92 research outputs found
War and Peace in Russia\u27s Realms: A&S 100 with Karen Petrone
No full textLater this spring, Professor Karen Petrone will begin teaching a new 7-week class as part of this year\u27s Passport to the World Program: Reimagining Russia’s Realms. The class, A&S: 100 - War & Peace in Russia\u27s Realms will explore the Russian and Soviet experience of World War I, the Russian Civil War, and World War II through literature, film, and history. Additionally, students will have the opportunity to discover Russian author Leo Tolstoy’s surprisingly influential role in the development of the non-violent resistance movement.
Petrone, the chair of the Department of History, hopes to help students analyze how Russian memories of past wars shape the country today. This topic is one Petrone is already quite familiar with—so much so in fact she\u27s written a book on the subject: The Great War in Russian Memory. The course also offers a unique opportunity for students to learn about Russia\u27s past through its connection to a series of other classes and a play that students will have the opportunity to see at the end of the semester
Early Detection of Photovoltaic Panel Degradation through Artificial Neural Network
No full textIn this paper, an artificial neural network (ANN) is used for isolating faults and degradation phenomena occurring in photovoltaic (PV) panels. In the literature, it is well known that the values of the single diode model (SDM) associated to the PV source are strictly related to degradation phenomena and their variation is an indicator of panel degradation. On the other hand, the values of parameters that allow to identify the degraded conditions are not known a priori because they can be different from panel to panel and are strongly dependent on environmental conditions, PV technology and the manufacturing process. For these reasons, to correctly detect the presence of degradation, the effect of environmental conditions and fabrication processes must be properly filtered out. The approach proposed in this paper exploits the intrinsic capability of ANN to map in its architecture two effects: (1) the non-linear relations existing among the SDM parameters and the environmental conditions, and (2) the effect of the degradation phenomena on the I−V curves and, consequently, on the SDM parameters. The ANN architecture is composed of two stages that are trained separately: one for predicting the SDM parameters under the hypothesis of healthy operation and the other one for degraded condition. The variation of each parameter, calculated as the difference of the output of the two ANN stages, will give a direct identification of the type of degradation that is occurring on the PV panel. The method was initially tested by using the experimental I−V curves provided by the NREL database, where the degradation was introduced artificially, later tested by using some degraded experimental I−V curves.Photovoltaic Materials and Device
Development of an Automatic Pipeline for Data Analysis and Pre-Processing for Data Driven-Based Engine Emission Modeling in a Real Industrial Application
No full textDuring the development of an Internal Combustion Engine-based powertrain, traditional procedures for control strategies calibration and validation produce huge amount of data, that can be used to develop innovative data-driven applications, such as emission virtual sensing. One of the main criticalities is related to the data quality, that cannot be easily assessed for such a big amount of data. This work focuses on an emission modeling activity, using an enhanced Light Gradient Boosting Regressor and a dedicated data pre-processing pipeline to improve data quality. First thing, a software tool is developed to access a database containing data coming from emissions tests. The tool performs a data cleaning procedure to exclude corrupted data or invalid parts of the test. Moreover, it automatically tunes model hyperparameters, it chooses the best set of features, and it validates the procedure by comparing the estimation and the experimental measurement. The proposed pre-processing pipeline shows an improvement in terms of accuracy, demonstrating the utility of using large training data which cover a wide set of vehicle maneuvers. Thus, custom designed tests are performed for dataset enrichment, allowing the model to predict non-conventional conditions of aftertreatment systems inefficiency. Real case applications of the proposed model are exposed, such as emission estimation in non-measurable conditions, virtual assessment of the impact of new control strategy calibration on emissions, alignment of emission measurements with all other vehicle signals. Finally, a Principal Component Analysis-based algorithm is developed, to assess the epistemic uncertainty of the model and the prediction reliability during inference
Viewing Rural, Rurality, and Ruralities as Social Constructs: An Author Interview and Book Review of Teaching English in Rural Communities
No full textTeaching English in Rural Communities: Toward a Critical Rural English Pedagogy by Robert Petrone and Allison Wynhoff Olsen provides insights and practical strategies for teachers working in rural areas, where they often face unique challenges such as limited resources and cultural differences. This book provides a lens of criticality through the critiques and celebrations of rural living. This article opens with reviews of Critical Rural English Pedagogy and the chapters in the book. After the review, there are highlights of the exclusive interview with Petrone and Wynhoff Olsen as they relate their personal experiences and reflections on teaching in rural areas and stretch their pedagogy across education disciplines. Through the book review and author interview, this article sheds light on the importance of supporting and empowering educators in rural communities and highlights the key role of Critical Rural English Pedagogy in education
Petrone Print’s My-series: insight into the literature of the selfie era
No full textIt may be said that in contemporary society the perceiving and experiencing subject is in the foreground. This is also valid in the field of literature, which has been democratised, as anyone can make a book and anyone can write a book, as seen by the boom of autobiographies of all kinds. The My-series published by the Estonian publishing company Petrone Print illustrates this tendency. In this series of books, authors describe their lives and activities in a particular country or city. The majority of the authors are not writers, but hail from various fields. The series is a staple of contemporary Estonian literature: the books are constantly in the top ten list and are in high demand in libraries.
The phenomenon of this series maybe explained by its versatility: it boasts an array of authors from different fields who write about various places. The books are also well structured and easy to read. Taking the My-series as an example, the article maps tendencies in contemporary Estonian literature. Subject-centeredness is a central characteristic of contemporary literature, evidenced by the noteworthy volume of books concerned with one’s life experiences. The exact genre of this type of literature is ambiguous, which is another characteristic of contemporary literature. The My-series of books may be defined as ‘literary selfies’, as the author foregrounds him/herself, with the world around them serving merely as a backdrop
AI-Based Virtual Sensing of Gaseous Pollutant Emissions at the Tailpipe of a High-Performance Vehicle
No full textThis scientific publication presents the application of artificial intelligence (AI) techniques as a virtual sensor for tailpipe emissions of CO, NOx, and HC in a high-performance vehicle. The study aims to address critical challenges faced in real industrial applications, including signal alignment and signal dynamics management. A comprehensive pre-processing pipeline is proposed to tackle these issues, and a light gradient-boosting machine (LightGBM) model is employed to estimate emissions during real driving cycles. The research compares two modeling approaches: one involving a unique “direct model” and another using a “two-stage model” which leverages distinct models for the engine and the aftertreatment. The findings suggest that the direct model strikes the best balance between simplicity and accuracy. Furthermore, the study investigates two sensor setups: a standard configuration and an optimized one, which incorporates an additional lambda probe in the exhaust line after the main catalyst. The results indicate a significant enhancement in performance for NOx and CO estimations with the introduction of the third lambda probe, while HC results remain relatively unchanged. Additionally, the AI model is tested on two different electronic control unit (ECU) software calibrations, yielding excellent results in both cases. This suggests that machine learning models are robust to control software variation and can be used to optimize software calibrations in a virtual environment, reducing the reliance on extensive experimental testing. Moreover, the AI model’s performance demonstrates compatibility with real-time implementation. In conclusion, this work establishes the viability and efficiency of AI techniques in accurately estimating tailpipe emissions from an engine in an industrial context. The study showcases the potential for AI to contribute to emission estimation and optimization processes, offering a promising pathway for an innovative industrial practice
Política agrária e imigratória nas colônias japonesas de Santa Catarina (1961-1978).
No full textTrabalho de Conclusão de Curso - Universidade Federal de Santa Catarina. Curso de Licenciatura em História
Clinical and radiographic performance of indirect foraminal decompression with anterior retroperitoneal lumbar approach for interbody fusion (ALIF)
No full textStudy design: Retrospective study Background: Indirect decompression with ALIF allows the restoration of the disk and foraminal height with limited soft tissue damage. However, it does not offer a direct view of the neural structure and a direct intraoperative assessment of the results of the decompression is not possible. For this reason, ALIF is often accompanied by posterior, direct decompression. So far, there is no consensus on the effects of indirect decompression alone for L5-S1 foraminal stenosis. Objective: Evaluation of the clinical and mechanical performance of indirect decompression with anterior lumbar interbody fusion (ALIF) in L5-S1 foraminal stenosis. Methods: All patients who underwent ALIF at our institution and had a minimum follow-up of six months were assessed for inclusion. Radiographic parameters (anterior and posterior disc height, foraminal height and surface, L5-S1 angle, pelvic incidence, pelvic tilt and lumbar lordosis) and clinical data (Oswestry Disability Index - ODI and Numeric Rating Scale - NRS) before ALIF and at the last follow-up were compared. A regression analysis was performed to investigate the correlation between radiographic and clinical outcomes. Results: Thirty-four patients were available for the study (55.9% female, mean age 53.4 +/- 11.5 years), mean follow-up was 26.4 +/- 11.1 months. At the last follow-up, a significant increase in foraminal height (14.6 +/- 4.0 vs. 17.9 +/- 3.9 mm, p<0.001), posterior disc height (6.5 +/- 2 vs. 9.1 +/- 2 mm, p<0.001) was observed. ODI and NRS back and leg improved significantly. The NRS leg correlated with foraminal height (r=-0.45), foraminal surface (r=-0.36) and anterior (r=-0.41) and posterior disc height (r=-0.43). Conclusion: ALIF provided significant indirect foraminal decompression and improvement of radicular pain. The increase of foraminal height, surface, and posterior disc height is directly associated with radicular pain improvement. Level of evidence: IV Availability of data and material: The datasets used and/or analyzed in the present study are available from the corresponding author on reasonable request
Volcanic eruptions: From ionosphere to the plumbing system
No full textIt's open accessThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article.NHM Repositor
Terenzio
No full textTerenzio: una nuova sensibilità artistica. Il successo di un autore di palliate. Lo stile e lo opereTerenzio: a new artistic sensibility. The success of an author of palliate. Style it and it work
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