Flavia Oliveira Monteiro da Silva Abreu^1,2,*, Taysse Holanda¹, Joice Farias do Nascimento¹, Henety Nascimento Pinheiro¹, Rachel Menezes Castelo¹, Hélcio Silva dos Santos³, Thais Benincá⁴, Patrícia da Silva Malheiros⁴, Júlio César Sousa Prado⁵, Raquel de Oliveira Fontenelle⁵, Maria Madalena de Camargo Forte²

Journal of Renewable Materials, Vol.12, No.2, pp. 285-304, 2024, DOI:10.32604/jrm.2023.043919

Abstract With the increase in antimicrobial resistance, it has become necessary to explore alternative approaches for combating and preventing diseases. DB-cinnamaldehyde (CNM) and Benzyl4-amino (B4AM) are bioactive compounds derived from chalcones but with restricted solubility in aqueous media. Nanoemulsions can enhance the solubility of compounds and can be a promising alternative in the development of novel antimicrobials, with reduced side effects and prolonged release. The objective of this study was to evaluate the stability of oil-in-water nanoemulsions loaded with two distinct types of chalcones at two different dosages, to propose a stable formulation with antimicrobial properties. Results showed that nanoemulsions presented… More > Graphic Abstract

Shuwei Zhong, Yanbo Che^*, Shangyuan Zhang

Energy Engineering, Vol.121, No.3, pp. 603-618, 2024, DOI:10.32604/ee.2023.044667

Abstract Electric vehicle (EV) is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future. However, a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff. Therefore, this paper proposes a dynamic time-of-use tariff mechanism, which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean (FCM) clustering algorithm, and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period. Based on the proposed… More >

Jialin Yu^1,*, Xiaodi Zhang², Qi Zhong¹, Jian Feng¹

Energy Engineering, Vol.121, No.3, pp. 789-806, 2024, DOI:10.32604/ee.2023.043299

Abstract With a further increase in energy flexibility for customers, short-term load forecasting is essential to provide benchmarks for economic dispatch and real-time alerts in power grids. The electrical load series exhibit periodic patterns and share high associations with metrological data. However, current studies have merely focused on point-wise models and failed to sufficiently investigate the periodic patterns of load series, which hinders the further improvement of short-term load forecasting accuracy. Therefore, this paper improved Autoformer to extract the periodic patterns of load series and learn a representative feature from deep decomposition and reconstruction. In addition, a novel multi-factor attention mechanism… More >

FRANCESCO PETRELLA^*, ENRICO MARIO CASSINA, LIDIA LIBRETTI, EMANUELE PIRONDINI, FEDERICO RAVEGLIA, ANTONIO TUORO

Oncology Research, Vol.32, No.3, pp. 433-437, 2024, DOI:10.32604/or.2023.046497

Abstract The main aim of antineoplastic treatment is to maximize patient benefit by augmenting the drug accumulation within affected organs and tissues, thus incrementing drug effects and, at the same time, reducing the damage of non-involved tissues to cytotoxic agents. Mesenchymal stromal cells (MSC) represent a group of undifferentiated multipotent cells presenting wide self-renewal features and the capacity to differentiate into an assortment of mesenchymal family cells. During the last year, they have been proposed as natural carriers for the selective release of antitumor drugs to malignant cells, thus optimizing cytotoxic action on cancer cells, while significantly reducing adverse side effects… More >

Shasha Zhao^1,2,3,*, Huanwen Yan^1,2, Qifeng Lin^1,2, Xiangnan Feng^1,2, He Chen^1,2, Dengyin Zhang^1,2

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1135-1156, 2024, DOI:10.32604/cmc.2024.045660

Abstract Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment. Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios. In this work, the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm (HPSO-EABC) has been proposed, which hybrids our presented Evolutionary Artificial Bee Colony (EABC), and Hierarchical Particle Swarm Optimization (HPSO) algorithm. The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm. Comprehensive testing including evaluations of algorithm convergence speed, resource execution time, load balancing,… More >

Dinesh Mavaluru^1,*, Chettupally Anil Carie², Ahmed I. Alutaibi³, Satish Anamalamudi², Bayapa Reddy Narapureddy⁴, Murali Krishna Enduri², Md Ezaz Ahmed¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1487-1503, 2024, DOI:10.32604/cmes.2023.045277

Abstract In this paper, we present a comprehensive system model for Industrial Internet of Things (IIoT) networks empowered by Non-Orthogonal Multiple Access (NOMA) and Mobile Edge Computing (MEC) technologies. The network comprises essential components such as base stations, edge servers, and numerous IIoT devices characterized by limited energy and computing capacities. The central challenge addressed is the optimization of resource allocation and task distribution while adhering to stringent queueing delay constraints and minimizing overall energy consumption. The system operates in discrete time slots and employs a quasi-static approach, with a specific focus on the complexities of task partitioning and the management… More >

Dongyang Ou, Yongjian Ren, Congfeng Jiang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2043-2067, 2024, DOI:10.32604/cmes.2023.029987

Abstract Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster, where the resources can be pooled in order to maximize data center resource utilization. Due to resource competition between batch jobs and online services, co-location frequently impairs the performance of online services. This study presents a quality of service (QoS) prediction-based scheduling model (QPSM) for co-located workloads. The performance prediction of QPSM consists of two parts: the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on random forest. On-line service… More >

Ming Li^1,*, Rifucairen Fu¹, Tuerhong Yaxiaer¹, Yunping Zheng¹, Abiao Huang², Ronghui Liu², Shunfu Lin²

Energy Engineering, Vol.121, No.2, pp. 405-424, 2024, DOI:10.32604/ee.2023.044509

Abstract From the perspective of a community energy operator, a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads. The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system (IES) before and after; the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme, taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of… More >

Lifeng Wang¹, Jing Yu^2,*, Wenlu Ji¹

Energy Engineering, Vol.121, No.2, pp. 523-540, 2024, DOI:10.32604/ee.2023.041881

Abstract Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users, the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies. For this purpose, a power grid-flexible load bilevel model is constructed based on dynamic pricing, where the leader is the dispatching center and the lower-level flexible load acts as the follower. Initially, an upper-level day-ahead dispatching model for the power grid is established,… More >

Hayder Makki Shakir, Jaber Karimpour^*, Jafar Razmara

Computer Systems Science and Engineering, Vol.48, No.1, pp. 35-55, 2024, DOI:10.32604/csse.2023.038545

Abstract As the volume of data and data-generating equipment in healthcare settings grows, so do issues like latency and inefficient processing inside health monitoring systems. The Internet of Things (IoT) has been used to create a wide variety of health monitoring systems. Most modern health monitoring solutions are based on cloud computing. However, large-scale deployment of latency-sensitive healthcare applications is hampered by the cloud’s design, which introduces significant delays during the processing of vast data volumes. By strategically positioning servers close to end users, fog computing mitigates latency issues and dramatically improves scaling on demand, resource accessibility, and security. In this… More >