Projeto de Planejamento Estratégico a partir da Simulação de Cenários: O Caso de Um Supermercado do Paraná

oai:www6.uninove.br/ojs/journaliji:article/6O estudo apresenta um projeto de um plano de estratégias de crescimento para a empresa V. Müller e Cia. Ltda., utilizando o modelo de simulação de cenários proposto por Rojo (2006). De caráter exploratório, a pesquisa é um estudo de caso, com uma abordagem qualitativa, e uma amostra de seis dirigentes. O instrumento de coleta de dados é uma entrevista estruturada, utilizando-se da técnica Delphi. Como resultado, têm-se estratégias e ações elaboradas para cada um dos cenários simulados. Não se assegura assertividade, mas contribui para a geração de possibilidades que tornam mais segura a tomada de decisão

Near Infared Circularly Polarized Luminescence from water stable organic nanoparticles containing a chiral Yb(III) complex

We report the first example of very efficient NIR Circularly Polarized Luminescence (CPL) (around 970 nm) in water, obtained thanks to the combined use of a chiral Yb complex and of poly lactic-co-glycolic acid (PLGA) nanoparticles. [Yb L (tta) 2 ]CH 3 COO ( L = N, N'-bis(2-pyridylmethylidene)-1,2-( R,R + S,S ) cyclohexanediamine and tta = 2-thenoyltrifluoroacetonate) shows good CPL in organic solvents, because the tta ligands efficiently sensitize Yb NIR luminescence and the readily prepared chiral ligand L endows the complex with the necessary dissymmetry. PLGA nanoparticles incorporate the complex and protect the metal ion from the intrusion of solvent molecules, while ensuring biocompatibility, water solubility and stability to the complex. Hydrophilic NIR-CPL optical probes can find applications in the field of NIR-CPL bio-assays

JRC-Ispra Atmosphere-Biosphere-Climate Integrated monitoring Station 2012 report

The Institute for Environment and Sustainability provide long-term observations of the atmosphere within international programs and research projects. These observations are performed from the research infrastructure named ABC-IS: Atmosphere – Biosphere – Climate Integrated monitoring station. Most measurements are performed at the JRC-Ispra site. Observations are also carried out from two other platforms: the forest station in San Rossore, and a ship cruising in the Western Mediterranean sea. This document reports about measurement programs, the equipment which is deployed, the data quality assessment, and the results obtained for each site. Our observations are presented, compared to each other, as well as to historical data obtained over more than 25 years at the Ispra siteJRC.H.2-Air and Climat

JRC – Ispra Atmosphere – Biosphere – Climate Integrated monitoring Station : 2011 report

The Institute for Environment and Sustainability provide long-term observations of the atmosphere within international programs and research projects. These observations are performed from the research infrastructure named ABC-IS: Atmosphere-Biosphere-Climate Integrated monitoring station. Most measurements are performed at the JRC-Ispra site. Observations are also carried out from two other platforms: the forest station in San Rossore, and a ship cruising in the Western Mediterranean sea. This document reports about measurement programs, the equipment which is deployed, and the data quality assessment for each site. Our observations are presented, compared to each other, as well as to historical data obtained over the past 25 years at the Ispra site.JRC.H.2-Air and Climat

ACTRIS ACSM intercomparison – Part 1: Reproducibility of concentration and fragment results from 13 individual Quadrupole Aerosol Chemical Speciation Monitors (Q-ACSM) and consistency with co-located instruments

As part of the European ACTRIS project, the first large Quadrupole Aerosol Chemical Speciation Monitor (Q-ACSM) intercomparison study was conducted in the region of Paris for 3 weeks during the late-fall – early-winter period (November–December 2013). The first week was dedicated to the tuning and calibration of each instrument, whereas the second and third were dedicated to side-by-side comparison in ambient conditions with co-located instruments providing independent information on submicron aerosol optical, physical, and chemical properties. Near real-time measurements of the major chemical species (organic matter, sulfate, nitrate, ammonium, and chloride) in the non-refractory submicron aerosols (NR-PM1) were obtained here from 13 Q-ACSM. The results show that these instruments can produce highly comparable and robust measurements of the NR-PM1 total mass and its major components. Taking the median of the 13 Q-ACSM as a reference for this study, strong correlations (r2 > 0.9) were observed systematically for each individual Q-ACSM across all chemical families except for chloride for which three Q-ACSMs showing weak correlations partly due to the very low concentrations during the study. Reproducibility expanded uncertainties of Q-ACSM concentration measurements were determined using appropriate methodologies defined by the International Standard Organization (ISO 17025, 1999) and were found to be 9, 15, 19, 28, and 36 % for NR-PM1, nitrate, organic matter, sulfate, and ammonium, respectively. However, discrepancies were observed in the relative concentrations of the constituent mass fragments for each chemical component. In particular, significant differences were observed for the organic fragment at mass-to-charge ratio 44, which is a key parameter describing the oxidation state of organic aerosol. Following this first major intercomparison exercise of a large number of Q-ACSMs, detailed intercomparison results are presented, along with a discussion of some recommendations about best calibration practices, standardized data processing, and data treatment.JRC.H.2-Air and Climat

The SPATIAL Architecture:Design and Development Experiences from Gauging and Monitoring the AI Inference Capabilities of Modern Applications

Despite its enormous economical and societal impact, lack of human-perceived control and safety is re-defining the design and development of emerging AI-based technologies. New regulatory requirements mandate increased human control and oversight of AI, transforming the development practices and responsibilities of individuals interacting with AI. In this paper, we present the SPATIAL architecture, a system that augments modern applications with capabilities to gauge and monitor trustworthy properties of AI inference capabilities. To design SPATIAL, we first explore the evolution of modern system architectures and how AI components and pipelines are integrated. With this information, we then develop a proof-of-concept architecture that analyzes AI models in a human-in-the-loop manner. SPATIAL provides an AI dashboard for allowing individuals interacting with applications to obtain quantifiable insights about the AI decision process. This information is then used by human operators to comprehend possible issues that influence the performance of AI models and adjust or counter them. Through rigorous benchmarks and experiments in realworld industrial applications, we demonstrate that SPATIAL can easily augment modern applications with metrics to gauge and monitor trustworthiness, however, this in turn increases the complexity of developing and maintaining systems implementing AI. Our work highlights lessons learned and experiences from augmenting modern applications with mechanisms that support regulatory compliance of AI. In addition, we also present a road map of on-going challenges that require attention to achieve robust trustworthy analysis of AI and greater engagement of human oversight

The SPATIAL Architecture:Design and Development Experiences from Gauging and Monitoring the AI Inference Capabilities of Modern Applications

Despite its enormous economical and societal impact, lack of human-perceived control and safety is re-defining the design and development of emerging AI-based technologies. New regulatory requirements mandate increased human control and oversight of AI, transforming the development practices and responsibilities of individuals interacting with AI. In this paper, we present the SPATIAL architecture, a system that augments modern applications with capabilities to gauge and monitor trustworthy properties of AI inference capabilities. To design SPATIAL, we first explore the evolution of modern system architectures and how AI components and pipelines are integrated. With this information, we then develop a proof-of-concept architecture that analyzes AI models in a human-in-the-loop manner. SPATIAL provides an AI dashboard for allowing individuals interacting with applications to obtain quantifiable insights about the AI decision process. This information is then used by human operators to comprehend possible issues that influence the performance of AI models and adjust or counter them. Through rigorous benchmarks and experiments in realworld industrial applications, we demonstrate that SPATIAL can easily augment modern applications with metrics to gauge and monitor trustworthiness, however, this in turn increases the complexity of developing and maintaining systems implementing AI. Our work highlights lessons learned and experiences from augmenting modern applications with mechanisms that support regulatory compliance of AI. In addition, we also present a road map of on-going challenges that require attention to achieve robust trustworthy analysis of AI and greater engagement of human oversight

Universal scaling in the branching of the Tree of Life

Understanding the patterns and processes of diversification of life in the planet is a key challenge of science. The Tree of Life represents such diversification processes through the evolutionary relationships among the different taxa, and can be extended down to intra-specific relationships. Here we examine the topological properties of a large set of interspecific and intraspecific phylogenies and show that the branching patterns follow allometric rules conserved across the different levels in the Tree of Life, all significantly departing from those expected from the standard null models. The finding of non-random universal patterns of phylogenetic differentiation suggests that similar evolutionary forces drive diversification across the broad range of scales, from macro-evolutionary to micro-evolutionary processes, shaping the diversity of life on the planet.Comment: 6 pages + 19 of Supporting Informatio

Has COVID-19 Delayed the Diagnosis and Worsened the Presentation of Type 1 Diabetes in Children?

Objective: To evaluate whether the diagnosis of pediatric type 1 diabetes or its acute complications changed during the early phase of the coronavirus disease 2019 (COVID-19) pandemic in Italy. Research design and methods: This was a cross-sectional, Web-based survey of all Italian pediatric diabetes centers to collect diabetes, diabetic ketoacidosis (DKA), and COVID-19 data in patients presenting with new-onset or established type 1 diabetes between 20 February and 14 April in 2019 and 2020. Results: Fifty-three of 68 centers (77.9%) responded. There was a 23% reduction in new diabetes cases in 2020 compared with 2019. Among those newly diagnosed patient who presented in a state of DKA, the proportion with severe DKA was 44.3% in 2020 vs. 36.1% in 2019 (P = 0.03). There were no differences in acute complications. Eight patients with asymptomatic or mild COVID-19 had laboratory-confirmed severe acute respiratory syndrome coronavirus 2. Conclusions: The COVID-19 pandemic might have altered diabetes presentation and DKA severity. Preparing for any "second wave" requires strategies to educate and reassure parents about timely emergency department attendance for non-COVID-19 symptoms