An improved powertrain attributes development process with the use of design structure matrix

Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2004.Includes bibliographical references (p. 131).Automobiles are becoming increasingly complicated and are creating more of a challenge for the engineering teams working on them. This thesis focuses on improving the methods of managing powertrain attributes and the interactions between them. We are concentrating on the particular attributes of Shift Quality, Performance Feel, Driveability, and Trailer Towing. Engineering work to achieve specific attributes is currently handled attribute by attribute and the system is brought together later. This lack of a more holistic view results in a large amount of engineering rework as attributes are balanced. Reducing or eliminating this rework is the goal. A Design Structure Matrix (DSM) was used to document interactions between the powertrain attributes, sub-attributes and design parameters. Research on various reporting formats was done to determine the best method to communicate the interactions. DSM experts were interviewed about the benefits and pitfalls of using a DSM for reference. Several surveys were done to determine engineering's familiarity with various methods of displaying system interactions and their preferences for reporting the interactions. We also compared the interactions to existing CAE capability to determine the current state of attributes management. The DSM showed numerous interactions between powertrain attributes, other vehicle attributes and design parameters. The analysis of existing CAE tools showed a significant percentage of interactions are not currently being modeled. The responses to survey questions on output methods indicated that a DSM, while being an excellent tool for capturing the interactions, might not be the best tool for displaying the interactions to engineers. The surveys revealed that(cont.) engineers are looking for more information than a DSM or any systems interactions model contain, such as probability that an interaction exists, expected direction and levels of the interaction, and quick and simple methods for better understanding of these potential interactions. This desired level of detail highlights the need to share Lessons Learned, develop a corporate knowledge base and develop best practices. A review of the organizational structure and engineering focus indicated that increased focus is needed on powertrain attributes to better match customer expectations. Additionally, organizational structure changes are recommended to increase visibility of powertrain attributes.by Daniel J. Rinkevich [and] Frederick P. Samson.S.M

Qualitative approach to comparative exposure in alternatives assessment

Most alternatives assessments (AAs) published to date are largely hazard-based rankings, thereby ignoring potential differences in human and/or ecosystem exposures; as such, they may not represent a fully informed consideration of the advantages and disadvantages of possible alternatives. Building on the 2014 US National Academy of Sciences recommendations to improve AA decisions by including comparative exposure assessment into AAs, the Health and Environmental Sciences Institute\u27s (HESI) Sustainable Chemical Alternatives Technical Committee, which comprises scientists from academia, industry, government, and nonprofit organizations, developed a qualitative comparative exposure approach. Conducting such a comparison can screen for alternatives that are expected to have a higher or different routes of human or environmental exposure potential, which together with consideration of the hazard assessment, could trigger a higher tiered, more quantitative exposure assessment on the alternatives being considered, minimizing the likelihood of regrettable substitution. This article outlines an approach for including chemical ingredient- and product-related exposure information in a qualitative comparison, including ingredient and product-related parameters. A classification approach was developed for ingredient and product parameters to support comparisons between alternatives as well as a methodology to address exposure parameter relevance and data quality. The ingredient parameters include a range of physicochemical properties that can impact routes and magnitude of exposure, whereas the product parameters include aspects such as product-specific exposure pathways, use information, accessibility, and disposal. Two case studies are used to demonstrate the application of the methodology. Key learnings and future research needs are summarized. Integr Environ Assess Manag 2018;00:000-000. (c) 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC

Six priorities to advance the science and practice of coral reef restoration worldwide

Coral reef restoration is a rapidly growing movement galvanized by the accelerating degradation of the world's tropical coral reefs. The need for concerted and collaborative action focused on the recovery of coral reef ecosystems coalesced in the creation of the Coral Restoration Consortium (CRC) in 2017. In March 2020, the CRC leadership team met for a biennial review of international coral reef restoration efforts and a discussion of perceived knowledge and implementation bottlenecks that may impair scalability and efficacy. Herein we present six priorities wherein the CRC will foster scientific advancement and collaboration to: (1) increase restoration efficiency, focusing on scale and cost-effectiveness of deployment; (2) scale up larval-based coral restoration efforts, emphasizing recruit health, growth, and survival; (3) ensure restoration of threatened coral species proceeds within a population-genetics management context; (4) support a holistic approach to coral reef ecosystem restoration; (5) develop and promote the use of standardized terms and metrics for coral reef restoration; and (6) support coral reef restoration practitioners working in diverse geographic locations. These priorities are not exhaustive nor do we imply that accomplishing these tasks alone will be sufficient to restore coral reefs globally; rather these are topics where we feel the CRC community of practice can make timely and significant contributions to facilitate the growth of coral reef restoration as a practical conservation strategy. The goal for these collective actions is to provide tangible, local-scale advancements in reef condition that offset declines resulting from local and global stressors including climate change

Dooley\u27s Dictum

Dooley\u27s Dictum: A Newspaper of, by and for the Fighting Irish Lawyers of Notre Dame—A publication of the Student Bar Association, published between 1970 and 1971.https://scholarship.law.nd.edu/law_history_gallery/1010/thumbnail.jp

Variation in organophosphate and pyrethroid sensitivities by topical bioassays among three stocks of commonly used honey bees.

<p>Different letters for LD₅₀ values in the same row indicate significant differences. Different symbols for slope values in the same row indicate significant differences. The LD₅₀ values are in units of ng insecticide/mg bee.</p

Variation in neonicotinoid sensitivity by feeding bioassays among three stocks of commonly used honey bees.

<p>Different letters for LC₅₀ values in the same row indicate significant differences. Different symbols for slope values in the same row indicate significant differences. The LC₅₀ values for imidacloprid and thiamethoxam are expressed in ng/ml/mg bee.</p

Phenothrin sensitivity decreases with age in honey bees.

<p>Letters above data points indicate significant differences in the LD₅₀ values.</p

Miticides and P450 inhibitor synergizes phenothrin sensitivity among three stocks of honey bees.

<p>All Synergism Ratios (SR) indicate significantly increased sensitivity compared to non-synergized phenothrin treatment (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139841#pone.0139841.t001" target="_blank">Table 1</a>). Different letters for LD₅₀ values in the same row indicate significant differences. Different symbols for slope values in the same row indicate significant differences. The LD₅₀ values are in units of ng phenothrin/mg bee.</p

Genetics, Synergists, and Age Affect Insecticide Sensitivity of the Honey Bee, <i>Apis mellifera</i>

<div><p>The number of honey bee colonies in the United States has declined to half of its peak level in the 1940s, and colonies lost over the winter have reached levels that are becoming economically unstable. While the causes of these losses are numerous and the interaction between them is very complex, the role of insecticides has garnered much attention. As a result, there is a need to better understand the risk of insecticides to bees, leading to more studies on both toxicity and exposure. While much research has been conducted on insecticides and bees, there have been very limited studies to elucidate the role that bee genotype and age has on the toxicity of these insecticides. The goal of this study was to determine if there are differences in insecticide sensitivity between honey bees of different genetic backgrounds (Carniolan, Italian, and Russian stocks) and assess if insecticide sensitivity varies with age. We found that Italian bees were the most sensitive of these stocks to insecticides, but variation was largely dependent on the class of insecticide tested. There were almost no differences in organophosphate bioassays between honey bee stocks (<1-fold), moderate differences in pyrethroid bioassays (1.5 to 3-fold), and dramatic differences in neonicotinoid bioassays (3.4 to 33.3-fold). Synergism bioassays with piperonyl butoxide, amitraz, and coumaphos showed increased phenothrin sensitivity in all stocks and also demonstrated further physiological differences between stocks. In addition, as bees aged, the sensitivity to phenothrin significantly decreased, but the sensitivity to naled significantly increased. These results demonstrate the variation arising from the genetic background and physiological transitions in honey bees as they age. This information can be used to determine risk assessment, as well as establishing baseline data for future comparisons to explain the variation in toxicity differences for honey bees reported in the literature.</p></div