Emissions Reporting Maturity Model: supporting cities to leverage emissions-related processes through performance indicators and artificial intelligence

Climate change and global warming have been trending topics worldwide since the Eco-92 conference. However, little progress has been made in reducing greenhouse gases (GHGs). The problems and challenges related to emissions are complex and require a concerted and comprehensive effort to address them. Emissions reporting is a critical component of GHG reduction policy and is therefore the focus of this work. The main goal of this work is two-fold: (i) to propose an emission reporting evaluation model to leverage emissions reporting overall quality and (ii) to use artificial intelligence (AI) to support the initiatives that improve emissions reporting. Thus, this work presents an Emissions Reporting Maturity Model (ERMM) for examining, clustering, and analysing data from emissions reporting initiatives to help the cities to deal with climate change and global warming challenges. The Performance Indicator Development Process (PIDP) proposed in this work provides ways to leverage the quality of the available data necessary for the execution of the evaluations identified by the ERMM. Hence, the PIDP supports the preparation of the data from emissions-related databases, the classification of the data according to similarities highlighted by different clustering techniques, and the identification of performance indicator candidates, which are strengthened by a qualitative analysis of selected data samples. Thus, the main goal of ERRM is to evaluate and classify the cities regarding the emission reporting processes, pointing out the drawbacks and challenges faced by other cities from different contexts, and at the end to help them to leverage the underlying emissions-related processes and emissions mitigation initiatives

Weak antilocalization in quasi-two-dimensional electronic states of epitaxial LuSb thin films

Observation of large non-saturating magnetoresistance in rare-earth monopnictides has raised enormous interest in understanding the role of its electronic structure. Here, by a combination of molecular-beam epitaxy, low-temperature transport, angle-resolved photoemssion spectroscopy, and hybrid density functional theory we have unveiled the bandstructure of LuSb, where electron-hole compensation is identified as a mechanism responsible for large magnetoresistance in this topologically trivial compound. In contrast to bulk single crystal analogues, quasi-two-dimensional behavior is observed in our thin films for both electron and holelike carriers, indicative of dimensional confinement of the electronic states. Introduction of defects through growth parameter tuning results in the appearance of quantum interference effects at low temperatures, which has allowed us to identify the dominant inelastic scattering processes and elucidate the role of spin-orbit coupling. Our findings open up new possibilities of band structure engineering and control of transport properties in rare-earth monopnictides via epitaxial synthesis.Comment: 20 pages, 12 figures; includes supplementary informatio

Teaching Sciences in Virtual Worlds with Mastery Learning: A Case of Study in Elementary School

Virtual worlds are 3D environments that provide a feeling of immersion and a high degree of interaction, collaboration, communication between users. Its applicability can be focused on the educational scope, in which theories can be integrated as the basis to didactic activities carried out in the 3D environment, being its area of interdisciplinary comprehension. In this context, this article presents the use of a Virtual World built to assist in the teaching of Science for students of the middle school, whose articulation of the activities performed in the course are based on the precepts of the educational theory Mastery Learning. Tests were carried out in the subject of science, being divided into two periods with different groups for comparative purposes and realized evaluations during the period of the experiments. Kruskal-Wallis and Wilcoxon-Mann-Whitney non-parametric test were applied to the results of the assessments to ascertain the performance of each group. It was verified in the general analyzis that the participants who used the Virtual World had a growing performance, with high medians and adequate distribution of the results, being predominant of a smaller variability and amplitude. Thus, was possible to conclude that the results obtained with the approach were positive, which led to the validation of this research and presented a clear contribution to the academic environment

Rutin-functionalized multi-walled carbon nanotubes: molecular docking, physicochemistry and cytotoxicity in fibroblasts

Multi-Walled Carbon Nanotubes (MWCNT) have been functionalized with rutin through three steps (i. reaction step; ii. purification step; iii. drying step) and their physicochemical properties investigated with respect to morphological structure, thermal analysis, Fourier Transform Infrared Spectroscopy (FTIR), and cytotoxicity. The molecular docking suggested the rutin-functionalized MWCNT occurred by hydrogen bonds, which was confirmed by FTIR assays, corroborating the results obtained by thermal analyses. A tubular shape, arranged in a three-dimensional structure, could be observed. Mild cytotoxicity observed in 3T3 fibroblasts suggested a doseeffect relationship after exposure. These findings suggest the formation of aggregates of filamentous structures on the cells favoring the cell penetration.The authors acknowledge Classius Ferreira da Silva, from the Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Universidade Federal de São Paulo, for the scanning electron microscopy analyses.info:eu-repo/semantics/publishedVersio

Atividade educacional utilizando realidade aumentada para o ensino de física no ensino superior : Educational activity using Augmented Reality for Teaching Physics in Higher Education

O uso de recursos de Realidade Aumentada em dispositivos móveis para a Educação tem sido explorado nos últimos anos de forma mais significativa. Desta forma, o objetivo deste artigo foi avaliar a qualidade de uma abordagem educacional neste contexto em termos de Usabilidade, Engajamento, Motivação e Aprendizagem. Um estudo voltado para o processo de ensino e aprendizagem de Física foi conduzido com 27 alunos de uma universidade federal, sendo aplicado o questionário MAREEA para avaliar a abordagem. Os resultados obtidos foram satisfatórios e instigadores, em que as quatro dimensões foram avaliadas positivamente, havendo também um importante feedback dos participantes para as melhorias nos recursos educacionais em realidade aumentada.The use of Augmented Reality features in mobile devices for Education has been explored in recent years in a more meaningful way. In this way, the objective of this article was to evaluate the quality of an educational approach in this context in terms of Usability, Engagement, Motivation, and Learning. A study focused on the teaching and learning process of Physics was conducted with 27 students from a federal university, using the MAREEA questionnaire to evaluate the approach. The results were satisfactory and instigators, in which the four dimensions were evaluated positively, and there was also significant feedback from the participants for improvements in educational resources in augmented reality.Facultad de Informátic

Parâmetros genéticos, dissimilaridade e desempenho per se em acessos de abóbora

A abóbora tem grande importância na alimentação humana e animal, principalmente para a agricultura familiar. O banco de germoplasma de hortaliças da Universidade Federal de Viçosa (BGH-UFV) possui coleção de acessos de abóbora com ampla variabilidade genética. Toda esta variabilidade genética é de grande importância para o melhoramento genético. Porém, pouco se sabe sobre o verdadeiro potencial do BGH-UFV, pois há poucos estudos com informações desses acessos. Objetivou-se obter informações sobre os parâmetros genéticos, dissimilaridade e desempenho per se de acessos de abóbora do BGH-UFV. Foram avaliados 11 descritores morfoagronômicos em 55 acessos e três cultivares comerciais. Foram estimados parâmetros genéticos, ganho esperado com a seleção, correlações fenotípicas, genotípicas e ambientais. Para o estudo de dissimilaridade, foi realizado o teste Tocher e dispersão gráfica das duas primeiras variáveis canônicas. Houve variabilidade genética entre os acessos, com predominância dos efeitos genéticos sobre os ambientais. É esperado maior ganho de seleção para a massa por fruto, aspecto fitossanitário e localização do nó da primeira flor masculina. As cultivares comerciais Butternut e Tetsukabuto se destacaram em função da menor massa por fruto e maior precocidade de florescimento, porém tiveram os piores resultados quanto ao aspecto fitossanitário. Há estimativas negativas de correlação entre o aspecto fitossanitário com o hábito de crescimento, comprimento e taxa de crescimento da rama principal, indicando que plantas compactas podem ter maiores problemas fitossanitários. O cruzamento do acesso BGH-7003 ou da cultivar Butternut com os acessos BGH-1946 ou BGH-7765 podem gerar progênies com potencial para o melhoramento genético.Pumpkin is very important in human and animal food, especially concerning family farms. The germplasm bank of vegetables of Universidade Federal de Viçosa (Federal University of Viçosa, UFV-BGH), Brazil, has several pumpkin accessions with wide genetic variability. All this genetic variability is of great importance for plant breeding. However, little is known about the true potential of BGH-UFV, because there are few scientific papers published with information on these accessions. The objective was to obtain information on genetic parameters, dissimilarity and performance of BGH-UFV pumpkin accessions. We evaluated 11 morphological descriptors of 55 accessions and three cultivars. The genetic parameters, expected gain with selection, phenotypic, genotypic and environmental correlations were estimated. For the dissimilarity study, the Tocher test was carried out and graphic dispersion of the canonical variables was evaluated. There was genetic variability among accessions, with a predominance of genetic effects over the environment. Higher gain selection for mass per fruit, plant appearance and location of the first male flower node are expected. The commercial cultivars Butternut and Tetsukabuto have excelled due to the lower mass per fruit and precocity of flowering, but they had the worst results in terms of phytosanitary aspect. There are negative correlation estimates between the phytosanitary aspect and growth habit, length and growth rate of the main stem, indicating that compact plants may have greater phytossanitary problems. Crossing accession BGH-7003 or cultivar Butternut with accessions BGH-1946 or BGH-7765 can generate progenies with potential for breeding

ULEEN: A Novel Architecture for Ultra Low-Energy Edge Neural Networks

The deployment of AI models on low-power, real-time edge devices requires accelerators for which energy, latency, and area are all first-order concerns. There are many approaches to enabling deep neural networks (DNNs) in this domain, including pruning, quantization, compression, and binary neural networks (BNNs), but with the emergence of the "extreme edge", there is now a demand for even more efficient models. In order to meet the constraints of ultra-low-energy devices, we propose ULEEN, a model architecture based on weightless neural networks. Weightless neural networks (WNNs) are a class of neural model which use table lookups, not arithmetic, to perform computation. The elimination of energy-intensive arithmetic operations makes WNNs theoretically well suited for edge inference; however, they have historically suffered from poor accuracy and excessive memory usage. ULEEN incorporates algorithmic improvements and a novel training strategy inspired by BNNs to make significant strides in improving accuracy and reducing model size. We compare FPGA and ASIC implementations of an inference accelerator for ULEEN against edge-optimized DNN and BNN devices. On a Xilinx Zynq Z-7045 FPGA, we demonstrate classification on the MNIST dataset at 14.3 million inferences per second (13 million inferences/Joule) with 0.21 $\mu$s latency and 96.2% accuracy, while Xilinx FINN achieves 12.3 million inferences per second (1.69 million inferences/Joule) with 0.31 $\mu$s latency and 95.83% accuracy. In a 45nm ASIC, we achieve 5.1 million inferences/Joule and 38.5 million inferences/second at 98.46% accuracy, while a quantized Bit Fusion model achieves 9230 inferences/Joule and 19,100 inferences/second at 99.35% accuracy. In our search for ever more efficient edge devices, ULEEN shows that WNNs are deserving of consideration.Comment: 14 pages, 14 figures Portions of this article draw heavily from arXiv:2203.01479, most notably sections 5E and 5F.

Aplicação do método Peer Instruction no ensino de Algoritmos e programação de computadores

O presente trabalho discute e apresenta os resultados de um experimento realizado na disciplina de algoritmos e programação de computadores de uma escola pública, utilizando o método de ensino Peer Instruction (Instrução por Pares). O objetivo foi avaliar a eficácia do método, considerando aspectos referentes ao desempenho e o engajamento de estudantes novatos e experientes em programação do curso Técnico em Informática integrado ao Ensino Médio. Análises preliminares mostram um crescimento no desempenho dos alunos e indicam que aqueles em iniciação na programação têm uma pré-disposição em trabalhar de modo colaborativo comparado aos alunos com mais experiência