Garden Cities: A flawed model for Ecological Urbanism?

Since the beginning of the 20th century, the Garden City model has been a predominant theory emerging from Ecological Urbanism. In his book Howard observed the disastrous effects of rapid urbanization and as a response, proposed the Garden City. Although Howard’s proposal was first published in the late 1800’s, the clear imbalance that Howard aimed to address is still prevalent in the UK today. Each year, the UK wastes nearly 15 million tons of food, despite this an estimated 500,000 people in the UK go without sufficient access to food. While the urban population is rapidly increasing and cities are becoming hubs of economic activity, producing wealth and improving education and access to markets, it is within these cities that the imbalance is most evident, with a significant proportion of the world’s population with unmet needs living in urban areas. Despite Howard’s model being a response to 17th century London, many still consider the Garden City model to be an effective solution for the 21st century. In his book, Howard details the metrics required for the design of a Garden City. This paper will discuss how, by using this methodology and comparing it with more recent studies by Cornell University and Matthew Wheeland (Pure Energies); it is possible to test the validity of Howard’s proposal to establish whether the Garden City model is a viable solution to the increasing pressures of urbanization.
This paper outlines how the analysis of Howard’s proposal has shown the model to be flawed, incapable of producing enough food to sustain the proposed 32,000 population, with a capacity to produce only 23% of the food required to meet the current average UK consumption rate. Beyond the limited productive capacity of Howard’s model, the design itself does little to increase local resilience or the ecological base. This paper will also discuss how a greater understanding of the
Land-share requirements enables the design of a new urban model, building on the foundations initially laid out by Howard and combining a number of other theories to produce a more resilient and efficient model of ecological urbanism.

An adaptive motion model for person tracking with instantaneous head-pose features

This letter presents novel behaviour-based tracking of people in low-resolution using instantaneous priors mediated by head-pose. We extend the Kalman Filter to adaptively combine motion information with an instantaneous prior belief about where the person will go based on where they are currently looking. We apply this new method to pedestrian surveillance, using automatically-derived head pose estimates, although the theory is not limited to head-pose priors. We perform a statistical analysis of pedestrian gazing behaviour and demonstrate tracking performance on a set of simulated and real pedestrian observations. We show that by using instantaneous `intentional' priors our algorithm significantly outperforms a standard Kalman Filter on comprehensive test data.

Cytotoxicity Evaluation of Si-Diatom Frustules in a Mouse Model

Silica additives in bone substitute materials are topical, clinically interesting and have significant support in the Orthopaedic field. Biosilica, e.g isolated from diatoms, has many advantages over its synthetic counterparts, e.g. it is amorphous, thus will be absorbed by the body, however, issues such as purity, presence of endotoxins and cytotoxicity need to be addressed before it can be further exploited. Biosilica isolated from Cyclotella Meneghiniana was then tested in a mouse model, to test the immunological response, organ toxicity (kidney, spleen, liver) and route of metabolism/excretion of silica. Five-week-old Balb-c mice were injected subcutaneously with a single high dose (50mg/ml) of Si-frustules, Si-frustules + organic linker and vehicle only control. Animals were sacrificed at 1d and 28d. The animal studies were conducted under an ethically approved protocol at Queen’s University, Belfast. The animals showed no adverse stress during the experiment and remained healthy until sacrifice. Blood results using ICP-OES analysis suggest the frustules were metabolized between comparator groups at different rates, and clearly showed elevated levels of silicon in groups injected with frustules relative to control. The histology of organs showed no variation in morphology of mice injected frustules relative compared to the control group.
Acknowledgements: The authors would like to thank Marie Curie International Outgoing Fellowships from the EU and Beaufort Marine Biodiscovery Award as part of the Marine Biotechnology Ireland Programme for providing financial support to this project.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

Sepsis: the LightCycler SeptiFast Test MGRADE®, SepsiTest™ and IRIDICA BAC BSI assay for rapidly identifying bloodstream bacteria and fungi – a systematic review and economic evaluation

Background: Sepsis can lead to multiple organ failure and death. Timely and appropriate treatment can reduce in-hospital mortality and morbidity. Objectives: To determine the clinical effectiveness and cost-effectiveness of three tests [LightCycler SeptiFast Test MGRADE® (Roche Diagnostics, Risch-Rotkreuz, Switzerland); SepsiTest™ (Molzym Molecular Diagnostics, Bremen, Germany); and the IRIDICA BAC BSI assay (Abbott Diagnostics, Lake Forest, IL, USA)] for the rapid identification of bloodstream bacteria and fungi in patients with suspected sepsis compared with standard practice (blood culture with or without matrix-absorbed laser desorption/ionisation time-offlight mass spectrometry). Data sources: Thirteen electronic databases (including MEDLINE, EMBASE and The Cochrane Library) were searched from January 2006 to May 2015 and supplemented by hand-searching relevant articles. Review methods: A systematic review and meta-analysis of effectiveness studies were conducted. A review of published economic analyses was undertaken and a de novo health economic model was constructed. A decision tree was used to estimate the costs and quality-adjusted life-years (QALYs) associated with each test; all other parameters were estimated from published sources. The model was populated with evidence from the systematic review or individual studies, if this was considered more appropriate (base case 1). In a secondary analysis, estimates (based on experience and opinion) from seven clinicians regarding the benefits of earlier test results were sought (base case 2). A NHS and Personal Social Services perspective was taken, and costs and benefits were discounted at 3.5% per annum. Scenario analyses were used to assess uncertainty. Results: For the review of diagnostic test accuracy, 62 studies of varying methodological quality were included. A meta-analysis of 54 studies comparing SeptiFast with blood culture found that SeptiFast had an estimated summary specificity of 0.86 [95% credible interval (CrI) 0.84 to 0.89] and sensitivity of 0.65 (95% CrI 0.60 to 0.71). Four studies comparing SepsiTest with blood culture found that SepsiTest had an estimated summary specificity of 0.86 (95% CrI 0.78 to 0.92) and sensitivity of 0.48 (95% CrI 0.21 to 0.74), and four studies comparing IRIDICA with blood culture found that IRIDICA had an estimated summary specificity of 0.84 (95% CrI 0.71 to 0.92) and sensitivity of 0.81 (95% CrI 0.69 to 0.90). Owing to the deficiencies in study quality for all interventions, diagnostic accuracy data should be treated with caution. No randomised clinical trial evidence was identified that indicated that any of the tests significantly improved key patient outcomes, such as mortality or duration in an intensive care unit or hospital. Base case 1 estimated that none of the three tests provided a benefit to patients compared with standard practice and thus all tests were dominated. In contrast, in base case 2 it was estimated that all cost per QALY-gained values were below £20,000; the IRIDICA BAC BSI assay had the highest estimated incremental net benefit, but results from base case 2 should be treated with caution as these are not evidence based. Limitations: Robust data to accurately assess the clinical effectiveness and cost-effectiveness of the interventions are currently unavailable. Conclusions: The clinical effectiveness and cost-effectiveness of the interventions cannot be reliably determined with the current evidence base. Appropriate studies, which allow information from the tests to be implemented in clinical practice, are required.

Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.

Assessment of turbulence model predictions for a centrifugal compressor simulation

Steady-state computational fluid dynamics (CFD) simulations are an essential tool in the design process of centrifugal compressors. Whilst global parameters, such as pressure ratio and efficiency, can be predicted with reasonable accuracy, the accurate prediction of detailed compressor flow fields is a much more significant challenge. Much of the inaccuracy is associated with the incorrect selection of turbulence model. The need for a quick turnaround in simulations during the design optimisation process, also demands that the turbulence model selected be robust and numerically stable with short simulation times.
In order to assess the accuracy of a number of turbulence model predictions, the current study used an exemplar open CFD test case, the centrifugal compressor ‘Radiver’, to compare the results of three eddy viscosity models and two Reynolds stress type models. The turbulence models investigated in this study were (i) Spalart-Allmaras (SA) model, (ii) the Shear Stress Transport (SST) model, (iii) a modification to the SST model denoted the SST-curvature correction (SST-CC), (iv) Reynolds stress model of Speziale, Sarkar and Gatski (RSM-SSG), and (v) the turbulence frequency formulated Reynolds stress model (RSM-ω). Each was found to be in good agreement with the experiments (below 2% discrepancy), with respect to total-to-total parameters at three different operating conditions. However, for the off-design conditions, local flow field differences were observed between the models, with the SA model showing particularly poor prediction of local flow structures. The SST-CC showed better prediction of curved rotating flows in the impeller. The RSM-ω was better for the wake and separated flow in the diffuser. The SST model showed reasonably stable, robust and time efficient capability to predict global and local flow features.