Exploring Bank Managers\u27 Strategies for Developing Millennials for Leadership Roles in Commercial Banks

Understanding strategies to prepare Millennials for leadership roles in commercial banks is critical to ensure organizational stability and success and to avoid knowledge gaps and leadership deficiencies created by large numbers of retiring Baby Boomers. Guided by learning network theory and generational theory, the purpose of this multiple case study was to explore the strategies that 3 bank managers in North Carolina and South Carolina used to prepare Millennials for leadership. These 3 bank managers had a minimum of 2 years of experience leading teams of employees which included Millennials. The study included semistructured interviews to elicit detailed narratives from the bank managers on their experiences in preparing Millennials for leadership roles. Additional data included a review of public and private documents containing developmental activities and leadership program details used with Millennials. All data were analyzed and coded to identify recurring themes. Methodological triangulation was used to identify 5 key strategies used by managers to help prepare Millennials for leadership including structured development processes, generational alignment and engagement, coaching and mentoring, leveraging technology, and communications. Bank managers could use these findings to implement successful strategies to help Millennials prepare for leadership roles. Doing so promotes positive social change by identifying these strategies for bank managers to prepare key talent for leadership roles within organizations

An Open Source Pattern Recognition Toolbox for MATLAB

Pattern recognition and machine learning are becoming integral parts of algorithms in a wide range of applications. Different algorithms and approaches for machine learning include different tradeoffs between performance and computation, so during algorithm development it is often necessary to explore a variety of different approaches to a given task. A toolbox with a unified framework across multiple pattern recognition techniques enables algorithm developers the ability to rapidly evaluate different choices prior to deployment. MATLAB is a widely used environment for algorithm development and prototyping, and although several MATLAB toolboxes for pattern recognition are currently available these are either incomplete, expensive, or restrictively licensed. In this work we describe a MATLAB toolbox for pattern recognition and machine learning known as the PRT (Pattern Recognition Toolbox), licensed under the permissive MIT license. The PRT includes many popular techniques for data preprocessing, supervised learning, clustering, regression and feature selection, as well as a methodology for combining these components using a simple, uniform syntax. The resulting algorithms can be evaluated using cross-validation and a variety of scoring metrics to ensure robust performance when the algorithm is deployed. This paper presents an overview of the PRT as well as an example of usage on Fisher's Iris dataset

Early Origins of Adult Cancer Risk Among Men and Women: Influence of Childhood Misfortune?

Objective—To examine the effect of five childhood misfortune domains—parental behavior, socioeconomic status, infectious diseases, chronic diseases, and impairments—on all-site and selected site-specific cancer prevalence and all-site cancer incidence. Method—Panel data from the Health and Retirement Study (2004–2012) were used to investigate cancer risk among adults above the age of 50. Results—Risky parental behavior and impairment in childhood were associated with higher odds of all-site cancer prevalence, and childhood chronic disease was associated with prostate cancer, even after adjusting for adult health and socioeconomic factors. Moreover, having one infectious disease in childhood lowered the odds of colon cancer. Cancer trends varied by race and ethnicity, most notably, higher prostate cancer prevalence among Black men and lower all-site cancer among Hispanic adults. Discussion—These findings underscore the importance of examining multiple domains of misfortune because the type and amount of misfortune influence cancer risk in different ways

Fatigue in C/Si/Mn steels.

British Railways is a major material user. It has high maintenance costs due partly to the premature withdrawal of components from service caused by metal fatigue. The main interest in fatigue, in terms of greater component efficiency, lies in the successful prediction of life for different, variable amplitude loading conditions. This requires extensive knowledge of both the service load environment and the response of metals to variable cyclic loads. This thesis presents the results of an investigation into the cyclic behaviour of ferrite-pearlite, C/Si/Mn steels. An analytical, computer based method for predicting fatigue life, forms the basis of the approach used. The materials data required in the analysis is obtained for a series of steels containing a wide range of compositions and microstructures. This data is assessed in terms of more easily obtained mechanical properties and also in terms of the metallurgical variables. Certain assumptions in the model regarding material behaviour are also evaluated using the data. Finally, the data is used to assess the importance of material changes in variable amplitude fatigue situations.Observations of surface fatigue damage and fracture surfaces have also been carried out. This work is used to develop a theory for the formation and development of cracks in ferrite-pearlite structures.To conclude, the results of the various investigations are used to consider the future development of fatigue resistant materials

A multiple opening/closing net and environmental sensing system for sampling zooplankton

The MOCNESS is based on the Tucker Trawl principle and has nine rectangular nets (1 m × 1.4 m) which are opened and closed sequentially by commands through conducting cable from the surface. Environmental sensors to measure conductivity, temperature, and depth are attached to the net support frame. In addition, sensors to monitor flow past the net and the angle of the net assembly from the vertical, and indicators to record the electrical and mechanical function of the opening/closing mechanism are present...

Early Origins of Adult Cancer Risk Among Men and Women: Influence of Childhood Misfortune?

Objective—To examine the effect of five childhood misfortune domains—parental behavior, socioeconomic status, infectious diseases, chronic diseases, and impairments—on all-site and selected site-specific cancer prevalence and all-site cancer incidence. Method—Panel data from the Health and Retirement Study (2004–2012) were used to investigate cancer risk among adults above the age of 50. Results—Risky parental behavior and impairment in childhood were associated with higher odds of all-site cancer prevalence, and childhood chronic disease was associated with prostate cancer, even after adjusting for adult health and socioeconomic factors. Moreover, having one infectious disease in childhood lowered the odds of colon cancer. Cancer trends varied by race and ethnicity, most notably, higher prostate cancer prevalence among Black men and lower all-site cancer among Hispanic adults. Discussion—These findings underscore the importance of examining multiple domains of misfortune because the type and amount of misfortune influence cancer risk in different ways

Celebrating 30 Years of the Venice Project Center

In the 30 years since its founding, the Venice Project Center (VPC) has collected and analyzed a vast amount of data on a variety of subjects about Venice. Our team’s mission was to celebrate the 30th anniversary by furthering the Venice Project Center’s goal of publishing data in accessible formats and providing it to anyone interested in Venetian culture. Our team focused on ways to do this both digitally, such as through the new VPC 3.0 Website, and in print through a booklet series: “Knowing Venice.” The most notable deliverable is the redesign of the Sandbox application, which can be used to turn the Venice Project Center’s data into informative data visualizations. Each of our deliverables contribute to the VPC’s mission of making its decades of work open to all

G-LiHT: Goddard's LiDAR, Hyperspectral and Thermal Airborne Imager

Scientists at NASA's Goddard Space Flight Center have developed an ultra-portable, low-cost, multi-sensor remote sensing system for studying the form and function of terrestrial ecosystems. G-LiHT integrates two LIDARs, a 905 nanometer single beam profiler and 1550 nm scanner, with a narrowband (1.5 nanometers) VNIR imaging spectrometer and a broadband (8-14 micrometers) thermal imager. The small footprint (approximately 12 centimeters) LIDAR data and approximately 1 meter ground resolution imagery are advantageous for high resolution applications such as the delineation of canopy crowns, characterization of canopy gaps, and the identification of sparse, low-stature vegetation, which is difficult to detect from space-based instruments and large-footprint LiDAR. The hyperspectral and thermal imagery can be used to characterize species composition, variations in biophysical variables (e.g., photosynthetic pigments), surface temperature, and responses to environmental stressors (e.g., heat, moisture loss). Additionally, the combination of LIDAR optical, and thermal data from G-LiHT is being used to assess forest health by sensing differences in foliage density, photosynthetic pigments, and transpiration. Low operating costs (approximately $1 ha) have allowed us to evaluate seasonal differences in LiDAR, passive optical and thermal data, which provides insight into year-round observations from space. Canopy characteristics and tree allometry (e.g., crown height:width, canopy:ground reflectance) derived from G-LiHT data are being used to generate realistic scenes for radiative transfer models, which in turn are being used to improve instrument design and ensure continuity between LiDAR instruments. G-LiHT has been installed and tested in aircraft with fuselage viewports and in a custom wing-mounted pod that allows G-LiHT to be flown on any Cessna 206, a common aircraft in use throughout the world. G-LiHT is currently being used for forest biomass and growth estimation in the CONUS and Mexico in support of NASA's Carbon Monitoring System (CMS) and AMIGA-Carb (AMerican Icesat Glas Assessment of Carbon). For NASA's CMS, wall-to-wall G-LiHT data have been acquired over intensive study sites with historic LiDAR datasets, dense inventory data, stem maps and flux tower observations. For AMIGA-Carb, G-LiHT transects have been acquired over ICESat tracks and USDA-FS inventory plots throughout the CONUS, and similar data will be acquired in Mexico during 2013. This talk will highlight recent science results from continental-scale transects landscape-scale deployments of G-LiHT, as well as seasonal forest dynamics from repeat pass G-LiHT acquisitions

Sixty-Eight Previously Uncollected Reviews of Walt Whitman

Lists sixty-eight previously uncollected reviews of Whitman\u27s work published during his lifetime, and reprints thirty-eight of these newly discovered documents; with an introduction (1-7) and notes (70-76)