Influência da espessura da aleta na convecção forçada em um duplo tubo aletado internamente - solução pelo método de golub

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Engenharia Mecânica

Development of “LvL UP 1.0”: a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders

BackgroundNon-communicable diseases (NCDs) and common mental disorders (CMDs) are the leading causes of death and disability worldwide. Lifestyle interventions via mobile apps and conversational agents present themselves as low-cost, scalable solutions to prevent these conditions. This paper describes the rationale for, and development of, “LvL UP 1.0″, a smartphone-based lifestyle intervention aimed at preventing NCDs and CMDs.Materials and MethodsA multidisciplinary team led the intervention design process of LvL UP 1.0, involving four phases: (i) preliminary research (stakeholder consultations, systematic market reviews), (ii) selecting intervention components and developing the conceptual model, (iii) whiteboarding and prototype design, and (iv) testing and refinement. The Multiphase Optimization Strategy and the UK Medical Research Council framework for developing and evaluating complex interventions were used to guide the intervention development.ResultsPreliminary research highlighted the importance of targeting holistic wellbeing (i.e., both physical and mental health). Accordingly, the first version of LvL UP features a scalable, smartphone-based, and conversational agent-delivered holistic lifestyle intervention built around three pillars: Move More (physical activity), Eat Well (nutrition and healthy eating), and Stress Less (emotional regulation and wellbeing). Intervention components include health literacy and psychoeducational coaching sessions, daily “Life Hacks” (healthy activity suggestions), breathing exercises, and journaling. In addition to the intervention components, formative research also stressed the need to introduce engagement-specific components to maximise uptake and long-term use. LvL UP includes a motivational interviewing and storytelling approach to deliver the coaching sessions, as well as progress feedback and gamification. Offline materials are also offered to allow users access to essential intervention content without needing a mobile device.ConclusionsThe development process of LvL UP 1.0 led to an evidence-based and user-informed smartphone-based intervention aimed at preventing NCDs and CMDs. LvL UP is designed to be a scalable, engaging, prevention-oriented, holistic intervention for adults at risk of NCDs and CMDs. A feasibility study, and subsequent optimisation and randomised-controlled trials are planned to further refine the intervention and establish effectiveness. The development process described here may prove helpful to other intervention developers

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Multi-objective Optimization Model for a Green Vehicle Routing Problem

AbstractThe concept of green logistics stems from green economic concepts which are inherently driven by the environmental sustainability challenges. In this work, measures of carbon dioxide (CO2) emission are added to the canonical capacitated vehicle routing problem. The proposed multi-objective optimization model tackles the conflicting objectives of the emission reduction while holding-off the economic cost uplift, leading to a set of Pareto optimal solutions. A biologically inspired Ant Colony Optimization (ACO) based evolutionary constructive heuristic is used to obtain routing plans with minimum financial impact. A Variable Neighborhood Search (VNS) algorithm is designed to obtain low emission routes by exploring the neighborhood of the ant foraging paths. The hybrid ACO-VNS heuristic will provide a set of non-dominated solutions leading to the Pareto optimal solution frontier. For consistency of solutions and solution convergence, the algorithm is tested on randomly generated problem instances

A memristive architecture for process variation aware gas sensing and logic operations

We propose novel memristive gas sensor architectures that can significantly reduce process and parametric variations in a predictable manner, while improving accuracy and overall power consumption. The proposed architecture can also be configured to realize multifunction logic operations as well as Complementary Resistive Switch with low hardware overhead in the absence of gasses. Our results show that the proposed architecture is significantly immune to process and parametric effects compared to a single sensor and almost unaffected by wire resistance, while offering much higher accuracy and much lower power consumption compared to existing techniques