The effect of poser race on the happy categorization advantage depends on stimulus type, set size, and presentation duration

The question as to whether poser race affects the happy categorization advantage, the faster categorization of happy than of negative emotional expressions, has been answered inconsistently. Hugenberg (2005) found the happy categorization advantage only for own race faces whereas faster categorization of angry expressions was evident for other race faces. Kubota and Ito (2007) found a happy categorization advantage for both own race and other race faces. These results have vastly different implications for understanding the influence of race cues on the processing of emotional expressions. The current study replicates the results of both prior studies and indicates that face type (computer-generated vs. photographic), presentation duration, and especially stimulus set size influence the happy categorization advantage as well as the moderating effect of poser race.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Rural self-reliance: the impact on health experiences of people living with type II diabetes in rural Queensland, Australia

Objective: The objective of the study was to explore whether and how rural culture influences type II diabetes management and to better understand the social processes that rural people construct in coping with diabetes and its complications. In particular, the study aimed to analyse the interface and interactions between rural people with type II diabetes and the Australian health care system, and to develop a theoretical understanding that reflects constructs that may be more broadly applicable. Methods: The study applied constructivist grounded theory methods within an interpretive interactionist framework. Data from 39 semi-structured interviews with rural and urban type II diabetes patients and a mix of rural health care providers were analysed to develop a theoretical understanding of the social processes that define diabetes management in that context. Results: The analysis suggests that although type II diabetes imposes limitations that require adjustment and adaptation, these processes are actively negotiated by rural people within the environmental context to fit the salient social understandings of autonomy and self-reliance. Thus, people normalized self-reliant diabetes management behaviours because this was congruent with the rural culture. Factors that informed the actions of normalization were relationships between participants and health care professionals, support, and access to individual resources. Conclusions: The findings point to ways in which rural self-reliance is conceived as the primary strategy of diabetes management. People face the paradox of engaging with a health care system that at the same time maximizes individual responsibility for health and minimizes the social support by which individuals manage the condition. The emphasis on self-reliance gives some legitimacy to a lack of prevention and chronic care services. Success of diabetes management behaviours is, however, contingent on relative resources. Where there is good primary care, there develops a number of downstream effects including a sense of empowerment to manage difficult rural environmental circumstances. This has particular bearing on health outcomes for people with fewer resources.

The construction of social identity in new nuclear operators : a longitudinal study

Countless studies have stressed the importance of social identity, particularly its role in various organizational outcomes, yet questions remain as to how identities initially develop, shift and change based on the configuration of multiple, pluralistic relationships grounded in an organizational setting. The interactive model of social identity formation has been proposed recently to explain the internalization of shared norms and values – critical in identity formation – has not received empirical examination. We analyzed multiple sources of data from nine nuclear professionals over three years to understand the construction of social identity in new entrants entering an organization. Informed by our data analyses, we found support for the interactive model and that age and level of experience influenced whether they undertook an inductive or deductive route of the group norm and value internalization. This study represents an important contribution to the study of social identity and the process by which identities are formed, particularly under conditions of duress or significant organizational disruption.

Effect of text type on near work-induced contrast adaptation in myopic and emmetropic young adults

Purpose Contrast adaptation has been speculated to be an error signal for emmetropization. Myopic children exhibit higher contrast adaptation than emmetropic children. This study aimed to determine whether contrast adaptation varies with the type of text viewed by emmetropic and myopic young adults. Methods Baseline contrast sensitivity was determined in 25 emmetropic and 25 spectacle-corrected myopic young adults for 0.5, 1.2, 2.7, 4.4, and 6.2 cycles per degree (cpd) horizontal sine wave gratings. The adults spent periods looking at a 6.2 cpd high-contrast horizontal grating and reading lines of English and Chinese text (these texts comprised 1.2 cpd row and 6 cpd stroke frequencies). The effects of these near tasks on contrast sensitivity were determined, with decreases in sensitivity indicating contrast adaptation. Results Contrast adaptation was affected by the near task (F2,672 = 43.0; P < 0.001). Adaptation was greater for the grating task (0.13 ± 0.17 log unit, averaged across all frequencies) than reading tasks, but there was no significant difference between the two reading tasks (English 0.05 ± 0.13 log unit versus Chinese 0.04 ± 0.13 log unit). The myopic group showed significantly greater adaptation (by 0.04, 0.04, and 0.05 log units for English, Chinese, and grating tasks, respectively) than the emmetropic group (F1,48 = 5.0; P = 0.03). Conclusions In young adults, reading Chinese text induced similar contrast adaptation as reading English text. Myopes exhibited greater contrast adaptation than emmetropes. Contrast adaptation, independent of text type, might be associated with myopia development.

Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

A metastatic neuroendocrine anaplastic small cell tumor in a patient with multiple endocrine neoplasia type 1 syndrome : assessment of disease status and response to doxorubicin, cyclophosphamide, etoposide chemotherapy through scintigraphic imaging with 111In-pentetreotide

Extrapulmonary small cell and small cell neuroendocrine tumors of unknown primary site are, in general, aggressive neoplasms with a short median survival. Like small cell lung cancer (SCLC), they often are responsive to chemotherapy and radiotherapy. Small cell lung cancer and well differentiated neuroendocrine carcinomas of the gastrointestinal tract and pancreas tend to express somatostatin receptors. These tumors may be localized in patients by scintigraphic imaging using radiolabeled somatostatin analogues. A patient with an anaplastic neuroendocrine small cell tumor arising on a background of multiple endocrine neoplasia type 1 syndrome is reported. The patient had a known large pancreatic gastrinoma and previously treated parathyroid adenopathy. At presentation, there was small cell cancer throughout the liver and skeleton. Imaging with a radiolabeled somatostatin analogue, 111In- pentetreotide (Mallinckrodt Medical B. V., Petten, Holland), revealed all sites of disease detected by routine biochemical and radiologic methods. After six cycles of chemotherapy with doxorubicin, cyclophosphamide, and etoposide, there was almost complete clearance of the metastatic disease. 111In-pentetreotide scintigraphy revealed uptake consistent with small areas of residual disease in the liver, the abdomen (in mesenteric lymph nodes), and posterior thorax (in a rib). The primary gastrinoma present before the onset of the anaplastic small cell cancer showed no evidence of response to the treatment. The patient remained well for 1 year and then relapsed with brain, lung, liver, and skeletal metastases. Despite an initial response to salvage radiotherapy and chemotherapy with carboplatin and dacarbazine, the patient died 6 months later.

Assessing the suitability of market approach valuation methods for mine and quarry valuations

An area of property valuation that has attracted less attention than other property markets over the past 20 years has been the mining and extractive industries. These operations can range from small operators on leased or private land to multinational companies. Although there are a number of national mining standards that indicate the type of valuation methods that can be adopted for this asset class, these standards do not specify how or when these methods are best suited to particular mine operations. The RICS guidance notes and the draft IVSC guidance notes also advise the various valuations methods that can be used to value mining properties; but, again they do not specify what methods should be applied where and when. One of the methods supported by these standards and guidelines is the market approach. This paper will carry out an analysis of all mine, extractive industry and waste disposal sites sale transactions in Queensland Australia, a major world mining centre, to determine if a market valuation approach such as direct comparison is actually suitable for the valuation of a mine or extractive industry. The analysis will cover the period 1984 to 2011 and covers sale transactions for minerals, petroleum and gas, waste disposal sites, clay, sand and stone. Based on this analysis, the suitability of direct comparison for valuation purposes in this property sector will be tested.

Percutaneous coronary intervention with drug-eluting stents or coronary artery bypass surgery in subjects with type 2 diabetes : evaluation of: Farkouth ME, Domanski M, Sleeper LA, et al. Strategies for multivessel revascularization in patients with diabetes. N Engl J Med 2012;367(25):2375-84, and Contini GA, Nicolini F, Fortuna D, et al. Five-year outcomes of surgical or percutaneous myocardial revascularization in diabetic patients. Int J Cardiol 2012. [Epub ahead of print]

There is debate as to whether percutaneous coronary intervention (PCI) with drug-eluting stents or coronary artery bypass surgery (CABG) is the best procedure for subjects with type 2 diabetes and coronary artery disease requiring revascularization. There is some evidence that following these procedures there is less further revascularization with CABG than PCI in subjects with diabetes. Two recent studies; the FREEDOM (Future Revascularization Evaluation in patients with Diabetes mellitus: Optimal Management of Multivessel Disease) trial, and a trial using a real world diabetic population from a Registry, have shown that the benefits of CABG over PCI in subjects with type 2 diabetes extends to lower rates of death and myocardial infarct, in addition to lower rates of revascularization. However, the rates of stroke may be higher with CABG than PCI with drug-eluting stents in this population. Thus, if CABG is going to be preferred to PCI in subjects with type 2 diabetes and multivessel coronary disease, consideration should be given to how to reduce the rates of stroke with CABG.

Soybean dwarf luteovirus contains the third variant genome type in the luteovirus group

Complementary DNAs covering the entire RNA genome of soybean dwarf luteovirus (SDV) were cloned and sequenced. Computer analysis of the 5861 nucleotide sequence revealed five major open reading frames (ORFs) possessing conservation of sequence and organisation with known luteovirus sequences. Comparative analyses of the genome structure show that SDV shares sequence homology and features of gene organisation with barley yellow dwarf virus (PAV isolate) in the 5' half of the genome, yet is more closely related to potato leafroll virus in its 3' coding regions. In addition, SDV differs from other known luteoviruses in possessing an exceptionally long 3' terminal sequence with no apparent coding capacity. We conclude from these data that the SDV genome represents a third variant genome type in the luteovirus group.

Longitudinal assessment of neuropathy in type 1 diabetes using novel ophthalmic markers (LANDMark) : study design and baseline characteristics

Aims Corneal nerve morphology and corneal sensation threshold have recently been explored as potential surrogate markers for the evaluation of diabetic neuropathy. We present the baseline findings of the ‘Longitudinal Assessment of Neuropathy in type 1 Diabetes using novel ophthalmic Markers’(LANDMark) study. Methods The LANDMark study is a 4-year, two-site, natural history study of three participant groups: type 1 diabetes with neuropathy (T1W), type 1 diabetes without neuropathy (T1WO) and control participants without diabetes or neuropathy. All participants undergo a detailed annual assessment of neuropathy including corneal nerve parameters measured using corneal confocal microscopy and corneal sensitivity measured using non-contact corneal aesthesiometry. Results 76 T1W, 166 T1WO and 154 control participants were enrolled into the study. Corneal sensation threshold (mbars) was significantly higher (i.e. sensitivity was lower) in T1W (1.0 ± 1.1) than T1WO (0.7 ± 0.7) and controls (0.6 ± 0.4) (p < 0.001), with no difference between T1WO and controls. Corneal nerve fibre length was lower in T1W (14.0 ± 6.4 mm/mm2) compared to T1WO (19.1 ± 5.8 mm/mm2) and controls (23.2 ± 6.3 mm/mm2) (p < 0.001). Corneal nerve fibre length was lower in T1WO compared to controls. Conclusions The LANDMark baseline findings confirm a reduction in corneal sensitivity only in Type 1 patients with neuropathy. However, corneal nerve fibre length is reduced even in Type 1 patients without neuropathy with an even greater deficit in Type 1 patients with neuropathy.

Model-predictive control and closed-loop stability considerations for nonlinear plants described by local ARX-type models

In this paper, a model-predictive control (MPC) method is detailed for the control of nonlinear systems with stability considerations. It will be assumed that the plant is described by a local input/output ARX-type model, with the control potentially included in the premise variables, which enables the control of systems that are nonlinear in both the state and control input. Additionally, for the case of set point regulation, a suboptimal controller is derived which has the dual purpose of ensuring stability and enabling finite-iteration termination of the iterative procedure used to solve the nonlinear optimization problem that is used to determine the control signal.