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Dehydrated natural feed for dogs: influence on digestibility, immunity, and antioxidant response

Comparative Clinical Pathology 2025年第2期34卷 269-280页

作者： Cecere, Bruno G. O. Zatti, Emerson Bissacotti, Bianca F. Copetti, Priscila M. da Silveira, Marcylene V. Schetinger, Maria Rosa C. Klein, Bruna Suarez, Walter H. C. da Silva, Aleksandro S. Graduate Multicenter Program in Biochemistry and Molecular Biology University of the State of Santa Catarina (UDESC) Lages Brazil Graduate Program in Animal Science Universidade Federal de Santa Maria Santa Maria Brazil Graduate Program in Toxicological Biochemistry Universidade Federal de Santa Maria Santa Maria Brazil Department of Animal Science UDESC Chapecó Brazil Department of Animal Nutrition Tectron Tecnologia e Inovação Toledo Brazil

With the intensification of domestication, companion animals have become precious members of family homes;therefore, there is a constant search for improving the quality of life and well-being of these animals, where nutrition is considered a factor of great relevance. Natural diets appear as an alternative to differentiated feeds for pets, and the dehydration of natural feeds favors their use, maintaining their quality and increasing their shelf life. The present study objective was to determine whether dehydrated natural feed can replace extruded dry feed while maintaining good digestibility without impairing its metabolism, inflammatory/immune responses, and antioxidant status. Ten male beagle dogs housed in an experimental kennel and fed individually were used. They were divided into two groups with five animals each, one group received natural dehydrated feed (DNF), and another consumed commercial dry feed (DCF), calculated from the determination of metabolizable energy (ME) requirements based on the animal’s metabolic weight (BW). The experiment lasted 45 days, with 40 days of adaptation and health assessment and days of feces collection from animals in metabolism cages. At the end of this first phase, after a 10-day interval, the experiment was repeated;however, in this phase, the animals from the DCF group were transferred to the DNF group so that all animals received both feeds. During the 40 days, the animals were weighed, and blood was collected. On the other 5 days, total feces were collected, and the feces score was calculated. The animals in the DNF group showed higher digestibility of digestible fiber and mineral matter and lower digestibility of ether extract and dry matter. The dogs from the DNF group had a higher volume of excreted feces, with higher humidity and a score of 3;for the DCF group, the score was 2. DNF dogs had lower blood leukocyte and granulocyte counts;however, there was a tendency toward increased lymphocytes on day 40. Dogs in the

关键词： Alternative feed Animal health Dry feed Immune response Inflammatory

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Load Balancing to Optimize MPEG-DASH Video Streaming

Load Balancing to Optimize MPEG-DASH Video Streaming

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International Conference on Information Networking

作者： Edenilson Jônatas Dos Passos Adriano Fiorese Department of Computer Science (DCC) Graduate Program in Apllied Computing (PPGCAP) Santa Catarina State University (UDESC) Joinville Brazil

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

Recent advancements in on-demand multimedia streaming have revealed the potential of this business model, driven by the convenience of accessing content anytime and anywhere. However, delivering a seamless user experience remains challenging due to the demanding nature of audiovisual streams, despite significant resource allocation. A promising solution involves using load balancers to distribute workloads evenly among processing units. This study proposes optimizing the processing and transmission resources by means of Software-Defined Networks (SDN). By continuously monitoring performance metrics like CPU usage and throughput, the SDN network controller determines the best server for handling new connections, even allowing seamless server migration during playback. The results show up to 80% faster response times and more consistent video quality, with reduced latency and uninterrupted playback. The approach also confirms the feasibility of SDN in streaming services, providing a foundation for future network improvements.

关键词： Transform coding Streaming media Load management User experience Quality assessment Servers Time factors Software defined networking Video recording Monitoring

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Using synthetic data to develop machine learning models to predict the performance of fiber-reinforced concrete

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Asian Journal of Civil Engineering 2025年第5期26卷 2209-2221页

作者： Silva, Victor Hugo Peres Pessoa, Carolina Luiza Emereciana Sousa, Derica dos Santos Stefani, Ricardo Graduate Program in Materials Science Federal University of Mato Grosso Campus Araguaia MT Cuiaba 78605-091 Brazil Center for Agricultural and Veterinary Sciences University for the Development of Santa Catarina State (UDESC) Campus Lages SC Florianópolis 88520-000 Brazil Departament of Chemistry Federal University of Ouro Preto MG Ouro Preto 35402-136 Brazil

Concrete is a widely used construction material owing to its high compressive strength. However, its durability is often compromised by the development of cracks caused by tensile stress within the structures. These cracks can occur during the drying process, leading to water infiltration and corrosion of the concrete reinforcement, which subsequently require repair. Consequently, innovative technologies, such as self-repairing concrete and crack control, have become crucial for reducing the costs associated with structural repairs. In this context, this study investigated novel crack-control technologies in concrete structures using a machine-learning model that can accurately predict the performance of a specific fiber in fiber-reinforced concrete using a comprehensive dataset. The dataset was compiled from 18 studies and further augmented using synthetic data-generation techniques. It encompasses 13 different fiber types and 1953 fiber-reinforced concrete formulations. The computational model was implemented in Python, and multiple linear regression (MLR), support vector regression (SVR), random forest, and gradient boosting techniques were employed to develop the prediction model. The results showed that the Random Forest (R² = 0.887 and RMSE = 0.110), gradient boosting (R² = 0.868 and RMSE = 0.368), and SVR models (R² = 0.856 and RMSE = 0.376) outperformed their MLR counterparts (R² = 0.587 and RMSE = 0.637). Moreover, the Random Forest method showed a lower RMSE, making it more suitable for accurately predicting the performance of fiber-reinforced concrete. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Crack control Fiber-reinforced concrete Machine learning

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Agricultural sustainability index in Brazil

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Environmental Challenges 2025年 19卷

作者： Christo, Bruno Fardim Andrade Okawati, Gabriel Akira Vasconcellos, Daniel M. de Rosas, Jorge Tadeu Fim de Araujo, Marcela Almeida Dourado-Neto, Durval Nóia-Júnior, Rogério de S. UFSC Federal University of Santa Catarina Graduate Program in Administration Santa Catarina Florianópolis Brazil Bachelor of Science in Economics Santa Catarina State University (UDESC) Florianópolis Brazil Luiz de Queiroz College of Agriculture University of São Paulo São Paulo Piracicaba Brazil LEPSE Univ Montpellier INRAE Institut Agro Montpellier Montpellier France

Agriculture faces the challenge of increasing food production while reducing environmental impacts like soil erosion and greenhouse gas emissions. This study introduces a comprehensive Agricultural Sustainability Index for Brazil, integrating economic, social, and environmental indicators. The quantitative index includes seven environmental indicators (e.g., Burned Area, Carbon Loss, Soil Erosion), five social indicators (e.g., Education, Gender Inequality, Land Distribution), and five economic indicators (e.g., Credit Access, Economic Income, Infrastructure). Results show that Agricultural Sustainability Index values range from 0.12 to 0.67, with a mean and median of 0.42. Since 1 represents the highest sustainability and 0 the lowest, half of Brazil's municipalities fall below 0.42, indicating room for improvement. Municipalities in the South and Southeast perform better, while those in the North and Northeast face economic constraints and lower scores. Environmental challenges are particularly significant in the Pantanal and Cerrado biomes. These findings emphasize the need for region-specific strategies and infrastructure improvements. Future research should refine the index and incorporate dynamic factors like climate change to enhance agricultural sustainability in Brazil. © 2025 The Authors

关键词： Economic indicators Environmental indicators Greenhouse Gas Emissions Social indicators Soil Erosion

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Fraud detection in water meters using pattern recognition techniques 17

Fraud detection in water meters using pattern recognition te...

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32nd Annual ACM Symposium on applied computing, SAC 2017

作者： Detroz, Juliana Patrícia Da Silva, André Tavares PPGCA - Graduate Program in Applied Computing UDESC - Santa Catarina State University Brazil

ISBN: (纸本)9781450344869

Water supply utilities have been increasingly looking for solutions to reduce water wastage. Many efforts have been made aiming to promote a better management of this resource. Fraud detection is one of these actions, as the irregular violations are usually held precariously, thus, causing leaks. In this context, the use of technology in order to automate the identification of potential frauds can be an important support tool to avoid water waste. Thus, this research aims to apply pattern recognition techniques in the implementation of an automated detection of suspected irregularities cases in water meters, through image analysis. The proposed computer vision system is composed of three steps: the detection of the water meter location, obtained by OPF classifier and HOG descriptor, detecting the seals through morphological image processing and segmentation methods;and the classification of frauds, in which the condition of the water meter seals is assessed. We validated the proposed framework using a dataset containing images of water meter inspections. At the last step, the proposed framework reached an average accuracy up to 81.29%. We concluded that a computer vision system is a promising strategy and has potential to benefit the analysis of fraud detection. Copyright 2017 ACM.

关键词： Object detection

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Comparing Best and Quota Fragment Picker Protocols applied to Protein Structure Prediction 20th

Comparing Best and Quota Fragment Picker Protocols Applied t...

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20th International Conference on Hybrid Intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

作者： Will, Nilcimar Neitzel Parpinelli, Rafael Stubs UDESC Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783030730499

The use of fragment insertion in the protein structure prediction problem can be considered one of the most successful strategies to add problem-dependent information. The well known Rosetta suite provides two protocols for generating fragment libraries: Best and Quota. The first aims to maximize a given score function, while the second aims add fragment diversity. This paper presents the results with four proteins to verify the impact of using more secondary structure information through the quota protocol when compared to the best protocol. The tests were performed considering the PSIPRED, SPIDER2, and MUFold predictors. Results obtained are compared in terms of RMSD, processing time, and convergence. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Forecasting

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GOTE: An Edge computing Architecture for Mobile Gaming 25

GOTE: An Edge Computing Architecture for Mobile Gaming

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25th International Conference on Enterprise Information Systems, ICEIS 2023

作者： Robaina, Gabriel Fiorese, Adriano Graduate Program in Applied Computing - PPGCAP Santa Catarina State University - UDESC Joinville Brazil

ISBN: (纸本)9789897586484

The mobile games market has grown in relevancy compared to traditional gaming platforms. The standard architecture for these games requires the processing of game logic and graphics using the device's own hardware. Alternatively, cloud based architectures for remote gaming on smartphones present high game input delay at a high cost for the service provider. This poses a limitation to the variety and complexity of games that target these platforms as well as constraining user QoE. To address that limitation, this work proposes the Gaming On The Edge (GOTE) architecture, that aims to enable complex games to be played on smartphone devices while leveraging edge computing infrastructure into graphics processing and content distribution systems. A GOTE architecture's proof of concept is developed and tested using WebRTC with an RTP streaming pipeline that exploits NVENC for achieving low latency video encoding. Experimental results show that GOTE architecture is a viable alternative to cloud based remote gaming on smartphones at the advantage of lowering latency of video and game input. An open source implementation of the architecture is provided in order to assist further research in this area. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Edge computing

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A method to automatically identify road centerlines from georeferenced smartphone data

A method to automatically identify road centerlines from geo...

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14th Brazilian Symposium on GeoInformatics, GEOINFO 2013

作者： Costa, George Henrique Rangel Baldo, Fabiano Graduate Program in Applied Computing Computer Science Department UDESC Santa Catarina State University Joinville Brazil

Digital road maps have gained fundamental role in population's daily life, so they need to be accurate and up-to-date. A viable solution is to generate maps by processing GPS data. However, one of the most challenging tasks regarding this approach is how to extract road centerlines from the cloud of georeferenced GPS points. The literature presents various methods that do it, but none have been found that is prepared for the continuous update of the map and refinement of its roads' accuracy. In this context, the objective of this work is to propose a method to identify road centerlines using an evolutive algorithm in order to generate and update road maps. This work uses as source of data GPS traces collected by smartphones. Although suitable to obtain a large amount of georeferenced data, these devices bring the additional problem of identifying the transport vehicle used along each trace. Preliminary results indicate that the method's performance is satisfactory, with an average variation of 2.95 meters in relation to satellite images.

关键词： Smartphones

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Identifying Network Congestion on SDN-Based Data Centers with Supervised Classification 37th

Identifying Network Congestion on SDN-Based Data Centers wi...

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37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： da Silva de Oliveira, Filipe Pillon, Maurício Aronne Miers, Charles Christian Koslovski, Guilherme Piêgas Graduate Program in Applied Computing Santa Catarina State University Santa Catarina Joinville Brazil

ISBN: (纸本)9783031284502

Data centers have networks that provide, for a large number of users, various services such as video streaming, financial services, file storage, among others. Like any network-based system, a Data Center (DC) is subject to congestion, a fact that can cause slowness and instability, affecting the performance of applications for end users. Among the technologies for data center management, Software Defined Networking (SDN) separate the control from the data plane, allowing applications to access statistical information and other details about current state of the network through a controller. In this sense, SDN brings a new opportunity to detect congestion on DC networks in a centralized manner. However, identifying the occurrence of congestion in networks is an arduous task due to the high number of related data. With these data, this work seeks to apply supervised classification to identify congestion events. The experimental campaign demonstrated that the SDN-based supervised classification mechanisms find more congestion events then the native congestion control algorithms from Transmission Control Protocol (TCP). Moreover, among diverse supervised algorithms, we demonstrate which one has better accuracy and efficient performance when analyzing Cubic and DCTCP variants. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Transmission control protocol

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A GPU-based hybrid jDE algorithm applied to the 2D-AB protein structure prediction problem 8

A GPU-based hybrid jDE algorithm applied to the 2D-AB protei...

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8th Brazilian Conference on Intelligent Systems, BRACIS 2019

作者： Boiani, Mateus Dominico, Gabriel Stubs Parpinelli, Rafael Graduate Program in Applied Computing Santa Catarina State University Joinville Santa Catarina Brazil

ISBN: (纸本)9781728142531

Protein Structure Prediction (PSP) problem is an open problem in bioinformatics and, as the problem scales, complexity and processing time increases. In this way, robust methods and massively parallel architectures are required. This paper presents a GPU-based hybrid algorithm, named cuHjDE, to handle the 2D-AB off-lattice PSP problem. The cuHjDE is composed of the jDE algorithm and the Hooke-Jeeves local search algorithm. An important feature present in the cuHjDE algorithm is the use of a crowding mechanism to avoid premature convergence promoting diversification in the search space. The proposed algorithm is compared with four state-of-the-art algorithms in both artificial and real proteins. Also, the impact of using GPU is analyzed. Experimental results point out that the proposed approach is competitive in artificial sequences and achieved new best results for all real sequence proteins. © 2019 IEEE.

关键词： Proteins

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