Plasmodium vivax malaria incidence over time and its association with temperature and rainfall in four counties of Yunnan Province, China

Background Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China. Methods Plasmodium vivax malaria surveillance data (1991–2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence. Results There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas. Conclusions The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.

Higher-order non-linear analysis of steel structures. Part I : elastic second-order formulation

This paper presents a higher-order beam-column formulation that can capture the geometrically non-linear behaviour of steel framed structures which contain a multiplicity of slender members. Despite advances in computational frame software, analyses of large frames can still be problematic from a numerical standpoint and so the intent of the paper is to fulfil a need for versatile, reliable and efficient non-linear analysis of general steel framed structures with very many members. Following a comprehensive review of numerical frame analysis techniques, a fourth-order element is derived and implemented in an updated Lagrangian formulation, and it is able to predict flexural buckling, snap-through buckling and large displacement post-buckling behaviour of typical structures whose responses have been reported by independent researchers. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. The higher-order element forms a basis for augmenting the geometrically non-linear approach with material non-linearity through the refined plastic hinge methodology described in the companion paper.

Higher-order non-linear analysis of steel structures. Part II : refined plastic hinge formulation

In the companion paper, a fourth-order element formulation in an updated Lagrangian formulation was presented to handle geometric non-linearities. The formulation of the present paper extends this to include material non-linearity by proposing a refined plastic hinge approach to analyse large steel framed structures with many members, for which contemporary algorithms based on the plastic zone approach can be problematic computationally. This concept is an advancement of conventional plastic hinge approaches, as the refined plastic hinge technique allows for gradual yielding, being recognized as distributed plasticity across the element section, a condition of full plasticity, as well as including strain hardening. It is founded on interaction yield surfaces specified analytically in terms of force resultants, and achieves accurate and rapid convergence for large frames for which geometric and material non-linearity are significant. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. In addition to the numerical efficiency, the present versatile approach is able to capture different kinds of material and geometric non-linearities on general applications of steel structures, and thereby it offers an efficacious and accurate means of assessing non-linear behaviour of the structures for engineering practice.

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.

Capturing complex, non-linear team behaviours during competitive football performance

This study investigated changes in the complexity (magnitude and structure of variability) of the collective behaviours of association football teams during competitive performance. Raw positional data from an entire competitive match between two professional teams were obtained with the ProZone® tracking system. Five compound positional variables were used to investigate the collective patterns of performance of each team including: surface area, stretch index, team length, team width, and geometrical centre. Analyses involve the coefficient of variation (%CV) and approximate entropy (ApEn), as well as the linear association between both parameters. Collective measures successfully captured the idiosyncratic behaviours of each team and their variations across the six time periods of the match. Key events such as goals scored and game breaks (such as half time and full time) seemed to influence the collective patterns of performance. While ApEn values significantly decreased during each half, the %CV increased. Teams seem to become more regular and predictable, but with increased magnitudes of variation in their organisational shape over the natural course of a match.

Local inter-session variability modelling for object classification

Object classification is plagued by the issue of session variation. Session variation describes any variation that makes one instance of an object look different to another, for instance due to pose or illumination variation. Recent work in the challenging task of face verification has shown that session variability modelling provides a mechanism to overcome some of these limitations. However, for computer vision purposes, it has only been applied in the limited setting of face verification. In this paper we propose a local region based intersession variability (ISV) modelling approach, and apply it to challenging real-world data. We propose a region based session variability modelling approach so that local session variations can be modelled, termed Local ISV. We then demonstrate the efficacy of this technique on a challenging real-world fish image database which includes images taken underwater, providing significant real-world session variations. This Local ISV approach provides a relative performance improvement of, on average, 23% on the challenging MOBIO, Multi-PIE and SCface face databases. It also provides a relative performance improvement of 35% on our challenging fish image dataset.

Comparison of high level FPGA hardware design for solving tri-diagonal linear systems

Reconfigurable computing devices can increase the performance of compute intensive algorithms by implementing application specific co-processor architectures. The power cost for this performance gain is often an order of magnitude less than that of modern CPUs and GPUs. Exploiting the potential of reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) is typically a complex and tedious hardware engineering task. Re- cently the major FPGA vendors (Altera, and Xilinx) have released their own high-level design tools, which have great potential for rapid development of FPGA based custom accelerators. In this paper, we will evaluate Altera’s OpenCL Software Development Kit, and Xilinx’s Vivado High Level Sythesis tool. These tools will be compared for their per- formance, logic utilisation, and ease of development for the test case of a Tri-diagonal linear system solver.

Vulnerability and damage analysis of reinforced concrete framed buildings subjected to near field blast events

Terrorists usually target high occupancy iconic and public buildings using vehicle borne incendiary devices in order to claim a maximum number of lives and cause extensive damage to public property. While initial casualties are due to direct shock by the explosion, collapse of structural elements may extensively increase the total figure. Most of these buildings have been or are built without consideration of their vulnerability to such events. Therefore, the vulnerability and residual capacity assessment of buildings to deliberately exploded bombs is important to provide mitigation strategies to protect the buildings' occupants and the property. Explosive loads and their effects on a building have therefore attracted significant attention in the recent past. Comprehensive and economical design strategies must be developed for future construction. This research investigates the response and damage of reinforced concrete (RC) framed buildings together with their load bearing key structural components to a near field blast event. Finite element method (FEM) based analysis was used to investigate the structural framing system and components for global stability, followed by a rigorous analysis of key structural components for damage evaluation using the codes SAP2000 and LS DYNA respectively. The research involved four important areas in structural engineering. They are blast load determination, numerical modelling with FEM techniques, material performance under high strain rate and non-linear dynamic structural analysis. The response and damage of a RC framed building for different blast load scenarios were investigated. The blast influence region for a two dimensional RC frame was investigated for different load conditions and identified the critical region for each loading case. Two types of design methods are recommended for RC columns to provide superior residual capacities. They are RC columns detailing with multi-layer steel reinforcement cages and a composite columns including a central structural steel core. These are to provide post blast gravity load resisting capacity compared to typical RC column against a catastrophic collapse. Overall, this research broadens the current knowledge of blast and residual capacity analysis of RC framed structures and recommends methods to evaluate and mitigate blast impact on key elements of multi-storey buildings.

Australian baby boomers switched to more environment friendly modes of transport during the global financial crisis

The global financial crisis (GFC) in 2008 rocked local, regional, and state economies throughout the world. Several intermediate outcomes of the GFC have been well documented in the literature including loss of jobs and reduced income. Relatively little research has, however, examined the impacts of the GFC on individual level travel behaviour change. To address this shortcoming, HABITAT panel data were employed to estimate a multinomial logit model to examine mode switching behaviour between 2007 (pre-GFC) and 2009 (post-GFC) of a baby boomers cohort in Brisbane, Australia—a city within a developed country that has been on many metrics the least affected by the GFC. In addition, a Poisson regression model was estimated to model the number of trips made by individuals in 2007, 2008, and 2009. The South East Queensland Travel Survey datasets were used to develop this model. Four linear regression models were estimated to assess the effects of the GFC on time allocated to travel during a day: one for each of the three travel modes including public transport, active transport, less environmentally friendly transport; and an overall travel time model irrespective of mode. The results reveal that individuals were more likely to switch to public transport who lost their job or whose income reduced between 2007 and 2009. Individuals also made significantly fewer trips in 2008 and 2009 compared to 2007. Individuals spent significantly less time using less environmentally friendly transport but more time using public transport in 2009. Baby boomers switched to more environmentally friendly travel modes during the GFC.

Detecting and Analyzing Linear Structures in Biomedical Images : A Case Study Using Corneal Nerve Fibers

Diabetic peripheral neuropathy (DPN) is one of the most common long-term complications of diabetes. The accurate detection and quantification of DPN are important for defining at-risk patients, anticipating deterioration, and assessing new therapies. Current methods of detecting and quantifying DPN, such as neurophysiology, lack sensitivity, require expert assessment and focus primarily on large nerve fibers. However, the earliest damage to nerve fibers in diabetic neuropathy is to the small nerve fibers. At present, small nerve fiber damage is currently assessed using skin/nerve biopsy; both are invasive technique and are not suitable for repeated investigations.

Transforming morning to afternoon using linear regression techniques

Visual localization in outdoor environments is often hampered by the natural variation in appearance caused by such things as weather phenomena, diurnal fluctuations in lighting, and seasonal changes. Such changes are global across an environment and, in the case of global light changes and seasonal variation, the change in appearance occurs in a regular, cyclic manner. Visual localization could be greatly improved if it were possible to predict the appearance of a particular location at a particular time, based on the appearance of the location in the past and knowledge of the nature of appearance change over time. In this paper, we investigate whether global appearance changes in an environment can be learned sufficiently to improve visual localization performance. We use time of day as a test case, and generate transformations between morning and afternoon using sample images from a training set. We demonstrate the learned transformation can be generalized from training data and show the resulting visual localization on a test set is improved relative to raw image comparison. The improvement in localization remains when the area is revisited several weeks later.

Wide area controls for transient and dynamic stability enhancement

This paper presents a study done into the effectiveness of using local acceleration measurements vs. remote angle measurements in providing stabilising control via SVCs following large disturbances. The system studied was an analogue of the Queensland-New South Wales Interconnection (QNI) and involved the control of an existing Static Var Compensators (SVC) at Sydney West. This study is placed in the context of wide area controls for large systems using aggregated models for groups of machines.

UV Photodissociation Action Spectroscopy of Haloanilinium Ions in a Linear Quadrupole Ion Trap Mass Spectrometer

UV-vis photodissociation action spectroscopy is becoming increasingly prevalent because of advances in, and commercial availability of, ion trapping technologies and tunable laser sources. This study outlines in detail an instrumental arrangement, combining a commercial ion-trap mass spectrometer and tunable nanosecond pulsed laser source, for performing fully automated photodissociation action spectroscopy on gas-phase ions. The components of the instrumentation are outlined, including the optical and electronic interfacing, in addition to the control software for automating the experiment and performing online analysis of the spectra. To demonstrate the utility of this ensemble, the photodissociation action spectra of 4-chloroanilinium, 4-bromoanilinium, and 4-iodoanilinium cations are presented and discussed. Multiple photoproducts are detected in each case and the photoproduct yields are followed as a function of laser wavelength. It is shown that the wavelength-dependent partitioning of the halide loss, H loss, and NH3 loss channels can be broadly rationalized in terms of the relative carbon-halide bond dissociation energies and processes of energy redistribution. The photodissociation action spectrum of (phenyl)Ag-2 (+) is compared with a literature spectrum as a further benchmark.

Entrenchment of GIS technology for enterprise solutions in Maryland's state and local government

Beginning in 1974, the State of Maryland created spatial databases under the MAGI (Maryland's Automated Geographic Information) system. Since that early GIS, other state and local agencies have begun GISs covering a range of applications from critical lands inventories to cadastral mapping. In 1992, state agencies, local agencies, universities, and businesses began a series of GIS coordination activities, resulting in the formation of the Maryland Local Geographic Information Committee and the Maryland State Government Geographic Information Coordinating Committee. GIS activities and system installations can be found in 22 counties plus Baltimore City, and most state agencies. Maryland's decision makers rely on a variety of GIS reports and products to conduct business and to communicate complex issues more effectively. This paper presents the status of Maryland's GIS applications for local and state decision making.

Metacognitive instruction : global and local shifts in considering listening input

A key shift of thinking for effective learning and teaching of listening input has been seen and organized in education locally and globally. This study has probed whether metacognitive instruction through a pedagogical cycle shifts high-intermediate students' English language learning and English as a second language (ESL) teacher's teaching focus on listening input. Twenty male Iranian students with an age range of 18 to 24 received a guided methodology including metacognitive strategies (planning, monitoring, and evaluation) for a period of three months. This study has used the strategies and probed the importance of metacognitive instruction through interviewing both the teacher and the students. The results have shown that metacognitive instruction helped both the ESL teacher's and the students' shift of thinking about teaching and learning listening input. This key shift of thinking has implications globally and locally for classroom practices of listening input.