Trait resilience fosters adaptive coping when control opportunities are high : implications for the motivating potential of active work

Purpose: We examine the interaction between trait resilience and control in predicting coping and performance. Drawing on a person–environment fit perspective, we hypothesized resilient individuals would cope and perform better in demanding work situations when control was high. In contrast, those low in resilience would cope and perform better when control was low. Recognizing the relationship between trait resilience and performance also could be indirect, adaptive coping was examined as a mediating mechanism through which high control enables resilient individuals to demonstrate better performance. Methodology: In Study 1 (N = 78) and Study 2 (N = 94), participants completed a demanding inbox task in which trait resilience was measured and high and low control was manipulated. Study 3 involved surveying 368 employees on their trait resilience, control, and demand at work (at Time 1), and coping and performance 1 month later at Time 2. Findings: For more resilient individuals, high control facilitated problem-focused coping (Study 1, 2, and 3), which was indirectly associated with higher subjective performance (Study 1), mastery (Study 2), adaptive, and proficient performance (Study 3). For more resilient individuals, high control also facilitated positive reappraisal (Study 2 and 3), which was indirectly associated with higher adaptive and proficient performance (Study 3). Implications: Individuals higher in resilience benefit from high control because it enables adaptive coping. Originality/value: This research makes two contributions: (1) an experimental investigation into the interaction of trait resilience and control, and (2) investigation of coping as the mechanism explaining better performance.

Institutional investors, risk/return and corporate governance : practical lessons from the Global Financial Crisis

The global grown in institutional investors means that firms can no longer ignore their influence in capital markets. However, not all institutional investors have the same motives to influence the firms they invest in. Institution investors' ability to influence management depends on the size of their investment and whether they have any business relations with the firm. Using a sample of Australian firms from 2006 to 2008, our empirical results show that the proportion of a company's shares held by institutional investors is positively associated with firm governance ratings, risk and profitability. This study shows that a positive association between risk and return is associated with large active institutional ownership, which we interpret as shareholders with sufficient power to pressure management to increase short-term profits.

Modelling and performance of an active heave compensator for offshore operations

The development of offshore oil and gas fields require the placement of different equipment on the sea floor. This is done by deploying the equipment from vessels operating in dynamic positioning on the surface. The deployment operation has different phases, and in higher sea states, it may require wave-load synchronization, when the load is going through the splash zone, and heave compensation when the load is close to the sea floor. In this paper, we analyse the performance of a particular type of hardware operating in a heave compensation mode. We derive a comprehensive model, analyse limits of performance and evaluate a control strategy.

Power and paradigms : the Dutch response to pressures for shareholder value

In recent years, research aimed at identifying and relating the antecedents and consequences of diffusing organizational practices/ideas has turned its attention to debating the international adoption and implementation of the Anglo-American model of corporate governance, i.e., a shareholder-value-orientation (SVO). While financial economists characterize the adoption of an SVO as necessary and performance-enhancing, behavioral scientists have disputed such claims, invoking institutional contingencies in the appropriateness of an SVO. Our study seeks to provide some resolution to the debate by developing an overarching socio-political perspective that links the antecedents and consequences of the adoption of the contested practice of SVO. We test our framework using extensive longitudinal data from 1992-2006 from the largest listed corporations in the Netherlands, and we find a negative relationship between SVO adoption and subsequent firm performance, although this effect is attenuated when accompanied by greater SVO-alignment among major owners and a firm’s visible commitment to an SVO. This study extends prior research on the diffusion of contested organizational practices that has taken a socio-political perspective by offering an original contingency perspective that addresses how and why the misaligned preferences of corporate owners will affect (i) a company’s inclination to espouse an SVO, and (ii) the performance consequences of such misalignment.This study suggests when board members are considering the adoption of new ideas/practices (e.g., SVO), they should consider the contextual fitness of the idea/practice with the firm’s owners and their interests.

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.

Automated power semiconductor switching performance feature extraction from experimental double-pulse waveform data

Double-pulse tests are commonly used as a method for assessing the switching performance of power semiconductor switches in a clamped inductive switching application. Data generated from these tests are typically in the form of sampled waveform data captured using an oscilloscope. In cases where it is of interest to explore a multi-dimensional parameter space and corresponding result space it is necessary to reduce the data into key performance metrics via feature extraction. This paper presents techniques for the extraction of switching performance metrics from sampled double-pulse waveform data. The reported techniques are applied to experimental data from characterisation of a cascode gate drive circuit applied to power MOSFETs.

Fourier active appearance models

Gaining invariance to camera and illumination variations has been a well investigated topic in Active Appearance Model (AAM) fitting literature. The major problem lies in the inability of the appearance parameters of the AAM to generalize to unseen conditions. An attractive approach for gaining invariance is to fit an AAM to a multiple filter response (e.g. Gabor) representation of the input image. Naively applying this concept with a traditional AAM is computationally prohibitive, especially as the number of filter responses increase. In this paper, we present a computationally efficient AAM fitting algorithm based on the Lucas-Kanade (LK) algorithm posed in the Fourier domain that affords invariance to both expression and illumination. We refer to this as a Fourier AAM (FAAM), and show that this method gives substantial improvement in person specific AAM fitting performance over traditional AAM fitting methods.

A switching control strategy for single and dual inductor push-pull converters

A switching control strategy is proposed for single and dual inductor current-fed push-pull converters. The proposed switching control strategy can be used with both current-fed push-pull converters with an active voltage doubler rectifier, or active rectifier, in the secondary side of the isolation transformer. The proposed switching control strategy makes turn-on and turn-off processes of the primary side power switches zero-voltage-switching and zero-current-switching respectively. The soft-switching operation of the single and dual inductor push-pull converters, with both types of active rectifier, is explained. Simulation and experimental results are provided to validate soft switching operation of the current-fed push-pull converters with the proposed switching control strategy.

Comparison of the gate drive parameter space for driving power MOSFETs using conventional and cascode configurations

Conventional voltage driven gate drive circuits utilise a resistor to control the switching speed of power MOS-FETs. The gate resistance is adjusted to provide controlled rate of change of load current and voltage. The cascode gate drive configuration has been proposed as an alternative to the conventional resistor-fed gate drive circuit. While cascode drive is broadly understood in the literature the switching characteristics of this topology are not well documented. This paper explores, through both simulation and experimentation, the gate drive parameter space of the cascode gate drive configuration and provides a comparison to the switching characteristics of conventional gate drive.

Making climate change manageable : how accounting constructs new power-knowledge regimes

This paper examines the modern power of accounting to permeate new spheres and create new objects by examining how climate change becomes a new category for accounting’s attention. It outlines the socio-political problem space where accounting and climate change connect by tracing the emergence of the UK’s Climate Change Act (2008) to a specifically modern calculating attitude described here as ‘managing by the numbers’. It suggests the intersection of accounting and climate change was made possible by accounting’s role in tying disciplinary subjectivities and objectivities together whilst operating simultaneously at the level of individuals, organisations and government. Such that when faced with new unknowns we revert to previous ways of managing we have come to know and experienced throughout our formative years in schools, hospitals, firms and government departments. In this way, accounting’s emergence in the domain of managing climate change implies a transformation that cannot be explained merely as a practical response to a global warming problem, but rather as an example of a new power-knowledge regime that makes possible the management and control of a new organisational phenomenon called climate change.

Factors influencing robustness and effectiveness of conditional random fields in active learning frameworks

Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.

An SECM study on the influence of cationic, membrane-active peptides on a gold-supported self-assembled monolayer

The influence of the membrane active peptides, Tat44–57 (activator in HIV-1) and melittin (active content of bee venom), on self-assembled monolayers of 6-mercaptohexanoic acid (MHA) on gold electrodes has been studied with scanning electrochemical microscopy (SECM). It was found that MHA, when deprotonated at physiological pH, significantly affected the relative rates of electron transfer between the [Fe(CN)6]4− solution based mediator and the underlying gold electrode, predominantly by the electrostatic interaction between the mediator and MHA. Upon the introduction of Tat44–57 ormelittin to the electrolyte, the relative rate of electron transfer through the MHA layer could be increased or decreased depending on the mediator used. However, in all cases it was found that these peptides have the ability to be incorporated into synthetic SAMs, which has implications for future electrochemical studies carried out using cell mimicking membranes immobilised on such layers.

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

Partial shading and rapidly changing irradiance conditions significantly impact on the performance of photovoltaic (PV) systems. These impacts are particularly severe in tropical regions where the climatic conditions result in very large and rapid changes in irradiance. In this paper, a hybrid maximum power point (MPP) tracking (MPPT) technique for PV systems operating under partially shaded conditions witapid irradiance change is proposed. It combines a conventional MPPT and an artificial neural network (ANN)-based MPPT. A low cost method is proposed to predict the global MPP region when expensive irradiance sensors are not available or are not justifiable for cost reasons. It samples the operating point on the stairs of I–V curve and uses a combination of the measured current value at each stair to predict the global MPP region. The conventional MPPT is then used to search within the classified region to get the global MPP. The effectiveness of the proposed MPPT is demonstrated using both simulations and an experimental setup. Experimental comparisons with four existing MPPTs are performed. The results show that the proposed MPPT produces more energy than the other techniques and can effectively track the global MPP with a fast tracking speed under various shading patterns.

Prevalence of active foot disease and foot disease risk factors in a subacute inpatient rehabilitation facility: a cross-sectional prevalence study

Background Australian subacute inpatient rehabilitation facilities face significant challenges from the ageing population and the increasing burden of chronic disease. Foot disease complications are a negative consequence of many chronic diseases. With the rapid expansion of subacute rehabilitation inpatient services, it seems imperative to investigate the prevalence of foot disease and foot disease risk factors in this population. The primary aim of this cross-sectional study was to determine the prevalence of active foot disease and foot disease risk factors in a subacute inpatient rehabilitation facility. Methods Eligible participants were all adults admitted at least overnight into a large Australian subacute inpatient rehabilitation facility over two different four week periods. Consenting participants underwent a short non-invasive foot examination by a podiatrist utilising the validated Queensland Health High Risk Foot Form to collect data on age, sex, medical co-morbidity history, foot disease risk factor history and clinically diagnosed foot disease complications and foot disease risk factors. Descriptive statistics were used to determine the prevalence of clinically diagnosed foot disease complications, foot disease risk factors and groups of foot disease risk factors. Logistic regression analyses were used to investigate any associations between defined explanatory variables and appropriate foot disease outcome variables. Results Overall, 85 (88%) of 97 people admitted to the facility during the study periods consented; mean age 80 (±9) years and 71% were female. The prevalence (95% confidence interval) of participants with active foot disease was 11.8% (6.3 – 20.5), 32.9% (23.9 – 43.5) had multiple foot disease risk factors, and overall, 56.5% (45.9 – 66.5) had at least one foot disease risk factor. A self-reported history of peripheral neuropathy diagnosis was independently associated with having multiple foot disease risk factors (OR 13.504, p = 0.001). Conclusion This study highlights the potential significance of the burden of foot disease in subacute inpatient rehabilitation facilities. One in eight subacute inpatients were admitted with active foot disease and one in two with at least one foot disease risk factor in this study. It is recommended that further multi-site studies and management guidelines are required to address the foot disease burden in subacute inpatient rehabilitation facilities. Keywords: Subacute; Inpatient; Foot; Complication; Prevalence

Probabilistic power system contingency analysis considering wind

This thesis was a step forward in developing probabilistic assessment of power system response to faults subject to intermittent generation by renewable energy. It has investigated the wind power fluctuation effect on power system stability, and the developed fast estimation process has demonstrated the feasibility for real-time implementation. A better balance between power network security and efficiency can be achieved based on this research outcome.