The relationship of fear of intimacy, body image avoidance and body mass index

Issues of body image and ability to achieve intimacy are connected to body weight, yet remain largely unexplored and have not been evaluated by gender. The underlying purpose of this research was to determine if avoidant attitudes and perceptions of one's body may hold implications toward its use in intimate interactions, and if an above average body weight would tend to increase this avoidance. The National Health and Nutrition Examination Survey (NHANES, 1999-2002) finds that 64.5% of US adults are overweight, with 61.9% of women and 67.2% of men. The increasing prevalence of overweight and obesity in men and women shows no reverse trend, nor have prevention and treatment proven effective in the long term. The researcher gathered self-reported age, gender, height and weight data from 55 male and 58 female subjects (determined by a prospective power analysis with a desired medium effect size (r=.30) to determine body mass index (BMI), determining a mean age of 21.6 years and mean BMI of 25.6. Survey instruments consisted of two scales that are germane to the variables being examined. They were (1) Descutner and Thelen of the University of Missouri‘s (1991) Fear-of-Intimacy scale; and (2) Rosen, Srebnik, Saltzberg, and Wendt's (1991) Body Image Avoidance Questionnaire. Results indicated that as body mass index increases, fear of intimacy increases (p<0.05) and that as body mass index increases, body image avoidance increases (p<0.05). The relationship that as body image avoidance increases, fear of intimacy increases was not supported, but approached significance at (p<0.07). No differences in these relationships were determined between gender groups. For age, the only observed relationship was that of a difference between scores for age groups [18 to 22 (group 1) and ages 23 to 34 (group 2)] for the relationship of body image avoidance and fear of intimacy (p<0.02). The results suggest that the relationship of body image avoidance and fear of intimacy, as well as age, bear consideration toward the escalating prevalence of overweight and obesity. An integrative approach to body weight that addresses issues of body image and intimacy may prove effective in prevention and treatment.

Racial/ethnic differences on the body image perceptions and weight concerns of fourth grade girls

The purpose of this study was to determine the racial and ethnic differences on body image perceptions and weight concerns of fourth grade girls. A purposive sample of 182 fourth grade girls were eligible to participate, 166 were included in the data analysis. The Children's Eating Attitude Test (ChEAT) and a Dieting and Demographic Questionnaire (DDQ) were used to determine eating attitudes of fourth grade girls. A pictoral instrument that was modified from the original was used to assess body image. Anthropometric data was assessed and body mass index (BMI) values were used to classify subjects into percentiles. Results revealed that 56% of all fourth grade girls studied wanted to be thinner and 53% had tried to lose weight. Significantly more non-Hispanic white (NHW) girls reported wanting to be thinner than non-Hispanic black (NHB) and H girls (65.5% vs.32% and 47%, respectively, P=0.005) No significant racial/ethnic differences were revealed for the ChEAT scores. However, 19% of all subjects studied fell into the category indicative of anorexia nervosa. H girls who were less than the 85" %tile for BMI chose significantly smaller figures as their perceived body image (3.5±0.7) than both NHB and NHW girls (4.0±0.6 and 3.9±0.5, respectively, P<0.01). These findings demonstrated that weight concerns were prevalent among girls ages 9- 11 years. NHW and H girls may have more concerns about their body size and shape than their NHB counterparts. Implementing intervention programs at an early age may prevent eating disorders in adolescence and adulthood.

Seawater carbonate chemistry and growth, carbon acquisition, and species interaction of Antarctic phytoplankton species in a laboratory experiment

Despite the fact that ocean acidification is considered to be especially pronounced in the Southern Ocean, little is known about CO2-dependent physiological processes and the interactions of Antarctic phytoplankton key species. We therefore studied the effects of CO2 partial pressure (PCO2) (16.2, 39.5, and 101.3 Pa) on growth and photosynthetic carbon acquisition in the bloom-forming species Chaetoceros debilis, Pseudo-nitzschia subcurvata, Fragilariopsis kerguelensis, and Phaeocystis antarctica. Using membrane-inlet mass spectrometry, photosynthetic O2 evolution and inorganic carbon (Ci) fluxes were determined as a function of CO2 concentration. Only the growth of C. debilis was enhanced under high PCO2. Analysis of the carbon concentrating mechanism (CCM) revealed the operation of very efficient CCMs (i.e., high Ci affinities) in all species, but there were species-specific differences in CO2-dependent regulation of individual CCM components (i.e., CO2 and uptake kinetics, carbonic anhydrase activities). Gross CO2 uptake rates appear to increase with the cell surface area to volume ratios. Species competition experiments with C. debilis and P. subcurvata under different PCO2 levels confirmed the CO2-stimulated growth of C. debilis observed in monospecific incubations, also in the presence of P. subcurvata. Independent of PCO2, high initial cell abundances of P. subcurvata led to reduced growth rates of C. debilis. For a better understanding of future changes in phytoplankton communities, CO2-sensitive physiological processes need to be identified, but also species interactions must be taken into account because their interplay determines the success of a species.

Brain hyperintensity location determines outcome in the triad of impaired cognition, physical health and depressive symptoms : A cohort study in late life

The authors would like to thank the participants of the Aberdeen 1936 Birth Cohort (ABC36). Image acquisition and image analysis for ABC36 were funded by the Alzheimer’s Research Trust (now Alzheimer’s Research UK). A.D.M., C.J.M., S.S., L.J.W., and R.T.S. have received grants from: Chief Scientist Office, Department of Health, Scottish Government; Biotechnology and Biological Sciences Research Council

Brain hyperintensity location determines outcome in the triad of impaired cognition, physical health and depressive symptoms : A cohort study in late life

The authors would like to thank the participants of the Aberdeen 1936 Birth Cohort (ABC36). Image acquisition and image analysis for ABC36 were funded by the Alzheimer’s Research Trust (now Alzheimer’s Research UK). A.D.M., C.J.M., S.S., L.J.W., and R.T.S. have received grants from: Chief Scientist Office, Department of Health, Scottish Government; Biotechnology and Biological Sciences Research Council

Automated Assessment of Image Quality and Dose Attributes in Clinical CT Images

Computed tomography (CT) is a valuable technology to the healthcare enterprise as evidenced by the more than 70 million CT exams performed every year. As a result, CT has become the largest contributor to population doses amongst all medical imaging modalities that utilize man-made ionizing radiation. Acknowledging the fact that ionizing radiation poses a health risk, there exists the need to strike a balance between diagnostic benefit and radiation dose. Thus, to ensure that CT scanners are optimally used in the clinic, an understanding and characterization of image quality and radiation dose are essential.

The state-of-the-art in both image quality characterization and radiation dose estimation in CT are dependent on phantom based measurements reflective of systems and protocols. For image quality characterization, measurements are performed on inserts imbedded in static phantoms and the results are ascribed to clinical CT images. However, the key objective for image quality assessment should be its quantification in clinical images; that is the only characterization of image quality that clinically matters as it is most directly related to the actual quality of clinical images. Moreover, for dose estimation, phantom based dose metrics, such as CT dose index (CTDI) and size specific dose estimates (SSDE), are measured by the scanner and referenced as an indicator for radiation exposure. However, CTDI and SSDE are surrogates for dose, rather than dose per-se.

Currently there are several software packages that track the CTDI and SSDE associated with individual CT examinations. This is primarily the result of two causes. The first is due to bureaucracies and governments pressuring clinics and hospitals to monitor the radiation exposure to individuals in our society. The second is due to the personal concerns of patients who are curious about the health risks associated with the ionizing radiation exposure they receive as a result of their diagnostic procedures.

An idea that resonates with clinical imaging physicists is that patients come to the clinic to acquire quality images so they can receive a proper diagnosis, not to be exposed to ionizing radiation. Thus, while it is important to monitor the dose to patients undergoing CT examinations, it is equally, if not more important to monitor the image quality of the clinical images generated by the CT scanners throughout the hospital.

The purposes of the work presented in this thesis are threefold: (1) to develop and validate a fully automated technique to measure spatial resolution in clinical CT images, (2) to develop and validate a fully automated technique to measure image contrast in clinical CT images, and (3) to develop a fully automated technique to estimate radiation dose (not surrogates for dose) from a variety of clinical CT protocols.

The Relationship of Fear of Intimacy, Body Image Avoidance and Body Mass Index

Issues of body image and ability to achieve intimacy are connected to body weight, yet remain largely unexplored and have not been evaluated by gender. The underlying purpose of this research was to determine if avoidant attitudes and perceptions of one’s body may hold implications toward its use in intimate interactions, and if an above average body weight would tend to increase this avoidance. The National Health and Nutrition Examination Survey (NHANES, 1999-2002) finds that 64.5% of US adults are overweight, with 61.9% of women and 67.2% of men. The increasing prevalence of overweight and obesity in men and women shows no reverse trend, nor have prevention and treatment proven effective in the long term. The researcher gathered self-reported age, gender, height and weight data from 55 male and 58 female subjects (determined by a prospective power analysis with a desired medium effect size (r =.30) to determine body mass index (BMI), determining a mean age of 21.6 years and mean BMI of 25.6. Survey instruments consisted of two scales that are germane to the variables being examined. They were (1) Descutner and Thelen of the University of Missouri’s (1991) Fear-of-Intimacy scale and (2) Rosen, Srebnik, Saltzberg, and Wendt’s (1991) Body Image Avoidance Questionnaire. Results indicated that as body mass index increases, fear of intimacy increases (p<0.05) and that as body mass index increases, body image avoidance increases (p<0.05). The relationship that as body image avoidance increases, fear of intimacy increases was not supported, but approached significance at (p<0.07). No differences in these relationships were determined between gender groups. For age, the only observed relationship was that of a difference between scores for age groups [18 to 22 (group 1) and ages 23 to 34 (group 2)] for the relationship of body image avoidance and fear of intimacy (p<0.02). The results suggest that the relationship of body image avoidance and fear of intimacy, as well as age, bear consideration toward the escalating prevalence of overweight and obesity. An integrative approach to body weight that addresses issues of body image and intimacy may prove effective in prevention and treatment.

Renouncing the Single Image: Photography and the Realism of Abstraction

This essay addresses the issue of the relationship between abstraction and realism that it argues is at stake in the rejection of any primacy accorded to the single image, in favour of a sequencing of photographs according to certain, often novelistic and epic ideas of narrative form. Setting out from the opening text of Allan Sekula’s Fish Story, the article explores the competing tendencies towards what Georg Lukács termed ‘narration’ and ‘description’ as these are traced throughout Sekula's project (in part through a comparison with the contrasting works of Andreas Gursky). The essay concludes by suggesting the ways in which it is the irreducible actuality of abstraction within the concrete everydayness of capitalism's social world that means that all photographic ‘realism’ is intrinsically ‘haunted’ by a certain spectre of that ‘self-moving substance in the ‘shape of money’, as Marx calls it, or of the abstract form of capital itself.

Leveraging Multiple Features for Image Retrieval and Matching

The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task. In this work, we focus on leveraging multiple features for accurate and efficient image retrieval and matching. We first propose two graph-based approaches to rerank initially retrieved images for generic image retrieval. In the graph, vertices are images while edges are similarities between image pairs. Our first approach employs a mixture Markov model based on a random walk model on multiple graphs to fuse graphs. We introduce a probabilistic model to compute the importance of each feature for graph fusion under a naive Bayesian formulation, which requires statistics of similarities from a manually labeled dataset containing irrelevant images. To reduce human labeling, we further propose a fully unsupervised reranking algorithm based on a submodular objective function that can be efficiently optimized by greedy algorithm. By maximizing an information gain term over the graph, our submodular function favors a subset of database images that are similar to query images and resemble each other. The function also exploits the rank relationships of images from multiple ranked lists obtained by different features. We then study a more well-defined application, person re-identification, where the database contains labeled images of human bodies captured by multiple cameras. Re-identifications from multiple cameras are regarded as related tasks to exploit shared information. We apply a novel multi-task learning algorithm using both low level features and attributes. A low rank attribute embedding is joint learned within the multi-task learning formulation to embed original binary attributes to a continuous attribute space, where incorrect and incomplete attributes are rectified and recovered. To locate objects in images, we design an object detector based on object proposals and deep convolutional neural networks (CNN) in view of the emergence of deep networks. We improve a Fast RCNN framework and investigate two new strategies to detect objects accurately and efficiently: scale-dependent pooling (SDP) and cascaded rejection classifiers (CRC). The SDP improves detection accuracy by exploiting appropriate convolutional features depending on the scale of input object proposals. The CRC effectively utilizes convolutional features and greatly eliminates negative proposals in a cascaded manner, while maintaining a high recall for true objects. The two strategies together improve the detection accuracy and reduce the computational cost.

The role of context in image annotation and recommendation

With the rise of smart phones, lifelogging devices (e.g. Google Glass) and popularity of image sharing websites (e.g. Flickr), users are capturing and sharing every aspect of their life online producing a wealth of visual content. Of these uploaded images, the majority are poorly annotated or exist in complete semantic isolation making the process of building retrieval systems difficult as one must firstly understand the meaning of an image in order to retrieve it. To alleviate this problem, many image sharing websites offer manual annotation tools which allow the user to “tag” their photos, however, these techniques are laborious and as a result have been poorly adopted; Sigurbjörnsson and van Zwol (2008) showed that 64% of images uploaded to Flickr are annotated with < 4 tags. Due to this, an entire body of research has focused on the automatic annotation of images (Hanbury, 2008; Smeulders et al., 2000; Zhang et al., 2012a) where one attempts to bridge the semantic gap between an image’s appearance and meaning e.g. the objects present. Despite two decades of research the semantic gap still largely exists and as a result automatic annotation models often offer unsatisfactory performance for industrial implementation. Further, these techniques can only annotate what they see, thus ignoring the “bigger picture” surrounding an image (e.g. its location, the event, the people present etc). Much work has therefore focused on building photo tag recommendation (PTR) methods which aid the user in the annotation process by suggesting tags related to those already present. These works have mainly focused on computing relationships between tags based on historical images e.g. that NY and timessquare co-exist in many images and are therefore highly correlated. However, tags are inherently noisy, sparse and ill-defined often resulting in poor PTR accuracy e.g. does NY refer to New York or New Year? This thesis proposes the exploitation of an image’s context which, unlike textual evidences, is always present, in order to alleviate this ambiguity in the tag recommendation process. Specifically we exploit the “what, who, where, when and how” of the image capture process in order to complement textual evidences in various photo tag recommendation and retrieval scenarios. In part II, we combine text, content-based (e.g. # of faces present) and contextual (e.g. day-of-the-week taken) signals for tag recommendation purposes, achieving up to a 75% improvement to precision@5 in comparison to a text-only TF-IDF baseline. We then consider external knowledge sources (i.e. Wikipedia & Twitter) as an alternative to (slower moving) Flickr in order to build recommendation models on, showing that similar accuracy could be achieved on these faster moving, yet entirely textual, datasets. In part II, we also highlight the merits of diversifying tag recommendation lists before discussing at length various problems with existing automatic image annotation and photo tag recommendation evaluation collections. In part III, we propose three new image retrieval scenarios, namely “visual event summarisation”, “image popularity prediction” and “lifelog summarisation”. In the first scenario, we attempt to produce a rank of relevant and diverse images for various news events by (i) removing irrelevant images such memes and visual duplicates (ii) before semantically clustering images based on the tweets in which they were originally posted. Using this approach, we were able to achieve over 50% precision for images in the top 5 ranks. In the second retrieval scenario, we show that by combining contextual and content-based features from images, we are able to predict if it will become “popular” (or not) with 74% accuracy, using an SVM classifier. Finally, in chapter 9 we employ blur detection and perceptual-hash clustering in order to remove noisy images from lifelogs, before combining visual and geo-temporal signals in order to capture a user’s “key moments” within their day. We believe that the results of this thesis show an important step towards building effective image retrieval models when there lacks sufficient textual content (i.e. a cold start).

Cross-linguistic influences in the phonetic and lexical component in English, Baque and Spanish: Contextual and individual factors in language acquisition and attrition.

350 p.

Body image dissatisfaction and low self-esteem due to physical appeareance in students of the faculty of medicine at the university of los andes (mérida, venezuela)

The purpose of this investigation was to evaluate body image dissatisfaction in relation to low self-esteem due to physical appearance in students of the Faculty of Medicine at the University of Los Andes in Mérida, Venezuela.  It was a non-experimental and correlational study.  The sample included 189 students (27% male and 73% female) with an average age of 19.58 ± 1.57 (men: 19.81 years of age ± 1.74 and women: 20.24 years of age ± 1.76).  Participants were intentionally selected from first-year courses of the Medicine, Nursing and Nutrition programs.  The Body Shape Questionnaire (BSQ) (Cooper and Taylor, 1987) was the instrument used to measure body image dissatisfaction and Graffar’s modified method (Méndez and De Méndez, 1994) was applied to determine the participants’ socioeconomic status.  A descriptive analysis (frequency, percentages, mean) and an inferential analysis (one-way ANOVA) were applied to the data using SPSS (Statistical Package for Social Sciences) version 9.0.  One of the most important findings in this study was the determination of a statistically significant relationship between dissatisfaction and body image and between low self-esteem and gender χ2 (2, N= 189) = 9.686, p=0.008.  Using ANOVA also helped determine that differences in the mean for dissatisfaction and low self-esteem levels with body image and gender are statistically significant, F= 11.236; p=0.008, F=10.23; p=0.002, respectively.  Conclusions: results obtained suggest a relationship between dissatisfaction and low self-esteem due to physical appearance. Consequently, subjects reject their body image because of a distorted or undistorted perception of their physical appearance, which can possibly affect self-esteem.  Moreover, it is observed that the students’ psychological health is more related to their satisfaction with their body-image than to the way their body image is perceived. Consequently, this group of participants must be analyzed regarding their self-esteem due to body image, as an expression in the institutional environment.  It is also important to emphasize that gender may be a risk factor concerning eating disorders.  We believe the foregoing because women showed higher dissatisfaction levels because of their physical appearance being conditioned by a higher dissatisfaction with their perceived body image, which is characterized by an overestimation of the physical dimension of their body image.