Global Patterns and Controls of Nutrient Immobilization On Decomposing Cellulose In Riverine Ecosystems

Microbes play a critical role in plant litter decomposition and influence the fate of carbon in rivers and riparian zones. When decomposing low-nutrient plant litter, microbes acquire nitrogen (N) and phosphorus (P) from the environment (i.e., nutrient immobilization), and this process is potentially sensitive to nutrient loading and changing climate. Nonetheless, environmental controls on immobilization are poorly understood because rates are also influenced by plant litter chemistry, which is coupled to the same environmental factors. Here we used a standardized, low-nutrient organic matter substrate (cotton strips) to quantify nutrient immobilization at 100 paired stream and riparian sites representing 11 biomes worldwide. Immobilization rates varied by three orders of magnitude, were greater in rivers than riparian zones, and were strongly correlated to decomposition rates. In rivers, P immobilization rates were controlled by surface water phosphate concentrations, but N immobilization rates were not related to inorganic N. The N:P of immobilized nutrients was tightly constrained to a molar ratio of 10:1 despite wide variation in surface water N:P. Immobilization rates were temperature-dependent in riparian zones but not related to temperature in rivers. However, in rivers nutrient supply ultimately controlled whether microbes could achieve the maximum expected decomposition rate at a given temperature

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)

The Night Kitchen: A Simulation Study of Night Baking: PowerPoint Presentation

Outline Setting the Objectives Collecting the Data Building the Model Some Assumptions and Limitations The Bake-Off Recommendation

Choosing a Ph.D. Topic

Six months ago I began the course work for my Ph.D. degree. Obtaining a doctorate has been a personal goal ever since practical considerations prevented me from pursuing a Ph.D. in astrophysics some 20 years ago. Instead, I became a programmer in the newly deregulated telecommunications industry. As I rose through the ranks over the years I became keenly interested in engineering communication and culture. The more I studied, the more I realized that communication among software engineers was under-researched. Since research opportunities were limited as a manager, I entered the Engineering and Technology Management Ph.D. program at Portland State University. I seek the Ph.D. degree because I believe it is the most practical way for me to study software development communication and culture. My personal goal is to complete the Ph.D. by 2006, and afterwards to devote myself to research, writing, and teaching. This paper describes the process I followed to decide on a topic for my dissertation research. I considered two dissertation topics deriving from my past industry experience

The Night Kitchen: A Simulation Study of Night Baking

Abstract A discrete system simulation study was conducted to assess whether the addition of a night baking shift would result in a significant reduction in the average workorder cycle time or work- in-progress at a small wholesale bakery in Portland, Oregon. Four shift configurations were compared: a regular 5-day shift scenario, a regular night baking scenario, an extended 6-day shift scenario, and an extended night baking scenario. The simulation model indicates that the bakery could achieve as much as a 40% reduction in the average order cycle time and nearly 50% reduction in work- in-progress by shifting two of its employees to a night baking shift. Findings are reported at the 99% confidence level. Some caution is indicated before placing too much emphasis on the expected magnitude of improvement, since other factors would likely come into play. However, this simulation study provides evidence in favor of night baking, a practice which previously had enjoyed only antedotal support

A Reactive Model of the Innovation-Decision Process

Historically, technology transfer within the software industry has been a difficult, slow, and poorly understood process. Redwine and Riddle found that a mean time of 17 years was required for software engineering technologies to pass from the initial concept stage until to usage by 70% of the industry. In a survey of software process innovation (SPI) champions, Goldenson and Herbsleb discovered that lack of guidance, mentoring, and assistance for change agents was a major factor in retarding progress: Our data suggest a number of factors that can make process innovation difficult to achieve. Aspects of organizational culture are among those most likely to inhibit such change. When our respondents say that they have seen excessive turf guarding and organizational politics, they also report less success in addressing the findings and recommendations that were raised in their appraisals ... We need to learn more about how to make change happen, not just what needs to be improved. The social barriers facing SPI are especially formidable when infusing software innovations into large organizations. Technology infusion refers to the micro-level organizational process of adopting a new process technology. The macro-level industry counterpart is technology transfer. In large organizations recipients may be widely scattered, inhibiting interpersonal contact between SPI change agents and software engineers. Internal SPI agencies face formidable project planning difficulties. They lack the tools needed to accurately estimate required resources and campaign duration. It is not well understood how to forecast the number of internal change agents who would be needed to infuse a software process innovation. Humphrey states that full-time staffing levels for internal change agencies in software organizations should run to about l-3% of overall staffing levels, but this is only a rough estimate. Change agencies also the ability need to assess the impact and effectiveness of communication strategies in support of infusion campaigns. Formative evaluation techniques can help to refine the message, but the ability to experiment is limited by the modest resources of most change agencies. As staff :functions their budgets tend to be limited in comparison to line :functions, so it is important for them to leverage their resources as efficiently as possible. In short, technology infusion involves a good deal of guesswork, which contributes to the lengthy periods of time reported by Redwine and Riddle. As part of an effort to address the problem this paper poses the following longterm management questions: How can we improve estimates of the cost, effort and duration of technology infusion projects? How can we identify points of maximum leverage for ehange agency resources? How can we evaluate the effectiveness of change agency communication strategies? How can we identify points of resistance in the organizational culture and test the effectiveness of risk migration strategies

Doing the Wave: A Quantitative Analysis of Response Variables in an Agent-Based Simulation of Self-Organizing Behavior

Abstract. This paper describes output data analysis for an agent-based simulation of self-organizing behavior in the StarLogo language. It discusses the rationale and design for constructing the simulation, issues involved in output data analysis, results and conclusions, and directions for future research

Doing the Wave A Quantitative Analysis of Response Variables in an Agent-Based Simulation of Self-Organizing Behavior: PowerPoint Presentation

Presentation Outline: What is Agent-Based Simulation (ABS)? Problem Statement Research Objectives Simulation Demonstration Research Design Data Collection and Analysis Findings and Conclusion

Wipro and the Rise of the Indian Software Industry

This paper examines the remarkable story of Wipro (NYSE: WIT), a company that has grown from a supplier of cooking oil to the Indian domestic market into one of the giants of the global software industry. This paper demonstrates how Wipro’s strategy did much more than establish its founder as one of the richest people in the world; it also launched the Indian software services industry and transformed Bangalore into the Silicon Valley of India