The Limits of Evaluating Sustainability

Designing technology with sustainability in mind is becoming more and more important, especially considering future scenarios of limited resources where the world’s current lifestyle of wasteful consumption needs to change. But how can researchers believably argue that their solutions are indeed sustainable? How can consumers and technology users reliably acquire, understand, and apply information about environmental sustainability? Those questions are difficult to answer, especially in research domains where the impact on sustainability is not immediately measurable, such as sustainable HCI. The evaluation of sustainability is an ongoing problem that is often glossed over, but we believe the community needs to intensify its efforts to articulate its evaluation methods to other disciplines and external stakeholders. Even if those disciplines and stakeholders understand the importance of designing for sustainability, we need convincing arguments – such as validation through thorough evaluations – to showcase why a specific design solution works in the real world. In this paper, we analyze this problem by highlighting examples of sustainable HCI research in which evaluation of sustainability failed. We also look at previous research that sought to address this issue and discuss how their solutions can be generalized – and when they might fail. While we do not have the final answer, our intention is to start a discussion as to why sustainable HCI research is oftentimes not doing enough to justify the validity of its solutions. We close our paper by suggesting a few examples of what we believe to be potential ways to address those issues and take action to improve the evaluation of sustainability

Accessible PDFs : applying artificial intelligence for automated remediation of STEM PDFs

People with visual impairments use assistive technology, e.g., screen readers, to navigate and read PDFs. However, such screen readers need extra information about the logical structure of the PDF, such as the reading order, header levels, and mathematical formulas, described in readable form to navigate the document in a meaningful way. This logical structure can be added to a PDF with tags. Creating tags for a PDF is time-consuming, and requires awareness and expert knowledge. Hence, most PDFs are left untagged, and as a result, they are poorly readable or unreadable for people who rely on screen readers. STEM documents are particularly problematic with their complex document structure and complicated mathematical formulae. These inaccessible PDFs present a major barrier for people with visual impairments wishing to pursue studies or careers in STEM fields, who cannot easily read studies and publications from their field. The goal of this Ph.D. is to apply artificial intelligence for document analysis to reasonably automate the remediation process of PDFs and present a solution for large mathematical formulae accessibility in PDFs. With these new methods, the Ph.D. research aims to lower barriers to creating accessible scientific PDFs, by reducing the time, effort, and expertise necessary to do so, ultimately facilitating greater access to scientific documents for people with visual impairments

Social network market: Storytelling on a web 2.0 original literature site

This article looks at a Chinese Web 2.0 original literature site, Qidian, in order to show the coevolution of market and non-market initiatives. The analytic framework of social network markets (Potts et al., 2008) is employed to analyse the motivations of publishing original literature works online and to understand the support mechanisms of the site, which encourage readers’ willingness to pay for user-generated content. The co-existence of socio-cultural and commercial economies and their impact on the successful business model of the site are illustrated in this case. This article extends the concept of social network markets by proposing the existence of a ripple effect of social network markets through convergence between PC and mobile internet, traditional and internet publishing, and between publishing and other cultural industries. It also examines the side effects of social network markets, and the role of market and non-market strategies in addressing the issues

CSF Metabolic and Proteomic Profiles in Patients Prodromal for Psychosis

BACKGROUND: The initial prodromal state of psychosis (IPS) is defined as an early disease stage prior to the onset of overt psychosis characterized by sub-threshold or more unspecific psychiatric symptoms. Little is known regarding the biochemical changes during this period. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the metabolic/proteomic profiles of cerebrospinal fluid (CSF) of first-onset drug naïve paranoid schizophrenia patients (n = 54) and individuals presenting with initial prodromal symptoms (n = 24), alongside healthy volunteers (n = 70) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy and surface enhanced laser desorption ionization (SELDI) mass spectrometry, respectively. Partial least square discriminant analysis (PLS-DA) showed that 36%/29% of IPS patients displayed proteomic/metabolic profiles characteristic of first-onset, drug naïve schizophrenia, i.e., changes in levels of glucose and lactate as well as changes in a VGF-derived peptide (VGF23-62) and transthyretin protein concentrations. However, only 29% (n = 7) of the investigated IPS patients (who to date have been followed up for up to three years) have so far received a diagnosis of schizophrenia. The presence of biochemical alterations in the IPS group did not correlate with the risk to develop schizophrenia. CONCLUSIONS/SIGNIFICANCE: Our results imply that schizophrenia-related biochemical disease processes can be traced in CSF of prodromal patients. However, the biochemical disturbances identified in IPS patients, at least when measured at a single time point, may not be sufficient to predict clinical outcome

The Structure-Function Linkage Database

The Structure–Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure–function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies ‘look alike’, making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity

Developmental variations in plasma leptin, leptin soluble receptor and their molar ratio in healthy infants

<p>Abstract</p> <p>Background</p> <p>Leptin and its soluble receptor (sOB-R) are important to regulation of body composition but there are no data on the developmental variations in these plasma variables and their relationship with body composition measurements,</p> <p>Methods</p> <p>Weight, length, and body composition (bone, fat and lean mass) by dual energy absorptiometry, and plasma variables were measured in healthy infants at 2, 4, 8 and 12 months.</p> <p>Results</p> <p>15 whites and 29 African Americans (21 males and 23 females) with mean birth weight 3357 +/- 45 (SEM) g and gestation of 39.3 +/- 0.17 weeks were studied. The overall Z score for weight, length and weight for length during the study were 0.00 +/- 0.15, -0.08 +/- 0.11 and 0.12 +/- 0.14 respectively. With increasing age, plasma leptin (1.0 to 18.2, median 5.5 ng/mL) and sOB-R:leptin molar ratio (10.1 to 247.4, median 59.9) were lowered (r = -0.47, p < 0.01; and r = -0.37, p < 0.05 respectively), best predicted by weight Z score and percentage of fat mass, and higher in African American and female. Presence of body composition measurements eliminated the race and gender effect on the plasma variables. Plasma sOB-R (49.5 to 173.9, median 81.3 ng/mL) did not change significantly with age and was correlated and predicted only by body composition measurements.</p> <p>Conclusion</p> <p>In healthy growing infants, plasma leptin but not sOB-R decreases with age. Gender, race and anthropometric measurements are additional physiological determinants predictive of plasma leptin and the receptor:ligand ratio. However, body composition is the only variable that can predict plasma leptin and its soluble receptor and the receptor: ligand ratio; and body composition measurements eliminated the race and gender effect on these plasma variables.</p

Mild cognitive impairment is associated with poor physical function but not bone structure or density in late adulthood:Findings from the Hertfordshire Cohort Study

Mini Abstract This study investigated the association between mild cognitive impairment (MCI) and physical function and bone health in older adults. MCI was associated with poor physical performance but not bone mineral density or bone microarchitecture. Abstract Purpose: Cross-sectional study to investigate the association between mild cognitive impairment (MCI) and physical performance, and bone health, in a community-dwelling cohort of older adults. Methods: Cognitive function of 222 men and 221 women (mean age 75.5 and 75.8 years in men and women, respectively) was assessed by the Strawbridge questionnaire and Mini Mental State Exam (MMSE). Participants underwent dual-energy x-ray absorptiometry (DXA), peripheral-quantitative computed tomography (pQCT) and high-resolution peripheral-quantitative computed tomography (HR-pQCT) scans to assess their bone density, strength and microarchitecture. Their physical function was assessed and a physical performance (PP) score was recorded. Results: 11.8% of women and 8.1% of men in the study were cognitive impaired on the MMSE (score&lt;24). 24% of women were deemed cognitively impaired on the Strawbridge questionnaire, compared to 22.3% of men. Cognitive impairment on the Strawbridge questionnaire was associated with poorer physical performance score in men but not women in the unadjusted analysis. MMSE &lt;24 was strongly associated with the risk of low physical performance in men (OR 12.9, 95% CI 1.67, 99.8, p=0.01) Higher MMSE score was associated with better physical performance in both sexes. Poorer cognitive function, whether assessed by the Strawbridge questionnaire, or by MMSE score, was not associated with bone density, shape or microarchitecture, in either sex. Conclusion: MCI in older adults was associated with poor physical performance, but not bone density, shape or microarchitecture