765 resultados para Self-help techniques.
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We propose an accurate technique for obtaining highly collimated beams, which also allows testing the collimation degree of a beam. It is based on comparing the period of two different self-images produced by a single diffraction grating. In this way, variations in the period of the diffraction grating do not affect to the measuring procedure. Self-images are acquired by two CMOS cameras and their periods are determined by fitting the variogram function of the self-images to a cosine function with polynomial envelopes. This way, loss of accuracy caused by imperfections of the measured self-images is avoided. As usual, collimation is obtained by displacing the collimation element with respect to the source along the optical axis. When the period of both self-images coincides, collimation is achieved. With this method neither a strict control of the period of the diffraction grating nor a transverse displacement, required in other techniques, are necessary. As an example, a LED considering paraxial approximation and point source illumination is collimated resulting a resolution in the divergence of the beam of σ φ = ± μrad.
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In the last decade, vertical-external-cavity surface-emitting lasers (VECSELs) have become promising sources of ultrashort laser pulses. While the mode-locked operation has been strongly relying on costly semiconductor saturable-Absorber mirrors for many years, new techniques have been found for pulse formation. Mode-locking VECSELs are nowadays not only achievable by using a variety of saturable absorbers, but also by using a saturable-Absorber-free technique referred to as self-mode-locking (SML), which is to be highlighted here.
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We report the results of a study into the factors controlling the quality of nanolithographic imaging. Self-assembled monolayer (SAM) coverage, subsequent postetch pattern definition, and minimum feature size all depend on the quality of the Au substrate used in material mask atomic nanolithographic experiments. We find that sputtered Au substrates yield much smoother surfaces and a higher density of {111}-oriented grains than evaporated Au surfaces. Phase imaging with an atomic force microscope shows that the quality and percentage coverage of SAM adsorption are much greater for sputtered Au surfaces. Exposure of the self-assembled monolayer to an optically cooled atomic Cs beam traversing a two-dimensional array of submicron material masks mounted a few microns above the self-assembled monolayer surface allowed determination of the minimum average Cs dose (2 Cs atoms per self-assembled monolayer molecule) to write the monolayer. Suitable wet etching, with etch rates of 2.2 nm min-1, results in optimized pattern definition. Utilizing these optimizations, material mask features as small as 230 nm in diameter with a fractional depth gradient of 0.820 nm were realized.
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X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.
A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.
Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.
The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).
First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.
Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.
Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.
The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.
To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.
The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.
The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.
Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.
The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.
In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.
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The focus on how one is behaving, feeling, and thinking, provides a powerful source of self-knowledge. How is this self-knowledge utilized in the dynamic reconstruction of autobiographical memories? How, in turn, might autobiographical memories support identity and the self-system? I address these questions through a critical review of the literature on autobiographical memory and the self-system, with a special focus on the self-concept, self-knowledge, and identity. I then outline the methods and results of a prospective longitudinal study examining the effects of an identity change on memory for events related to that identity. Participant-rated memory characteristics, computer-generated ratings of narrative content and structure, and neutral-observer ratings of coherence were examined for changes over time related to an identity-change, as well as for their ability to predict an identity-change. The conclusions from this study are threefold: (1) when the rated centrality of an event decreases, the reported instances of retrieval, as well as the phenomenology associated with retrieval and the number of words used to describe the memory, also decrease; (2) memory accuracy (here, estimating past behaviors) was not influenced by an identity change; and (3) remembering is not unidirectional – characteristics of identity-relevant memories and the life story predict and may help support persistence with an identity (here, an academic trajectory).
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Background: Rates of self-harm are high and have recently increased. This trend and the repetitive nature of self-harm pose a significant challenge to mental health services. Aims: To determine the efficacy of a structured group problem-solving skills training (PST) programme as an intervention approach for self-harm in addition to treatment as usual (TAU) as offered by mental health services. Method: A total of 433 participants (aged 18-64 years) were randomly assigned to TAU plus PST or TAU alone. Assessments were carried out at baseline and at 6-week and 6-month follow-up and repeated hospital-treated self-harm was ascertained at 12-month follow-up. Results: The treatment groups did not differ in rates of repeated self-harm at 6-week, 6-month and 12-month follow-up. Both treatment groups showed significant improvements in psychological and social functioning at follow-up. Only one measure (needing and receiving practical help from those closest to them) showed a positive treatment effect at 6-week (P = 0.004) and 6-month (P = 0.01) follow-up. Repetition was not associated with waiting time in the PST group. Conclusions: This brief intervention for self-harm is no more effective than treatment as usual. Further work is required to establish whether a modified, more intensive programme delivered sooner after the index episode would be effective.
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Ultrasound guidance is now a standard nerve localization technique for peripheral nerve block (PNB). Ultrasonography allows simultaneous visualization of the target nerve, needle, local anesthetic injectate and surrounding anatomical structures. Accurate deposition of local anesthetic next to the nerve is essential to the success of the nerve block procedure. Unfortunately, due to limitations in the visibility of both needle tip and nerve surface, the precise relationship between needle tip and target nerve is unknown at the moment of injection. Importantly, nerve injury may result both from an inappropriately placed needle tip and inappropriately placed local anesthetic. The relationship between the block needle tip and target nerve is of paramount importance to the safe conduct of peripheral nerve block. This review summarizes the evolution of nerve localization in regional anesthesia, characterizes a problem faced by clinicians in performing ultrasound guided nerve block and explores the potential technological solutions to this problem.
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Abstract Complexity science and its methodological applications have increased in popularity in social science during the last two decades. One key concept within complexity science is that of self-organization. Self-organization is used to refer to the emergence of stable patterns through autonomous and self-reinforcing dynamics at the micro-level. In spite of its potential relevance for the study of social dynamics, the articulation and use of the concept of self-organization has been kept within the boundaries of complexity science and links to and from mainstream social science are scarce. These links can be difficult to establish, even for researchers working in social complexity with a background in social science, because of the theoretical and conceptual diversity and fragmentation in traditional social science. This article is meant to serve as a first step in the process of overcoming this lack of cross-fertilization between complexity and mainstream social science. A systematic review of the concept of self-organization and a critical discussion of similar notions in mainstream social science is presented, in an effort to help practitioners within subareas of complexity science to identify literature from traditional social science that could potentially inform their research.
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This article makes a contribution to a growing number of works that discuss affect and social media. I use Freudian affect theory to analyse user posts on the public Site Governance Facebook page. Freud’s work may help us to explore the affectivity within the user narratives and I suggest that they are expressions of alienation, dispossession and powerlessness that relate to the users’ relations with Facebook as well as to their internal and wider social relations. The article thus introduces a new angle on studies of negative user experiences that draws on psychoanalysis and critical theory.
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The recent crisis of the capitalistic economic system has altered the working conditions and occupations in the European Union. The recession situation has accelerated trends and has brought transformations that have been observed before. Changes have not looked the same way in all the countries of the Union. The social occupation norms, labour relations models and the type of global welfare provision can help underline some of these inequalities. Poor working conditions can expose workers to situations of great risk. This is one of the basic assumptions of the theoretical models and analytical studies of the approach to the psychosocial work environment. Changes in working conditions of the population seems to be important to explain in the worst health states. To observe these features in the current period of economic recession it has made a comparative study of trend through the possibilities of the European Working Conditions Survey in the 2005 and 2010 editions. It has also set different multivariate logistic regression models to explore potential partnerships with the worst conditions of employment and work. It seems that the economic crisis has intensified changes in working conditions and highlighted the effects of those conditions on the poor health of the working population. This conclusion can’t be extended for all EU countries; some differences were observed in terms of global welfare models.
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Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.
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Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.
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This paper focuses on two basic issues: the anxiety-generating nature of the interpreting task and the relevance of interpreter trainees’ academic self-concept. The first has already been acknowledged, although not extensively researched, in several papers, and the second has only been mentioned briefly in interpreting literature. This study seeks to examine the relationship between the anxiety and academic self-concept constructs among interpreter trainees. An adapted version of the Foreign Language Anxiety Scale (Horwitz et al., 1986), the Academic Autoconcept Scale (Schmidt, Messoulam & Molina, 2008) and a background information questionnaire were used to collect data. Students’ t-Test analysis results indicated that female students reported experiencing significantly higher levels of anxiety than male students. No significant gender difference in self-concept levels was found. Correlation analysis results suggested, on the one hand, that younger would-be interpreters suffered from higher anxiety levels and students with higher marks tended to have lower anxiety levels; and, on the other hand, that younger students had lower self-concept levels and higher-ability students held higher self-concept levels. In addition, the results revealed that students with higher anxiety levels tended to have lower self-concept levels. Based on these findings, recommendations for interpreting pedagogy are discussed.
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Two experiments investigated the consequences of action at encoding and recall on the ability to follow sequences of instructions. Children aged 7–9 years recalled sequences of spoken action commands under presentation and recall conditions that either did or did not involve their physical performance. In both experiments, recall was enhanced by carrying out the instructions as they were being initially presented and also by performing them at recall. In contrast, the accuracy of instruction-following did not improve above spoken presentation alone, either when the instructions were silently read or heard by the child (Experiment 1), or when the child repeated the spoken instructions as they were presented (Experiment 2). These findings suggest that the enactment advantage at presentation does not simply reflect a general benefit of a dual exposure to instructions, and that it is not a result of their self-production at presentation. The benefits of action-based recall were reduced following enactment during presentation, suggesting that the positive effects of action at encoding and recall may have a common origin. It is proposed that the benefits of physical movement arise from the existence of a short-term motor store that maintains the temporal, spatial, and motoric features of either planned or already executed actions.
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Funded by HSC R&D Division, Public Health Agency Why did we start? Most people who complete suicide are in contact with their family doctors or other services in the months prior to death. A better understanding of the nature of these contacts and the various pathways experienced by suicidal people should reveal the gaps and barriers to effective service provision. We also need better information about the difficulties experienced by family carers, both prior to the death and afterwards. Of particular interest to policy makers in Northern Ireland was a concern that people from rural areas may be at increasing risk of suicide. We were commissioned by the Health and Social Care R&D Division of the Northern Ireland Public Health Agency to address the gaps in our understanding of suicide in NI. What did we do? We undertook a mixed methods study in which we examined the records of 403 people who took their own lives over a two-year period between March 2007 and February 2009. We linked these data to GP records and then examined help-seeking pathways of people and their contacts with services. We did in-depth face-to-face interviews with 72 bereaved relatives and friends who discussed their understanding of the events and circumstances surrounding the death, the experience of seeking help for the family member, the personal impact of the suicide, and use of support services. Additionally, we interviewed 19 General Practitioners about their experiences of managing people who died by suicide.