Assessing the impact of transit and personal characteristics on mode choice of TOD users

Comparison are required to understand transport benefits of Transit Oriented Developments (TODs). Mode shares of TOD users need to be understood. Accurate travel demand models for TODs are needed.

The influence of underreported crashes on hotspot identification

Hot spot identification (HSID) plays a significant role in improving the safety of transportation networks. Numerous HSID methods have been proposed, developed, and evaluated in the literature. The vast majority of HSID methods reported and evaluated in the literature assume that crash data are complete, reliable, and accurate. Crash under-reporting, however, has long been recognized as a threat to the accuracy and completeness of historical traffic crash records. As a natural continuation of prior studies, the paper evaluates the influence that under-reported crashes exert on HSID methods. To conduct the evaluation, five groups of data gathered from Arizona Department of Transportation (ADOT) over the course of three years are adjusted to account for fifteen different assumed levels of under-reporting. Three identification methods are evaluated: simple ranking (SR), empirical Bayes (EB) and full Bayes (FB). Various threshold levels for establishing hotspots are explored. Finally, two evaluation criteria are compared across HSID methods. The results illustrate that the identification bias—the ability to correctly identify at risk sites--under-reporting is influenced by the degree of under-reporting. Comparatively speaking, crash under-reporting has the largest influence on the FB method and the least influence on the SR method. Additionally, the impact is positively related to the percentage of the under-reported PDO crashes and inversely related to the percentage of the under-reported injury crashes. This finding is significant because it reveals that despite PDO crashes being least severe and costly, they have the most significant influence on the accuracy of HSID.

Mesenchymal stem cells

Cell based therapies as they apply to tissue engineering and regenerative medicine, require cells capable of self renewal and differentiation, and a prerequisite is to be able to prepare an effective dose of ex vivo expanded cells for autologous transplants. The in vivo identification of a source of physiologically relevant cell types suitable for cell therapies therefore figures as an integral part of tissue engineering. Stem cells serve as a reserve for biological repair, having the potential to differentiate into a number of specialised cell types within the body; they therefore represent the most useful candidates for cell based therapies. The primary goal of stem cell research is to produce cells that are both patient specific, as well as having properties suitable for the specific conditions for which they are intended to remedy. From a purely scientific perspective, stem cells allow scientists to gain a deeper understanding of developmental biology and regenerative therapies. Stem cells have acquired a number of uses for applications in regenerative medicine, immunotherapy, gene therapy, but it is in the area of tissue engineering that they generate most excitement, primarily as a result of their capacity for self-renewal and pluripotency. A unique feature of stem cells is their ability to maintain an uncommitted quiescent state in vivo and then, once triggered by conditions such as disease, injury or natural wear or tear, serve as a reservoir and natural support system to replenish lost cells. Although these cells retain the plasticity to differentiate into various tissues, being able to control this differentiation process is still one of the biggest challenges facing stem cell research. In an effort to harness the potential of these cells a number of studies have been conducted using both embryonic/foetal and adult stem cells. The use of embryonic stem cells (ESC) have been hampered by strong ethical and political concerns, this despite their perceived versatility due to their pluripotency. Ethical issues aside, other concerns raised with ESCs relates to the possibility of tumorigenesis, immune rejection and complications with immunosuppressive therapies, all of which adds layers of complications to the application ESC in research and which has led to the search for alternative sources for stem cells. The adult tissues in higher organisms harbours cells, termed adult stem cells, and these cells are reminiscent of unprogrammed stem cells. A number of sources of adult stem cells have been described. Bone marrow is by far the most accessible source of two potent populations of adult stem cells, namely haematopoietic stem cells (HSCs) and bone marrow mesenchymal stem cells (BMSCs). Autologously harvested adult stem cells can, in contrast to embryonic stem cells, readily be used in autografts, since immune rejection is not an issue; and their use in scientific research has not attracted the ethical concerns which have been the case with embryonic stem cells. The major limitation to their use, however, is the fact that adult stem cells are exceedingly rare in most tissues. This fact makes identifying and isolating these cells problematic; bone marrow being perhaps the only notable exception. Unlike the case of HSCs, there are as yet no rigorous criteria for characterizing MSCs. Changing acuity about the pluripotency of MSCs in recent studies has expanded their potential application; however, the underlying molecular pathways which impart the features distinctive to MSCs remain elusive. Furthermore, the sparse in vivo distribution of these cells imposes a clear limitation to their study in vitro. Also, when MSCs are cultured in vitro, there is a loss of the in vivo microenvironment, resulting in a progressive decline in proliferation potential and multipotentiality. This is further exacerbated with increased passage numbers in culture, characterized by the onset of senescence related changes. As a consequence, it is necessary to establish protocols for generating large numbers of MSCs but without affecting their differentiation potential. MSCs are capable of differentiating into mesenchymal tissue lineages, including bone, cartilage, fat, tendon, muscle, and marrow stroma. Recent findings indicate that adult bone marrow may also contain cells that can differentiate into the mature, nonhematopoietic cells of a number of tissues, including cells of the liver, kidney, lung, skin, gastrointestinal tract, and myocytes of heart and skeletal muscle. MSCs can readily be expanded in vitro and can be genetically modified by viral vectors and be induced to differentiate into specific cell lineages by changing the microenvironment–properties which makes these cells ideal vehicles for cellular gene therapy. MSCs can also exert profound immunosuppressive effects via modulation of both cellular and innate immune pathways, and this property allows them to overcome the issue of immune rejection. Despite the many attractive features associated with MSCs, there are still many hurdles to overcome before these cells are readily available for use in clinical applications. The main concern relates to in vivo characterization and identification of MSCs. The lack of a universal biomarker, sparse in vivo distribution, and a steady age related decline in their numbers, makes it an obvious need to decipher the reprogramming pathways and critical molecular players which govern the characteristics unique to MSCs. This book presents a comprehensive insight into the biology of adult stem cells and their utility in current regeneration therapies. The adult stem cell populations reviewed in this book include bone marrow derived MSCs, adipose derived stem cells (ASCs), umbilical cord blood stem cells, and placental stem cells. The features such as MSC circulation and trafficking, neuroprotective properties, and the nurturing roles and differentiation potential of multiple lineages have been discussed in details. In terms of therapeutic applications, the strengths of MSCs have been presented and their roles in disease treatments such as osteoarthritis, Huntington’s disease, periodontal regeneration, and pancreatic islet transplantation have been discussed. An analysis comparing osteoblast differentiation of umbilical cord blood stem cells and MSCs has been reviewed, as has a comparison of human placental stem cells and ASCs, in terms of isolation, identification and therapeutic applications of ASC in bone, cartilage regeneration, as well as myocardial regeneration. It is my sincere hope that this book will update the reader as to the research progress of MSC biology and potential use of these cells in clinical applications. It will be the best reward to all contributors of this book, if their efforts herein may in some way help the readers in any part of their study, research, and career development.

Genome-wide identification and expression analysis of the NF-Y family of transcription factors in Triticum aestivum

Nuclear Factor Y (NF-Y) is a trimeric complex that binds to the CCAAT box, a ubiquitous eukaryotic promoter element. The three subunits NF-YA, NF-YB and NF-YC are represented by single genes in yeast and mammals. However, in model plant species (Arabidopsis and rice) multiple genes encode each subunit providing the impetus for the investigation of the NF-Y transcription factor family in wheat. A total of 37 NF-Y and Dr1 genes (10 NF-YA, 11 NF-YB, 14 NF-YC and 2 Dr1) in Triticum aestivum were identified in the global DNA databases by computational analysis in this study. Each of the wheat NF-Y subunit families could be further divided into 4-5 clades based on their conserved core region sequences. Several conserved motifs outside of the NF-Y core regions were also identified by comparison of NF-Y members from wheat, rice and Arabidopsis. Quantitative RT-PCR analysis revealed that some of the wheat NF-Y genes were expressed ubiquitously, while others were expressed in an organ-specific manner. In particular, each TaNF-Y subunit family had members that were expressed predominantly in the endosperm. The expression of nine NF-Y and two Dr1 genes in wheat leaves appeared to be responsive to drought stress. Three of these genes were up-regulated under drought conditions, indicating that these members of the NF-Y and Dr1 families are potentially involved in plant drought adaptation. The combined expression and phylogenetic analyses revealed that members within the same phylogenetic clade generally shared a similar expression profile. Organ-specific expression and differential response to drought indicate a plant-specific biological role for various members of this transcription factor family.

Investigation into travel modes of TOD users : impacts of personal and transit characteristics

Transit Oriented Developments (TODs) are often designed to promote the use of sustainable modes of transport and reduce car usage. This paper investigates the effect of personal and transit characteristics on travel choices of TOD users. Binary logistic regression models were developed to determine the probability of choosing sustainable modes of transport including walking, cycling and public transport. Kelvin Grove Urban Village (KGUV) located in Brisbane, Australia was chosen as case study TOD. The modal splits for employees, students, shoppers and residents showed that 47% of employees, 84% of students, 71% of shoppers and 56% of residents used sustainable modes of transport.

Design for inspiration : children, personal connections and educational technology

The project is working towards building an understanding of the personal interests and experiences of children with the aim of designing appropriate, usable and, most importantly, inspirational educational technology. kidprobe, an adaptation of the technology probe concept, has been used as a lightweight method of gaining contextual information about children's interactions with 'fun' technology. kidprobe has produced design inspiration which focuses primarily on the social and emotional connections children made. The use of kidprobe has generated some important ideas for improving the use of probes with children. It is an important first step in understanding how to effectively adapt probing techniques to inspire the design of technology for children.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Modeling object identification and tracking errors on image-based safety assessment of earthmoving operations

Object identification and tracking have become critical for automated on-site construction safety assessment. The primary objective of this paper is to present the development of a testbed to analyze the impact of object identification and tracking errors caused by data collection devices and algorithms used for safety assessment. The testbed models workspaces for earthmoving operations and simulates safety-related violations, including speed limit violations, access violations to dangerous areas, and close proximity violations between heavy machinery. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of device and algorithm errors were investigated for safety planning purposes.

Fast content-based file type identification

Digital forensic examiners often need to identify the type of a file or file fragment based only on the content of the file. Content-based file type identification schemes typically use a byte frequency distribution with statistical machine learning to classify file types. Most algorithms analyze the entire file content to obtain the byte frequency distribution, a technique that is inefficient and time consuming. This paper proposes two techniques for reducing the classification time. The first technique selects a subset of features based on the frequency of occurrence. The second speeds classification by sampling several blocks from the file. Experimental results demonstrate that up to a fifteen-fold reduction in file size analysis time can be achieved with limited impact on accuracy.

Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Probabilistic subgroup identification using Bayesian finite mixture modelling : a case study in Parkinson’s disease phenotype identification

This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).

Image-based safety assessment : automated spatial safety risk identification of earthmoving and surface mining activities

This paper presents an automated image‐based safety assessment method for earthmoving and surface mining activities. The literature review revealed the possible causes of accidents on earthmoving operations, investigated the spatial risk factors of these types of accident, and identified spatial data needs for automated safety assessment based on current safety regulations. Image‐based data collection devices and algorithms for safety assessment were then evaluated. Analysis methods and rules for monitoring safety violations were also discussed. The experimental results showed that the safety assessment method collected spatial data using stereo vision cameras, applied object identification and tracking algorithms, and finally utilized identified and tracked object information for safety decision making.

Changing personal epistemologies in early childhood pre-service teachers using an integrated teaching program

This study investigated changes in pre-service teachers’ personal epistemologies as they engaged in an integrated teaching program. Personal epistemology refers to individual beliefs about the nature of knowing and knowledge and has been shown to influence teaching practice. An integrated approach to teaching, based on both an implicit and explicit focus on personal epistemology, was developed by an academic team within a Bachelor of Education (Early Childhood). The teaching program integrated content across four units of study, modelling personal epistemologies implicitly through collaborative reflexive practice. The students were also required to engage in explicit reflections on their personal epistemologies. Quantitative measures of personal epistemology were collected at the beginning and end of the semester using the Epistemological Beliefs Survey (EBS) to assess changes across the teaching period. Results indicated that pre-service teachers’ epistemological beliefs about the integration of knowledge became more sophisticated over the course of the teaching period. Qualitative data included pre-service teachers’ responses to open ended questions and field experience journal reflections about their perceptions of the teaching program and were collected at the end of the semester. These data showed that pre-service teachers held different conceptions about learning as integration, which provided a more nuanced understanding of the EBS data. Understanding pre-service teachers’ epistemological beliefs provides promising directions for teacher preparation and professional enrichment.