Transforming organic chemistry research paradigms: moving from manual efforts to the intersection of automation and artificial intelligence

Organic chemistry is undergoing a major paradigm shift, moving from a labor-intensive approach to a new era dominated by automation and artificial intelligence (AI). This transformative shift is being driven by technological advances, the ever-increasing demand for greater research efficiency and accuracy, and the burgeoning growth of interdisciplinary research. AI models, supported by computational power and algorithms, are drastically reshaping synthetic planning and introducing groundbreaking ways to tackle complex molecular synthesis. In addition, autonomous robotic systems are rapidly accelerating the pace of discovery by performing tedious tasks with unprecedented speed and precision. This article examines the multiple opportunities and challenges presented by this paradigm shift and explores its far-reaching implications. It provides valuable insights into the future trajectory of organic chemistry research, which is increasingly defined by the synergistic interaction of automation and AI

UIDEF Research syntheses : 2020-2023

This book is supported by National Funds through FCT-Portuguese Foundation for Science and Technology, I.P., under the scope of UIDEF - Unidade de Investigação e Desenvolvimento em Educação e Formação, UIDB/04107/2020.This is the first volume of the series Research Syntheses, a quadrennial publication of the Research and Development Centre in Education and Training (UIDEF, Unidade de Investigação e Desenvolvimento em Educação e Formação), the research centre of the Instituto de Educação da Universidade de Lisboa, Portugal (IE-ULisboa). As a result of a collaborative work, the series testifies to UIDEF's investigative activity in searching for relevant inputs for the scientific community and support knowledge-driven processes of transformation within educational systems, policies, and practices.info:eu-repo/semantics/publishedVersio

SOCIOCULTURAL AND ECONOMIC VALUES – ORGANIC FOOD CONSUMPTION IN FAIRS AND SUPERMARKETS IN CAMPINAS, SP. BRAZIL

This scientific research was meant to encompass the meaning of economic and sociocultural consumption and its relationship to human values such as: environmental respect, commitment to health principles, solidarity among rural and urban social groups, and economic aspects (prices etc.)

National innovation systems, developing countries, and the role of intermediaries: a critical review of the literature

Developed over the past three decades, the national innovation system concept (NIS) has been widely used by both scholars and policy makers to explain how interactions between a set of distinct, nationally bounded institutions supports and facilitates technological change and the emergence and diffusion of new innovations. This concept provides a framework by which developing countries can adopt for purposes of catching up. Initially conceived on structures and interactions identified in economically advanced countries, the application of the NIS concept to developing countries has been gradual and has coincided – in the NIS literature – with a move away from overly macro-interpretations to an emphasis on micro-level interactions and processes, with much of this work questioning the nation state as the most appropriate level of analysis, as well as the emergence of certain intermediary actors thought to facilitate knowledge exchange between actors and institutions. This paper reviews the NIS literature chronologically, showing how this shift in emphasis has diminished somewhat the importance of both institutions, particularly governments, and the process of institutional capacity building. In doing so, the paper suggests that more recent literature on intermediaries such as industry associations may offer valuable insights to how institutional capacity building occurs and how it might be directed, particularly in the context of developing countries where governance capacities are often lacking, contributing to less effective innovation systems, stagnant economies, and unequal development

Model Based Systems Engineering Approaches to Chemicals and Materials Manufacturing

Model-based systems engineering (MBSE) is part of a long-term trend toward model-centric approaches adopted by many engineering disciplines. This work establishes the need for an MBSE approach by reviewing the importance, complexity, and vulnerability of the U.S. chemical supply chains. The origins, work processes, modeling approaches, and supporting tools of the systems engineering discipline (SE) are discussed, along with the limitations of the current Process Systems Engineering (PSE) framework. The case is made for MBSE as a more generalizable and robust approach. Systems modeling strategies for MBSE are introduced, as well as a novel MBSE method that supports the automation tailored and extended to support the analysis of chemical supply chains. This work demonstrate the potential of MBSE approaches in chemical manufacturing by presenting two cases studies involving two different Active Pharmaceutical Ingredients (API), Atropine and Albuterol. The conclusion offers a prospectus on developmental opportunities for extracting greater benefit from MBSE in the design and management of chemical supply chains

Graduate School: Course Decriptions, 1972-73

Official publication of Cornell University V.64 1972/7

The handbook for standardised field and laboratory measurements in terrestrial climate-change experiments and observational studies

Climate change is a worldwide threat to biodiversity and ecosystem structure, functioning, and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate‐change impacts across the soil–plant–atmosphere continuum. An increasing number of climate‐change studies is creating new opportunities for meaningful and high‐quality generalisations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re‐use, synthesis, and upscaling. Many of these challenges relate to a lack of an established “best practice” for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change