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Direct-driven generation is considered one of the most reliable selections in wave energy conversion systems. Therefore, a direct-driven linear-rotary wave generator (LRWG), which can transfer the low-speed linear wave motion to the high-speed rotating motion of the rotor and then generate electrical power simultaneously, is proposed in this paper. The proposed LRWG comprises three parts: translator, common rotor, and stator. From the energy view, the proposed LRWG can be divided into two sections: the energy transmission section to increase the velocity of the wave and the energy conversion section to generate power. The initial design method is given to determine the main dimensions of the proposed LRWG. To meet the maximum power tracking control requirements, a multi-mode and multi-objective optimization method, which can consider both generator and motor mode, is proposed to improve the performance of the proposed LRWG by sensitivity analysis, response surface methodology, and non-dominated sorting genetic algorithm II method. Finally, a prototype and its experimental platform are developed based on one of the optimization schemes from the possible solutions to verify the proposed approach and the performance of the proposed LRWG.

The distributed frequency control system of microgrids, which relies on classical communication networks between distributed generations (DGs) for frequency regulation and restoration, is vulnerable to cyber-attacks. Quantum distributed controllers offer a secure quantum communication scheme but are less efficient because of continuous communication in quantum systems. This paper proposes a quantum distributed event-triggered secondary frequency control strategy for the islanded AC microgrid. The suggested event-triggered control significantly lessens the communication load and is Zeno-free. Furthermore, a novel false data injection attack (FDIA) scenario is introduced for the quantum-microgrid system. The non-periodic nature of communication can be exploited to directly identify and isolate compromised communication links, thereby enhancing the resilience of the quantum-microgrid system. Finally, simulation results on an AC microgrid with four DGs validate the effectiveness of the suggested control scheme.

AbstractWe assessed hepatocellular carcinoma (HCC) risk associated with smoking and alcohol consumption and their interactions, using both questionnaire data and objective serum biomarkers. Information on smoking and alcohol consumption was collected at baseline from 450,112 participants of the EPIC cohort, among whom 255 developed HCC after a median follow‐up of 14 years. In a nested case–control subset of 108 HCC cases and 108 matched controls, known biomarkers of smoking (cotinine, nicotine) and habitual alcohol consumption (2‐hydroxy‐3‐methylbutyric acid) were annotated from untargeted metabolomics features. Multivariable‐adjusted hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were computed, and multiplicative and additive interaction parameters were calculated. Compared to never smokers, current smokers had a higher HCC risk (HR = 2.46, 95% CI = 1.77–3.43) dose‐dependently with the number of cigarettes smoked per day (Ptrend <.001). Compared to light drinkers, HCC risk was higher in former (HR = 3.20, 95% CI = 1.70–6.03), periodically heavy (HR = 1.98, 95% CI = 1.11–3.54), and always heavy (HR = 5.51, 95% CI = 2.39–12.7) drinkers. Higher HCC risk was also observed in the highest versus the lowest tertiles of cotinine (OR = 4.88, 95% CI = 1.52–15.70), nicotine (OR = 5.80, 95% CI = 1.33–25.30) and 2‐hydroxy‐3‐methylbutyric acid (OR = 5.89, 95% CI = 1.33–26.12). Questionnaire‐assessed smoking and alcohol exposures did not demonstrate an HCC risk interaction at the multiplicative (MI = 0.88, 95% CI = 0.40–1.96) or additive (RERI = 0.71, 95% CI = −10.1 to 23.6; attributable proportion = 0.17, 95% CI = −0.52 to 1.16; synergy index = 1.27, 95% CI = 0.98–1.66) scales. Similar analyses with cotinine, nicotine, and 2‐hydroxy‐3‐methylbutyric acid also did not show interactions between smoking and alcohol consumption on HCC risk. Smoking and alcohol consumption are strong independent risk factors for HCC and do not appear to synergistically impact its risk, but larger studies are needed.

Concentrating solar power (CSP) plants are seen as a key technology to achieve the needed energy transition since its use together with a thermal energy storage (TES) system ensures electricity dispatchability decreasing CSP plants environmental impact and life cycle costs. Latent TES using phase change materials (PCMs) has risen as a very interesting storage technology for such applications. Nevertheless, the selection of the adequate TES system and PCM, is one of the problems researchers and practitioners face to implement such technology. This paper presents a full characterization of fifteen PCMs suitable to work in the temperature range 400-600 ◦C. Melting temperature, melting enthalpy, degradation temperature, and solid-state thermal conductivity are presented, complemented with corrosion behaviour tests against stainless steel and Alloy 20. Moreover, the findings obtained in the characterization of the selected fifteen PCMs highlight the need of these analyses, as notable differences were observed compared to the available data, particularly in thermal stability and thermal conductivity. Furthermore, the compatibility test reveals that out of the fifteen selected PCMs, only two PCMs (binary mixtures of carbonates) are potentially compatible with stainless-steel 314 and Alloy 20 fibres under environmental conditions (air atmosphere). Finally, the results presented will allow researchers and practitioners to have very detailed data on the characterisation of those PCMs. This work was partially funded by the Ministerio de Ciencia e Innovación - Agencia Estatal de Investigación (AEI) (PID2021-123511OB-C31 - MCIN/AEI/10.13039/501100011033/FEDER, UE, and RED2022-134219-T). This work is partially supported by ICREA under the ICREA Academia programme. The authors would like to thank the Catalan Government for the quality accreditation given to their research group (2021 SGR 01615). GREiA is certified agent TECNIO in the category of technology developers from the Government of Catalonia. This paper is part of the RYC2023-044196-I, funded by MCIU/AEI/10.13039/501100011033 and FSE+. Franklin R. Martinez Alcocer thanks the National Doctorate Scholarship for foreign students ANID 2021 Folio 21211932 for the financial support in the research. S. Ushak acknowledges to ANID/PUENTE N° 1523A0006 and ANID/FONDECYT REGULAR N° 1231721 projects.

This letter has developed an electrical circuit analogy-based maximum latency calculation (MLC) method of the internet data center (IDC) in power-communication network. Firstly, by analogy with the circuit model, the basic concepts to describe information flow are defined, including information current, information resistance, information conductivity, and information voltage. Based on these concepts, the information processing model considering both channel blocking and user priority is established. By analogy with the electrical circuit, the information flow calculation laws are introduced to calculate the maximum latency of IDCs. Verification results show that the maximum latency of IDCs in power-communication network can be accurately calculated by the proposed MLC method.

Advancing a safe and sustainable waste-to-energy supply chain is predominant for achieving a circular business model. However, establishing such a supply chain requires addressing its inherent complexities and developing mitigation strategies for implementing safe and sustainable by-design practices. While earlier research has mainly focused on sustainable chemicals and materials for promoting sustainable by-design practices, the sustainable waste-to-energy supply chain has been largely overlooked. This study systematically evaluates challenges considering associated uncertain future events and examines mitigation strategies for the practical implementation of safe and sustainable by-design practices. To achieve this, a novel decision support framework is developed, integrating a trapezoidal fuzzy-based stratified best-worst method, quality function deployment, and a mixed-integer linear programming model. Data is collected from domain experts to the framework's applicability.