified speed control of induction motor based on indirect field oriented control (FOC). An original PI-P controller is designed to obtain good performances for speed tracking. Controller coefficients are carried out with analytic approach. The algorithm is implemented using a low cost Field Programmable Gate Array (FPGA). The implementation is followed by an efficient design methodology that offers considerable design advantages. The main advantage is the design of reusable and reconfigurable hardware modules for the control of electrical systems. Experimental results carried on a prototyping platform are given to illustrate the efficiency and the benefits of the proposed approach

Position estimation delays in signal injection-based sensorless PMSM drives

The causes of position estimation delays and their effects on the sensorless control of permanent magnet synchronous motor drives are investigated. The position of a permanent magnet synchronous machine is estimated via the injection of high frequency voltage signals. The delays under investigation are due to the digital implementation of the control algorithm and to the digital filters adopted for decoupling the inspection signals from the fundamental components of the stator current measures. If not correctly modeled and compensated, such delays can reduce the performance of the control scheme. Experimental results are provided, proving the accuracy of the modeling approach and the effectiveness of the related compensation strateg

Distributed machining control and monitoring using smart sensors/actuators

The study of smart sensors and actuators led, during the past few years, to the development of facilities which improve traditional sensors and actuators in a necessary way to automate production systems. In an other context, many studies are carried out aiming at defining a decisional structure for production activity control and the increasing need of reactivity leads to the autonomization of decisional levels close to the operational system. We suggest in this paper to study the natural convergence between these two approaches and we propose an integration architecture dealing with machine tool and machining control that enables the exploitation of distributed smart sensors and actuators in the decisional system

Linear matrix inequality based synthesis of PI controllers for PMSM with uncertain parameters

This paper addresses the design of robust PI controllers for permanent magnet synchronous motors in terms of a linear matrix inequality based problem. A polytopic model of the plant is obtained and validated for the motor uncertain parameters belonging to intervals. The design procedure proposed here encompasses: i. suitable plant uncertainties inclusion and the use of practical design control constraints; ii. robust PI computation based on linear matrix inequalities with a very fast solution; iii. simulation analyses; and iv. experimental evaluations. The robust PI controller can produce superior speed regulation than a PI controller designed only for the nominal parameters, including better disturbance rejection and H-infinity performance. Experimental results confirm the viability of the proposal, which can be seen as an efficient alternative to trade off performance and robustness for PI controllers in this application233310319CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES306197/2015-4não te

Design and Testing Neuro Networks Control System for Direct Current Machine

The paper presents an adaptive intelligent control method to overcome effects of some indeterminate and undealt factors that a DC. drive is suffered. In the speed loop, we use a three-layer neural networks through a backpropagation (BP) algorithm out of line learning to realize the fuzzy-control tactics. We use unit neuron through Hebb algorithm on-line dynamic learning to realize adaptive mechanism. The simulation is based on a MATLAB neural networks toolbox with simulink. The results of the simulation show that adaptive intelligent control method enables the system to have good dynamic and stability performance. The proposed method develops the use of simulink in the field of electrical drive of adaptive intelligent control

RHEBI Expression in Embryonic and Postnatal Mouse

Ras homolog enriched in brain (RHEB1) is a member within the superfamily of GTP-binding proteins encoded by the RAS oncogenes. RHEB1 is located at the crossroad of several important pathways including the insulin-signaling pathways and thus plays an important role in different physiological processes. To understand better the physiological relevance of RHEB1 protein, the expres- sion pattern of RHEB1 was analyzed in both embryonic (at E3.5–E16.5) and adult (1-month old) mice. RHEB1 immu- nostaining and X-gal staining were used for wild-type and Rheb1 gene trap mutant mice, respectively. These inde- pendent methods revealed similar RHEB1 expression pat- terns during both embryonic and postnatal developments. Ubiquitous uniform RHEB1/β-gal and/or RHEB1 expres- sion was seen in preimplantation embryos at E3.5 and post- implantation embryos up to E12.5. Between stages E13.5 and E16.5, RHEB1 expression levels became complex: In particular, strong expression was identified in neural tis- sues, including the neuroepithelial layer of the mesenceph- alon, telencephalon, and neural tube of CNS and dorsal root ganglia. In addition, strong expression was seen in certain peripheral tissues including heart, intestine, muscle, and urinary bladder. Postnatal mice have broad spatial RHEB1 expression in different regions of the cerebral cortex, sub- cortical regions (including hippocampus), olfactory bulb, medulla oblongata, and cerebellum (particularly in Purkinje cells). Significant RHEB1 expression was also viewed in internal organs including the heart, intestine, urinary blad- der, and muscle. Moreover, adult animals have complex tis- sue- and organ-specific RHEB1 expression patterns with different intensities observed throughout postnatal develop- ment. Its expression level is in general comparable in CNS and other organs of mouse. Thus, the expression pattern of RHEB1 suggests that it likely plays a ubiquitous role in the development of the early embryo with more tissue-specific roles in later development

Simulation-based coyote optimization algorithm to determine gains of PI controller for enhancing the performance of solar PV water-pumping system

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on theCanis latransspecies, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler-Nichols and trial-error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities