The effect of graded levels of exercise on energy intake and balance in free-living men, consuming their normal diet

Objective: To assess the effect of graded increases in exercised-induced energy expenditure (EE) on appetite, energy intake (EI), total daily EE and body weight in men living in their normal environment and consuming their usual diets. Design: Within-subject, repeated measures design. Six men (mean (s.d.) age 31.0 (5.0) y; weight 75.1 (15.96) kg; height 1.79 (0.10) m; body mass index (BMI) 23.3(2.4) kg/m2), were each studied three times during a 9 day protocol, corresponding to prescriptions of no exercise, (control) (Nex; 0 MJ/day), medium exercise level (Mex; ~1.6 MJ/day) and high exercise level (Hex; ~3.2 MJ/day). On days 1-2 subjects were given a medium fat (MF) maintenance diet (1.6 ´ resting metabolic rate (RMR)). Measurements: On days 3-9 subjects self-recorded dietary intake using a food diary and self-weighed intake. EE was assessed by continual heart rate monitoring, using the modified FLEX method. Subjects' HR (heart rate) was individually calibrated against submaximal VO2 during incremental exercise tests at the beginning and end of each 9 day study period. Respiratory exchange was measured by indirect calorimetry. Subjects completed hourly hunger ratings during waking hours to record subjective sensations of hunger and appetite. Body weight was measured daily. Results: EE amounted to 11.7, 12.9 and 16.8 MJ/day (F(2,10)=48.26; P<0.001 (s.e.d=0.55)) on the Nex, Mex and Hex treatments, respectively. The corresponding values for EI were 11.6, 11.8 and 11.8 MJ/day (F(2,10)=0.10; P=0.910 (s.e.d.=0.10)), respectively. There were no treatment effects on hunger, appetite or body weight, but there was evidence of weight loss on the Hex treatment. Conclusion: Increasing EE did not lead to compensation of EI over 7 days. However, total daily EE tended to decrease over time on the two exercise treatments. Lean men appear able to tolerate a considerable negative energy balance, induced by exercise, over 7 days without invoking compensatory increases in EI.

Use of IP addresses for high rate flooding attack detection

High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Molecular markers of obesity and diabetes

Recently it has been shown that the consumption of a diet high in saturated fat is associated with impaired insulin sensitivity and increased incidence of type 2 diabetes. In contrast, diets that are high in monounsaturated fatty acids (MUFAs) or polyunsaturated fatty acids (PUFAs), especially very long chain n-3 fatty acids (FAs), are protective against disease. However, the molecular mechanisms by which saturated FAs induce the insulin resistance and hyperglycaemia associated with metabolic syndrome and type 2 diabetes are not clearly defined. It is possible that saturated FAs may act through alternative mechanisms compared to MUFA and PUFA to regulate of hepatic gene expression and metabolism. It is proposed that, like MUFA and PUFA, saturated FAs regulate the transcription of target genes. To test this hypothesis, hepatic gene expression analysis was undertaken in a human hepatoma cell line, Huh-7, after exposure to the saturated FA, palmitate. These experiments showed that palmitate is an effective regulator of gene expression for a wide variety of genes. A total of 162 genes were differentially expressed in response to palmitate. These changes not only affected the expression of genes related to nutrient transport and metabolism, they also extend to other cellular functions including, cytoskeletal architecture, cell growth, protein synthesis and oxidative stress response. In addition, this thesis has shown that palmitate exposure altered the expression patterns of several genes that have previously been identified in the literature as markers of risk of disease development, including CVD, hypertension, obesity and type 2 diabetes. The altered gene expression patterns associated with an increased risk of disease include apolipoprotein-B100 (apo-B100), apo-CIII, plasminogen activator inhibitor 1, insulin-like growth factor-I and insulin-like growth factor binding protein 3. This thesis reports the first observation that palmitate directly signals in cultured human hepatocytes to regulate expression of genes involved in energy metabolism as well as other important genes. Prolonged exposure to long-chain saturated FAs reduces glucose phosphorylation and glycogen synthesis in the liver. Decreased glucose metabolism leads to elevated rates of lipolysis, resulting in increased release of free FAs. Free FAs have a negative effect on insulin action on the liver, which in turn results in increased gluconeogenesis and systemic dyslipidaemia. It has been postulated that disruption of glucose transport and insulin secretion by prolonged excessive FA availability might be a non-genetic factor that has contributed to the staggering rise in prevalence of type 2 diabetes. As glucokinase (GK) is a key regulatory enzyme of hepatic glucose metabolism, changes in its activity may alter flux through the glycolytic and de novo lipogenic pathways and result in hyperglycaemia and ultimately insulin resistance. This thesis investigated the effects of saturated FA on the promoter activity of the glycolytic enzyme, GK, and various transcription factors that may influence the regulation of GK gene expression. These experiments have shown that the saturated FA, palmitate, is capable of decreasing GK promoter activity. In addition, quantitative real-time PCR has shown that palmitate incubation may also regulate GK gene expression through a known FA sensitive transcription factor, sterol regulatory element binding protein-1c (SREBP-1c), which upregulates GK transcription. To parallel the investigations into the mechanisms of FA molecular signalling, further studies of the effect of FAs on metabolic pathway flux were performed. Although certain FAs reduce SREBP-1c transcription in vitro, it is unclear whether this will result in decreased GK activity in vivo where positive effectors of SREBP-1c such as insulin are also present. Under these conditions, it is uncertain if the inhibitory effects of FAs would be overcome by insulin. The effects of a combination of FAs, insulin and glucose on glucose phosphorylation and metabolism in cultured primary rat hepatocytes at concentrations that mimic those in the portal circulation after a meal was examined. It was found that total GK activity was unaffected by an increased concentration of insulin, but palmitate and eicosapentaenoic acid significantly lowered total GK activity in the presence of insulin. Despite the fact that total GK enzyme activity was reduced in response to FA incubation, GK enzyme translocation from the inactive, nuclear bound, to active, cytoplasmic state was unaffected. Interestingly, none of the FAs tested inhibited glucose phosphorylation or the rate of glycolysis when insulin is present. These results suggest that in the presence of insulin the levels of the active, unbound cytoplasmic GK are sufficient to buffer a slight decrease in GK enzyme activity and decreased promoter activity caused by FA exposure. Although a high fat diet has been associated with impaired hepatic glucose metabolism, there is no evidence from this thesis that FAs themselves directly modulate flux through the glycolytic pathway in isolated primary hepatocytes when insulin is also present. Therefore, although FA affected expression of a wide range of genes, including GK, this did not affect glycolytic flux in the presence of insulin. However, it may be possible that a saturated FA-induced decrease in GK enzyme activity when combined with the onset of insulin resistance may promote the dys-regulation of glucose homeostasis and the subsequent development of hyperglycaemia, metabolic syndrome and type 2 diabetes.

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.

Acoustic keyword spotting in speech with applications to data mining

Keyword Spotting is the task of detecting keywords of interest within continu- ous speech. The applications of this technology range from call centre dialogue systems to covert speech surveillance devices. Keyword spotting is particularly well suited to data mining tasks such as real-time keyword monitoring and unre- stricted vocabulary audio document indexing. However, to date, many keyword spotting approaches have su®ered from poor detection rates, high false alarm rates, or slow execution times, thus reducing their commercial viability. This work investigates the application of keyword spotting to data mining tasks. The thesis makes a number of major contributions to the ¯eld of keyword spotting. The ¯rst major contribution is the development of a novel keyword veri¯cation method named Cohort Word Veri¯cation. This method combines high level lin- guistic information with cohort-based veri¯cation techniques to obtain dramatic improvements in veri¯cation performance, in particular for the problematic short duration target word class. The second major contribution is the development of a novel audio document indexing technique named Dynamic Match Lattice Spotting. This technique aug- ments lattice-based audio indexing principles with dynamic sequence matching techniques to provide robustness to erroneous lattice realisations. The resulting algorithm obtains signi¯cant improvement in detection rate over lattice-based audio document indexing while still maintaining extremely fast search speeds. The third major contribution is the study of multiple veri¯er fusion for the task of keyword veri¯cation. The reported experiments demonstrate that substantial improvements in veri¯cation performance can be obtained through the fusion of multiple keyword veri¯ers. The research focuses on combinations of speech background model based veri¯ers and cohort word veri¯ers. The ¯nal major contribution is a comprehensive study of the e®ects of limited training data for keyword spotting. This study is performed with consideration as to how these e®ects impact the immediate development and deployment of speech technologies for non-English languages.

Safety-restraint use rate as function of law enforcement and other factors : preliminary analysis

Persistent use of safety restraints prevents deaths and reduces the severity and number of injuries resulting from motor vehicle crashes. However, safety-restraint use rates in the United States have been below those of other nations with safety-restraint enforcement laws. With a better understanding of the relationship between safety-restraint law enforcement and safety-restraint use, programs can be implemented to decrease the number of deaths and injuries resulting from motor vehicle crashes. Does safety-restraint use increase as enforcement increases? Do motorists increase their safety-restraint use in response to the general presence of law enforcement or to targeted law enforcement efforts? Does a relationship between enforcement and restraint use exist at the countywide level? A logistic regression model was estimated by using county-level safety-restraint use data and traffic citation statistics collected in 13 counties within the state of Florida in 1997. The model results suggest that safety-restraint use is positively correlated with enforcement intensity, is negatively correlated with safety-restraint enforcement coverage (in lanemiles of enforcement coverage), and is greater in urban than rural areas. The quantification of these relationships may assist Florida and other law enforcement agencies in raising safety-restraint use rates by allocating limited funds more efficiently either by allocating additional time for enforcement activities of the existing force or by increasing enforcement staff. In addition, the research supports a commonsense notion that enforcement activities do result in behavioral response.

Nitrogen fertilizer rate management as a nitrous oxide mitigation strategy: Development of a nitrous oxide emission reduction protocol (NERP)

Nitrous oxide (N2O) is a potent agricultural greenhouse gas (GHG). More than 50% of the global anthropogenic N2O flux is attributable to emissions from soil, primarily due to large fertilizer nitrogen (N) applications to corn and other non-leguminous crops. Quantification of the trade–offs between N2O emissions, fertilizer N rate, and crop yield is an essential requirement for informing management strategies aiming to reduce the agricultural sector GHG burden, without compromising productivity and producer livelihood. There is currently great interest in developing and implementing agricultural GHG reduction offset projects for inclusion within carbon offset markets. Nitrous oxide, with a global warming potential (GWP) of 298, is a major target for these endeavours due to the high payback associated with its emission prevention. In this paper we use robust quantitative relationships between fertilizer N rate and N2O emissions, along with a recently developed approach for determining economically profitable N rates for optimized crop yield, to propose a simple, transparent, and robust N2O emission reduction protocol (NERP) for generating agricultural GHG emission reduction credits. This NERP has the advantage of providing an economic and environmental incentive for producers and other stakeholders, necessary requirements in the implementation of agricultural offset projects.

Pandemic (H1N1) 2009 Influenza Outbreak in Australia: Impact on Emergency Departments.

Executive summary Objective: The aims of this study were to identify the impact of Pandemic (H1N1) 2009 Influenza on Australian Emergency Departments (EDs) and their staff, and to inform planning, preparedness, and response management arrangements for future pandemics, as well as managing infectious patients presenting to EDs in everyday practice. Methods This study involved three elements: 1. The first element of the study was an examination of published material including published statistics. Standard literature research methods were used to identify relevant published articles. In addition, data about ED demand was obtained from Australian Government Department of Health and Ageing (DoHA) publications, with several state health departments providing more detailed data. 2. The second element of the study was a survey of Directors of Emergency Medicine identified with the assistance of the Australasian College for Emergency Medicine (ACEM). This survey retrieved data about demand for ED services and elicited qualitative comments on the impact of the pandemic on ED management. 3. The third element of the study was a survey of ED staff. A questionnaire was emailed to members of three professional colleges—the ACEM; the Australian College of Emergency Nursing (ACEN); and the College of Emergency Nursing Australasia (CENA). The overall response rate for the survey was 18.4%, with 618 usable responses from 3355 distributed questionnaires. Topics covered by the survey included ED conditions during the (H1N1) 2009 influenza pandemic; information received about Pandemic (H1N1) 2009 Influenza; pandemic plans; the impact of the pandemic on ED staff with respect to stress; illness prevention measures; support received from others in work role; staff and others’ illness during the pandemic; other factors causing ED staff to miss work during the pandemic; and vaccination against Pandemic (H1N1) 2009 Influenza. Both qualitative and quantitative data were collected and analysed. Results: The results obtained from Directors of Emergency Medicine quantifying the impact of the pandemic were too limited for interpretation. Data sourced from health departments and published sources demonstrated an increase in influenza-like illness (ILI) presentations of between one and a half and three times the normal level of presentations of ILIs. Directors of Emergency Medicine reported a reasonable level of preparation for the pandemic, with most reporting the use of pandemic plans that translated into relatively effective operational infection control responses. Directors reported a highly significant impact on EDs and their staff from the pandemic. Growth in demand and related ED congestion were highly significant factors causing distress within the departments. Most (64%) respondents established a ‘flu clinic’ either as part of Pandemic (H1N1) 2009 Influenza Outbreak in Australia: Impact on Emergency Departments. the ED operations or external to it. They did not note a significantly higher rate of sick leave than usual. Responses relating to the impact on staff were proportional to the size of the colleges. Most respondents felt strongly that Pandemic (H1N1) 2009 Influenza had a significant impact on demand in their ED, with most patients having low levels of clinical urgency. Most respondents felt that the pandemic had a negative impact on the care of other patients, and 94% revealed some increase in stress due to lack of space for patients, increased demand, and filling staff deficits. Levels of concern about themselves or their family members contracting the illness were less significant than expected. Nurses displayed significantly higher levels of stress overall, particularly in relation to skill-mix requirements, lack of supplies and equipment, and patient and patients’ family aggression. More than one-third of respondents became ill with an ILI. Whilst respondents themselves reported taking low levels of sick leave, respondents cited difficulties with replacing absent staff. Ranked from highest to lowest, respondents gained useful support from ED colleagues, ED administration, their hospital occupational health department, hospital administration, professional colleges, state health department, and their unions. Respondents were generally positive about the information they received overall; however, the volume of information was considered excessive and sometimes inconsistent. The media was criticised as scaremongering and sensationalist and as being the cause of many unnecessary presentations to EDs. Of concern to the investigators was that a large proportion (43%) of respondents did not know whether a pandemic plan existed for their department or hospital. A small number of staff reported being redeployed from their usual workplace for personal risk factors or operational reasons. As at the time of survey (29 October –18 December 2009), 26% of ED staff reported being vaccinated against Pandemic (H1N1) 2009 Influenza. Of those not vaccinated, half indicated they would ‘definitely’ or ‘probably’ not get vaccinated, with the main reasons being the vaccine was ‘rushed into production’, ‘not properly tested’, ‘came out too late’, or not needed due to prior infection or exposure, or due to the mildness of the disease. Conclusion: Pandemic (H1N1) 2009 Influenza had a significant impact on Australian Emergency Departments. The pandemic exposed problems in existing plans, particularly a lack of guidelines, general information overload, and confusion due to the lack of a single authoritative information source. Of concern was the high proportion of respondents who did not know if their hospital or department had a pandemic plan. Nationally, the pandemic communication strategy needs a detailed review, with more engagement with media networks to encourage responsible and consistent reporting. Also of concern was the low level of immunisation, and the low level of intention to accept vaccination. This is a problem seen in many previous studies relating to seasonal influenza and health care workers. The design of EDs needs to be addressed to better manage infectious patients. Significant workforce issues were confronted in this pandemic, including maintaining appropriate staffing levels; staff exposure to illness; access to, and appropriate use of, personal protective equipment (PPE); and the difficulties associated with working in PPE for prolonged periods. An administrative issue of note was the reporting requirement, which created considerable additional stress for staff within EDs. Peer and local support strategies helped ensure staff felt their needs were provided for, creating resilience, dependability, and stability in the ED workforce. Policies regarding the establishment of flu clinics need to be reviewed. The ability to create surge capacity within EDs by considering staffing, equipment, physical space, and stores is of primary importance for future pandemics.

New criteria for evaluating methods of identifying hot spots

Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

Forecasting crashes at the planning level: Simultaneous negative binomial crash model applied in Tucson, Arizona

At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

Across-country comparisons of selected infant and young child feeding indicators and associated factors in four South Asian countries

Background: Information on infant and young child feeding is widely available in Demographic and Health Surveys and National Family Health Surveys for countries in South Asia; however, infant and young child feeding indicators from these surveys have not been compared between countries in the region. Objective. To compare the key indicators of breastfeeding and complementary feeding and their determinants in children under 24 months of age between four South Asian countries. Methods: We selected data sets from the Bangladesh Demographic and Health Survey 2004, the India National Family Health Survey (NFHS-03) 2005–06, the Nepal Demographic and Health Survey 2006, and the Sri Lanka 2000 Demographic and Health Survey. Infant feeding indicators were estimated according to the key World Health Organization indicators. Results: Exclusive breastfeeding rates were 42.5% in Bangladesh, 46.4% in India, and 53.1% in Nepal. The rate of full breastfeeding ranged between 60.6% and 73.9%. There were no factors consistently associated with the rate of no exclusive breastfeeding across countries. Utilization of health services (more antenatal clinic visits) was associated with higher rates of exclusive breastfeeding in India but lower rates in Nepal. Delivery at a health facility was a negative determinant of exclusive breastfeeding in India. Postnatal contacts by Public Health Midwives were a positive factor in Sri Lanka. A considerable proportion of infants under 6 months of age had been given plain water, juices, or other nonmilk liquids. The rate of timely first suckling ranged from 23.5% in India to 56.3% in Sri Lanka. Delivery by cesarean section was found to be a consistent negative factor that delayed initiation of breastfeeding. Nepal reported the lowest bottle-feeding rate of 3.5%. Socioeconomically privileged mothers were found to have higher bottlefeeding rates in most countries. Conclusions: Infant and young child feeding practices in the South Asia region have not reached the expected levels that are required to achieve a substantial reduction in child mortality. The countries with lower rates of exclusive breastfeeding have a great potential to improve the rates by preventing infants from receiving water and water-based or other nonmilk liquids during the first 6 months of life.