Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis

Many subproblems in automated skin lesion diagnosis (ASLD) canbe unified under a single generalization of assigning a label, from an predefinedset, to each pixel in an image. We first formalize this generalizationand then present two probabilistic models capable of solving it. The firstmodel is based on independent pixel labeling using maximum a-posteriori(MAP) estimation. The second model is based on conditional randomfields (CRFs), where dependencies between pixels are defined using agraph structure. Furthermore, we demonstrate how supervised learningand an appropriate training set can be used to automatically determineall model parameters. We evaluate both models\u27 ability to segment achallenging dataset consisting of 116 images and compare our results to5 previously published methods

Skin Roughness Assessment

Non

Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis

Many subproblems in automated skin lesion diagnosis (ASLD) can be unified under a single generalization of assigning a label, from an predefined set, to each pixel in an image. We first formalize this generalization and then present two probabilistic models capable of solving it. The first model is based on independent pixel labeling using maximum a-posteriori (MAP) estimation. The second model is based on conditional random fields (CRFs), where dependencies between pixels are defined using a graph structure. Furthermore, we demonstrate how supervised learning and an appropriate training set can be used to automatically determine all model parameters. We evaluate both models' ability to segment a challenging dataset consisting of 116 images and compare our results to 5 previously published methods

Real-Time Raman Spectroscopy for Noninvasive in vivo Skin Analysis and Diagnosis

Non

HOXB5 Cooperates with NKX2-1 in the Transcription of Human RET

The enteric nervous system (ENS) regulates peristaltic movement of the gut, and abnormal ENS causes Hirschsprung's disease (HSCR) in newborns. HSCR is a congenital complex genetic disorder characterised by a lack of enteric ganglia along a variable length of the intestine. The receptor tyrosine kinase gene (RET) is the major HSCR gene and its expression is crucial for ENS development. We have previously reported that (i) HOXB5 transcription factor mediates RET expression, and (ii) mouse with defective HOXB5 activity develop HSCR phenotype. In this study, we (i) elucidate the underlying mechanisms that HOXB5 mediate RET expression, and (ii) examine the interactions between HOXB5 and other transcription factors implicated in RET expression. We show that human HOXB5 binds to the promoter region 5′ upstream of the binding site of NKX2-1 and regulates RET expression. HOXB5 and NKX2-1 form a protein complex and mediate RET expression in a synergistic manner. HSCR associated SNPs at the NKX2-1 binding site (-5G>A rs10900296; -1A>C rs10900297), which reduce NKX2-1 binding, abolish the synergistic trans-activation of RET by HOXB5 and NKX2-1. In contrast to the synergistic activation of RET with NKX2-1, HOXB5 cooperates in an additive manner with SOX10, PAX3 and PHOX2B in trans-activation of RET promoter. Taken together, our data suggests that HOXB5 in coordination with other transcription factors mediates RET expression. Therefore, defects in cis- or trans-regulation of RET by HOXB5 could lead to reduction of RET expression and contribute to the manifestation of the HSCR phenotype

Looking for big 'fry': the motives and methods of middle-class international property investors

Anxieties about the effects of international property investment in world cities like London have mainly focused on super-rich investors and corporate vehicles that have generated price inflation of assets and accelerated exclusion from an already expensive market. In fact, many international investors in the city’s housing market are middle-class individuals, and focusing on Hong Kong as an emblematic example of such processes, we examine their motives and the products offered to them by important investment intermediaries. We find that an important rationale for these investments lies in local class-based uncertainties and existential anxieties concerning the future of Hong Kong itself. We focus on the cultural roots of these investor rationalities but also consider the role of investment intermediaries who have helped bolster confidence while shielding investors from the consequences of their aggregated market power - concerns in London over household displacement from foreign investment. We suggest that what may seem to be the predatory search to ‘fry’ property (炒樓), a Hongkonger colloquialism referring to the search for high performing investments, should also be understood as actions anchored in and generated by the habitus of the Hong Kong middle-class whose lives have been moulded by historical geopolitical uncertainty and worries about its longer-term social positioning and security

Forecasting risk in earnings

Conventional measures of risk in earnings based on historical standard deviation require long time series data and are inadequate when the distribution of earnings deviates from normality. We introduce a methodology based on current fundamentals and quantile regression to forecast risk reflected in the shape of the distribution of future earnings. We derive measures of dispersion, asymmetry and tail risk in future earnings using quantile forecasts as inputs. Our analysis shows that a parsimonious model based on accruals, cash flow, special items and a loss indicator can predict the shape of the distribution of earnings with reasonable power. We provide evidence that out-of-sample quantile-based risk forecasts explain incrementally analysts’ equity and credit risk ratings, future return volatility, corporate bond spreads and analyst-based measures of future earnings uncertainty. Our study provides insights into the relations between earnings components and risk in future earnings. It also introduces risk measures that will be useful for participants in both the equity and credit markets

Forecasting risk in earnings

Conventional measures of risk in earnings based on historical standard deviation require long time series data and are inadequate when the distribution of earnings deviates from normality. We introduce a methodology based on current fundamentals and quantile regression to forecast risk reflected in the shape of the distribution of future earnings. We derive measures of dispersion, asymmetry and tail risk in future earnings using quantile forecasts as inputs. Our analysis shows that a parsimonious model based on accruals, cash flow, special items and a loss indicator can predict the shape of the distribution of earnings with reasonable power. We provide evidence that out-of-sample quantile-based risk forecasts explain incrementally analysts’ equity and credit risk ratings, future return volatility, corporate bond spreads and analyst-based measures of future earnings uncertainty. Our study provides insights into the relations between earnings components and risk in future earnings. It also introduces risk measures that will be useful for participants in both the equity and credit markets

In situ observations of the “preexisting auroral arc” by THEMIS all sky imagers and the FAST spacecraft

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95671/1/jgra21670.pd

(Re)Conceptualising the space of markets: The case of the 2007–9 global financial crisis

The 2007–9 period saw an unprecedented crisis emerge in global financial markets with the collapse of several large western financial institutions, and the nearest moment of systemic crisis yet witnessed in the globalised financial system. The crisis has thus provoked a significant questioning of market theories, and in particular understandings of market within orthodox neoclassical economics. Within the social sciences, a significant element of this response has built on a growing heterodox socioeconomic literature which is heavily critical of hegemonic conceptions of the market within economics. However, whilst a small body of work in economic geography has begun to engage with this literature, geographical thinking has not directly sought to conceptualise the nature and significance of market spatiality. Utilising a cultural economy approach, this paper therefore argues that economic geographical theories need to foreground the concept of market rather than treat markets as a ‘component’ of wider processes. It further contends that the concept of the ‘market’ needs to be reconceptualised in a way that captures the spatialities of markets and the difference that space makes to market behaviours and outcomes. Drawing on the growing heterodox socioeconomic literature on markets, it thus proposes a practice-oriented ‘socio-spatial approach’ for framing conceptions of market spatiality, arguing that such a spatial epistemology opens up a range of theoretical possibilities for further contesting hegemonic neoclassical theories of the market beyond current socioeconomic critiques. It seeks to illustrate the utility of such a framework through a case study analysis of the limitations inherent in existing policy practices surrounding the early phase of the recent global financial crisis