Territoriality and the regulation of public space in Favela Morro da Formiga, Rio de Janeiro

Public space in many communities around the world has been identified as over-regulated and devoid of social vibrancy. This research contributed new knowledge regarding the way local residents territorialise and take ownership of streets and open areas in a favela, or informal settlement, in Rio De Janeiro, Brazil. Findings showed that public spaces were only partly activated by spatial pattern or structure. User agency also played a significant role, despite recent regulatory and policing interventions in the favela. This may have important implications for new communities where design could allow for more flexible usage and thereby enhance social vibrancy.

Fourier spectral methods for fractional-in-space reaction-diffusion equations

Fractional differential equations are becoming increasingly used as a powerful modelling approach for understanding the many aspects of nonlocality and spatial heterogeneity. However, the numerical approximation of these models is demanding and imposes a number of computational constraints. In this paper, we introduce Fourier spectral methods as an attractive and easy-to-code alternative for the integration of fractional-in-space reaction-diffusion equations described by the fractional Laplacian in bounded rectangular domains ofRn. The main advantages of the proposed schemes is that they yield a fully diagonal representation of the fractional operator, with increased accuracy and efficiency when compared to low-order counterparts, and a completely straightforward extension to two and three spatial dimensions. Our approach is illustrated by solving several problems of practical interest, including the fractional Allen–Cahn, FitzHugh–Nagumo and Gray–Scott models, together with an analysis of the properties of these systems in terms of the fractional power of the underlying Laplacian operator.

The association between ambient temperature and children's lung function in Baotou, China

The objective of this study is to examine the association between ambient temperature and children’s lung function in Baotou, China. We recruited 315 children (8–12 years) from Baotou, China in the spring of 2004, 2005, and 2006. They performed three successive forced expiratory measurements three times daily (morning, noon, and evening) for about 5 weeks. The highest peak expiratory flow (PEF) was recorded for each session. Daily data on ambient temperature, relative humidity, and air pollution were monitored during the same period. Mixed models with a distributed lag structure were used to examine the effects of temperature on lung function while adjusting for individual characteristics and environmental factors. Low temperatures were significantly associated with decreases in PEF. The effects lasted for lag 0–2 days. For all participants, the cumulative effect estimates (lag 0–2 days) were −1.44 (−1.93, −0.94) L/min, −1.39 (−1.92, −0.86) L/min, −1.40 (−1.97, −0.82) L/min, and −1.28 (−1.69, −0.88) L/min for morning, noon, evening, and daily mean PEF, respectively, associated with 1 °C decrease in daily mean temperature. Generally, the effects of temperature were slightly stronger in boys than in girls for noon, evening, and daily mean PEF, while the effects were stronger in girls for morning PEF. PM2.5 had joint effects with temperature on children’s PEF. Higher PM2.5 increased the impacts of low temperature. Low ambient temperatures are associated with lower lung function in children in Baotou, China. Preventive health policies will be required for protecting children from the cold weather.

Estimates on the coverage of parameter space using populations of models

In this paper we provide estimates for the coverage of parameter space when using Latin Hypercube Sampling, which forms the basis of building so-called populations of models. The estimates are obtained using combinatorial counting arguments to determine how many trials, k, are needed in order to obtain specified parameter space coverage for a given value of the discretisation size n. In the case of two dimensions, we show that if the ratio (Ø) of trials to discretisation size is greater than 1, then as n becomes moderately large the fractional coverage behaves as 1-exp-ø. We compare these estimates with simulation results obtained from an implementation of Latin Hypercube Sampling using MATLAB.

Numerical analysis of a new space-time variable fractional order advection-dispersion equation

Many physical processes appear to exhibit fractional order behavior that may vary with time and/or space. The continuum of order in the fractional calculus allows the order of the fractional operator to be considered as a variable. In this paper, we consider a new space–time variable fractional order advection–dispersion equation on a finite domain. The equation is obtained from the standard advection–dispersion equation by replacing the first-order time derivative by Coimbra’s variable fractional derivative of order α(x)∈(0,1]α(x)∈(0,1], and the first-order and second-order space derivatives by the Riemann–Liouville derivatives of order γ(x,t)∈(0,1]γ(x,t)∈(0,1] and β(x,t)∈(1,2]β(x,t)∈(1,2], respectively. We propose an implicit Euler approximation for the equation and investigate the stability and convergence of the approximation. Finally, numerical examples are provided to show that the implicit Euler approximation is computationally efficient.

Histopathological features of bone regeneration in a canine segmental ulnar defect model

Background Today, finding an ideal biomaterial to treat the large bone defects, delayed unions and non-unions remains a challenge for orthopaedic surgeions and researchers. Several studies have been carried out on the subject of bone regeneration, each having its own advantages. The present study has been designed in vivo to evaluate the effects of cellular auto-transplantation of tail vertebrae on healing of experimental critical bone defect in a dog model. Methods Six indigenous breeds of dog with 32 ± 3.6 kg average weight from both sexes (5 males and 1 female) received bilateral critical-sized ulnar segmental defects. After determining the health condition, divided to 2 groups: The Group I were kept as control I (n = 1) while in Group II (experimental group; n = 5) bioactive bone implants were inserted. The defects were implanted with either autogeneic coccygeal bone grafts in dogs with 3-4 cm diaphyseal defects in the ulna. Defects were stabilized with internal plate fixation, and the control defects were not stabilized. Animals were euthanized at 16 weeks and analyzed by histopathology. Results Histological evaluation of this new bone at sixteen weeks postoperatively revealed primarily lamellar bone, with the formation of new cortices and normal-appearing marrow elements. And also reformation cortical compartment and reconstitution of marrow space were observed at the graft-host interface together with graft resorption and necrosis responses. Finally, our data were consistent with the osteoconducting function of the tail autograft. Conclusions Our results suggested that the tail vertebrae autograft seemed to be a new source of autogenous cortical bone in order to supporting segmental long bone defects in dogs. Furthermore, cellular autotransplantation was found to be a successful replacement for the tail vertebrae allograft bone at 3-4 cm segmental defects in the canine mid- ulna. Clinical application using graft expanders or bone autotransplantation should be used carefully and requires further investigation.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Missing in space: An evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes

Background Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. Methods We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Results Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Conclusions Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

A directed continuous time random walk model with jump length depending on waiting time

In continuum one-dimensional space, a coupled directed continuous time random walk model is proposed, where the random walker jumps toward one direction and the waiting time between jumps affects the subsequent jump. In the proposed model, the Laplace-Laplace transform of the probability density function P(x,t) of finding the walker at position at time is completely determined by the Laplace transform of the probability density function φ(t) of the waiting time. In terms of the probability density function of the waiting time in the Laplace domain, the limit distribution of the random process and the corresponding evolving equations are derived.

Young people and urban public space in Australia-creating pathways to community, belonging and inclusion

Cities and urban spaces around the world are changing rapidly from their origins in the industrialising world to a post-industrial, hard wired surveillance landscape. This kind of monitoring and surveillance connects with attempts by civic authorities to rebrand urban public spaces into governable and predictable arenas of consumption. In this context of control, a number of groups are excluded from public space, such as some children and young people. This article discusses the surveillance, governance and control of public space environments used by children and young people in particular, and the capacity for their ongoing displacement and marginality, as well as possible greater inclusion.

Transformation of public space in contemporary urban neighbourhoods of Kathmandu Valley, Nepal: An investigation of changing provision, use and meaning

This research examined the transformation of public space in contemporary urban neighbourhoods of the Kathmandu Valley in Nepal. The development of neighbourhood public space remains a considerable challenge in the present changing context, with significant consequences for public life and social interaction. The findings will aid policy makers, urban planners and designers in addressing the adverse effects of the current urban growth and change, and in winning back public space for the well-being of the local community.

TrainYarn: Probing perceptions of social space in urban commuter trains

We studied the ways that urban commuter train passengers experience their journeys. We present the design process and in-situ evaluation of TrainYarn, a mobile app prototype designed to facilitate social interaction between co-located urban train passengers. Through the deployment of the prototype, we sought to probe perceptions of social space with a view to positively impact the assessment of public transport. Our results support that our target users saw value in the use of TrainYarn, perceiving it as emancipatory, in alignment with their communicative needs, and having the ability to transform their perceptions of social space. To further inform future research and practice, we put forward a series of design recommendations.

Time, place and space – student group collaboration using Google Drive

Virtual working environments are intrinsic to the contemporary workplace and collaborative skills are a vital graduate capability. To develop students’ collaborative skills, first year medical laboratory science students undertake a group poster project, based on a blended learning model. Learning is scaffolded in lectures, workshops in collaborative learning spaces, practitioner mentoring sessions, and online resources. Google Drive provides an online collaborative space for students to realise tangible outcomes from this learning. A Google Drive document is created for each group and shared with members. In this space, students assign tasks and plan workflow, share research, progressively develop poster content, reflect and comment on peer contributions and use the messaging functions to ‘talk’ to group members. This provides a readily accessible, transparent record of group work, crucial in peer assessment, and a communication channel for group members and the lecturer, who can support groups if required. This knowledge creation space also augments productivity and effectiveness of face-to-face collaboration. As members are randomly allocated to groups and are often of diverse backgrounds and unknown to each other, resilience is built as students navigate the uncertainties and complexities of group dynamics, learning to focus on the goal of the team task as they constructively and professionally engage in team dialogue. Students are responsible and accountable for individual and group work. The use of Google Drive was evaluated in a survey including Likert scale and open ended qualitative questions. Statistical analysis was carried out. Results show students (79%) valued the inclusion of online space in collaborative work and highly appreciated (78%) the flexibility provided by Google Drive, while recognising the need for improved notification functionality. Teaching staff recognised the advantages in monitoring and moderating collaborative group work, and the transformational progression in student collaborative as well as technological skill acquisition, including professional dialogue.

The function of the RNA-binding protein TEL1 in moss reveals ancient regulatory mechanisms of shoot development

The shoot represents the basic body plan in land plants. It consists of a repeated structure composed of stems and leaves. Whereas vascular plants generate a shoot in their diploid phase, non-vascular plants such as mosses form a shoot (called the gametophore) in their haploid generation. The evolution of regulatory mechanisms or genetic networks used in the development of these two kinds of shoots is unclear. TERMINAL EAR1-like genes have been involved in diploid shoot development in vascular plants. Here, we show that disruption of PpTEL1 from the moss Physcomitrella patens, causes reduced protonema growth and gametophore initiation, as well as defects in gametophore development. Leafy shoots formed on ΔTEL1 mutants exhibit shorter stems with more leaves per shoot, suggesting an accelerated leaf initiation (shortened plastochron), a phenotype shared with the Poaceae vascular plants TE1 and PLA2/LHD2 mutants. Moreover, the positive correlation between plastochron length and leaf size observed in ΔTEL1 mutants suggests a conserved compensatory mechanism correlating leaf growth and leaf initiation rate that would minimize overall changes in plant biomass. The RNA-binding protein encoded by PpTEL1 contains two N-terminus RNA-recognition motifs, and a third C-terminus non-canonical RRM, specific to TEL proteins. Removal of the PpTEL1 C-terminus (including this third RRM) or only 16–18 amino acids within it seriously impairs PpTEL1 function, suggesting a critical role for this third RRM. These results show a conserved function of the RNA-binding PpTEL1 protein in the regulation of shoot development, from early ancestors to vascular plants, that depends on the third TEL-specific RRM.