Identifying and explaining framing strategies of low carbon lifestyle movement organisations

Over the last decade we have seen the growth and development of low carbon lifestyle movement organisations, which seek to encourage members of the public to reduce their personal energy use and carbon emissions. As a first step to assess the transformational potential of such organisations, this paper examines the ways in which they frame their activities. This reveals an important challenge they face: in addressing the broader public, do they promote ‘transformative’ behaviours or do they limit themselves to encouraging ‘easy changes’ to maintain their appeal? We find evidence that many organisations within this movement avoid ‘transformative’ frames. The main reasons for this are organisers’ perceptions that transformational frames lack resonance with broader audiences, as well as wider cultural contexts that caution against behavioural intervention. The analysis draws on interviews with key actors in the low carbon lifestyle movement and combines insights from the literatures on collective action framing and lifestyle movements.

A robust sclera segmentation algorithm

Sclera segmentation is shown to be of significant importance for eye and iris biometrics. However, sclera segmentation has not been extensively researched as a separate topic, but mainly summarized as a component of a broader task. This paper proposes a novel sclera segmentation algorithm for colour images which operates at pixel-level. Exploring various colour spaces, the proposed approach is robust to image noise and different gaze directions. The algorithm’s robustness is enhanced by a two-stage classifier. At the first stage, a set of simple classifiers is employed, while at the second stage, a neural network classifier operates on the probabilities’ space generated by the classifiers at stage 1. The proposed method was ranked the 1st in Sclera Segmentation Benchmarking Competition 2015, part of BTAS 2015, with a precision of 95.05% corresponding to a recall of 94.56%.

On fusion for robust motion segmentation

While a multitude of motion segmentation algorithms have been presented in the literature, there has not been an objective assessment of different approaches to fusing their outputs. This paper investigates the application of 4 different fusion schemes to the outputs of 3 probabilistic pixel-level segmentation algorithms. We performed an extensive experimentation using 6 challenge categories from the changedetection.net dataset demonstrating that in general simple majority vote proves to be more effective than more complex fusion schemes.

Segmentation-level fusion for iris recognition

This paper investigates the potential of fusion at normalisation/segmentation level prior to feature extraction. While there are several biometric fusion methods at data/feature level, score level and rank/decision level combining raw biometric signals, scores, or ranks/decisions, this type of fusion is still in its infancy. However, the increasing demand to allow for more relaxed and less invasive recording conditions, especially for on-the-move iris recognition, suggests to further investigate fusion at this very low level. This paper focuses on the approach of multi-segmentation fusion for iris biometric systems investigating the benefit of combining the segmentation result of multiple normalisation algorithms, using four methods from two different public iris toolkits (USIT, OSIRIS) on the public CASIA and IITD iris datasets. Evaluations based on recognition accuracy and ground truth segmentation data indicate high sensitivity with regards to the type of errors made by segmentation algorithms.

Spectacular foodscapes: food celebrities and the politics of lifestyle mediation in an age of inequality

This editorial introduces a special issue of Food, Culture & Society and works to add a parallel, substantive take on the phenomenon of the food celebrity and the mediated, everyday cultural politics they create. We start by exploring the concept of the foodscape. Specifically, we argue that food celebrities represent a fundamental component of contemporary foodscapes, how they “perform” and function, and the socio-material means by which they are produced. We then explore the key roles and privileges of food celebrity, arguing that the celebrity chef is not the only high-profile, mediating figure at work on the foodscape. Key food celebrity paradoxes are identified and discussed: food celebrities must work to be authentic and aspirational, accessible yet exclusive, responsibilizing but also empowering. We conclude with a short contextualization of the papers in this special issue, and argue for the rich potential of food celebrity scholarship as a way to better understand food inequalities

Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population

Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.

Explaining sleep duration in adolescents: The impact of socio-demographic and lifestyle factors and working status

Previous studies found students who both work and attend school undergo a partial sleep deprivation that accumulates across the week. The aim of the present study was to obtain information using a questionnaire on a number of variables (e.g., socio-demographics, lifestyle, work timing, and sleep-wake habits) considered to impact on sleep duration of working (n = 51) and non-working (n = 41) high-school students aged 14-21 yrs old attending evening classes (19:00-22:30h) at a public school in the city of Sao Paulo, Brazil. Data were collected for working days and days off. Multiple linear regression analyses were performed to assess the factors associated with sleep duration on weekdays and weekends. Work, sex, age, smoking, consumption of alcohol and caffeine, and physical activity were considered control variables. Significant predictors of sleep duration were: work (p < 0.01), daily work duration (8-10h/day; p < 0.01), sex (p = 0.04), age 18-21 yrs (0.01), smoking (p = 0.02) and drinking habits (p = 0.03), irregular physical exercise (p < 0.01), ease of falling asleep (p = 0.04), and the sleep-wake cycle variables of napping (p < 0.01), nocturnal awakenings (p < 0.01), and mid-sleep regularity (p < 0.01). The results confirm the hypotheses that young students who work and attend school showed a reduction in night-time sleep duration. Sleep deprivation across the week, particularly in students working 8-10h/day, is manifested through a sleep rebound (i.e., extended sleep duration) on Saturdays. However, the different roles played by socio-demographic and lifestyle variables have proven to be factors that intervene with nocturnal sleep duration. The variables related to the sleep-wake cyclenaps and night awakeningsproved to be associated with a slight reduction in night-time sleep, while regularity in sleep and wake-up schedules was shown to be associated with more extended sleep duration, with a distinct expression along the week and the weekend. Having to attend school and work, coupled with other socio-demographic and lifestyle factors, creates an unfavorable scenario for satisfactory sleep duration.

How does a riverine setting affect the lifestyle of shellmound builders in Brazil?

The contact of inland and coastal prehistoric groups in Brazil is believed to have been restricted to regions with no geographical barrier, as is the case in the Ribeira de Iguape valley. The inland osteological collection from the riverine shellmound Moraes (5800-4500 BP) represents a unique opportunity to test this assumption for this region. Despite cultural similarities between riverine and coastal shellmounds, important ecological and site distribution differences are expected to impact on lifestyle. The purpose of this study is thus to document and interpret health and lifestyle indicators in Moraes in comparison to coastal shellmound groups. Specifically we test if the rare evidence of fish and mollusc remains in the riverine shellmound led to (a) higher caries rates and (b) lower auditory exostosis frequency and (c) if the small size of the riverine shellmound translates into reduced demographic density and thus rarity of communicable infectious diseases. Of the three hypotheses, (a) was confirmed, (b) was rejected and (c) was partly rejected. Bioanthropological similarities between Moraes and coastal shellmounds include auditory exostoses with equally high frequencies; significantly more frequent osteoarthritis in upper than in lower limbs; cranial and dental morphological affinities and low frequencies of violent trauma. However, there are also important differences: Moraes subsisted on a much broader protein diet and consumed more cariogenic food, but showed a stature even shorter than coastal groups. Thus, despite the contact also suggested by treponematoses in both site types, there was enough time for the people at the riverine site to adapt to local conditions. (c) 2008 Elsevier GmbH. All rights reserved.

Endotoxin levels correlate positively with a sedentary lifestyle and negatively with highly trained subjects

Introduction: A sedentary lifestyle increases the risk of developing cardiovascular disease, obesity, and diabetes. This phenomenon is supported by recent studies suggesting a chronic, low-grade inflammation status. Endotoxin derived from gut flora may be key to the development of inflammation by stimulating the secretion of inflammatory factors. This study aimed to examine plasma inflammatory markers and endotoxin levels in individuals with a sedentary lifestyle and/or in highly trained subjects at rest. Methods: Fourteen male subjects (sedentary lifestyle n = 7; highly trained subjects n = 7) were recruited. Blood samples were collected after an overnight fast (similar to 12 h). The plasmatic endotoxin, plasminogen activator inhibitor type-1 (PAI-1), monocyte chemotactic protein-1 (MCP1), ICAM/CD54, VCAM/CD106 and lipid profile levels were determined. Results: Endotoxinemia was lower in the highly trained subject group relative to the sedentary subjects (p < 0.002). In addition, we observed a positive correlation between endotoxin and PAI-1 (r = 0.85, p < 0.0001), endotoxin and total cholesterol (r = 0.65; p < 0.01), endotoxin and LDL-c (r = 0.55; p < 0.049) and endotoxin and TG levels (r = 0.90; p < 0.0001). The plasma levels of MCP-1, ICAM/CD54 and VCAM/CD106 did not differ. Conclusion: These results indicate that a lifestyle associated with high-intensity and high-volume exercise induces favorable changes in chronic low-grade inflammation markers and may reduce the risk for diseases such as obesity, diabetes and cardiovascular diseases.

Chaotic synchronization in general network topology for scene segmentation

Chaotic synchronization has been discovered to be an important property of neural activities, which in turn has encouraged many researchers to develop chaotic neural networks for scene and data analysis. In this paper, we study the synchronization role of coupled chaotic oscillators in networks of general topology. Specifically, a rigorous proof is presented to show that a large number of oscillators with arbitrary geometrical connections can be synchronized by providing a sufficiently strong coupling strength. Moreover, the results presented in this paper not only are valid to a wide class of chaotic oscillators, but also cover the parameter mismatch case. Finally, we show how the obtained result can be applied to construct an oscillatory network for scene segmentation.

Chaotic synchronization in 2D lattice for scene segmentation

Synchronization and chaos play important roles in neural activities and have been applied in oscillatory correlation modeling for scene and data analysis. Although it is an extensively studied topic, there are still few results regarding synchrony in locally coupled systems. In this paper we give a rigorous proof to show that large numbers of coupled chaotic oscillators with parameter mismatch in a 2D lattice can be synchronized by providing a sufficiently large coupling strength. We demonstrate how the obtained result can be applied to construct an oscillatory network for scene segmentation. (C) 2007 Elsevier B.V. All rights reserved.

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

Fingerprint Segmentation

In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.

Color Segmentation using LVQ-Learning Vector Quantization

This thesis aims to present a color segmentation approach for traffic sign recognition based on LVQ neural networks. The RGB images were converted into HSV color space, and segmented using LVQ depending on the hue and saturation values of each pixel in the HSV color space. LVQ neural network was used to segment red, blue and yellow colors on the road and traffic signs to detect and recognize them. LVQ was effectively applied to 536 sampled images taken from different countries in different conditions with 89% accuracy and the execution time of each image among 31 images was calculated in between 0.726sec to 0.844sec. The method was tested in different environmental conditions and LVQ showed its capacity to reasonably segment color despite remarkable illumination differences. The results showed high robustness.