High-Level Concepts for Affective Understanding of Images

This paper aims to bridge the affective gap between image content and the emotional response of the viewer it elicits by using High-Level Concepts (HLCs). In contrast to previous work that relied solely on low-level features or used convolutional neural network (CNN) as a black-box, we use HLCs generated by pretrained CNNs in an explicit way to investigate the relations/associations between these HLCs and a (small) set of Ekman's emotional classes. As a proof-of-concept, we first propose a linear admixture model for modeling these relations, and the resulting computational framework allows us to determine the associations between each emotion class and certain HLCs (objects and places). This linear model is further extended to a nonlinear model using support vector regression (SVR) that aims to predict the viewer's emotional response using both low-level image features and HLCs extracted from images. These class-specific regressors are then assembled into a regressor ensemble that provide a flexible and effective predictor for predicting viewer's emotional responses from images. Experimental results have demonstrated that our results are comparable to existing methods, with a clear view of the association between HLCs and emotional classes that is ostensibly missing in most existing work

Passion Isn\u27t Always a Good Thing: Examining Entrepreneurs\u27 Network Centrality and Financial Performance with a Dualistic Model of Passion

We propose a conceptual model that links entrepreneurs\u27 passion, network centrality, and financial performance, and test this model with small business managers in formal business networking groups. Drawing on the dualistic model of passion, we explore the relationships that harmonious and obsessive passion have with financial performance, mediated by network centrality. Results indicate that harmoniously passionate entrepreneurs had higher out‐degree centrality in their networking group (i.e., they were more inclined to seek out members to discuss work issues), which increased the income they received from peer referrals and, ultimately, business income. Obsessively passionate entrepreneurs had lower in‐degree centrality (i.e., they were less likely to be approached by peers), and in turn received less income from referrals and less business income. These findings highlight that entrepreneurial passion does not always result in positive financial outcomes – the type of passion makes a difference. Implications for research and practice are discussed

Incidental Finding of Unusually Large Renal Cyst During Point of Care Ultrasound

Renal cysts are common, and their frequency and size increase as patients age. Renal cysts are derived primarily from tubules and can occur anywhere between Bowman’s capsule to the renal papilla. The cysts are composed of abnormally differentiated epithelial cells encapsulating a cavity of fluid. These abnormally differentiated cells are due to defects in the structure and function of cilia, the structures responsible for detecting urine flow as well as the epithelial composition of the epithelial architecture and repair. According to Campbell Urology, there are three processes in which renal cysts increase in their size – proliferation of epithelial cells in the tubules, accumulation of fluid in the in the expanding tubule segment, and disturbed organization and or metabolism of the extracellular matrix. The latter includes imbalances of the secretory and absorption resulting in unusual accumulation of fluid in renal tubules. In this case report, we describe an unusually large renal cyst with mass effect found in patient during routine POCUS scan shift