The Internet of Underwater Things (IoUT) supports marine sensing, environmental monitoring, subsea inspection, and autonomous underwater operations. However, IoUT communication is constrained by limited bandwidth, long propagation delay, time-varying underwater channels, intermittent connectivity, and strict energy budgets. Semantic Communication (SC) offers a promising alternative by transmitting task-relevant meaning rather than raw data, thereby improving communication efficiency in resource-constrained underwater networks. This paper presents a critical and feasibility-aware survey of SC for IoUT, focusing on architectures, opportunities, challenges, limitations, and future research directions. We first review the fundamentals of SC-enabled IoUT systems, including semantic representations, layered architectures, impairment-aware semantic channel modeling, and task-oriented evaluation metrics. We then examine learning-driven approaches based on machine learning (ML), knowledge graphs (KGs), vision-language models (VLMs), generative models, and federated learning (FL), with emphasis on their feasibility under underwater edge and channel constraints. Representative applications, including environmental monitoring, marine ecology, subsea infrastructure inspection, disaster response, and autonomous underwater vehicle (AUV) coordination, are analyzed from an SC perspective. Finally, we identify key research directions involving standardized semantic models, reproducible testbeds, compute-communication trade-offs, trustworthy reconstruction, hybrid underwater links, energy-aware edge intelligence, semantic security, digital twins (DTs), and cross-domain interoperability. This survey provides a structured foundation for developing reliable, efficient, and meaning-driven IoUT communication systems.
This research introduces and optimizes a novel multi-generation power system integrating a steam Rankine cycle (SRC), a gas turbine (GT), an absorption refrigeration cycle (ARC), a proton exchange membrane (PEM) electrolyzer, and a CO2 separation unit. This system is designed to improve energy efficiency while simultaneously capturing CO2 and producing hydrogen through electrolysis. Two configurations-with and without ARC-are evaluated using a genetic algorithm-based multi-objective optimization framework, which considers exergetic efficiency, CO2 emission reduction, and total cost rate. The findings demonstrate that the proposed system improves exergetic efficiency by up to 71% and reduces CO2 emissions by up to 3.9% compared to a standalone GT system. Furthermore, the system without ARC achieves higher hydrogen production, while the system with ARC provides valuable cooling. These findings demonstrate the feasibility and environmental advantages of integrated power, CO2 capture, and H 2 blending systems for sustainable energy generation.
Egg washing at home is generally discouraged in some regions because it can damage the egg's natural protective cuticle and increase the risk of bacterial penetration. However, little is known about how consumers in Southeast Asia wash and handle eggs in domestic settings. This study aims to investigate egg washing and handling practices among consumers using a mixed-method approach. A cross-sectional online survey was conducted with consumers from Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Thailand, and Vietnam. This was followed by 24 domestic kitchen observations and semi-structured interviews in Malaysia, Indonesia, and Thailand. Quantitative data were analysed using descriptive statistics, chi-square tests, Kruskal-Wallis tests, and logistic regression. Qualitative data were analysed thematically. The majority of participants reported washing eggs before cooking. More than half of those who washed eggs indicated that they would still wash eggs even when they appeared visually clean. Eggs were commonly rinsed under tap water, often to remove dirt, faeces, slime, or feathers. Respondents from Cambodia, Indonesia, Malaysia, Myanmar, the Philippines and those with greater perceived risk of Salmonella contamination in eggs were more confident in following the message. Observations revealed appropriate handwashing after handling or cracking eggs was rare and cross-contact opportunities were frequently observed. Semi-structured interview findings showed that egg washing was closely linked to perceived beliefs about cleanliness and safety, habitual practice, and uncertainty about how eggs had been handled before purchase. Some participants also described wiping as an alternative cleaning strategy, while informal information sources appeared to influence views on egg washing. Practical guidance should emphasise
Purpose Rupture of the extensor pollicis longus (EPL) tendon is an uncommon but clinically important complication of distal radius fractures. We investigated its incidence, timing, associated factors, and functional consequences in a prospective cohort. Methods This is a secondary analysis of a prospective multicenter cohort at two Swedish orthopedic departments, 2009–2012. Consecutive adults with acute distal radius fractures were enrolled and followed to 12 months. EPL function was assessed by active thumb extension testing at 3 and 12 months. Extensor tendon status was recorded in 419 fractures at 3 months and 373 at 12 months. Associations were analyzed between EPL rupture and age, sex, initial fracture displacement, dorsal comminution, treatment modality, surgical technique, 12-month grip strength, Disabilities of the Arm, Shoulder, and Hand (QuickDASH), and EQ-5D. Results Ten EPL ruptures were identified among the 419 fractures assessed at 3 months, representing an incidence of 2.4%. One rupture was acute; none occurred between 3 and 12 months. Seven ruptures occurred in undisplaced or minimally displaced fractures, and three occurred in displaced fractures (P = .06). Four followed surgical treatment, and six followed nonsurgical management. EPL rupture was not significantly associated with age, sex, dorsal comminution, treatment type, or surgical technique. At 12 months, grip strength, QuickDASH, and EQ-5D did not differ significantly between patients with and without EPL rupture. Seven of the 10 patients with rupture underwent tendon transfer; 12-month QuickDASH scores did not differ between these subgroups. Conclusions EPL rupture occurred in 2.4% of distal radius fractures, and all cases occurred within 3 months. No clear demographic, fracture-related, or treatment-related risk factors were identified. Long-term grip strength, function, and quality of life were comparable between patients with and without rupture. Outcomes were acceptable in the few selected patients managed nonsurgically, but the study was not powered to compare treatments. These findings underscore the importance of early surveillance and support an individualized approach. Type of study/level of evidence Prognostic II.
Advanced Encryption Standard (AES), PRESENT, and ASCON are widely deployed encryption algorithms in various applications ranging from servers to resource-constrained devices. This paper applies classical Correlation Power Analysis (CPA) and Machine Learning (ML) based power analysis attacks to all three ciphers. Power traces are captured with a ChipWhisperer-Lite from an 8-bit ATXMEGA microcontroller running each cipher. Subsequently, to emulate the practical side-channel countermeasures and assess the robustness of these methods, trace misalignment (jitter) and amplitude noise at controlled levels are injected into these clean captured traces. CPA and four ML models are employed and compared in three different phases: First using clean traces; second, using traces with either noise or jitter; and the last phase uses traces where both noise and jitter have been combined. A comprehensive performance evaluation is conducted by measuring key recovery rate, accuracy, F1 score, and runtime. On the clean traces, every method recovers the full key for AES and PRESENT ciphers. However, ASCON resists standard CPA, so it is attacked with second-order (SO) CPA, which recovers up to 50% of the key bytes. Under distortion, no single method holds up in every case: CPA and Random Forest tolerate noise but fail under jitter, while SVM tolerates jitter but collapses under noise. Overall, the ML power analysis attacks outperform CPA under most noise and misalignment conditions, whereas the phase three evaluation confirms that combining noise with jitter defeats nearly all of the evaluated attacks.
