Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

Studying relationships in project management through social network analysis

Successful project management depends upon forming and maintaining relationships between and among project team members and stakeholder groups. The nature of these relationships and the patterns that they form affect communication, collaboration and resource flows. Networks affect us directly, and we use them to influence people and processes. Social Network Analysis (SNA) can be an extremely valuable research tool to better understand how critical social networks develop and influence work processes, particularly as projects become larger and more complex. This chapter introduces foundational network concepts, helps you determine if SNA could help you answer your research questions, and explains how to design and implement a social network study. At the end of this chapter, the reader can: understand foundational concepts about social networks; decide if SNA is an appropriate research methodology to address particular questions or problems; design and implement a basic social network study.

Impacts of sodic soil amelioration on hydraulic conductivity and deep drainage in the Lower Burdekin

An understanding of the influence of soil chemistry on soil hydraulic properties is of critical importance for the management of sodic soils under irrigation. The hydraulic conductivity of sodic soils has been shown to be affected by properties of the applied solution including pH (Suarez et al. 1984), sodicity and salt concentration (McNeal and Coleman 1966). The changes in soil hydraulic conductivity are the result of changes in the spacing between clay layers in response to changes in soil solution chemistry. While the importance o f soil chemistry in controlling hydraulic conductivity is known, the exact impacts of sodic soil amelioration on hydraulic conductivity and deep drainage at a given location are difficult to predict. This is because the relationships between soil chemical factors and hydraulic conductivity are soil specific and because local site specific factors also need to be considered to determine the actual impacts on deep drainage rates.

Network security metrics and performance for healthcare systems management

While enhanced cybersecurity options, mainly based around cryptographic functions, are needed overall speed and performance of a healthcare network may take priority in many circumstances. As such the overall security and performance metrics of those cryptographic functions in their embedded context needs to be understood. Understanding those metrics has been the main aim of this research activity. This research reports on an implementation of one network security technology, Internet Protocol Security (IPSec), to assess security performance. This research simulates sensitive healthcare information being transferred over networks, and then measures data delivery times with selected security parameters for various communication scenarios on Linux-based and Windows-based systems. Based on our test results, this research has revealed a number of network security metrics that need to be considered when designing and managing network security for healthcare-specific or non-healthcare-specific systems from security, performance and manageability perspectives. This research proposes practical recommendations based on the test results for the effective selection of network security controls to achieve an appropriate balance between network security and performance

The vertebral venous system in healthy and scoliotic adolescent spines - a 3D MRI investigation

Introduction. The venous drainage system within vertebral bodies (VBs) has been well documented previously in cadaveric specimens. Advances in 3D imaging and image processing now allow for in vivo quantification of larger venous vessels, such as the basivertebral vein. Differences between healthy and scoliotic VB veins can therefore be investigated. Methods. 20 healthy adolescent controls and 21 AIS patients were recruited (with ethics approval) to undergo 3D MRI, using a 3 Tesla, T1-weighted 3D gradient echo sequence, resulting in 512 slices across the thoraco-lumbar spine, with a voxel size of 0.5x0.5x0.5mm. Using Amira Filament Editor, five transverse slices through the VB were examined simultaneously and the resulting observable vascular network traced. Each VB was assessed, and a vascular network recorded when observable. A local coordinate system was created in the centre of each VB and the vascular networks aligned to this. The length of the vascular network on the left and right sides (with a small central region) of the VB was calculated, and the spatial patterning of the networks assessed level-by-level within each subject. Results. An average of 6 (range 4-10) vascular networks, consistent with descriptions of the basivertebral vein, were identifiable within each subject, most commonly between T10-L1. Differences were seen in the left/right distribution of vessels in the control and AIS subjects. Healthy controls saw a percentage distribution of 29:18:53 across the left:centre:right regions respectively, whereas the AIS subjects had a slightly shifted distribution of 33:25:42. The control group showed consistent spatial patterning of the vascular networks across most levels, but this was not seen in the AIS group. Conclusion. Observation and quantification of the basivertebral vein in vivo is possible using 3D MRI. The AIS group lacked the spatial pattern repetition seen in the control group and minor differences were seen in the left/right distribution of vessels.

Variations in vertebral venous vasculature

INTRODUCTION Cadaveric studies have previously documented typical patterns of venous drainage within vertebral bodies (VBs) [1,2,3], comprised primarily of the basivertebral vein, a planar tree like structure at the mid-height of the VB. These studies, however, are limited in the number of samples available, and so have not examined any potential differences in this anatomy in conditions such as scoliosis. MRI is able to create 3D images of soft tissue structures in the spine, including the basivertebral vein without the use of contrast. As a non-invasive imaging technique this opens up the possibility of examining the venous network in multiple VBs within the same subject, in healthy controls as well as in subjects with abnormal anatomy such as adolescent idiopathic scoliosis (AIS). CONCLUSIONS High resolution MRI scans allow in vivo quantification of the vertebral venous system at multiple levels on healthy and scoliotic populations for the first time. The length of the basivertebral vein was seen to have a significant bias to the right hand side of the VB in both healthy and AIS adolescents. The spatial pattern of this vein showed large variations in branching both within and across individuals.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Fractal and complex network analyses of protein molecular dynamics

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q)h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2)h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2)h(2) of MF-DFA on the time series, exponent λλ of the exponential degree distribution and fractal dimension dBdB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈h(2)〉〈h(2)〉 (from MF-DFA on time series) and 〈dB〉〈dB〉 of the converted HVGs for different energy, pressure and volume.

Topological properties and fractal analysis of a recurrence network constructed from fractional Brownian motions

Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the average degree exponent 〈λ〉 increases first and then decreases with the increase of Hurst index H of the associated FBMs; the relationship between H and 〈λ〉 can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e., the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension 〈dB〉 of recurrence networks decreases with the Hurst index H of the associated FBMs, and their dependence approximately satisfies the linear formula 〈dB〉≈2-H, which means that the fractal dimension of the associated recurrence network is close to that of the graph of the FBM. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index H=0.5 possesses the strongest multifractality. In addition, the dependence relationships of the average information dimension 〈D(1)〉 and the average correlation dimension 〈D(2)〉 on the Hurst index H can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic and the fractal nature of the associated FBM series.

Condition monitoring and rating of bridge components in a rail or road network by using SHM systems within SRP

The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.

Creating heterogeneity: Evolving use of groupware in a network of freelancers

This contribution is a long-term study of the evolving use of the organization-wide groupware in a service network. We are describing the practices related to organization-wide groupware in conjunction with local groupware-related practices and how they have proceeded since the organization was established. In the discussion of these practices we are focussing on issues such as: 1. tendencies for proliferation and integration, 2. local appropriations of a variety of systems, 3. creative appropriations, including the creation of a unique heterogeneous groupware fabric, 4. the design strategy of multiple parallel experimental use an; 5. the relation between disparate local meanings and successful computer supported cooperative practice. As an overarching theme we are exploring the explanatory value of the concepts of objectification and appropriation as compared to the concepts of design vs. use.

Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Submission to the draft Migration Assurance Policy - Improving the transition to the fixed-line national broadband network review

The rights of individuals to self-determination and participation in social, political and economic life are recognised and supported by Articles 1, 3 and 25 of the International Covenant on Civil and Political Rights 1966.4 Article 1 of the United Nations’ Human Rights Council’s Resolution on the Promotion and Protection of Human Rights on the Internet of July 2012 confirms individuals have the same rights online as offline. Access to the internet is essential and as such the UN: Calls upon all States to promote and facilitate access to the Internet and international cooperation aimed at the development of media and information and communications facilities in all countries (Article 3) Accordingly, access to the internet per se is a fundamental human right, which requires direct State recognition and support.5 The obligations of the State to ensure its citizens are able, and are enabled, to access the internet, are not matters that should be delegated to commercial parties. Quite simply – access to the internet, and high-speed broadband, by whatever means are “essential services” and therefore “should be treated as any other utility service”...