An organizational learning approach to expatriate cross-cultural adjustment, organizational commitment, and job satisfaction

The purpose of this study was to investigate the relationship between organizational learning and expatriation in overseas subsidiaries as well as in organizations as a whole. In doing so, two issues were addressed--(i) the use of expatriation as firms internationalize, and (ii) the significance of various factors to expatriate success as firms gain international experience. The sample of companies for this study was drawn from U.S. Fortune 500 multinational corporations (MNCs) in two sets of related industries--computers/electronics and petroleum/chemicals. Based on the learning that takes place within organizations as they increase their involvement overseas, a positive relationship was expected between international experience and expatriation when internationalization was low, and a negative relationship was expected when internationalization was high. Results indicate a significant positive relationship between country experience and the proportion of expatriates in that subsidiary when subsidiaries were relatively young, and a negative relationship, however not significant, for more mature subsidiaries. The relationship between overall firm degree of internationalization (DOI) and the proportion of expatriates in the firm as a whole was negative regardless of stage of internationalization, but this relationship was significant only for highly internationalized firms. It was further suspected that individual, environmental, and family-related characteristics would have a significant effect on the success of expatriates whose firms were low on internationalization, and that organizational characteristics would play a significant role in highly internationalized firms. Support for these hypotheses was received with respect to certain outcomes and some determinants of success. The preponderance of support was found for those addressing the effects of both environmental and family-related characteristics on the cross-cultural adjustment of expatriates in firms with little international experience. Considerable support was also found for those hypotheses addressing the impact of organizational characteristics on the job satisfaction levels of expatriates assigned to mature subsidiaries. The relevant literatures on organizational learning and expatriation are reviewed, and a model is developed underlying the logic of the hypotheses. Research methods are then described in full detail, results are reported, and implications for theory and for management are discussed. ^

Synthesis, characterization and study of physical properties of novel M(n+1)AX(n) compounds

Mn+1AXn compounds, the ternary layered nanolaminates have gathered momentum in the last decade since its advent because of their unusual but exciting properties. These technologically important compounds combine some of the best properties of metals and ceramics. Like ceramics they are refractory, oxidation resistant, elastically stiff and relatively light. They also exhibit metallic properties like excellent machinability, thermal and electrical conductivity. This dissertation concentrates on the synthesis of germanium-based 211 Mn+1AXn compounds. The main objective of the research was to synthesize predominantly single phase samples of Cr2GeC, V2GeC and Ti2GeC. Another goal was to study the effect of solid substitutions on the M-site of Mn+1AXn compounds with Ge as an A-element. This study is in itself the first to demonstrate the synthesis of (Cr0.5V0.5)2GeC a novel Mn+1AXn compound. Scanning electron microscopy coupled with energy dispersive spectroscopy, x-ray diffraction and electron probe microanalysis were employed to confirm the presence of predominantly single phase samples of M2GeC compounds where M = Ti, V, Cr and (Cr 0.5V0.5). A large part of the dissertation also focuses on the effect of the compressibility on the Ge-based 211 Mn+1AXn compounds with the aid of diamond anvil cell and high energy synchrotron radiation. This study also concentrates on the stability of these compounds at high temperature and thereby determines its suitability as high temperature structural materials. In order to better understand the effect of substitutions on A-site of 211 Mn+1 AXn compounds under high pressure and high temperature, a comparison is made with previously reported 211 Mn+1AXn compounds with Al, Ga and S as A-site elements.

Study of Periodic and Quasi-Periodic Structures in Silicon-on-Insulator

In this thesis, a numerical design approach has been proposed and developed based on the transmission matrix method in order to characterize periodic and quasi-periodic photonic structures in silicon-on-insulator. The approach and its performance have been extensively tested with specific structures in 2D and its validity has been verified in 3D.

Stable-isotope ratios and accumulation rates of four firn cores from the Dronning Maud Land, Antarctica

Four firn cores were retrieved in 2007 at two ridges in the area of the Ekström Ice Shelf, Dronning Maud Land, coastal East Antarctica, in order to investigate the recent regional climate variability and the potential for future extraction of an intermediate-depth core. Stable water-isotope analysis, tritium content and electrical conductivity were used to date the cores. For the period 1981-2006 a strong and significant correlation between the stable-isotope composition of firn cores in the hinterland and mean monthly air temperatures at Neumayer station was (r=0.54-0.71). No atmospheric warming or cooling trend is inferred from our stable-isotope data for the period 1962-2006. The stable-isotope record of the ice/firn cores could expand well beyond the meteorological record of the region. No significant temporal variation of accumulation rates was detected. However, decreasing accumulation rates were found from coast to hinterland, as well as from east (Halvfarryggen) to west (Søråsen). The deuterium excess (d) exhibits similar differences (higher d at Søråsen, lower d at Halvfarryggen), with a weak negative temporal trend on Halvfarryggen (0.04 per mil/a), probably implying increasing oceanic input. We conclude that Halvfarryggen acts as a natural barrier for moisture-carrying air masses circulating in the region from east to west.

Growth, Characterization, and Properties of Hybrid Graphene-Carbon Nanotube Films and Related Carbon Nanostructures

Graphene, first isolated in 2004 and the subject of the 2010 Nobel Prize in physics, has generated a tremendous amount of research interest in recent years due to its incredible mechanical and electrical properties. However, difficulties in large-scale production and low as-prepared surface area have hindered commercial applications. In this dissertation, a new material is described incorporating the superior electrical properties of graphene edge planes into the high surface area framework of carbon nanotube forests using a scalable and reproducible technology.

The objectives of this research were to investigate the growth parameters and mechanisms of a graphene-carbon nanotube hybrid nanomaterial termed “graphenated carbon nanotubes” (g-CNTs), examine the applicability of g-CNT materials for applications in electrochemical capacitors (supercapacitors) and cold-cathode field emission sources, and determine materials characteristics responsible for the superior performance of g-CNTs in these applications. The growth kinetics of multi-walled carbon nanotubes (MWNTs), grown by plasma-enhanced chemical vapor deposition (PECVD), was studied in order to understand the fundamental mechanisms governing the PECVD reaction process. Activation energies and diffusivities were determined for key reaction steps and a growth model was developed in response to these findings. Differences in the reaction kinetics between CNTs grown on single-crystal silicon and polysilicon were studied to aid in the incorporation of CNTs into microelectromechanical systems (MEMS) devices. To understand processing-property relationships for g-CNT materials, a Design of Experiments (DOE) analysis was performed for the purpose of determining the importance of various input parameters on the growth of g-CNTs, finding that varying temperature alone allows the resultant material to transition from CNTs to g-CNTs and finally carbon nanosheets (CNSs): vertically oriented sheets of few-layered graphene. In addition, a phenomenological model was developed for g-CNTs. By studying variations of graphene-CNT hybrid nanomaterials by Raman spectroscopy, a linear trend was discovered between their mean crystallite size and electrochemical capacitance. Finally, a new method for the calculation of nanomaterial surface area, more accurate than the standard BET technique, was created based on atomic layer deposition (ALD) of titanium oxide (TiO2).

Stimulus Integration and Parsing in the Primate Auditory Midbrain

Integrating information from multiple sources is a crucial function of the brain. Examples of such integration include multiple stimuli of different modalties, such as visual and auditory, multiple stimuli of the same modality, such as auditory and auditory, and integrating stimuli from the sensory organs (i.e. ears) with stimuli delivered from brain-machine interfaces.

The overall aim of this body of work is to empirically examine stimulus integration in these three domains to inform our broader understanding of how and when the brain combines information from multiple sources.

First, I examine visually-guided auditory, a problem with implications for the general problem in learning of how the brain determines what lesson to learn (and what lessons not to learn). For example, sound localization is a behavior that is partially learned with the aid of vision. This process requires correctly matching a visual location to that of a sound. This is an intrinsically circular problem when sound location is itself uncertain and the visual scene is rife with possible visual matches. Here, we develop a simple paradigm using visual guidance of sound localization to gain insight into how the brain confronts this type of circularity. We tested two competing hypotheses. 1: The brain guides sound location learning based on the synchrony or simultaneity of auditory-visual stimuli, potentially involving a Hebbian associative mechanism. 2: The brain uses a ‘guess and check’ heuristic in which visual feedback that is obtained after an eye movement to a sound alters future performance, perhaps by recruiting the brain’s reward-related circuitry. We assessed the effects of exposure to visual stimuli spatially mismatched from sounds on performance of an interleaved auditory-only saccade task. We found that when humans and monkeys were provided the visual stimulus asynchronously with the sound but as feedback to an auditory-guided saccade, they shifted their subsequent auditory-only performance toward the direction of the visual cue by 1.3-1.7 degrees, or 22-28% of the original 6 degree visual-auditory mismatch. In contrast when the visual stimulus was presented synchronously with the sound but extinguished too quickly to provide this feedback, there was little change in subsequent auditory-only performance. Our results suggest that the outcome of our own actions is vital to localizing sounds correctly. Contrary to previous expectations, visual calibration of auditory space does not appear to require visual-auditory associations based on synchrony/simultaneity.

My next line of research examines how electrical stimulation of the inferior colliculus influences perception of sounds in a nonhuman primate. The central nucleus of the inferior colliculus is the major ascending relay of auditory information before it reaches the forebrain, and thus an ideal target for understanding low-level information processing prior to the forebrain, as almost all auditory signals pass through the central nucleus of the inferior colliculus before reaching the forebrain. Thus, the inferior colliculus is the ideal structure to examine to understand the format of the inputs into the forebrain and, by extension, the processing of auditory scenes that occurs in the brainstem. Therefore, the inferior colliculus was an attractive target for understanding stimulus integration in the ascending auditory pathway.

Moreover, understanding the relationship between the auditory selectivity of neurons and their contribution to perception is critical to the design of effective auditory brain prosthetics. These prosthetics seek to mimic natural activity patterns to achieve desired perceptual outcomes. We measured the contribution of inferior colliculus (IC) sites to perception using combined recording and electrical stimulation. Monkeys performed a frequency-based discrimination task, reporting whether a probe sound was higher or lower in frequency than a reference sound. Stimulation pulses were paired with the probe sound on 50% of trials (0.5-80 µA, 100-300 Hz, n=172 IC locations in 3 rhesus monkeys). Electrical stimulation tended to bias the animals’ judgments in a fashion that was coarsely but significantly correlated with the best frequency of the stimulation site in comparison to the reference frequency employed in the task. Although there was considerable variability in the effects of stimulation (including impairments in performance and shifts in performance away from the direction predicted based on the site’s response properties), the results indicate that stimulation of the IC can evoke percepts correlated with the frequency tuning properties of the IC. Consistent with the implications of recent human studies, the main avenue for improvement for the auditory midbrain implant suggested by our findings is to increase the number and spatial extent of electrodes, to increase the size of the region that can be electrically activated and provide a greater range of evoked percepts.

My next line of research employs a frequency-tagging approach to examine the extent to which multiple sound sources are combined (or segregated) in the nonhuman primate inferior colliculus. In the single-sound case, most inferior colliculus neurons respond and entrain to sounds in a very broad region of space, and many are entirely spatially insensitive, so it is unknown how the neurons will respond to a situation with more than one sound. I use multiple AM stimuli of different frequencies, which the inferior colliculus represents using a spike timing code. This allows me to measure spike timing in the inferior colliculus to determine which sound source is responsible for neural activity in an auditory scene containing multiple sounds. Using this approach, I find that the same neurons that are tuned to broad regions of space in the single sound condition become dramatically more selective in the dual sound condition, preferentially entraining spikes to stimuli from a smaller region of space. I will examine the possibility that there may be a conceptual linkage between this finding and the finding of receptive field shifts in the visual system.

In chapter 5, I will comment on these findings more generally, compare them to existing theoretical models, and discuss what these results tell us about processing in the central nervous system in a multi-stimulus situation. My results suggest that the brain is flexible in its processing and can adapt its integration schema to fit the available cues and the demands of the task.

Lattice Engineering of III-Nitride Heterostructures and Their Applications

III-Nitride materials have recently become a promising candidate for superior applications over the current technologies. However, certain issues such as lack of native substrates, and high defect density have to be overcome for further development of III-Nitride technology. This work presents research on lattice engineering of III-Nitride materials, and the structural, optical, and electrical properties of its alloys, in order to approach the ideal material for various applications. We demonstrated the non-destructive and quantitative characterization of composition modulated nanostructure in InAlN thin films with X-ray diffraction. We found the development of the nanostructure depends on growth temperature, and the composition modulation has impacts on carrier recombination dynamics. We also showed that the controlled relaxation of a very thin AlN buffer (20 ~ 30 nm) or a graded composition InGaN buffer can significantly reduce the defect density of a subsequent epitaxial layer. Finally, we synthesized an InAlGaN thin films and a multi-quantum-well structure. Significant emission enhancement in the UVB range (280 – 320 nm) was observed compared to AlGaN thin films. The nature of the enhancement was investigated experimentally and numerically, suggesting carrier confinement in the In localization centers.

Synergy between Piezo1 and Piezo2 channels confers high-strain mechanosensitivity to articular cartilage.

Diarthrodial joints are essential for load bearing and locomotion. Physiologically, articular cartilage sustains millions of cycles of mechanical loading. Chondrocytes, the cells in cartilage, regulate their metabolic activities in response to mechanical loading. Pathological mechanical stress can lead to maladaptive cellular responses and subsequent cartilage degeneration. We sought to deconstruct chondrocyte mechanotransduction by identifying mechanosensitive ion channels functioning at injurious levels of strain. We detected robust expression of the recently identified mechanosensitive channels, PIEZO1 and PIEZO2. Combined directed expression of Piezo1 and -2 sustained potentiated mechanically induced Ca(2+) signals and electrical currents compared with single-Piezo expression. In primary articular chondrocytes, mechanically evoked Ca(2+) transients produced by atomic force microscopy were inhibited by GsMTx4, a PIEZO-blocking peptide, and by Piezo1- or Piezo2-specific siRNA. We complemented the cellular approach with an explant-cartilage injury model. GsMTx4 reduced chondrocyte death after mechanical injury, suggesting a possible therapy for reducing cartilage injury and posttraumatic osteoarthritis by attenuating Piezo-mediated cartilage mechanotransduction of injurious strains.

A Comparison of the Impacts of Lithium Extraction and Lithium Recycling Processes

Lithium is used in the cathode and electrolyte of rechargeable batteries in many portable electronics and electric vehicles, and is thus seen as a critical component of modern technology (Gruber et al., 2011). Electric vehicles are promoted as a way to reduce carbon emissions associated with the transportation sector, which accounts for 14.3% of anthropogenic greenhouse gas emissions (OECD International Transport Forum, 2010). However, the sustainability of lithium procurement will influence the overall environmental impact of this proposed “green” solution. It is estimated that 66% of the world’s lithium resource is contained in natural brines, 24% in pegmatites, and 8% in sedimentary rocks such as hectorite clays (Gruber et al., 2011). It has been shown that “[r]ecycling of lithium from Li-ion batteries may be a critical factor in balancing the supply of lithium with future demand” (Gruber et al., 2011). In an attempt to quantify energy and materials consumption associated with production of a unit of useful lithium compounds, industry reports and peer-reviewed scientific literature concerning lithium mining and lithium recycling were reviewed and compared. Other aspects of sustainability, such as waste or by-products produced in the production of a unit of useful lithium, were also explored. Thus, this paper will serve to further the evaluation of the comparative environmental consequences associated with lithium production via extraction versus recycling. Efficiencies must be made in both processes to maximize productivity while minimizing ecological harm.

Joint Power Amplifiers and I/Q Modulator Impairments Modelling and Compensation for LTE Transmitters Using Artificial Neural Networks

This work introduces joint power amplifier (PA) and I/Q modulator modelling and compensation for LongTerm Evolution (LTE) transmitters using artificial neural networks (ANNs). The proposed solution util-izes a powerful nonlinear autoregressive with exogenous inputs (NARX) ANN architecture, which yieldsnoticeable results for high peak to average power ratio (PAPR) LTE signals. Given the ANNs learning capa-bilities, this one-step solution, which includes the mitigation of both PA nonlinearity and I/Q modulatorimpairments, is both accurate and adaptable

Bit-index sort: A fast non-comparison integer sorting algorithm for permutations

This paper describes a fast integer sorting algorithm, herein referred to as Bit-index sort, which does not use comparisons and is intended to sort partial permutations. Experimental results exhibit linear complexity order in execution time. Bit-index sort uses a bit-array to classify input sequences of distinct integers, and exploits built-in bit functions in C compilers, supported by machine hardware, to retrieve the ordered output sequence. Results show that Bit-index sort outperforms quicksort and counting sort algorithms when compared in their execution time. A parallel approach for Bit-index sort using two simultaneous threads is also included, which obtains further speedups of up to 1.6 compared to its sequential case.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Management of public water supply to reduce power cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Tailoring Magnetic, Mechanical and Dielectric Properties of Magnetorheological Elastomers based on Natural Rubber and Iron by Magnetic Field Assisted Curing for Possible Applications

If magnetism is universal in nature, magnetic materials are ubiquitous. A life without magnetism is unthinkable and a day without the influence of a magnetic material is unimaginable. They find innumerable applications in the form of many passive and active devices namely, compass, electric motor, generator, microphone, loud speaker, maglev train, magnetic resonance imaging, data recording and reading, hadron collider etc. The list is endless. Such is the influence of magnetism and magnetic materials in ones day to day life. With the advent of nanoscience and nanotechnology, along with the emergence of new areas/fields such as spintronics, multiferroics and magnetic refrigeration, the importance of magnetism is ever increasing and attracting the attention of researchers worldwide. The search for a fluid which exhibits magnetism has been on for quite some time. However nature has not bestowed us with a magnetic fluid and hence it has been the dream of many researchers to synthesize a magnetic fluid which is thought to revolutionize many applications based on magnetism. The discovery of a magnetic fluid by Jacob Rabinow in the year 1952 paved the way for a new branch of Physics/Engineering which later became magnetic fluids. This gave birth to a new class of material called magnetorheological materials. Magnetorheological materials are considered superior to electrorheological materials in that magnetorheology is a contactless operation and often inexpensive.Most of the studies in the past on magnetorheological materials were based on magnetic fluids. Recently the focus has been on the solid state analogue of magnetic fluids which are called Magnetorheological Elastomers (MREs). The very word magnetorheological elastomer implies that the rheological properties of these materials can be altered by the influence of an external applied magnetic field and this process is reversible. If the application of an external magnetic field modifies the viscosity of a magnetic fluid, the effect of external magnetic stimuli on a magnetorheological elastomer is in the modification of its stiffness. They are reversible too. Magnetorheological materials exhibit variable stiffness and find applications in adaptive structures of aerospace, automotive civil and electrical engineering applications. The major advantage of MRE is that the particles are not able to settle with time and hence there is no need of a vessel to hold it. The possibility of hazardous waste leakage is no more with a solid MRE. Moreover, the particles in a solid MRE will not affect the performance and durability of the equipment. Usually MR solids work only in the pre yield region while MR fluids, typically work in the post yield state. The application of an external magnetic field modifies the stiffness constant, shear modulus and loss modulus which are complex quantities. In viscoelastic materials a part of the input energy is stored and released during each cycle and a part is dissipated as heat. The storage modulus G′ represents the capacity of the material to store energy of deformation, which contribute to material stiffness. The loss modulusG′′ represents the ability of the material to dissipate the energy of deformation. Such materials can find applications in the form of adaptive vibration absorbers (ATVAs), stiffness tunable mounts and variable impedance surfaces. MREs are an important material for automobile giants and became the focus of this research for eventual automatic vibration control, sound isolation, brakes, clutches and suspension systems