AN INCREASINGLY ENTREPRENEURIAL MINDSET AMONG TOP AND MIDDLE MANAGEMENT IN A STRATEGIC IMPLEMENTATION

This paper seeks to outline the implications of an increasingly entrepreneurial mindset among top and middle management on the execution of key managerial activities in a successful strategic implementation and the interrelated outcomes. The intention is the draw valid managerial implications for those considering strategic change as well as implications for future research. The research contributed to literature by composing a model to unify the disparate theories on managerial activities in strategic implementation. Research found that an increasingly entrepreneurial mindset influences all five necessary managerial activities for successful implementation of strategic renewal. Research found that, with an increasingly entrepreneurial mindset, managerial activities became progressively interwoven. These five activities influence management mindset, however they do so indirectly – either through the organisational factors or outcomes in strategic implementation. The outcomes from managerial activities that are influenced by an increasingly entrepreneurial mindset are also increasingly entrepreneurial. As a result, there is a potentially positive loop between an increasingly entrepreneurial mindset, managerial activities for strategic renewal and increasingly entrepreneurial outcomes

The Jefferson Scale of Empathy: a nationwide study of measurement properties, underlying components, latent variable structure, and national norms in medical students.

The Jefferson Scale of Empathy (JSE) is a broadly used instrument developed to measure empathy in the context of health professions education and patient care. Evidence in support of psychometrics of the JSE has been reported in health professions students and practitioners with the exception of osteopathic medical students. This study was designed to examine measurement properties, underlying components, and latent variable structure of the JSE in a nationwide sample of first-year matriculants at U.S. colleges of osteopathic medicine, and to develop a national norm table for the assessment of JSE scores. A web-based survey was administered at the beginning of the 2017-2018 academic year which included the JSE, a scale to detect good impression responses, and demographic/background information. Usable surveys were received from 6009 students enrolled in 41 college campuses (median response rate = 92%). The JSE mean score and standard deviation for the sample were 116.54 and 10.85, respectively. Item-total score correlations were positive and statistically significant (p \u3c 0.01), and Cronbach α = 0.82. Significant gender differences were observed on the JSE scores in favor of women. Also, significant differences were found on item scores between top and bottom third scorers on the JSE. Three factors of Perspective Taking, Compassionate Care, and Walking in Patient\u27s Shoes emerged in an exploratory factor analysis by using half of the sample. Results of confirmatory factor analysis with another half of the sample confirmed the 3-factor model. We also developed a national norm table which is the first to assess students\u27 JSE scores against national data

DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling

Vehicle trajectory prediction is crucial for autonomous driving and advanced driver assistant systems. While existing approaches may sample from a predicted distribution of vehicle trajectories, they lack the ability to explore it -- a key ability for evaluating safety from a planning and verification perspective. In this work, we devise a novel approach for generating realistic and diverse vehicle trajectories. We extend the generative adversarial network (GAN) framework with a low-dimensional approximate semantic space, and shape that space to capture semantics such as merging and turning. We sample from this space in a way that mimics the predicted distribution, but allows us to control coverage of semantically distinct outcomes. We validate our approach on a publicly available dataset and show results that achieve state-of-the-art prediction performance, while providing improved coverage of the space of predicted trajectory semantics.Comment: 8 pages, 5 figures, 1 tabl

A High-Rate, Heterogeneous Data Set from the Darpa Urban Challenge

This paper describes a data set collected by MIT’s autonomous vehicle Talos during the 2007 DARPA Urban Challenge. Data from a high-precision navigation system, five cameras, 12 SICK planar laser range scanners, and a Velodyne high-density laser range scanner were synchronized and logged to disk for 90 km of travel. In addition to documenting a number of large loop closures useful for developing mapping and localization algorithms, this data set also records the first robotic traffic jam and two autonomous vehicle collisions. It is our hope that this data set will be useful to the autonomous vehicle community, especially those developing robotic perception capabilities.United States. Defense Advanced Research Projects Agency (Urban Challenge, ARPA Order No. W369/00, Program Code DIRO, issued by DARPA/CMO under Contract No. HR0011-06-C-0149

BMQ

BMQ: Boston Medical Quarterly was published from 1950-1966 by the Boston University School of Medicine and the Massachusetts Memorial Hospitals. Pages 49-52, v17n2, provided courtesy of Howard Gotlieb Archival Research Center

Perception fields: analysing distributions of optical features as a proximity navigation tool for autonomous probes around asteroids

This paper suggests a new way of interpreting visual information perceived by visible cameras in the proximity of small celestial bodies. At close ranges, camera-based perception processes generally rely on computational constructs known as features. Our hypothesis is that trends in the quantity of available optical features can be correlated to variations in the angular distance from the source of illumination. Indeed, the discussed approach is based on treating properties related to these detected optical features as readings of a field - the perception fields of the title, assumed induced by the coupling of the environmental conditions and the state of the sensing device. The extreme spectrum of shapes, surface properties and gravity fields of small celestial bodies heavily affects visual proximity operational procedures. Therefore, self-contained ancillary tools providing context and an evaluation of estimators' performance while using the least number of priors are extremely significant in these conditions. This preliminary study presents an analysis of the occurrences of optical feature observed around two asteroids, 101955 Bennu and (8567) 1996 HW1 in visual data simulated within Blender, a computer graphics engine. The comparison of three different feature detectors showed distinctive trends in the distribution of the detected optical features, directly correlated to the spacecraft-target-Sun angle, confirming our hypothesis