Chipping Away at Workplace Privacy: The Implantation of RFID Microchips and Erosion of Employee Privacy

With the advent of new technologies and workplace policies, employees have lowered expectations of privacy. These technologies and policies include the implantation of microchips in employees; bring your own device to work policies; and wearable technologies. The lack of both state and federal statutes to protect employees means that employees have few methods to redress their privacy concerns. To protect their privacy rights, employees should use a collectivist approach to bargain with their employers for such rights

Sustainable Software Ecosystems for Open Science

Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source professionals work together and treat software as a first-class product of scientific investigation-just as mathematics is treated in the physical sciences. Kitware has a rich history of establishing collaborative projects in the science, engineering and medical research fields, and continues to work on improving that model as new technologies and approaches become available. This approach closely follows and is enhanced by the movement towards practicing open, reproducible research in the sciences where data, source code, methodology and approach are all available so that complex experiments can be independently reproduced and verified.Comment: Workshop on Sustainable Software: Practices and Experiences, 4 pages, 3 figure

Fast Segmentation and High-Quality Three-Dimensional Volume Mesh Creation from Medical Images for Diffuse Optical Tomography

Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform

Expressions 1988

https://openspace.dmacc.edu/expressions/1031/thumbnail.jp

New Frontiers-class Uranus Orbiter: Exploring the feasibility of achieving multidisciplinary science with a mid-scale mission

n/

Is there a space–time continuum in olfaction?

The coding of olfactory stimuli across a wide range of organisms may rely on fundamentally similar mechanisms in which a complement of specific odorant receptors on olfactory sensory neurons respond differentially to airborne chemicals to initiate the process by which specific odors are perceived. The question that we address in this review is the role of specific neurons in mediating this sensory system—an identity code—relative to the role that temporally specific responses across many neurons play in producing an olfactory perception—a temporal code. While information coded in specific neurons may be converted into a temporal code, it is also possible that temporal codes exist in the absence of response specificity for any particular neuron or subset of neurons. We review the data supporting these ideas, and we discuss the research perspectives that could help to reveal the mechanisms by which odorants become perceptions

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Conceptualizing and measuring strategy implementation – a multi-dimensional view

Through quantitative methodological approaches for studying the strategic management and planning process, analysis of data from 208 senior managers involved in strategy processes within ten UK industrial sectors provides evidence on the measurement properties of a multi-dimensional instrument that assesses ten dimensions of strategy implementation. Using exploratory factor analysis, results indicate the sub-constructs (the ten dimensions) are uni-dimensional factors with acceptable reliability and validity; whilst using three additional measures, and correlation and hierarchical regression analysis, the nomological validity for the multi-dimensional strategy implementation construct was established. Relative importance of ten strategy implementation dimensions (activities) for practicing managers is highlighted, with the mutually and combinative effects drawing conclusion that senior management involvement leads the way among the ten key identified activities vital for successful strategy implementation