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Abstract Three-dimensional optical nanostructures have garnered significant interest in photonics due to their extraordinary capabilities to manipulate the amplitude, phase, and polarization states of light. However, achieving complex three-dimensional optical nanostructures with bottom-up fabrication has remained challenging, despite its nanoscale precision and cost-effectiveness, mainly due to inherent limitations in structural controllability. Here, we report the optical characteristics of intricate two- and three-dimensional nanoarchitectures made of colloidal quantum dots fabricated with multi-dimensional transfer printing. Our customizable fabrication platform, directed by tailored interface polarity, enables flexible geometric control over a variety of one-, two-, and three-dimensional quantum dot architectures, achieving tunable and advanced optical features. For example, we demonstrate a two-dimensional quantum dot nanomesh with tuned subwavelength square perforations designed by finite-difference time-domain calculations, achieving an 8-fold enhanced photoluminescence due to the maximized optical resonance. Furthermore, a three-dimensional quantum dot chiral structure is also created via asymmetric stacking of one-dimensional quantum dot layers, realizing a pronounced circular dichroism intensity exceeding 20°.

Submerged breakwaters can be installed underneath floating structures to reduce the external wave loads acting on the structure. The objective of this study was to establish an optimization analysis framework to determine the corresponding shape and position of the submerged breakwater that can minimize or maximize the external forces acting on the floating structure. A two-dimensional frequency-domain boundary element method (FD-BEM) based on the linear potential theory was developed to perform the hydrodynamic analysis. A metaheuristic algorithm, the advanced particle swarm optimization, was newly coupled to the FD-BEM to perform the optimization analysis. The optimization analysis process was performed by calling FD-BEM for each generation, performing a numerical analysis of the design variables of each particle, and updating the design variables using the collected results. The results of the optimization analysis showed that the height of the submerged breakwater has a significant effect on the surface piercing body and that there is a specific area and position with an optimal value. In this study, the optimal values of the shape and position of a single submerged breakwater were determined and analyzed so that the external force acting on a surface piercing body was minimum or maximum.

This paper introduces a comprehensive, data-driven framework for parametrically estimating directional ocean wave spectra from numerically simulated FPSO (Floating Production Storage and Offloading) vessel motions. Leveraging a mid-fidelity digital twin of a spread-moored FPSO vessel in the Guyana Sea, this approach integrates a wide range of statistical values calculated from the time histories of vessel responses—displacements, angular velocities, and translational accelerations. Artificial neural networks (ANNs), trained and optimized through hyperparameter tuning and feature selection, are employed to estimate wave parameters including the significant wave height, peak period, main wave direction, enhancement parameter, and directional-spreading factor. A systematic correlation analysis ensures that informative input features are retained, while extensive sensitivity tests confirm that richer input sets notably improve predictive accuracy. In addition, comparisons against other machine learning (ML) methods—such as Support Vector Machines, Random Forest, Gradient Boosting, and Ridge Regression—demonstrate the present ANN model’s superior ability to capture intricate nonlinear interdependencies between vessel motions and environmental conditions.

A case study is conducted for a submerged floating tunnel module (SFTM) in wet tow conditions. Inspired by the successful wet tow operations of spar platforms, a wet tow scenario is examined where a tunnel module, floating horizontally with a half-diameter draft, is towed by tugboats using towlines. To evaluate the static stability of the SFTM during wet tow, numerical static offset tests are performed at varying tow speeds to determine the equivalent system stiffness. These static offset tests consider surge, sway, roll, and yaw motions. Statistical analyses are subsequently performed based on the encounter-frequency approximation with varying equivalent stiffnesses. The most probable extreme motion analysis for 3 h under sea state 4 (HS=2.44 m and TP=8.1 s) shows that the beam sea condition causes the largest heave (0.6 m), and the stern sea (30 deg.) leads to the largest yaw response (0.85 deg.), which is likely to cause an instantaneous decrease in towing stability.

This paper proposes an effective inertia coefficient (EIC) in the Morison equation for better wave-force calculations. The OC4 semi-submersible floating offshore wind turbine (FOWT) platform was considered to test the feasibility. Large diffraction at large Keulegan– Carpenter (KC) numbers and the interaction between columns can result in errors in estimating the wave force using the Morison equation with a theoretical inertia coefficient, which can be corrected by the EIC as a function of the wave period and direction. The horizontal and vertical wave forces were calculated using the Morison equation and potential theory at each column, wave period, and wave direction. The EICs of each column were then obtained, resulting in a minimal difference between the Morison inertia force and the wave excitation force by the potential theory. The EICs, wave forces, phase angles, and dynamic motions were compared to confirm the feasibility of an EIC concept under regular and random waves.

Abstract The peripheral nervous system (PNS) is a fascinatingly complex and crucial component of the human body, responsible for transmitting vital signals throughout the body's intricate network of nerves. Its efficient functioning is paramount to our health, with any dysfunction often resulting in serious medical conditions, including motor disorders, neurological diseases, and psychiatric disorders. Recent strides in science and technology have made neuromodulation of the PNS a promising avenue for addressing these health issues. Neuromodulation involves modifying nerve activity using a range of techniques, such as electrical, chemical, optical, and mechanical stimulation. Bioelectronics plays a critical role in this effort, allowing for precise, controlled, and sustained stimulation of the PNS. This paper provides an overview of the PNS, discusses the current state of neuromodulation devices, and presents emerging trends in the field, including advances in wireless power transfer and materials, that are shaping the future of neuromodulation.

This study proposes riser fatigue monitoring based on digital twin models with a motion sensor attached to the platform and riser. The reference model was a spread-moored Floating Production Storage and Offloading (FPSO) with Steel Lazy-Wave Risers (SLWR). Coupled dynamics simulations under given environmental conditions were performed to generate synthetic sensor signals for digital twin models. Finite-element-based riser digital twin models were then constructed to run with the synthetic sensor inputs. A machine learning algorithm that estimates the 3D current profile along the water column was employed to improve the digital twin models by inputting the estimated current profile as additional loads. The digital twin models with or without the estimated current produce the time histories of behaviors and stresses along the riser, and the corresponding fatigue damage and life were estimated by the rainflow-counting method. The fatigue assessment results demonstrate its feasibility through small errors in fatigue damage.

A Surface-Riding Wave Energy Converter (SR-WEC) featuring a sliding magnet inside a pitching cylindrical hull is investigated as an easily deployable small power device to support small-scale marine operations. This study extends the earlier development of the system by authors to enhance power performance through the application of end spring and latching control. The inclusion of springs at the tube’s end enhances the magnet release and travel speeds as well as the average power output compared to systems without them. Further improvement of power output can also be achieved by employing optimal latching control. We introduced constant-angle and variable-angle unlatching strategies to determine optimal parameters in combination with passive and reactive power take-off (PTO) controls to assess their effectiveness. The optimized latching control and end spring can increase 60–80% more power output compared with the case without them under certain PTO damping. Additionally, we discussed the effects of limiting peak powers and associated energy leaks with latching.

This study proposes a mooring design strategy for a submerged floating tunnel (SFT) subject to extreme waves and earthquakes. Several critical design parameters, such as submerged depth and mooring station interval, are taken into account. As a target structure, a 700 m long SFT system with permanent stations at both ends, representing the fixed–fixed-end boundary condition, is established. To consider coupled dynamics between the tunnel and the mooring system with structural elasticity, an efficient time-domain simulation model is established. Three combinations of environmental conditions are considered: extreme wave only, extreme earthquake only, and both extreme earthquake and operating wave. First, to check the submerged-depth effect on the dynamic response of the SFT system, including mooring tension, two different submerged-depth (deep and shallow) types are simulated and analyzed. It is confirmed that the deep submerged-depth model (A-type) has an advantage under extreme wave conditions, whereas the shallow submerged-depth model (B-type) is equipped with better resistance when subject to an earthquake. Thus, the compromise submerged-depth model (C-type) is newly devised to enhance structural integrity under various environmental circumstances. Furthermore, a mooring station interval sensitivity test with the C-type is performed and demonstrates the integrity of the C-type.

Abstract Recently, personalized medical diagnostics and treatments have received significant interest due to the rising demand for reliable, rapid, and cost‐effective healthcare services. In the recent development of wearable devices, ways to engineer devices to extend their reliability, minimize the risk of infection, and expand the scope of application have been focused on improving conventional clinical procedures. With the increasing interest in personalized healthcare, wearable devices have received substantial interest because they monitor each physiological parameter for specific clinical interest. These unique bio‐parameters of individuals can be recorded from different target organs for the analysis of various functions, ranging from simple bodily movement to clinical treatment. In this review, the recent advances in sensors for recording unique bio‐signals from the human body are discussed. Based on each unique bio‐signals, a comprehensive analysis of wearable platforms for clinical diagnosis is provided, including subjects such as the selection of materials, device design structure, and application strategies for therapeutic significance. Furthermore, the challenges and future potential direction of modern bio‐sensor devices are discussed extensively.

Abstract Electrical stimulation as a therapeutic approach is widely applicable in terms of target tissues or target effects. This method can be an alternative to conventional therapies for patients who are resistant to drugs or are ineligible for surgical operations. In addition, as researchers have actively studied how to adjust the parameters for electrical stimulation in order to improve effectiveness, many patients have already received treatments with electrical stimulation. With respect to devices for electrical stimulation, recent studies are focused on developing reliability for safe and long‐term operations. From the point of view of engineers, a comprehensive understanding of how electrical stimulation modulates the biological system is essential to develop advanced strategies that provide effective therapeutic results. Herein, the fundamental mechanisms for delivering electrical stimulation on biological tissues are reviewed along with the requirements that need to be qualified by the electrodes. Furthermore, the latest advances in electrical stimulation devices are discussed followed by an introduction of representative applications of therapeutic electrical stimulation.

One pathway for improving the performance of optoelectronics is the tailoring energy bands of the charge transport layer. Here, Kim et al present a charge transfer complex composed out of nanodomains of MoO3 embedded within an NiO matrix, significantly improving green and blue OLED performance.

This paper aims to numerically estimate the dynamic ice load on a conical structure. The Discrete Element Method (DEM) is employed to model the level ice as the assembly of numerous spherical particles. To mimic the realistic fracture mechanism of ice, the parallel bonding method is introduced. Cases with four different ice drifting velocities are considered in time domain. For validation, the statistics of time-varying ice forces and their frequencies obtained by numerical simulations are extensively compared against the physical model-test results. Ice properties are directly adopted from the targeted experimental test set up. The additional parameters for DEM simulations are systematically determined by a numerical three-point bending test. The findings reveal that the numerical simulation estimates the dynamic ice force in a reasonably acceptable range and its results agree well with experimental data.

Abstract Background Pharmacokinetic-pharmacodynamic (PK/PD) targets of vancomycin therapy have been recognized for methicillin-resistant Staphylococcus aureus infections but not for other gram-positive bacterial infections. Therefore, we investigated whether vancomycin concentration targets such as the trough level and ratio of the area under the curve to minimum inhibitory concentration (AUC/MIC) are associated with the treatment outcome in enterococcal bacteremia. Methods A retrospective cohort analysis enrolled patients with bacteremia caused by vancomycin-susceptible Enterococcus faecium and Enterococcus faecalis who were treated with vancomycin from January 2007 to December 2017 at a tertiary hospital located in Seoul, South Korea. Patients without vancomycin concentrations were excluded from the study. The primary outcome was 28-day all-cause mortality. Results A total of 37 patients were enrolled—26 with E. faecium infection and 11 with E. faecalis infection. The 28-day all-cause mortality rate was 21.6 %. In univariate analysis, vancomycin trough level (≤ 15 µg/mL; p = 0.042), age (p = 0.044), and septic shock (p = 0.049) were associated with 28-day mortality but not AUC24/MIC (> 389; p = 0.479). In multivariate analysis, vancomycin trough concentration (≤ 15 µg/mL; p = 0.041) and younger age (p = 0.031) were associated with 28-day mortality in patients with enterococcal bacteremia. Conclusions In this study, a vancomycin trough level of 15 µg/mL or lower was associated with 28-day mortality in enterococcal bacteremia. However, relatively large prospective studies are needed to examine the efficacy of vancomycin PK/PD parameters in patients with enterococcal bacteremia.

Improved design of three-dimensionally nanostructured catalysts for oxygen evolution reaction (OER) can play a key role in maximizing the catalytic performance. Here, the authors show that woodpile-structured iridium consisting of 3D-printed, highly-ordered nanowire building blocks significantly improve OER mass activity.

Designing quantum dot light emitting diodes with full-colour pixel arrays with sub-micron feature size remains a challenge. Here, the authors demonstrate red-green-blue quantum dots arrays with resolutions up to 368 pixels per degree by leveraging thermodynamic-driven immersion transfer-printing.

In this study, a passive Tuned Mass Damper (TMD) is investigated to dampen resonant motions of a Submerged Floating Tunnel (SFT) in waves and earthquakes. TMD is adopted to control resonant lateral motion. A time-domain dynamics simulation model that considers the elasticity of the tunnel and mooring lines is first established, which is based on the lumped mass method and Morison equation, and the SFT-TMD interaction is considered through springs and dampers. Next, by using the Harmony Search (HS) algorithm, TMD's spring and damping coefficients are optimized; the dynamics simulations under white noise seismic excitations are continuously carried out with updated spring and damping coefficients produced by HS rules until the designed maximum iteration number. The influence of TMD's mass is individually investigated through a parametric study. After the optimization process is completed, the global performances of SFT with and without TMD are systematically evaluated in both waves and earthquakes. It is found that TMD plays a crucial role in controlling SFT vibrations when environmental loads are close to the system's fundamental lateral natural frequency under both wave and seismic excitations. TMD also enhances the comfort of passengers and reduces static and dynamic mooring tensions.

This study suggests a novel riser structural health monitoring methodology based on a dual algorithm (DA). In this method, the displacement tracing algorithm first traces the node displacement and tension up to the last sensor position called the target point. Then, the movement and tension at the target point are used for boundary conditions of the finite element (FE) simulator to obtain displacements and stresses below the target point. The developed method is validated through numerical simulations by comparing riser behaviors/stresses from the fully coupled model with those from the proposed method with numerical sensors. For that, a moored FPSO (floating production storage offloading) system with SCR (steel catenary riser) or SLWR (steel lazy-wave riser) is employed. Only three angle sensors are used at the top portion to monitor the entire length of riser. Much simpler forced top oscillation method is also investigated, which only uses riser top movement for running FE simulator, which cannot accurately reproduce the dynamics of the upper portion of riser since real-time wave action is ignored. The developed DA riser monitoring methodology can reproduce the movements and stresses along the entire length within around 5% error regardless of riser shapes and materials.

An Arctic Spar is characterized by its conical shape near the waterline. In this case, the nonlinear effects from its irregular hull shape would be significant if there is either a large amplitude floater motion or steep wave conditions. Therefore, in this paper, the nonlinear effects of an Arctic Spar are numerically investigated by introducing a weakly nonlinear time-domain model that considers the time dependent hydrostatic restoring stiffness and Froude-Krylov forces. Through numerical simulations under multiple regular and irregular wave conditions, the nonlinear behavior of the Arctic Spar is clearly observed, but it is not shown in the linear analysis. In particular, it is found that the nonlinear Froude-Krylov force plays an important role when the wave frequency is close to the heave natural frequency. In addition, the nonlinear hydrostatic restoring stiffness causes the structure's unstable motion at a half of heave natural period.

The development of wearable sensors is aimed at enabling continuous real-time health monitoring, which leads to timely and precise diagnosis anytime and anywhere. Unlike conventional wearable sensors that are somewhat bulky, rigid, and planar, research for next-generation wearable sensors has been focused on establishing fully-wearable systems. To attain such excellent wearability while providing accurate and reliable measurements, fabrication strategies should include (1) proper choices of materials and structural designs, (2) constructing efficient wireless power and data transmission systems, and (3) developing highly-integrated sensing systems. Herein, we discuss recent advances in wearable devices for non-invasive sensing, with focuses on materials design, nano/microfabrication, sensors, wireless technologies, and the integration of those.

The marine elastomeric bearing consists of an elastomer and several reinforcing inserted plates. Unlike land bearings that are to absorb high-frequency vibration during earthquakes, offshore elastomeric bearings are to support topside-module weight while efficiently absorbing wave-induced hull motions. The bearing is to receive three loads: compression, shear, and bending, and providing sufficient stiffness to resist the loads by inserting an adequate number of reinforcing plates is a major design issue for marine bearings. The stiffness of elastomeric bearings is largely influenced by the ratio of height to the area of the bearing and the number of laminated reinforcing plates. In this study, for the given size of the elastomeric bearing, the effect of the number of reinforcing plates on its compression, shear, and bending stiffness is investigated by using ANSYS Mechanical APDL, a commercial structural FE (finite element) analysis program. First, full analysis is done for the compression, shear, and bending stiffness with increasing respective displacements and the number of reinforcing plates from 0 to 8. The numerical results are partly validated by authors’ experimental results. Based on the numerical results, several empirical formulas are suggested for the variation of the three stiffnesses as a function of the number of reinforcing plates. Next, the design of the elastomer bearing for a representative FPSO (Floating Production Storage and Offloading) operated in the North Sea is conducted according to the required load and displacement conditions. Then, the adequate number of reinforcing plates for the case is determined and the results are shown to satisfy all the required safety factors for various required loading conditions.

This paper presents a machine learning method for detecting the mooring failures of SFT (submerged floating tunnel) based on DNN (deep neural network). The floater-mooring-coupled hydro-elastic time-domain numerical simulations are conducted under various random wave excitations and failure/intact scenarios. Then, the big-data is collected at various locations of numerical motion sensors along the SFT to be used for the present DNN algorithm. In the input layer, tunnel motion-sensor signals and wave conditions are inputted while the output layer provides the probabilities of 21 failure scenarios. In the optimization stage, the numbers of hidden layers, neurons of each layer, and epochs for reliable performance are selected. Several activation functions and optimizers are also tested for the present DNN model, and Sigmoid function and Adamax are respectively adopted to enhance the classification accuracy. Moreover, a systematic sensitivity test with respect to the numbers and arrangements of sensors is performed to find the appropriate sensor combination to achieve target prediction accuracy. The technique of confusion matrix is used to represent the accuracy of the DNN algorithms for various cases, and the classification accuracy as high as 98.1% is obtained with seven sensors. The results of this study demonstrate that the DNN model can effectively monitor the mooring failures of SFTs utilizing real-time sensor signals.

In recent years, to develop more spontaneous and instant interfaces between a system and users, technology has evolved toward designing efficient and simple gesture recognition (GR) techniques. As a tool for acquiring human motion, a tactile sensor system, which converts the human touch signal into a single datum and executes a command by translating a bundle of data into a text language or triggering a preset sequence as a haptic motion, has been developed. The tactile sensor aims to collect comprehensive data on various motions, from the touch of a fingertip to large body movements. The sensor devices have different characteristics that are important for target applications. Furthermore, devices can be fabricated using various principles, and include piezoelectric, capacitive, piezoresistive, and field-effect transistor types, depending on the parameters to be achieved. Here, we introduce tactile sensors consisting of field-effect transistors (FETs). GR requires a process involving the acquisition of a large amount of data in an array rather than a single sensor, suggesting the importance of fabricating a tactile sensor as an array. In this case, an FET-type pressure sensor can exploit the advantages of active-matrix sensor arrays that allow high-array uniformity, high spatial contrast, and facile integration with electrical circuitry. We envision that tactile sensors based on FETs will be beneficial for GR as well as future applications, and these sensors will provide substantial opportunities for next-generation motion sensing systems.

Purpose: Coronavirus disease-2019 (COVID-19) is a novel respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); there are few specific treatments. Convalescent plasma (CP), donated by people who have recovered from COVID-19, is an investigational therapy for severe or critically ill patients with COVID-19. Materials and Methods: This retrospective cohort study evaluated the effectiveness of CP therapy in patients with severe or lifethreatening cases of COVID-19 at two hospitals in Seoul, Korea, between May and September 2020. Clinical outcomes were evaluated in 20 patients with CP therapy in a descriptive manner. Additionally, the changes in cycle threshold (Ct) values of 10 patients with CP therapy were compared to those of 10 controls who had the same (±0.8) initial Ct values but did not receive CP. Results: Of the 20 patients (mean age 66.6 years), 18 received high-dose oxygen therapy using mechanical ventilators or high-flow nasal cannulas. Systemic steroids were administered to 19 patients who received CP. The neutralizing antibody titers of the administered CP were between 1:80 and 1:10240. There were two ABO-mismatched transfusions. The World Health Organization ordinal scale score and National Institutes of Health severity score improved in half of the patients within 14 days. Those who received CP showed a higher increase in Ct values at 24 h and 72 h after CP therapy compared to controls with similar initial Ct values (p=0.002). No transfusion-related side effects were observed. Conclusion: CP therapy may be a potential therapeutic option in severe or critically ill patients with COVID-19. [ABSTRACT FROM AUTHOR]