Academic achievement among recently arrived Chinese adolescent migrants: The role of social support, school belonging, and acculturative stress

Factors contributing to academic achievement among recently arrived Chinese adolescents in Australia remains relatively underexplored. Previous studies focused on Asian migrants, including Chinese, but did not distinguish Chinese from other Asian migrants. The current study specifically looks at Chinese migrants who have recently arrived as opposed to Asian migrants. This study aims to explore the role of social support, school belonging, and acculturative stress on academic achievement of recently arrived Chinese adolescents (n = 55). Questionnaires were administered to this sample. The results indicated that school belonging, interestingly, was negatively associated with academic achievement. Perceived social support and acculturative stress were not significantly associated with academic achievement. The findings provide insights into risk and protective factors influencing academic achievement of Chinese migrants. Implications of the findings are discussed.

A Spatial Planning Support System for Managing Bangalore's Urban Sprawl

Urban sprawl is the outgrowth along the periphery of cities and along highways. Although an accurate definition of urban sprawl may be debated, a consensus is that urban sprawl is characterized by an unplanned and uneven pattern of growth, driven by multitude of processes and leading to inefficient resource utilization. Urbanization in India has never been as rapid as it is in recent times. As one of the fastest growing economies in the world, India faces stiff challenges in managing the urban sprawl, while ensuring effective delivery of basic services in urban areas. The urban areas contribute significantly to the national economy (more than 50% of GDP), while facing critical challenges in accessing basic services and necessary infrastructure, both social and economic. The overall rise in the population of the urban poor or the increase in travel times due to congestion along road networks are indicators of the effectiveness of planning and governance in assessing and catering for this demand. Agencies of governance at all levels: local bodies, state government and federal government, are facing the brunt of this rapid urban growth. It is imperative for planning and governance to facilitate, augment and service the requisite infrastructure over time systematically. Provision of infrastructure and assurance of the delivery of basic services cannot happen overnight and hence planning has to facilitate forecasting and service provision with appropriate financial mechanisms.

A Control Strategy for Reference Wave Adaptive Current Generation

Speed control of ac motors requires variable frequency, variable current, or variable voltage supply. Variable frequency supply can be obtained directly from a fixed frequency supply by using a frequency converter or from a dc source using inverters. In this paper a control technique for reference wave adaptive-current generation by modulating the inverter voltage is explained. Extension of this technique for three-phase induction-motor speed control is briefly explained. The oscillograms of the current waveforms obtained from the experimental setup are also shown.

The Emerging Phenotype: Ecological Genetics of Color, Form and Sex in the Common Frog

One of the main aims of evolutionary biology is to explain why organisms vary phenotypically as they do. Proximately, this variation arises from genetic differences and from environmental influences, the latter of which is referred to as phenotypic plasticity. Phenotypic plasticity is thus a central concept in evolutionary biology, and understanding its relative importance in causing the phenotypic variation and differentiation is important, for instance in anticipating the consequences of human induced environmental changes. The aim of this thesis was to study geographic variation and local adaptation, as well as sex ratios and environmental sex reversal, in the common frog (Rana temporaria). These themes cover three different aspects of phenotypic plasticity, which emerges as the central concept for the thesis. The first two chapters address geographic variation and local adaptation in two potentially thermally adaptive traits, namely the degree of melanism and the relative leg length. The results show that although there is an increasing latitudinal trend in the degree of melanism in wild populations across Scandinavian Peninsula, this cline has no direct genetic basis and is thus environmentally induced. The second chapter demonstrates that although there is no linear, latitudinally ordered phenotypic trend in relative leg length that would be expected under Allen s rule an ecogeographical rule linking extremity length to climatic conditions there seems to be such a trend at the genetic level, hidden under environmental effects. The first two chapters thus view phenotypic plasticity through its ecological role and evolution, and demonstrate that it can both give rise to phenotypic variation and hide evolutionary patterns in studies that focus solely on phenotypes. The last three chapters relate to phenotypic plasticity through its ecological and evolutionary role in sex determination, and consequent effects on population sex ratio, genetic recombination and the evolution of sex chromosomes. The results show that while sex ratios are strongly female biased and there is evidence of environmental sex reversals, these reversals are unlikely to have caused the sex ratio skew, at least directly. The results demonstrate that environmental sex reversal can have an effect on the evolution of sex chromosomes, as the recombination patterns between them seem to be controlled by phenotypic, rather than genetic, sex. This potentially allows Y chromosomes to recombine, lending support for the recent hypothesis suggesting that sex-reversal may play an important role on the rejuvenation of Y chromosomes.

Empowerment climate, supervisory support for creativity and work role performance in new product development settings: A team level investigation

This thesis is an examination of how organisational context variables affect the performance of new product development (NPD) teams. Specifically, the extent to how team empowerment climate and supervisory support for creativity impact NPD team performance. Moreover, this thesis is a step forward in the ongoing development of work role performance theory by examining Griffin et al.'s (2007) work role performance model in the context of NPD teams. This thesis addresses the lack of research exploring work role performance dimensions in NPD teams and the extent to which a team empowerment climate and supervisory support for creativity impact NPDs performance.

Applications of gene sequence polymorphisms in evolutionary genetic studies of Atlantic salmon (Salmo salar) and other teleost fish species

Evolutionary genetics incorporates traditional population genetics and studies of the origins of genetic variation by mutation and recombination, and the molecular evolution of genomes. Among the primary forces that have potential to affect the genetic variation within and among populations, including those that may lead to adaptation and speciation, are genetic drift, gene flow, mutations and natural selection. The main challenges in knowing the genetic basis of evolutionary changes is to distinguish the adaptive selection forces that cause existent DNA sequence variants and also to identify the nucleotide differences responsible for the observed phenotypic variation. To understand the effects of various forces, interpretation of gene sequence variation has been the principal basis of many evolutionary genetic studies. The main aim of this thesis was to assess different forms of teleost gene sequence polymorphisms in evolutionary genetic studies of Atlantic salmon (Salmo salar) and other species. Firstly, the level of Darwinian adaptive evolution affected coding regions of the growth hormone (GH) gene during the teleost evolution was investigated based on the sequence data existing in public databases. Secondly, a target gene approach was used to identify within population variation in the growth hormone 1 (GH1) gene in salmon. Then, a new strategy for single nucleotide polymorphisms (SNPs) discovery in salmonid fishes was introduced, and, finally, the usefulness of a limited number of SNP markers as molecular tools in several applications of population genetics in Atlantic salmon was assessed. This thesis showed that the gene sequences in databases can be utilized to perform comparative studies of molecular evolution, and some putative evidence of the existence of Darwinian selection during the teleost GH evolution was presented. In addition, existent sequence data was exploited to investigate GH1 gene variation within Atlantic salmon populations throughout its range. Purifying selection is suggested to be the predominant evolutionary force controlling the genetic variation of this gene in salmon, and some support for gene flow between continents was also observed. The novel approach to SNP discovery in species with duplicated genome fragments introduced here proved to be an effective method, and this may have several applications in evolutionary genetics with different species - e.g. when developing gene-targeted markers to investigate quantitative genetic variation. The thesis also demonstrated that only a few SNPs performed highly similar signals in some of the population genetic analyses when compared with the microsatellite markers. This may have useful applications when estimating genetic diversity in genes having a potential role in ecological and conservation issues, or when using hard biological samples in genetic studies as SNPs can be applied with relatively highly degraded DNA.

Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling

The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Development and evaluation of a spatial decision support system for malaria elimination in Bhutan

Background: Bhutan has reduced its malaria incidence significantly in the last 5 years, and is aiming for malaria elimination by 2016. To assist with the management of the Bhutanese malaria elimination programme a spatial decision support system (SDSS) was developed. The current study aims to describe SDSS development and evaluate SDSS utility and acceptability through informant interviews. Methods: The SDSS was developed based on the open-source Quantum geographical information system (QGIS) and piloted to support the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) in the two sub-districts of Samdrup Jongkhar District. It was subsequently used to support reactive case detection (RACD) in the two sub-districts of Samdrup Jongkhar and two additional sub-districts in Sarpang District. Interviews were conducted to ascertain perceptions on utility and acceptability of 11 informants using the SDSS, including programme and district managers, and field workers. Results: A total of 1502 households with a population of 7165 were enumerated in the four sub-districts, and a total of 3491 LLINs were distributed with one LLIN per 1.7 persons. A total of 279 households representing 728 residents were involved with RACD. Informants considered that the SDSS was an improvement on previous methods for organizing LLIN distribution, IRS and RACD, and could be easily integrated into routine malaria and other vector-borne disease surveillance systems. Informants identified some challenges at the programme and field level, including the need for more skilled personnel to manage the SDSS, and more training to improve the effectiveness of SDSS implementation and use of hardware. Conclusions: The SDSS was well accepted and informants expected its use to be extended to other malaria reporting districts and other vector-borne diseases. Challenges associated with efficient SDSS use included adequate skills and knowledge, access to training and support, and availability of hardware including computers and global positioning system receivers.

Systemic Inflammation in Preterm Infants

Even though mortality among preterm infants has decreased, their risk for chronic complications such as bronchopulmonary dysplasia (BPD) and neurological disability remains significant. One common risk factor for these is exposure to inflammation. The fetus may be exposed prenatally during maternal chorioamnionitis. Pre-eclampsia is also associated with low-grade maternal inflammation. Postnatally, local and systemic inflammation is present during respiratory distress syndrome (RDS). Furthermore, septic infections in the preterm infant are an important source of inflammatory stimuli and can lead to death in only a few hours. The diagnosis of septic infection is difficult, since reliable diagnostic markers are unavailable. This thesis evaluates peri- and postnatal systemic inflammation in preterm infants in septic infections, in RDS treated with mechanical ventilation and surfactant treatment, and in preterm infants prenatally exposed to chorioamnionitis and pre-eclampsia. Surface expressions of the activation markers CD11b, CD54, and CD62L, determined by flow cytometry on circulating phagocytes and T lymphocytes, serve as indicators of systemic inflammation. The main findings: I) In preterm infants with developing late-onset sepsis and fulminant necrotizing enterocolitis, a significant increase in CD11b expression on circulating phagocytes is already present on the day of onset of clinical symptoms. II) In preterm infants with RDS, circulating phagocytes become activated within hours after start of mechanical ventilation. In preterm infants treated for RDS with nasal continuous positive airway pressure, no such activation occurs. III) In preterm infants, RDS is associated during the first days of life with fewer circulating helper and cytotoxic T lymphocytes, of which the greater proportions are activated. Even greater proportions of circulating T cells are activated in infants subsequently developing BPD. IV) In preterm infants born after maternal pre-eclampsia, RDS-associated phagocyte CD11b up-regulation is greater than in preterm infants not exposed to pre-eclampsia during the first week of life. These findings suggest that I) an increase in CD11b expression on circulating phagocytes can identify preterm infants with late-onset sepsis as early as at sampling for blood culture and may thus aid in the diagnosis. II) In preterm infants with RDS, initiation of mechanical ventilation, but not the use of nasal continuous positive airway pressure, promotes a systemic inflammatory reaction; exogenous surfactant does not seem to promote inflammation. III) In addition to activation of circulating cells of the innate immunity in preterm infants with RDS, the circulating cells of the adaptive immunity are activated. The activation of adaptive immunity may link acute inflammation and development of chronic inflammation-associated problems such as BPD. IV) Maternal pre-eclampsia may prime neonatal immunity to react more strongly to postnatal stimuli. In conclusion, the preterm infant is exposed to numerous potentially injurious events such as intrauterine inflammation, respiratory distress syndrome (RDS), and systemic infections, all evoking systemic inflammation. Due to ongoing development of the lung and the brain, this may, in addition to acute injury, lead to aberrant lung and brain development and to clinical syndromes of BPD and neurologic sequelae.

Effects of opioids on ventilation and hemodynamics

Opioids are most commonly used for treatment of severe pain. However, the fear of respiratory depression has restricted the use of opioids. Depending on the monitoring system used, different modes of opioid respiratory effects have been noted in previous studies. All opioids also cause alterations in hemodynamics at least to some extent. The main goal of this series of investigations was to elucidate the native ventilatory and hemodynamic effects of different opioids. Studies I-IV each involved 8 healthy male volunteers. Study V involved 13 patients with lower or upper extremity traumas. The opioids studied were morphine, oxycodone, pethidine, fentanyl, alfentanil, tramadol and ketamine. The respiratory parameters used in this study were breathing pattern measured with respiratory inductive plethysmography, gas exchange measured with indirect calorimetry, blood gas analysis and pulse oximetry. Hemodynamics was measured with arterial blood pressure, heart rate and oxygen consumption. Plasma catecholamine and histamine concentrations were also determined. All opioids studied caused an alteration in respiratory function. Respiratory rate, alveolar ventilation and minute ventilation decreased, while tidal volume increased in most situations. Breathing pattern was also significantly affected after opioid administration. The respiratory depression caused by oxycodone was deeper than the one caused by same dose of morphine. An equianalgesic dose of tramadol caused markedly smaller respiratory depression compared to pethidine. The potency ratio for respiratory depression of fentanyl and alfentanil is similar to analgesic potency ratio studied elsewhere. Racemic ketamine attenuated the respiratory depression caused by fentanyl, if measured with minute ventilation. However, this effect was counteracted by increased oxygen consumption. Supplemental oxygen did not offer any benefits, nor did it cause any atelectasis when given to opioid treated trauma patients. Morphine caused a transient hemodynamic stimulation, which was accompanied by an increase in oxygen consumption. Oxycodone, alfentanil, fentanyl, tramadol and pethidine infusions had minimal effects on hemodynamics. Plasma catecholamine concentrations were increased after high dose opioid administration. Plasma histamine concentrations were not elevated after morphine nor oxycodone administration. Respiratory depression is a side effect noted with all opioids. The profile of this phenomenon is quite similar with different opioid-receptor agonists. The hemodynamic effects of opioids may vary depending on the opioid used, morphine causing a slight hemodynamic stimulation. However, all opioids studied could be considered hemodynamically stable.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.