Table Traits

Table Traits
Author: Dr. Doran (John)
Publisher:
Total Pages: 516
Release: 1855
Genre: Diet
ISBN:

A history of eating.

Personality Psychology

Personality Psychology
Author: Jim McMartin
Publisher: SAGE Publications
Total Pages: 409
Release: 2016-01-29
Genre: Psychology
ISBN: 1483385248

Personality Psychology: A Student-Centered Approach by Jim McMartin organizes the field of personality psychology around basic questions relevant to the reader’s past, present, and future selves. Answers to the questions are based on findings from up-to-date research and shed light on the validity of personality theories to help students deepen their understanding of their own personalities. Concise, conversational, and easy-to-understand, the Second Edition is enhanced with new chapters, new research that reflects the latest scholarship, and new photos and illustrations throughout.

Predicting Personality

Predicting Personality
Author: Drew D'Agostino
Publisher: John Wiley & Sons
Total Pages: 254
Release: 2019-11-12
Genre: Business & Economics
ISBN: 1119630967

The ultimate playbook for using artificial intelligence to communicate effectively, build teams, and win customers Not long ago, we imagined a hyper-connected world full of trust and openness—a world where effortless communication would bring about a new understanding between people everywhere. Judging from our current environment, this vision of the future may have been overly optimistic. With infinite channels and countless voices flooding them with messages, most people have become highly skeptical and guarded by necessity. As a result, communication is much harder than ever before. Despite the unprecedented connectivity enabled by modern technology, we are far less likely to trust and to invest the time needed to build strong relationships. How can we use technology to reverse this trend? A groundbreaking new branch of artificial intelligence—Personality AI—may be the answer. Combining traditional machine learning, data analytics, and behavioral psychology, Personality AI helps professional communicators tear down walls, establish trust with their audiences, and utilize data to build meaningful relationships, strengthen empathy, and win more customers. Predicting Personality is a practical, real-world playbook for any individual or business whose success hinges on the ability to communicate effectively and build teams. Authors Drew D’Agostino and Greg Skloot—CEO and President, respectively, of Crystal, the app that tells you anyone's personality—show you how businesses can leverage Personality AI and machine learning to grow faster and communicate more effectively than was previously possible. This reader-friendly guide teaches you what Personality AI is, how it works, and demonstrates its practical applications in both life and business. This book: ● Explains how to understand personality types in various contexts, including sales, recruiting, coaching ● Provides guidelines for using personality data to learn and execute ● Explores ethics and compliance considerations surrounding the use of Personality AI ● Offers valuable insights from a leader in the business applications of Personality AI Predicting Personality: Using AI to Understand People and Win More Business is a must-have guide for C-suite executives, sales and marketing professionals, coaches, recruiters, and business owners.

Advances in Statistical Methods for the Genetic Dissection of Complex Traits in Plants

Advances in Statistical Methods for the Genetic Dissection of Complex Traits in Plants
Author: Yuan-Ming Zhang
Publisher: Frontiers Media SA
Total Pages: 278
Release: 2024-01-26
Genre: Science
ISBN: 2832543693

Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. However, there are still limits in current GWAS statistics. For example, (1) almost all the existing methods do not estimate additive and dominance effects in quantitative trait nucleotide (QTN) detection; (2) the methods for detecting QTN-by-environment interaction (QEI) are not straightforward and do not estimate additive and dominance effects as well as additive-by-environment and dominance-by-environment interaction effects, leading to unreliable results; and (3) no or too simple polygenic background controls have been employed in QTN-by-QTN interaction (QQI) detection. As a result, few studies of QEI and QQI for complex traits have been reported based on multiple-environment experiments. Recently, new statistical tools, including 3VmrMLM, have been developed to address these needs in GWAS. In 3VmrMLM, all the trait-associated effects, including QTN, QEI and QQI related effects, are compressed into a single effect-related vector, while all the polygenic backgrounds are compressed into a single polygenic effect matrix. These compressed parameters can be accurately and efficiently estimated through a unified mixed model analysis. To further validate these new GWAS methods, particularly 3VmrMLM, they should be rigorously tested in real data of various plants and a wide range of other species.