The effects of video compression on acceptability of images for monitoring life sciences experiments

Future manned space operations for Space Station Freedom will call for a variety of carefully planned multimedia digital communications, including full-frame-rate color video, to support remote operations of scientific experiments. This paper presents the results of an investigation to determine if video compression is a viable solution to transmission bandwidth constraints. It reports on the impact of different levels of compression and associated calculational parameters on image acceptability to investigators in life-sciences research at ARC. Three nonhuman life-sciences disciplines (plant, rodent, and primate biology) were selected for this study. A total of 33 subjects viewed experimental scenes in their own scientific disciplines. Ten plant scientists viewed still images of wheat stalks at various stages of growth. Each image was compressed to four different compression levels using the Joint Photographic Expert Group (JPEG) standard algorithm, and the images were presented in random order. Twelve and eleven staffmembers viewed 30-sec videotaped segments showing small rodents and a small primate, respectively. Each segment was repeated at four different compression levels in random order using an inverse cosine transform (ICT) algorithm. Each viewer made a series of subjective image-quality ratings. There was a significant difference in image ratings according to the type of scene viewed within disciplines; thus, ratings were scene dependent. Image (still and motion) acceptability does, in fact, vary according to compression level. The JPEG still-image-compression levels, even with the large range of 5:1 to 120:1 in this study, yielded equally high levels of acceptability. In contrast, the ICT algorithm for motion compression yielded a sharp decline in acceptability below 768 kb/sec. Therefore, if video compression is to be used as a solution for overcoming transmission bandwidth constraints, the effective management of the ratio and compression parameters according to scientific discipline and experiment type is critical to the success of remote experiments

Management of Research Data in Image Format: An Exploratory Study on Current Practices

Research data management is the basis for making data more Findable, Accessible, Interoperable and Reusable. In this context, little attention is given to research data in image format. This article presents the preliminary results of a study on the habits related to the management of images in research. We collected 107 answers from researchers using a questionnaire. These researchers were PhD students, fellows and university professors from Life and Health Sciences, Exact Sciences and Engineering, Natural and Environmental Sciences and Social Sciences and Humanities. This study shows that 83.2% of researcher use images as research data, however, its use is generally not accompanied by a guidance document such as a research data management plan. These results provide valuable insights into the processes and habits regarding the production and use of images in the research context. (c) 2020, Springer Nature Switzerland AG

Large-scale analysis, management, and retrieval of biological and medical images

Biomedical image data have been growing quickly in volume, speed, and complexity, and there is an increasing reliance on the analysis of these data. Biomedical scientists are in need of efficient and accurate analyses of large-scale imaging data, as well as innovative retrieval methods for visually similar imagery across a large-scale data collection to assist complex study in biological and medical applications. Moreover, biomedical images rely on increased resolution to capture subtle phenotypes of diseases, but this poses a challenge for clinicians to sift through haystacks of visual cues to make informative diagnoses. To tackle these challenges, we developed computational methods for large-scale analysis of biological and medical imaging data using simulated annealing to improve the quality of image feature extraction. Furthermore, we designed a Big Data infrastructure for the large-scale image analysis and retrieval of digital pathology images and conducted a longitudinal study of clinician's usage patterns of an image database management system (MDID) to shed light on the potential adoption of new informatics tools. This research also resulted in image analysis, management, and retrieval applications relevant to dermatology, radiology, pathology, life sciences, and palynology disciplines. These tools provide the potential to answer research questions that would not be answerable without our novel innovations that take advantage of Big Data technologies

BP’s use of posture to respond to the deepwater horizon crisis

This paper focuses on the posture the oil company BP adopted when faced with a legitimacy crisis during one of the worst environmental disasters in history. Against a backdrop of a discussion of the rhetorical aspects of image repair discourse and organisational legitimacy, Hearit’s strategy of corporate apologia was employed to determine the posture BP adopted in relation to the crisis. This paper adds to the literature on image repair strategies by heeding a call by Hearit for the context within which corporate apologia takes place to be taken account of, an approach that warrants a distinct line of research. The literature was further extended by complementing Hearit's strategy with semiotics and analysing its use in both the annual and sustainability reports. The additional focus on the sustainability reports is important, due to the high premium placed on sustainability in the changing business environment. On a practical level this paper contributes to an understanding of how organisations use sustainability reports to respond to legitimacy challenges

Metabolic Control, Quality of Life, and Body Image in Patients with Glycogen Storage Disease Type Ia

Glycogen storage disease is a group of inborn errors of metabolism, with type Ia being the most common form of the disorder. Glycogen storage disease type Ia (GSDIa) is a multisystemic condition in which individuals have various complications secondary to an inability to properly break down glycogen and to perform gluconeogenesis. Complex management is then necessary for patients and includes dietary modification, frequent cornstarch usage, and evaluation for additional complications such as hepatic adenomas, hypertriglyceridemia, and kidney disease. Previous studies have found lower scores in quality of life and body image in GSDIa patients; however, the specific factors influencing this relationship remain unknown. In this study, 24 adult participants (n=24) with glycogen storage disease type Ia completed a survey including measures of health-related quality of life, body image, and metabolic control. Results found that quality of life was significantly lower than the general population on both the physical and mental component scores (t=-3.11, p=0.005; t=-2.21, p=0.03). Additionally, body image was significantly lower on all subscales: Weight (t=-5.88,

Conservative surgery of breast cancer in women; psychological benefits

Breast surgery was one of the most dynamic fields of medicine which benefited from significant progress during the last decades. The transition from aggressive and mutilating amputations to conservative, oncoplastic and reconstructive techniques has been constant, offering improved and rewarding results, viewed from both, oncological and aesthetical perspectives. Conservative techniques, especially those which preserve the nipple areola complex, are followed by improved patient’s perception of their body image, confidence and sexuality, with the only drawback of increased anxiety linked to recurrence risk

Treatment of osteolytic solitary painful osseous metastases with radiofrequency ablation or cryoablation: a retrospective study by propensity analysis

The present study aimed to measure the improvement in pain relief and quality of life in patients with osteolytic solitary painful bone metastasis treated by cryoablation (CA) or radiofrequency ablation (RFA). Fifty patients with solitary osteolytic painful bone metastases were retrospectively studied and selected by propensity analysis. Twenty-five patients underwent CA and the remaining twenty-five underwent RFA. Pain relief, in terms of complete response (CR), the number of patients requiring analgesia and the changes in self-rated quality of life (QoL) were measured following the two treatments. Thirty-two percent of patients treated by CA experienced a CR at 12 weeks versus 20% of patients treated by RFA. The rate of CR increased significantly with respect to baseline only in the group treated by CA. In both groups there was a significant change in the partial response with respect to baseline (36% in the CA group vs. 44% in the RFA group). The recurrence rate in the CA and RFA groups was 12% and 8%, respectively. The reduction in narcotic medication requirements with respect to baseline was only significant in the group treated by CA. A significant improvement in self-rated QoL was observed in both groups. The present study seems to suggest that CA only significantly improves the rate of CR and decreases the requirement of narcotic medications. Both CA and RFA led to an improvement in the self-rated QoL of patients after the treatments. However, the results of the present study should be considered as preliminary and to serve as a framework around which future trials may be designed

Adapting Visual Question Answering Models for Enhancing Multimodal Community Q&A Platforms

Question categorization and expert retrieval methods have been crucial for information organization and accessibility in community question & answering (CQA) platforms. Research in this area, however, has dealt with only the text modality. With the increasing multimodal nature of web content, we focus on extending these methods for CQA questions accompanied by images. Specifically, we leverage the success of representation learning for text and images in the visual question answering (VQA) domain, and adapt the underlying concept and architecture for automated category classification and expert retrieval on image-based questions posted on Yahoo! Chiebukuro, the Japanese counterpart of Yahoo! Answers. To the best of our knowledge, this is the first work to tackle the multimodality challenge in CQA, and to adapt VQA models for tasks on a more ecologically valid source of visual questions. Our analysis of the differences between visual QA and community QA data drives our proposal of novel augmentations of an attention method tailored for CQA, and use of auxiliary tasks for learning better grounding features. Our final model markedly outperforms the text-only and VQA model baselines for both tasks of classification and expert retrieval on real-world multimodal CQA data.Comment: Submitted for review at CIKM 201