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Graphene platelets (GPLs) are gaining popularity across various sectors for enhancing the strength and reducing the weight of structures, thanks to their outstanding mechanical characteristics and low manufacturing cost. Among many engineering structures, wind turbine blades are a prime candidate for the integration of such advanced nanofillers, offering potential improvements in the efficiency of energy generation and reductions in the construction costs of support structures. This study aims to explore the potential of GPLs for use in wind turbine blades by evaluating their impact on material costs as well as mechanical performance. A series of finite element analyses (FEAs) were conducted to examine the variations of mechanical performances—specifically, free vibration, bending, torsional deformation, and weight reductions relative to conventional fiberglass-based blades. Details of computational modeling techniques are presented in this paper. Based on the outcomes of these analyses, the mechanical performances of GPL-reinforced wind turbine blades are reviewed along with a cost–benefit analysis, exemplified through a 5MW-class wind turbine blade. The findings affirm the practicality and benefits of employing GPLs in the design and fabrication of wind turbine blades.

With the growth of the wind energy market and the increase in the size of wind turbines, the demand for advanced composite materials with high strength and low density for wind turbine blades has become imperative. Graphene platelets (GPLs) stand out as highly premising reinforcements due to their exceptional physical properties, resulting in their widespread adoption in the composite industry in recent years. The present study aims to analyze the applicability of a graphene-platelet-reinforced composite (GPLRC) to wind turbine blades in terms of structural performance. A finite element blade model is constructed by referring to the National Renewable Energy Laboratory (NREL) 5 MW wind turbine, and its reliability is verified through a convergence test. The performance of the wind turbine blade is quantitatively examined in terms of the deflection and stress, natural frequencies, and twist angle. The applicability of the GPL-reinforced wind blade is explored through a comparison with wind blades manufactured with glass fiber and carbon nanotubes (CNTs). The comparison indicates that the performance of a wind blade can be remarkably improved by reinforcing with GPLs instead of traditional fillers, and the weight of not only the wind blade itself but also the wind turbine system can be remarkably reduced. The present results can be useful in the development of next-generation high-strength lightweight wind turbine blades.

Renewable energy markets, particularly wind energy, have experienced remarkable growth, predominantly driven by the urgent need for decarbonization in the face of accelerating global warming. As the wind energy sector expands and turbines increase in size, there is a growing demand for advanced composite materials that offer both high strength and low density. Among these materials, graphene stands out for its excellent mechanical properties and low density. Incorporating graphene reinforcement into wind turbine blades has the potential to enhance generation efficiency and reduce the construction costs of foundation structures. As a pilot study of graphene reinforcement on wind turbine blades, this study aims to investigate the variations of mechanical characteristics and weights between traditional fiberglass-based blades and those reinforced with graphene platelets (GPLs). A finite element model of the SNL 61.5 m horizontal wind turbine blade is used and validated by comparing the analysis results with those presented in the existing literature. Case studies are conducted to explore the effects of graphene reinforcement on wind turbine blades in terms of mechanical characteristics, such as free vibration, bending, and torsional deformation. Furthermore, the masses and fabrication costs are compared among fiberglass, CNTRC, and GPLRC-based wind turbine blades. Finally, the results obtained from this study demonstrate the effectiveness of graphene reinforcement on wind turbine blades in terms of both their mechanical performance and weight reduction.

Aging ships and offshore structures face harsh environmental and operational conditions in remote areas, leading to age-related damages such as corrosion wastage, fatigue cracking, and mechanical denting. These deteriorations, if left unattended, can escalate into catastrophic failures, causing casualties, property damage, and marine pollution. Hence, ensuring the safety and integrity of aging ships and offshore structures is paramount and achievable through innovative healthcare schemes. One such paradigm, digital healthcare engineering (DHE), initially introduced by the final coauthor, aims at providing lifetime healthcare for engineered structures, infrastructure, and individuals (e.g., seafarers) by harnessing advancements in digitalization and communication technologies. The DHE framework comprises five interconnected modules: on-site health parameter monitoring, data transmission to analytics centers, data analytics, simulation and visualization via digital twins, artificial intelligence-driven diagnosis and remedial planning using machine and deep learning, and predictive health condition analysis for future maintenance. This article surveys recent technological advancements pertinent to each DHE module, with a focus on its application to aging ships and offshore structures. The primary objectives include identifying cost-effective and accurate techniques to establish a DHE system for lifetime healthcare of aging ships and offshore structures—a project currently in progress by the authors.

In this work, the authors determine the crystal structure of a ProQ/FinO RNA chaperone bound to its RNA target. This provides insight into how this family of bacterial proteins recognize transcriptional terminator structures.

Abstract Calsequestrin is among the most abundant proteins in muscle sarcoplasmic reticulum and displays a high capacity but a low affinity for Ca2+ binding. In mammals, calsequestrin is encoded by two genes, CASQ1 and CASQ2, which are expressed almost exclusively in skeletal and cardiac muscles, respectively. Phylogenetic analysis indicates that calsequestrin is an ancient gene in metazoans, and that the duplication of the ancestral calsequestrin gene took place after the emergence of the lancelet. CASQ2 gene variants associated with catecholaminergic polymorphic ventricular tachycardia (CPVT) in humans are positively correlated with a high degree of evolutionary conservation across all calsequestrin homologues. The mutations are distributed in diverse locations of the calsequestrin protein and impart functional diversity but remarkably manifest in a similar phenotype in humans.

Primitive neuroectodermal tumor (PNET) arising primarily in the lung is an extremely rare and aggressive malignancy with poor chances of patient survival. We present a case of long-term survival by a 29-year-old woman with PNET diagnosed after a hertological and immunohertochemical examination of a biopsy specimen obtained by performing video-assisted thoracic surgery. The patient underwent a left lower lung lobe lobectomy and 6 cycles of adjuvant chemotherapy. The patient has been free of any symptoms of the recurrence of the disease for 6 years after treatment completion.

Follicular lymphoma is the most common form of low-grade B cell lymphoma. Follicular lymphoma occurs predominantly at lymph node sites and rarely in the gastrointestinal tract. Rare gastrointestinal follicular lymphoma is most commonly found in the small intestine, especially in the duodenum, and appears as multiple granules. However, gastric follicular lymphoma mostly appears as a subepithelial tumor. We observed two primary gastric follicular lymphomas that resembled subepithelial tumors located in the body of the stomach. Endoscopic ultrasound revealed hypoechoic lesions located in the submucosa layer. Since endoscopic forceps biopsies were inconclusive, we performed endoscopic submucosal dissection, which resulted in a final pathologic diagnosis of follicular lymphoma. Because of the indolent nature of gastrointestinal follicular lymphoma, the “watch and wait” strategy can be applied in the early phase. The identification of endoscopic characteristics of gastric follicular lymphoma can be helpful for differential diagnosis and decision of treatment strategy. Therefore, we report two cases of primary gastrointestinal follicular lymphoma diagnosed following endoscopic submucosal dissection.

Malignant melanoma is one of the most common malignant diseases of the gastrointestinal tract. It has been reported that the malignant melanoma metastasizes not only to the small intestine due to the abundant blood supply, but also to the stomach, colon, and esophagus. Gastrointestinal metastasis is usually suspected depending on the clinical symptoms, as well as based on radiological or endoscopic findings. Imunohistochemical stains, such as Melan-A/Melanoma antigen recognized by T cell-1 or human melanoma black-45, are useful for confirming the diagnosis of malignant melanoma. A 44-year-old male received an operation due to a malignant melanoma at the left thumb two years ago. On the national health screening endoscopy, a submucosal tumor with hyperemic change on the top was found. The final diagnosis was a metastatic malignant melanoma in the stomach, pancreas, and pelvic bone. We recommend that endoscopists should consider the potential malignancy of subepithelial tumor with mucosa change, despite the tumor size being less than 1 cm.

Protein losing enteropathy (PLE) due to systemic lupus erythematosus (SLE) is relatively uncommon. PLE may be appeared sequentially after the diagnosis of SLE or concurrently with SLE. In most of concurrent cases, PLE was diagnosed one of various symptoms of SLE. Cases of PLE as the initial and only clinical presentation of SLE have been rarely reported. We described a 30-year old woman with general edema and abdominal distension was diagnosed PLE after stool alpha 1 antitrypsin clearance test. Her symptoms were getting worse even though the treatment with intravenous albumin. She was finally diagnosed PLE associated with SLE by additional laboratory findings (positive antinuclear antibody and anti-dsDNA IgG and low C3, C4 and CH50). She was treated with high dose of steroids and her symptoms were improved.

Introduction: We propose an automatic sleep stage scoring model, referred to as SeriesSleepNet, based on convolutional neural network (CNN) and bidirectional long short-term memory (bi-LSTM) with partial data augmentation. We used single-channel raw electroencephalography signals for automatic sleep stage scoring. Methods: Our framework was focused on time series information, so we applied partial data augmentation to learn the connected time information in small series. In specific, the CNN module learns the time information of one epoch (intra-epoch) whereas the bi-LSTM trains the sequential information between the adjacent epochs (inter-epoch). Note that the input of the bi-LSTM is the augmented CNN output. Moreover, the proposed loss function was used to fine-tune the model by providing additional weights. To validate the proposed framework, we conducted two experiments using the Sleep-EDF and SHHS datasets. Results and Discussion: The results achieved an overall accuracy of 0.87 and 0.84 and overall F1-score of 0.80 and 0.78 and kappa value of 0.81 and 0.78 for five-class classification, respectively. We showed that the SeriesSleepNet was superior to the baselines based on each component in the proposed framework. Our architecture also outperformed the state-of-the-art methods with overall F1-score, accuracy, and kappa value. Our framework could provide information on sleep disorders or quality of sleep to automatically classify sleep stages with high performance. [ABSTRACT FROM AUTHOR]