Navigating student transition in higher education: induction, development, becoming

Student transition into higher education (HE) has increased in importance in recent times, with the growing trend in OECD nations towards universal HE provision and the concomitant widening of participation to include previously under-represented groups. However, 'transition' as a concept has remained largely uncontested and taken for granted, particularly by practitioners but also by many researchers. Based on an analysis of recent research in the field, the chapter suggests three broad ways in which transition can be conceived and, hence, three approaches to managing and supporting student transition in HE: as (1) induction; (2) development; and (3) becoming. The third — transition as 'becoming' — offers the most theoretically sophisticated and student sympathetic account, and has the greatest potential for transforming understandings of, and practices that support, transitions in HE. It is also the least prevalent and least well-understood. Apart from being explicit about how transition is defined, this chapter argues that future research in the field needs to foreground students' lived realities and to broaden its theoretical and empirical base if students' capacities to navigate change are to be fully understood and resourced.

Functional similarities between pigeon 'milk' and mammalian milk : induction of immune gene expression and modification of the microbiota

Pigeon ‘milk’ and mammalian milk have functional similarities in terms of nutritional benefit and delivery of immunoglobulins to the young. Mammalian milk has been clearly shown to aid in the development of the immune system and microbiota of the young, but similar effects have not yet been attributed to pigeon ‘milk’. Therefore, using a chicken model, we investigated the effect of pigeon ‘milk’ on immune gene expression in the Gut Associated Lymphoid Tissue (GALT) and on the composition of the caecal microbiota. Chickens fed pigeon ‘milk’ had a faster rate of growth and a better feed conversion ratio than control chickens. There was significantly enhanced expression of immune-related gene pathways and interferon-stimulated genes in the GALT of pigeon ‘milk’-fed chickens. These pathways include the innate immune response, regulation of cytokine production and regulation of B cell activation and proliferation. The caecal microbiota of pigeon ‘milk’-fed chickens was significantly more diverse than control chickens, and appears to be affected by prebiotics in pigeon ‘milk’, as well as being directly seeded by bacteria present in pigeon ‘milk’. Our results demonstrate that pigeon ‘milk’ has further modes of action which make it functionally similar to mammalian milk. We hypothesise that pigeon ‘lactation’ and mammalian lactation evolved independently but resulted in similarly functional products.

Online motor fault detection and diagnosis using a hybrid FMM-CART model

In this brief, a hybrid model combining the fuzzy min-max (FMM) neural network and the classification and regression tree (CART) for online motor detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. To evaluate the applicability of the proposed FMM-CART model, an evaluation with a benchmark data set pertaining to electrical motor bearing faults is first conducted. The results obtained are equivalent to those reported in the literature. Then, a laboratory experiment for detecting and diagnosing eccentricity faults in an induction motor is performed. In addition to producing accurate results, useful rules in the form of a decision tree are extracted to provide explanation and justification for the predictions from FMM-CART. The experimental outcome positively shows the potential of FMM-CART in undertaking online motor fault detection and diagnosis tasks.

Induction and prepatterning of the zebrafish pectoral fin bud requires axial retinoic acid signaling

Vertebrate forelimbs arise as bilateral appendages from the lateral plate mesoderm (LPM). Mutants in aldh1a2 (raldh2), an embryonically expressed gene encoding a retinoic acid (RA)-synthesizing enzyme, have been used to show that limb development and patterning of the limb bud are crucially dependent on RA signaling. However, the timing and cellular origin of RA signaling in these processes have remained poorly resolved. We have used genetics and chemical modulators of RA signaling to resolve these issues in the zebrafish. By rescuing pectoral fin induction in the aldh1a2/neckless mutant with exogenous RA and by blocking RA signaling in wild-type embryos, we find that RA acts as a permissive signal that is required during the six- to eight-somite stages for pectoral fin induction. Cell-transplantation experiments show that RA production is not only crucially required from flanking somites, but is sufficient to permit fin bud initiation when the trunk mesoderm is genetically ablated. Under the latter condition, intermediate mesoderm alone cannot induce the pectoral fin field in the LPM. We further show that induction of the fin field is directly followed by a continued requirement for somite-derived RA signaling to establish a prepattern of anteroposterior fates in the condensing fin mesenchyme. This process is mediated by the maintained expression of the transcription factor hand2, through which the fin field is continuously posteriorized, and lasts up to several hours prior to limb-budding. Thus, RA signaling from flanking somites plays a dual early role in the condensing limb bud mesenchyme.

Voltage oscillations in power distribution networks in the presence of DFIGs and induction motor loads

This paper investigates the oscillatory behavior of power distribution systems in the presence of distributed generation. The analysis is carried out over a distribution test system with two doubly fed induction type wind generators and different types of induction motor loads. The system is linearized by the perturbation method. Eigenvalues are calculated to see the modal interaction within the system. The study indicates that interactions between closely placed converter controllers and induction motor loads significantly influence the damping of the oscillatory modes of the system. The critical modes have a frequency of oscillation between the electromechanical and subsynchronous oscillations of power systems. Time-domain simulations are carried out to verify the validity of the modal analysis and to provide a physical feel for the types of oscillations that occur in distribution systems. Finally, significant parameters of the system that affect the damping and frequency of the oscillation are identified.

Space vector modulation based fast speed response field-orientation control of induction motor drive with adaptive neural integrator

This paper presents a novel fast speed response control strategy for the poly-phase induction motor drive system based on flux angle. The control scheme is derived in rotor field coordinates and employs the estimation of the rotor flux and its position. An adaptive notch filter is proposed to eliminate the dc component of the integration of signals used for the rotor flux estimation. To improve the performance of the rotor flux estimator, derivative term of the back emf is incorporated in the system. The voltage components in the synchronous reference frame are generated in the controllers which are transformed to stationary reference frame for driving the motor. Space vector modulation technique is used here. Simulation of the drive system was carried out and the results were compared with those obtained for a system that produces the above mentioned voltage components using the conventional PI controller. It is observed that the proposed control methodology provides faster response than the conventional PI controller incorporated system.

Genetic algorithm based PI controller tuning for induction motor drive with ANN flux estimator

This paper presents a Genetic Algorithm (GA) based fast speed response controller for poly-phase induction motor drive. Here the proportional and integral gains of PI controller are optimized by GA to achieve quick speed response. An adaptive Recurrent Neural Network (RNN) with Real Time Recurrent Learning (RTRL) algorithm is proposed to estimate rotor flux. An online tuning scheme to update the weight of RNN is presented to overcome stator resistance variation problem. This tuning scheme requires torque estimator to calculate the torque error. Space vector modulation (SVM) technique is used to produce the motor input voltage. Simulation tests have been performed to study the dynamic performances of the drive system for both the classical PI and the genetic algorithm based PI controllers.

Three algorithms for learning artificial neural network: A comparison for induction motor flux estimation

This paper presents a comparative study of three algorithms for learning artificial neural network. As neural estimator, back-propagation (BP) algorithm, uncorrelated real time recurrent learning (URTRL) algorithm and correlated real time recurrent learning (CRTRL) algorithm are used in the present work to learn the artificial neural network (ANN). The approach proposed here is based on the flux estimation of high performance induction motor drives. Simulation of the drive system was carried out to study the performance of the motor drive. It is observed that the proposed CRTRL algorithm based methodology provides better performance than the BP and URTRL algorithm based technique. The proposed method can be used for accurate measurement of the rotor flux.