Induction of long-term depression and rebound potentiation by inositol trisphosphate in cerebellar Purkinje neurons

Cerebellar Purkinje neurons receive two major excitatory inputs, the climbing fibers (CFs) and parallel fibers (PFs). Simultaneous, repeated activation of CFs and PFs results in the long-term depression (LTD) of the amplitude of PF-evoked synaptic currents. To induce LTD, activation of CFs may be substituted with depolarization of the Purkinje neuron to turn on voltage-activated calcium channels and increase the intracellular calcium concentration. The role of PFs in the induction of LTD, however, is less clear. PFs activate glutamate metabotropic receptors that increase phosphoinositide turnover and elevate cytosolic inositol 1,4,5-trisphosphate (InsP3). It has been proposed that calcium release from intracellular stores via InsP3 receptors may be important in the induction of LTD. We studied the role of InsP3 in the induction of LTD by photolytic release of InsP3 from its biologically inactive “caged” precursor in voltage-clamped Purkinje neurons in acutely prepared cerebellar slices. We find that InsP3-evoked calcium release is as effective in LTD induction as activation of PFs. InsP3-induced LTD was prevented by calcium chelator 1,2-bis(2-amino phenoxy)ethane-N,N,N′,N′-tetraacetic acid. LTD produced either by repeated activation of PFs combined with depolarization (PF+ΔV), or by InsP3 combined with depolarization (InsP3+ΔV) saturated at ≈50%. Maximal LTD induced by PF+ΔV could not be further increased by InsP3+ΔV and vice versa, which suggests that both protocols for induction of LTD share a common path. In addition to inducing LTD, photo-release of InsP3+ΔV resulted in the rebound potentiation of inhibitory synaptic currents. In the presence of heparin, an InsP3 receptor antagonist, repeated activation of PF+ΔV failed to induce LTD, suggesting that InsP3 receptors play an important role in LTD induction under physiological conditions.

Time controlled photo-oxidation of polyolefins by polymer bound additives

A variety of iron compounds containing vinyl or thiol functional groups (used as photoactivators) have been synthesised and some of these were successfully bound to both polyethylene and polypropylene backbones during processing in the presence of peroxide and interlinking agent. Concentrates (masterbatches) of the photoactivators in PP and PE were prepared and the pro-oxidant effect of the diluted masterbatches in absence and presence of an antioxidant was evaluated. An antioxidant photoactivator (FeDNC ) was found to sensitise the photoactivity of pro-oxidants (Metone A / Metone M) whereas an antioxidant (ZnDNC) was found to stabilise the polymer (PP and PE) containing both of these combinations. It was observed that the lower concentration of FeDNC sensitises the stability of the polymer containing very small concentration of NiDNC whereas higher concentration of FeDNC stabilises the polymer (LDPE) containing same amount of NiDNC compared to FeDNC alone. The photostability of unstabilised PP containing FeAc could be varied by varying the concentration of ZnDEC. Both the induction period and the UV - life time of the polymer increased by increasing concentration of ZnDEC. It is suggested that ligand exchange reaction may take place between FeAc and ZnDNC. A polymer bound UV stabiliser (HAEB) and a thermal stabiliser (DBBA) were used with a non extractable photoactivator (FeAc) in PP. Small concentrations of the stabilisers (HAEB and DBBA) in combination with the photoactivator (FeAc) sensitise the polymer. The antioxidant present in commercial polymer (LDPE and PP) was found to be of a hindered phenol type, which was found to antagonise with ZnDNC when used in combination with the photoactivators.

Teacher induction in Australia : a sample of what’s really happening

Retention rates and stress levels of beginning teachers are of concern. Well-planned induction programs can assist beginning teachers to make the transition successfully into the profession, which may increase retention rates. This qualitative, year-long study aims to explore and describe the induction experiences of eight beginning teachers as they negotiated their first year of teaching. Data gathered through interviews and emails indicated that these teachers required further development on: catering for individual differences, assessing in terms of outcomes, relating to parents, relating to the wider community, and understanding school policies; however, relating to students and understanding legal responsibilities and duty of care were not issues. At the conclusion of their first year only one beginning teacher was assisted by a mentor (veteran teacher) on whole-school programming, and planning for improving teaching with opportunities to visit other classrooms. This was also the only beginning teacher who received a reduced workload in order to meet with the mentor to discuss pedagogical developments. The inadequate support provided to beginning teachers in this study highlights the need for principals and school staff to reassess induction processes, which includes providing time, funding, mentoring support and clear guidelines for a quality induction program.

Investigation of shaft voltage in wind turbine systems with induction generators

This paper presents the analysis of shaft voltage in different configurations of a doubly fed induction generator (DFIG) and an induction generator (IG) with a back-to-back inverter in wind turbine applications. Detailed high frequency model of the proposed systems have been developed based on existing capacitive couplings in IG & DFIG structures and common mode voltage sources. In this research work, several arrangements of DFIG based wind energy conversion systems (WES) are investigated in case of shaft voltage calculation and its mitigation techniques. Placements of an LC line filter in different locations and its effects on shaft voltage elimination are studied via Mathematical analysis and simulations. A pulse width modulation (PWM) technique and a back-to-back inverter with a bidirectional buck converter have been presented to eliminate the shaft voltage in a DFIG wind turbine.

Calculations of capacitive couplings in induction generators to analyse shaft voltage

This paper deals with the analysis of the parameters which are effective in shaft voltage generation of induction generators. It focuses on different parasitic capacitive couplings by mathematical equations, finite element simulations and experiments. The effects of different design parameters have been studied on proposed capacitances and resultant shaft voltage. Some parameters can change proposed capacitive coupling such as: stator slot tooth, the gap between slot tooth and winding, and the height of the slot tooth, as well as the air gap between the rotor and the stator. This analysis can be used in a primary stage of a generator design to reduce motor shaft voltage and avoid additional costs of resultant bearing current mitigation.

Composite load model decomposition : induction motor contribution

In this thesis, a new technique has been developed for determining the composition of a collection of loads including induction motors. The application would be to provide a representation of the dynamic electrical load of Brisbane so that the ability of the power system to survive a given fault can be predicted. Most of the work on load modelling to date has been on post disturbance analysis, not on continuous on-line models for loads. The post disturbance methods are unsuitable for load modelling where the aim is to determine the control action or a safety margin for a specific disturbance. This thesis is based on on-line load models. Dr. Tania Parveen considers 10 induction motors with different power ratings, inertia and torque damping constants to validate the approach, and their composite models are developed with different percentage contributions for each motor. This thesis also shows how measurements of a composite load respond to normal power system variations and this information can be used to continuously decompose the load continuously and to characterize regarding the load into different sizes and amounts of motor loads.

Decomposition of aggregated load : finding induction motor fraction in real load

The main contribution of this paper is decomposition/separation of the compositie induction motors load from measurement at a system bus. In power system transmission buses load is represented by static and dynamic loads. The induction motor is considered as the main dynamic loads and in the practice for major transmission buses there will be many and various induction motors contributing. Particularly at an industrial bus most of the load is dynamic types. Rather than traing to extract models of many machines this paper seeks to identify three groups of induction motors to represent the dynamic loads. Three groups of induction motors used to characterize the load. These are the small groups (4kw to 11kw), the medium groups (15kw to 180kw) and the large groups (above 630kw). At first these groups with different percentage contribution of each group is composite. After that from the composite models, each motor percentage contribution is decomposed by using the least square algorithms. In power system commercial and the residential buses static loads percentage is higher than the dynamic loads percentage. To apply this theory to other types of buses such as residential and commerical it is good practice to represent the total load as a combination of composite motor loads, constant impedence loads and constant power loads. To validate the theory, the 24hrs of Sydney West data is decomposed according to the three groups of motor models.

A versatile and reliable two-component system for tissue-specific gene induction in Arabidopsis

Developmental progression and differentiation of distinct cell types depend on the regulation of gene expression in space and time. Tools that allow spatial and temporal control of gene expression are crucial for the accurate elucidation of gene function. Most systems to manipulate gene expression allow control of only one factor, space or time, and currently available systems that control both temporal and spatial expression of genes have their limitations. We have developed a versatile two-component system that overcomes these limitations, providing reliable, conditional gene activation in restricted tissues or cell types. This system allows conditional tissue-specific ectopic gene expression and provides a tool for conditional cell type- or tissue-specific complementation of mutants. The chimeric transcription factor XVE, in conjunction with Gateway recombination cloning technology, was used to generate a tractable system that can efficiently and faithfully activate target genes in a variety of cell types. Six promoters/enhancers, each with different tissue specificities (including vascular tissue, trichomes, root, and reproductive cell types), were used in activation constructs to generate different expression patterns of XVE. Conditional transactivation of reporter genes was achieved in a predictable, tissue-specific pattern of expression, following the insertion of the activator or the responder T-DNA in a wide variety of positions in the genome. Expression patterns were faithfully replicated in independent transgenic plant lines. Results demonstrate that we can also induce mutant phenotypes using conditional ectopic gene expression. One of these mutant phenotypes could not have been identified using noninducible ectopic gene expression approaches.

The application of neural networks to induction machine control

Neural networks (NNs) are discussed in connection with their possible use in induction machine drives. The mathematical model of the NN as well as a commonly used learning algorithm is presented. Possible applications of NNs to induction machine control are discussed. A simulation of an NN successfully identifying the nonlinear multivariable model of an induction-machine stator transfer function is presented. Previously published applications are discussed, and some possible future applications are proposed.

Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme