908 resultados para Induction Loop
Resumo:
It is recognised worldwide that beginning teachers require more support as reasons for high attrition rates (e.g., lack of appreciation from colleagues, unsatisfying working conditions, inadequate teacher preparation) indicate current systems are failing them. One way of addressing their specific needs is to understand their achievements and challenges during their first year of teaching. This qualitative study tracks 10 beginning primary teachers’ achievements and challenges at two points (April and September) during their first year of teaching in Australian public schools. Findings showed that building relationships and behaviour management were considered achievements at these two points, yet behaviour management was also considered a challenge. Other challenges included: learning differentiation, working with parents, and negotiating a life-work balance. Induction into the school culture and infrastructure continued to be important, especially developing skills on handling difficult parents and creating a life-work balance. Simultaneously, they required mentoring for effective teaching in classroom management and differentiation. A two-prong approach of induction into the school culture and infrastructure and mentoring for effective teaching needs to continue throughout the first year of teaching, and possibly beyond.
Resumo:
Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.
Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies
Resumo:
The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.
Resumo:
In power hardware in the loop (PHIL) simulations, a real-time simulated power system is interfaced to a piece of hardware, usually called hardware under test (HuT). A PHIL test can be realized using several simulation tools. Among them Real Time Digital Simulator (RTDS) is an ideal tool to perform complex power system simulations in near real-time. Stable operation of the entire system, along with the accuracy of simulation results are the main concerns regarding a PHIL simulation. In this paper, a simulated power network on RTDS will be interfaced to HuT through a voltage source converter (VSC). Issues around stability and other interface problems are studied and a new method to stabilize some unstable PHIL cases is proposed. PHIL simulation results in PSCAD and RSCAD are presented.
Resumo:
The Nrf2/ARE pathway is a major cellular defense mechanism that prevents damage by reactive oxygen species through induction of antioxidative phase II enzymes. However, the activity of the Nrf2/ARE system is not uniform with variability in response presumed to be dependent on the Nrf2 genotype. We recently completed a pilot human coffee intervention trial with healthy humans, where large interindividual differences in the antioxidative response to the study coffee were examined. Here, we address the question whether differences in the modulation of Nrf2 gene transcription, assessed as an induction of Nrf2 gene transcription by Q-PCR, might be correlated with specific Nrf2 genotypes. To date, nine single nucleotide polymorphisms (SNPs) have been identified in the Nrf2 (NFE2L2) gene. Two of these, the -617C/A and -651G/A SNPs are located within the promoter region and have previously been reported to influence the activity of the Nrf2/ARE pathway by reducing Nrf2 transcriptional activity. Sequencing of the critical Nrf2 gene promoter region not only confirmed the existence of these SNPs within the participants of the trial at the expected frequency (33% carrying the -617C/A, 17% the -651G/A and 56% the -653A/G SNP) but also indicated reduced Nrf2 gene transcription associated with a normal diet if the SNPs at position -617, -651 or -653 were present. Of note, the data also indicated the study coffee increased Nrf2 gene transcription even in SNP carriers. This further highlights the relevance of genotype-dependent induction of Nrf2 gene transcription that appears to be largely influenced by dietary factors.
Resumo:
Rationale Developing models to efficiently explore the mechanisms by which stress can mediate reinstatement of drug-seeking behavior is crucial to the development of new pharmacotherapies for alcohol use disorders. Objectives We examined the effects of multiple reinstatement sessions using the pharmacological stressor, yohimbine, in ethanol- and sucrose-seeking rats in order to develop a more efficient model of stress-induced reinstatement. Methods Long–Evans rats were trained to self-administer 10% ethanol with a sucrose-fading procedure, 20% ethanol without a sucrose-fading procedure, or 5% sucrose in 30-min operant self-administration sessions, followed by extinction training. After reaching extinction criteria, the animals were tested once per week with yohimbine vehicle and yohimbine (2 mg/kg), respectively, 30 min prior to the reinstatement sessions or blood collection. Levels of reinstatement and plasma corticosterone (CORT) were determined each week for four consecutive weeks. Results Yohimbine induced reinstatement of ethanol- and sucrose-seeking in each of the 4 weeks. Interestingly, the magnitude of the reinstatement decreased for the 10% ethanol group after the first reinstatement session but remained stable for the 20% ethanol group trained without sucrose. Plasma CORT levels in response to injection of both vehicle and yohimbine were significantly higher in the ethanol-trained animals compared to sucrose controls. Conclusions The stable reinstatement in the 20% ethanol group supports the use of this training procedure in studies using within-subject designs with multiple yohimbine reinstatement test sessions. Additionally, these results indicate that the hormonal response to stressors can be altered following extinction from self-administration of relatively modest amounts of ethanol.
Resumo:
To determine whether [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) could predict the pathological response in oesophageal cancer after only the first week of neoadjuvant chemoradiation. Thirty-two patients with localised oesophageal cancer had a pretreatment PET scan and a repeat after the first week of chemoradiation. The change in mean maximum standardised uptake value (SUV) and volume of metabolically active tissue (MTV) was compared with the tumour regression grade (TRG) in the final histology. Those who achieved a TRG of 1 and 2 were deemed responders and 3-5 nonresponders. In the responders (28%), the SUV fell from 12.6 (±6.3) to 8.1 (±2.9) after 1 week of chemoradiation (P = 0.070). In nonresponders (72%), the results were 9.7 (±5.4) and 7.1 (±3.8), respectively (P = 0.003). The MTV in responders fell from 36.6 (±22.7) to 22.3 (±10.4) cm3 (P = 0.180), while in nonresponders, this fell from 35.9 (±36.7) to 31.9 (±52.7) cm3 (P = 0.405). There were no significant differences between responders and nonresponders. The hypothesis that early repeat FDG-PET scanning may predict histomorphologic response was not proven. This may reflect an inflammatory effect of radiation that obscures tumour-specific metabolic changes at this time. This assessment may have limited application in predicting response to multimodal regimens for oesophageal cancer. © 2006 Cancer Research UK.
Resumo:
In this paper, a model-predictive control (MPC) method is detailed for the control of nonlinear systems with stability considerations. It will be assumed that the plant is described by a local input/output ARX-type model, with the control potentially included in the premise variables, which enables the control of systems that are nonlinear in both the state and control input. Additionally, for the case of set point regulation, a suboptimal controller is derived which has the dual purpose of ensuring stability and enabling finite-iteration termination of the iterative procedure used to solve the nonlinear optimization problem that is used to determine the control signal.
Resumo:
The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.
Resumo:
A microgrid contains both distributed generators (DGs) and loads and can be viewed by a controllable load by utilities. The DGs can be either inertial synchronous generators or non-inertial converter interfaced. Moreover, some of them can come online or go offline in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new phase locked loop (PLL) algorithm is proposed for smooth synchronization of plug and play DGs. A frequency droop for power sharing is used and a pseudo inertia has been introduced to non-inertial DGs in order to match their response with inertial DGs. The proposed strategy is validated through PSCAD simulation studies.
Resumo:
This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.
Resumo:
This time last year we proposed the theme of the 'loop' issue to the M/C collective because it sounded deeply cool, satisfying our poststructuralist posturings about reflexivity and representation, while also tapping into everyday cultural objects and practices. We expected that the 'loop' issue would generate some interesting and varied responses, and it did. We received submissions about music, visual art, language, child development, pop-cultural artefacts, mathematics and culture in general. These explorations of disparate fields seemed, however, to be tied together by a common thread: the concept of "generation" itself. Each article in the 'loop' issue describes a loop that does not simply repeat an original operation, but that through iteration creates new possibilities and new meanings...
Resumo:
Heparan sulfate proteoglycans cooperate with basic fibroblast growth factor (bFGF/FGF2) signaling to control osteoblast growth and differentiation, as well as metabolic functions of osteoblasts. FGF2 signaling modulates the expression and activity of Runt-related transcription factor 2 (Runx2/Cbfa1), a key regulator of osteoblast proliferation and maturation. Here, we have characterized novel Runx2 target genes in osteoprogenitors under conditions that promote growth arrest while not yet permitting sustained phenotypic maturation. Runx2 enhances expression of genes related to proteoglycan-mediated signaling, including FGF receptors (e.g., FGFR2 and FGFR3) and proteoglycans (e.g., syndecans [Sdc1, Sdc2, Sdc3], glypicans [Gpc1], versican [Vcan]). Runx2 increases expression of the glycosyltransferase Exostosin-1 (Ext1) and heparanase, as well as alters the relative expression of N-linked sulfotransferases (Ndst1 = Ndst2 > Ndst3) and enzymes mediating O-linked sulfation of heparan sulfate (Hs2st > Hs6st) or chondroitin sulfate (Cs4st > Cs6st). Runx2 cooperates with FGF2 to induce expression of Sdc4 and the sulfatase Galns, but Runx2 and FGF2 suppress Gpc6, thus suggesting intricate Runx2 and FGF2 dependent changes in proteoglycan utilization. One functional consequence of Runx2 mediated modulations in proteoglycan-related gene expression is a change in the responsiveness of bone markers to FGF2 stimulation. Runx2 and FGF2 synergistically enhance osteopontin expression (>100 fold), while FGF2 blocks Runx2 induction of alkaline phosphatase. Our data suggest that Runx2 and the FGF/proteoglycan axis may form an extracellular matrix (ECM)-related regulatory feed-back loop that controls osteoblast proliferation and execution of the osteogenic program.
Resumo:
In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.
Resumo:
The effects of oxygen availability and induction culture biomass upon production of an industrially important monoamine oxidase (MAO) were investigated in fed-batch cultures of a recombinant E. coli. For each induction cell biomass 2 different oxygenation methods were used, aeration and oxygen enriched air. Induction at higher biomass levels increased the culture demand for oxygen, leading to fermentative metabolism and accumulation of high levels of acetate in the aerated cultures. Paradoxically, despite an almost eight fold increase in acetate accumulation to levels widely reported to be highly detrimental to protein production, when induction wet cell weight (WCW) rose from 100% to 137.5%, MAO specific activity in these aerated processes showed a 3 fold increase. By contrast, for oxygenated cultures induced at WCW's 100% and 137.5% specific activity levels were broadly similar, but fell rapidly after the maxima were reached. Induction at high biomass levels (WCW 175%) led to very low levels of specific MAO activity relative to induction at lower WCW's in both aerated and oxygenated cultures. Oxygen enrichment of these cultures was a useful strategy for boosting specific growth rates, but did not have positive effects upon specific enzyme activity. Based upon our findings, consideration of the amino acid composition of MAO and previous studies on related enzymes, we propose that this effect is due to oxidative damage to the MAO enzyme itself during these highly aerobic processes. Thus, the optimal process for MAO production is aerated, not oxygenated, and induced at moderate cell density, and clearly represents a compromise between oxygen supply effects on specific growth rate/induction cell density, acetate accumulation, and high specific MAO activity. This work shows that the negative effects of oxygen previously reported in free enzyme preparations, are not limited to these acellular environments but are also discernible in the sheltered environment of the cytosol of E. coli cells.