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Components in neural implants, such as the electrode array and stimulator circuit, are often fabricated discretely. This modular fabrication scheme offers flexibility during development but poses difficulties during assembly, as components must be compactly integrated for implantation. It is particularly difficult in cases where the electrode array is required to have a high number of channels, such as in retinal prostheses. This paper presents the development of a parylene C‐based, double‐sided microelectrode array with 294 hemispheric electrodes for subretinal stimulation. The bonding pads on the bottom side of the double‐sided array are connected with electrodes through vias, eliminating the interconnection lines. The array can be integrated with a stimulator circuit through pad‐to‐pad bonding, resulting in a compact implant. The hemispheric electrodes are fabricated using thermally reflowed photoresist infillings, through which the height and width of the hemispheres can be easily controlled. The long‐term stability and biocompatibility of the materials and methods used to fabricate and package the electrodes are demonstrated in in vitro and in vivo environments over months. Finally, subretinal stimulation by the developed electrodes is successfully demonstrated using in vitro retinal patches from mice and monkeys. [ABSTRACT FROM AUTHOR]

We utilize a dual plasma system to convert methane into graphite-like (turbostratic) carbon particles. A first plasma reactor nucleates seed carbon nanoparticles from precursors such as acetylene or toluene vapor. The seed particles are then injected into a second plasma, supplemented by methane gas. The addition of the seed particles greatly improves the conversion of methane into carbon nanoparticles. We have used the material as a conductive additive in lithium-ion battery anodes and found their performance to be comparable to that of commercial carbon black. This approach is one of the most energy-efficient plasma-based approaches to carbon black synthesis at the laboratory scale. [ABSTRACT FROM AUTHOR]

We propose a radio frequency (RF) and visibly transparent composite metasurface design comprising newly developed transparent multilayer conductive coatings. Detailed experimental and theoretical analysis of the RF/visible transparency of the proposed meta-glass is provided. The proposed nature-inspired symmetrical honeycomb-shaped meta-glass design, alters the electromagnetic properties of the glass substrate in the RF spectrum by utilizing visibly transparent Ag-based conductive coatings on each side. Furthermore, the competing effect of the Ag thickness on optical and RF transparency is discussed. We show that using multilayer dielectric-metal coatings, specifically 5-layered spectrally selective coatings, RF transparency of the meta-glass can be enhanced while preserving visible transparency. Herein we demonstrate high transparency meta-glass with 83% and 78% peak RF and optical transmission at 28 GHz and 550 nm, respectively. The meta-glass yields enhanced RF transmission by 80% and 10% when compared to low-emissivity glass and bare glass, respectively. The meta-glass design presented here is amenable to a variety of 5G applications including automobile radar systems. This work provides a superior alternative to the standard indium-tin-oxide (ITO) transparent material which is becoming scarce. Moreover, this study paves the way for the design of new visibly transparent metamaterials and artificial dielectrics.

This paper proposes a method for forecasting surface solar irradiance (SSI), the most critical factor in solar photovoltaic (PV) power generation. The proposed method uses 16-channel data obtained by the GEO-KOMPSAT-2A (GK2A) satellite of South Korea as the main data for SSI forecasting. To determine feature variables related to SSI from the 16-channel data, the differences and ratios between the channels were utilized. Additionally, to consider the fundamental characteristics of SSI originating from the sun, solar geometry parameters, such as solar declination (SD), solar elevation angle (SEA), and extraterrestrial solar radiation (ESR), were used. Deep learning-based feature selection (Deep-FS) was employed to select appropriate feature variables that affect SSI from various feature variables extracted from the 16-channel data. Lastly, spatio-temporal deep learning models, such as convolutional neural network–long short-term memory (CNN-LSTM) and CNN–gated recurrent unit (CNN-GRU), which can simultaneously reflect temporal and spatial characteristics, were used to forecast SSI. Experiments conducted to verify the proposed method against conventional methods confirmed that the proposed method delivers superior SSI forecasting performance. [ABSTRACT FROM AUTHOR]

The combination of X‐ray free‐electron lasers (XFELs) with serial femtosecond crystallography represents cutting‐edge technology in structural biology, allowing the study of enzyme reactions and dynamics in real time through the generation of 'molecular movies'. This technology combines short and precise high‐energy X‐ray exposure to a stream of protein microcrystals. Here, the XFEL structure of carbonic anhydrase II, a ubiquitous enzyme responsible for the interconversion of CO2 and bicarbonate, is reported, and is compared with previously reported NMR and synchrotron X‐ray and neutron single‐crystal structures. [ABSTRACT FROM AUTHOR]

In July 2023, four devastating landslides occurred in Yecheon County, South Korea, due to heavy rainfall. These landslides resulted in 10 deaths, one injury, and the evacuation of around 500 people. The landslides occurred in different locations, including forest roads and natural slopes, and were caused by the liquefaction of collapsed soil into debris flows. The study emphasizes the vulnerability of South Korea to nocturnal heavy rains during the summer and recommends the establishment of early warning systems and check dams to mitigate the risks of sediment-related disasters in mountainous regions. The authors of the study, Seungjun Lee, Hyunuk An, Minseok Kim, and Song Eu, declare no conflicts of interest, ensuring the credibility of their findings. [Extracted from the article]

In recent years, battery fires have become more common owing to the increased use of lithium-ion batteries. Therefore, monitoring technology is required to detect battery anomalies because battery fires cause significant damage to systems. We used Mahalanobis distance (MD) and independent component analysis (ICA) to detect early battery faults in a real-world energy storage system (ESS). The fault types included historical data of battery overvoltage and humidity anomaly alarms generated by the system management program. These are typical preliminary symptoms of thermal runaway, the leading cause of lithium-ion battery fires. The alarms were generated by the system management program based on thresholds. If a fire occurs in an ESS, the humidity inside the ESS will increase very quickly, which means that threshold-based alarm generation methods can be risky. In addition, industrial datasets contain many outliers for various reasons, including measurement and communication errors in sensors. These outliers can lead to biased training results for models. Therefore, we used MD to remove outliers and performed fault detection based on ICA. The proposed method determines confidence limits based on statistics derived from normal samples with outliers removed, resulting in well-defined thresholds compared to existing fault detection methods. Moreover, it demonstrated the ability to detect faults earlier than the point at which alarms were generated by the system management program: 15 min earlier for battery overvoltage and 26 min earlier for humidity anomalies. [ABSTRACT FROM AUTHOR]

Triangular mesh data structures are principal in computer graphics, serving as the foundation for many 3D models. To effectively utilize these 3D models across diverse industries, it is important to understand the model's overall shape and geometric features thoroughly. In this work, we introduce a novel method for generating camera paths that emphasize the model's local geometric characteristics. This method uses a toroidal patch-based spatial data structure, approximating the mesh's faces within a predetermined tolerance ϵ , encapsulating their geometric intricacies. This facilitates the determination of the camera position and gaze path, ensuring the mesh's key characteristics are captured. During the path construction, we create a bounding cylinder for the mesh, project the mesh's faces and associated toroidal patches onto the cylinder's lateral surface, and sequentially select grids of the cylinder containing the highest number of toroidal patches as we traverse the lateral surface. The centers of the selected grids are used as control points for a periodic B-spline curve, which serves as our foundational path. After initial curve generation, we generated camera position and gaze path from the curve by multiplying factors to ensure a uniform camera amplitude. We applied our method to ten triangular mesh models, demonstrating its effectiveness and adaptability across various mesh configurations. [ABSTRACT FROM AUTHOR]

The shape memory polymers (SMPs) is a potential alternative material for conventional shape memory alloys (SMAs) in various fields. Previous studies have focused on the application of SMPs materials as an alternative to SMAs. However, considering problems such as the poor mechanical properties, its application has been limited. This study developed a biodegradable, magnetically responsive SMPs material that can be used for medical implants with shape memory behavior under magnetic force and improved mechanical properties by adding nanoparticles. Moreover, effect of the added nanoparticle was investigated due to contents ratio. Nanocomposite was synthesized with polycaprolactone which has shape memory properties, Fe3O4 that generates heat under magnetic field, and carbon nanotubes with reinforcing effect. The morphology analysis confirmed the homogeneous dispersion of the Fe3O4/Carbon‐nanotubes (CNTs) in polymer matrix. The tensile test shows that tensile strength (14.9–17.6 MPa) increased when Fe3O4 (0–20 wt%) was included and that it did not increase significantly when CNTs (0–0.8 wt%) were included. The shape memory test result confirmed that developed composite had a shape memory under a magnetic field. It was confirmed that even if Fe3O4 was incorporated into polycaprolactone, did not lose its exothermic properties under magnetic field. The developed polymer showed high shape memory ratio (91%–98%) in all the nanoparticle content rates. With regard to biodegradability, weight loss occurred over time in the phosphate‐buffered saline solution. Therefore, the biocompatible, biodegradable, magnetic response shape memory polymer developed in this study might applied to various medical implant as advanced shape memory materials. [ABSTRACT FROM AUTHOR]

Identifying potential sources of suspended sediment (SS) in headwater catchments is crucial for water quality management. To differentiate these potential SS sources, we investigated the distribution of two fallout radionuclides (FRNs), 137Cs and 210Pbex, using gamma spectrometry along with soil organic matter (SOM) analysis in a headwater catchment with five potential SS sources: cultivated land, non-harvested forest floor, eroded hillslope, harvested forest floor, and stream bank. The 137Cs and 210Pbex concentrations and the SOM content were considerably higher in the harvested forest floor materials than in the other four potential SS source materials. FRN concentrations revealed distinct properties according to the type of potential SS sources. Specifically, the combination of FRNs (with the effect of SOM content removed) associated with the mineral fraction and SOM showed distinguishable differences among the potential SS sources, except for no difference between cultivated land and eroded hillslope. Therefore, SOM and FRNs, or their combination, can be effective indices to differentiate or trace potential SS sources on various land use/land cover types within a catchment. Further field tests will allow the tracing techniques that bind FRNs with SOM to contribute to understanding SS transport from non-point sources within a catchment. [ABSTRACT FROM AUTHOR]

In this article, the basic principles and the main applications of Huygens’ metasurfaces (HMSs) are reviewed from microwaves to optics. In general, HMSs comprise a thin layer of orthogonal electric and magnetic dipoles, which form an array of Huygens’ sources. In a refraction setting, these sources radiate mostly in the forward direction and can be used to manipulate an incident electromagnetic wave at will. In the case of passive HMSs, the Huygens’ sources are induced by an incident electromagnetic field. Examples of passive manipulations include reflectionless refraction, perfect anomalous reflection, and arbitrary antenna beam forming. In the case of active HMSs, the Huygens’ sources are impressed active sources. Active HMS manipulations include cloaking and subwavelength spot formation in a cavity environment.

Accurate and timely fault detection and isolation (FDI) improve the availability, safety, and reliability of target systems and enable cost-effective operations. In this study, a shared nearest neighbor (SNN)-based method is proposed to identify the fault variables of a circulating fluidized bed boiler. SNN is a derivative method of the k-nearest neighbor (kNN), which utilizes shared neighbor information. The distance information between these neighbors can be applied to FDI. In particular, the proposed method can effectively detect faults by weighing the distance values based on the number of neighbors they share, thereby readjusting the distance values based on the shared neighbors. Moreover, the data distribution is not constrained; therefore, it can be applied to various processes. Unlike principal component analysis and independent component analysis, which are widely used to identify fault variables, the main advantage of SNN is that it does not suffer from smearing effects, because it calculates the contributions from the original input space. The proposed method is applied to two case studies and to the failure case of a real circulating fluidized bed boiler to confirm its effectiveness. The results show that the proposed method can detect faults earlier (1 h 39 min 46 s) and identify fault variables more effectively than conventional methods. [ABSTRACT FROM AUTHOR]

Background and Purpose: Pruritic dermatitis is a disease with a considerable unmet need for treatment and appears to present with not only epidermal but also peripheral neuronal complications. Here, we propose a novel pharmacological modulation targeting both peripheral dorsal root ganglion (DRG) sensory neurons and skin keratinocytes. GPR35 is an orphan G‐protein‐coupled receptor expressed in DRG neurons and has been predicted to downregulate neuronal excitability when activated. Modulator information is currently increasing for GPR35, and pamoic acid (PA), a salt‐forming agent for drugs, has been shown to be an activator solely specific for GPR35. Here, we investigated its effects on dermatitic pathology. Experimental Approach: We confirmed GPR35 expression in peripheral neurons and tissues. The effect of PA treatment was pharmacologically evaluated in cultured cells in vitro and in in vivo animal models for acute and chronic pruritus. Key Results: Local PA application mitigated acute non‐histaminergic itch and, consistently, obstructed DRG neuronal responses. Keratinocyte fragmentation under dermatitic simulation was also dampened following PA incubation. Chronic pruritus in 1‐chloro‐2,4‐dinitrobenzene and psoriasis models were also moderately but significantly reversed by the repeated applications of PA. Dermatitic scores in the 1‐chloro‐2,4‐dinitrobenzene and psoriatic models were also improved by its application, indicating that it is beneficial for mitigating disease pathology. Conclusion and Implications: Our findings suggest that pamoic acid activation of peripheral GPR35 can contribute to the improvement of pruritus and its associated diseases. [ABSTRACT FROM AUTHOR]

Machine tools are used in a wide range of applications, and they can manufacture workpieces flexibly. Furthermore, they require maintenance; the overall costs include maintenance costs, which constitute a significant portion, and the costs involved in ensuring product quality. Therefore, anomaly detection in tool conditions is required, because these tools are essential industrial elements. However, the data related to tool conditions present some challenges: data imbalances and deficiencies. Data imbalances and deficiencies can affect the performance of anomaly detection models. A model trained using data with imbalances and deficiencies may miscalculate that abnormal data are normal data, leasing to errors. To overcome these problems, the proposed method has been designed using the wavelet transform, color space conversion, color extraction, puzzle-based data augmentation, and double transfer learning. The proposed method generated image data from time-series data, effectively extracted features, and generated new image data using puzzle-based data augmentation. The color information was processed to highlight features, and the proposed puzzle-based data augmentation was applied during processing to increase the amount of data to improve the performance of the anomaly detection model. The experimental results showed that the proposed method can classify normal and abnormal data with greater accuracy. In particular, the accuracy of abnormal data classification increased from 25.00% to 91.67%. This demonstrates that the proposed method is effective and can overcome data imbalances and deficiencies. [ABSTRACT FROM AUTHOR]

The crimping of copper terminals via hand-operated and hydraulic compressors is used to generate a compressive force between a terminal and a wire, generally on a worksite. However, this equipment often causes compression defects because non-uniform pressure is applied to the terminal surface in the radial direction during crimping. When the crimped terminal is connected to electrical parts such as the power transmission system, a low-quality crimped terminal can separate from the wire strands, increasing resistance to current flow through the terminal, energy loss, and the risk of fire due to overheating. For this reason, Magnetic Pulse Crimping (MPC), which can yield highly durable crimped terminals with uniform quality, has recently been developed. This process uses only the magnetic force generated by high electromagnetic interaction between the crimping coil part and the surface of the terminal, without physical contact. The objective of this research was to confirm the superiority of the MPC process over the conventional crimping process and then analyze the effects of the main process parameters, including the crimping length and the charge energy on the crimping part, so that this new process can be applied at worksites. To realize these goals, copper terminals and 35 mm2 copper wire strands were employed, and various types of crimping parts were manufactured under different crimping conditions. In particular, the distribution of electromagnetic force on the crimped parts were analyzed via numerical analysis. The crimping part performance was improved when the MPC process was applied to terminal crimping. In particular, decreasing the crimping length led to increased crimping quality, while increasing the charge energy caused increases in the compression ratio and pullout strength. However, excessively high charge energy caused the edge to break the wire strands; therefore, it is important to select the proper charge energy. [ABSTRACT FROM AUTHOR]

While numerous studies have examined microbial attacks on waterlogged archaeological wood, limited information is available regarding microbial attacks in waterlogged tropical hardwoods submerged in marine environments. In this context, we explored microbial attacks in waterlogged archaeological rosewood (Dalbergia species), a tropical hardwood species that was submerged in the Yellow Sea for approximately 700 years, using various microscopic techniques and next-generation sequencing (NGS) methods. Based on morphological features, Type-I soft rot decay was identified as the main decay type. Most fibers in waterlogged archaeological rosewood studied were gelatinous (G) fibers of tension wood and the mode of soft rot decay differed from fibers without the G-layer. Differences in decay resistance between vessel/axial parenchyma cells and fibers were not obvious. Vestured- and simple pit membranes showed higher decay resistance than vessel and axial parenchyma cell walls, respectively. Microbial community analysis by NGS revealed the dominance of Ascomycota and Basidiomycota in the fungal community. Various bacterial communities were also identified, although no prominent signs of bacterial decay were noted. The identified bacterial communities markedly differed from those reported previously in terms of their composition and abundance. Together, our results offer detailed insights into the microbial types and communities responsible for degrading waterlogged archaeological rosewood, contributing to a better understanding of microbial attacks in tropical hardwoods exposed to marine environments. [ABSTRACT FROM AUTHOR]

Te thin films have recently received considerable attention owing to its superior electrical and thermoelectric properties. During the deposition process, if the temperature of the substrate is raised, high crystallinity and improved electrical properties can be expected. In this study, we used radio frequency sputtering for Te deposition to study the relationship between the deposition temperature, crystal size, and electrical performance. As the deposition temperature is increased from room temperature to 100 °C, we observed an increase in crystal size from the x-ray diffraction patterns and full-width half maximum calculations. With this grain size increment, the Hall mobility and Seebeck coefficient of the Te thin film increased significantly from 16 to 33 cm2 V−1 s−1 and 50 to 138 μ V K−1, respectively. This study reveals the potential of a facile fabrication method for enhanced Te thin films using temperature control and highlights the importance of the Te crystal structure in determining the electrical/thermoelectrical properties. These findings are particularly significant for the development of semiconductor material systems for various applications, including thermoelectric devices, CMOS, FET, and solar devices. [ABSTRACT FROM AUTHOR]