Improvement of P300-Based Brain-Computer Interfaces for Home Appliances Control by Data Balancing Techniques.

The oddball paradigm used in P300-based brain-computer interfaces (BCIs) intrinsically poses the issue of data imbalance between target stimuli and nontarget stimuli. Data imbalance can cause overfitting problems and, consequently, poor classification performance. The purpose of this study is to improve BCI performance by solving this data imbalance problem with sampling techniques. The sampling techniques were applied to BCI data in 15 subjects controlling a door lock, 15 subjects an electric light, and 14 subjects a Bluetooth speaker. We explored two categories of sampling techniques: oversampling and undersampling. Oversampling techniques, including random oversampling, synthetic minority oversampling technique (SMOTE), borderline-SMOTE, support vector machine (SVM) SMOTE, and adaptive synthetic sampling, were used to increase the number of samples for the class of target stimuli. Undersampling techniques, including random undersampling, neighborhood cleaning rule, Tomek's links, and weighted undersampling bagging, were used to reduce the class size of nontarget stimuli. The over- or undersampled data were classified by an SVM classifier. Overall, some oversampling techniques improved BCI performance while undersampling techniques often degraded performance. Particularly, using borderline-SMOTE yielded the highest accuracy (87.27%) and information transfer rate (8.82 bpm) across all three appliances. Moreover, borderline-SMOTE led to performance improvement, especially for poor performers. A further analysis showed that borderline-SMOTE improved SVM by generating more support vectors within the target class and enlarging margins. However, there was no difference in the accuracy between borderline-SMOTE and the method of applying the weighted regularization parameter of the SVM. Our results suggest that although oversampling improves performance of P300-based BCIs, it is not just the effect of the oversampling techniques, but rather the effect of solving the data imbalance problem.

Scalable and High-Throughput Top-Down Manufacturing of Optical Metasurfaces.

Metasurfaces have shown promising potential to miniaturize existing bulk optical components thanks to their extraordinary optical properties and ultra-thin, small, and lightweight footprints. However, the absence of proper manufacturing methods has been one of the main obstacles preventing the practical application of metasurfaces and commercialization. Although a variety of fabrication techniques have been used to produce optical metasurfaces, there are still no universal scalable and high-throughput manufacturing methods that meet the criteria for large-scale metasurfaces for device/product-level applications. The fundamentals and recent progress of the large area and high-throughput manufacturing methods are discussed with practical device applications. We systematically classify various top-down scalable patterning techniques for optical metasurfaces: firstly, optical and printing methods are categorized and then their conventional and unconventional (emerging/new) techniques are discussed in detail, respectively. In the end of each section, we also introduce the recent developments of metasurfaces realized by the corresponding fabrication methods.

Collaborative accountability for sustainable public health: A Korean perspective on the effective use of ICT-based health risk communication.

The sustainability of public health practices requires collaboration between the government and its citizens. On the government's side, social media can provide a conduit for communicating health risk information in an effective and timely fashion, while also engaging citizens in informed decision-making. On the citizen's side, information communication technology (ICT)-based practices cannot function unless citizens recognize and act on their responsibility to actively engage with government social media platforms. Despite an increasing interest in understanding the adoption of ICT practices and e-government services for health risk communication, there remains a crucial need for a comprehensive framework to explain which factors determine citizen use of digital government resources. The purpose of this study is to investigate how to increase government accountability for motivating citizens to engage in ICT-based health risk communication, thereby attaining sustainable public health practices through collaborative governance. By integrating trust and health risk information into the e-government adoption model (GAM), this research examines factors that influence citizens' likelihood of using government social media resources. Survey data from 700 Korean citizens were analyzed using structural equation modeling. The results indicated that individuals with higher social media competency are more likely to (a) seek risk information through social media and (b) perceive the government's social media sites as easy to use. Consistent with the GAM, intentions to use the government's social media sites for information and interactions appear to increase as citizens perceive more value in using them regarding information quality, ease of use, functional benefit, and security. Furthermore, perceived trust in the government's social media resources appears to function as a mediator of this process. Initial trust in the government is an important determinant of perceptions of its digital resources. Citizens who trust the government tend to evaluate new initiatives positively and are more likely to accept and make use of them. The results of this study can inform policy design and implementation by elucidating the mechanisms that determine citizens' adoption and usage of digital government services. Theoretically, this work expands the GAM to include health risk communication and adds empirical evidence to the small yet growing body of knowledge of e-government initiatives. These findings also highlight the importance of public trust in the government, as this encourages citizens to seek health risk information and assistance from the government. Overall, the data and model generated in this investigation represent an important step toward the successful and sustainable modernization of public services.

Adoption of E-Government Applications for Public Health Risk Communication: Government Trust and Social Media Competence as Primary Drivers.

Building upon a framework of the unified theory of acceptance and use of technology, this study explores the determinants of citizens' intentions to use the government's mobile application for public health risk communication. An online survey was conducted with a quota sample of 700 Korean citizens. The results from structural equation modeling suggest that social media competence and trust in government information are primary determinants of willingness to accept the new application and intention to use it. Trust in government information appeared to influence the acceptance of the application both directly and indirectly through performance expectancy and effort expectancy. More confidence in the use of social media led to higher levels of performance expectancy, effort expectancy, and facilitating conditions, all of which subsequently contributed to willingness to accept the application. The acceptance of the application further influenced intention to use the application and the likelihood of positive recommendations. The findings suggest that while developing applications that meet public expectations for informational benefits and time efficiency is important, it is also necessary for the government to build trust and improve citizens' ability to use new tools in order for new information technology initiatives to fully benefit citizens.

A Rare Case of Giant Bilateral Adrenal Myelolipomas in a Patient With Classical Congenital Hyperplasia.

Congenital adrenal hyperplasia (CAH) is caused by genetic defects in the enzymes involved in cortisol biosynthesis in the adrenal gland and, in more than 90% of cases, due to a deficiency in the 21-hydroxylase enzyme. Classical CAH due to 21-hydroxylase deficiency is a severe form of the disease that presents with cortisol deficiency and is further categorized into salt-wasting or simple-virilizing types. Appropriate steroid replacement has been shown to effectively treat patients with classical CAH and prevent complications. Individuals who receive inadequate treatment or fail to comply with their prescribed steroid hormone regimen are susceptible to the development of adrenal myelolipomas. Myelolipomas are benign tumors composed of both adipose and hematopoietic tissues. While documented cases of adrenal myelolipomas exist in medical literature, instances of large bilateral myelolipomas remain exceedingly rare. This case report highlights a 40-year-old female patient with a known history of classical congenital adrenal hyperplasia who presented with unusually large bilateral adrenal myelolipomas. A diagnostic CT scan of the abdomen and pelvis revealed a 13.4 x 10.8 cm myelolipoma on the left adrenal gland and a 10 x 8.6 cm myelolipoma on the right adrenal gland. Prior to her presentation, the patient experienced recurrent nausea and vomiting, along with left upper quadrant pain, over five months. Hormonal assessments indicated significantly elevated serum androgen levels, suggesting inadequate management of her CAH. In this report, we present a rare case of symptomatic bilateral large adrenal myelolipomas, underscoring the significance of adhering to treatment regimens, diagnostic assessments, and management for adrenal myelolipomas in individuals diagnosed with CAH.

A comprehensive dataset for home appliance control using ERP-based BCIs with the application of inter-subject transfer learning.

Brain-computer interfaces (BCIs) have a potential to revolutionize human-computer interaction by enabling direct links between the brain and computer systems. Recent studies are increasingly focusing on practical applications of BCIs-e.g., home appliance control just by thoughts. One of the non-invasive BCIs using electroencephalography (EEG) capitalizes on event-related potentials (ERPs) in response to target stimuli and have shown promise in controlling home appliance. In this paper, we present a comprehensive dataset of online ERP-based BCIs for controlling various home appliances in diverse stimulus presentation environments. We collected online BCI data from a total of 84 subjects among whom 60 subjects controlled three types of appliances (TV: 30, door lock: 15, and electric light: 15) with 4 functions per appliance, 14 subjects controlled a Bluetooth speaker with 6 functions via an LCD monitor, and 10 subjects controlled air conditioner with 4 functions via augmented reality (AR). Using the dataset, we aimed to address the issue of inter-subject variability in ERPs by employing the transfer learning in two different approaches. The first approach, "within-paradigm transfer learning," aimed to generalize the model within the same paradigm of stimulus presentation. The second approach, "cross-paradigm transfer learning," involved extending the model from a 4-class LCD environment to different paradigms. The results demonstrated that transfer learning can effectively enhance the generalizability of BCIs based on ERP across different subjects and environments.

Adaptive Window Method Based on FBCCA for Optimal SSVEP Recognition.

In the conventional studies related to steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), the window length (detection time) was typically predetermined through the offline analysis, which had limitations of practical applicability of a BCI system due to the inter-subject/trial variability of electroencephalography (EEG) signals. To address these limitations, this study aims to automatically optimize the window length for each trial based on training-free approaches and proposes a novel adaptive window method (ANCOVA-based filter-bank canonical correlation analysis, ABFCCA) for SSVEP-based BCIs. The proposed method is based on analysis of covariance (ANCOVA) which is applied after feature extraction by the conventional training-free SSVEP recognition approaches. To evaluate the performance of the proposed method, conventional fixed window and recent adaptive window methods were compared using two open-access datasets. In the Benchmark dataset, the average information transfer rate (ITR) was 146.81 bits/min, the average accuracy 93.55%, and the average window length 1.53 s. In the OpenBMI dataset, the average ITR was 119.01 bits/min, the average accuracy 83.50%, and the average window length 0.65 s. The proposed method significantly outperformed the conventional approaches with fixed window in terms of the accuracy and ITR, and is applicable to various SSVEP-based BCI paradigms based on the criterion of significance level without offline analysis to find optimal hyper-parameters. ABFCCA is enabled the practical use of various BCI systems by automatically optimizing the window length independently.

Identification of Individual Hanwoo Cattle by Muzzle Pattern Images through Deep Learning.

The objective of this study was to identify Hanwoo cattle via a deep-learning model using muzzle images. A total of 9230 images from 336 Hanwoo were used. Images of the same individuals were taken at four different times to avoid overfitted models. Muzzle images were cropped by the YOLO v8-based model trained with 150 images with manual annotation. Data blocks were composed of image and national livestock traceability numbers and were randomly selected and stored as train, validation test data. Transfer learning was performed with the tiny, small and medium versions of Efficientnet v2 models with SGD, RMSProp, Adam and Lion optimizers. The small version using Lion showed the best validation accuracy of 0.981 in 36 epochs within 12 transfer-learned models. The top five models achieved the best validation accuracy and were evaluated with the training data for practical usage. The small version using Adam showed the best test accuracy of 0.970, but the small version using RMSProp showed the lowest repeated error. Results with high accuracy prediction in this study demonstrated the potential of muzzle patterns as an identification key for individual cattle.

A Case Series of Permanent Dorsal Root Ganglion Stimulation.

Introduction  Neuropathic pain commonly causes high levels of pain that impairs multiple facets of the lives of patients. Multiple first-line treatments such as physical therapy and pharmacological intervention exist. Treatment refractory to these interventions may be considered for spinal cord stimulation (SCS). However, modest rates of meaningful relief leave room for improvement. Dorsal root ganglion stimulation (DRGS) has been touted to be a viable alternative solution to SCS with more specific targets and, consequently, fewer side effects. Thus, DRGS has been accepted as a better alternative to spinal cord stimulation. In contrast, we report a series of DRGS patients who had lower rates of meaningful pain relief than what was reported in the literature. Methods We present a series of 11 patients who underwent both DRGS trial and subsequent permanent implantation with negative outcomes (defined by ≥ 50% of pre-surgical pain) in 55% of patients. Patient records were searched for comorbidities that could potentially affect the DRGS implant (diabetes, cancer, smoking, age > 70 years old). Once delineated, the predictive value of each comorbidity for negative outcomes was estimated. Results Eighteen patients had a successful DRGS trial which was defined as a ≥ 50% pain reduction as well as increased ability to perform daily activities. Seven patients elected not to proceed with the permanent DRGS. Of the 11 remaining patients that had the permanent DRGS, four patients reported being completely pain-free ≥ one month following implantation, one reported a significant increase in pain improvement at four months post-operation, and six patients reported pain that was ≥ 50% of their pre-surgical pain 4-12 months following implantation.  Conclusion In our case series, we observed a discrepancy between DRGS trial outcomes and outcomes following permanent implantation. We found that a stronger correlation may exist between worse outcomes and smoking. Older age, the presence of diabetes, and cancer had more modest associations. These comorbidities may have value as tests for predicting negative outcomes of permanent DRGS implantation. Additionally, we hypothesized that this could also be due to the presence of psychological factors which obscure the true result of the DRGS trial. Thus, we suggest that DRGS be prescribed with caution in these patient populations, and use comorbidities to test for the likelihood of negative outcomes. Limitations of this study are those that are intrinsic to a retrospective case series.

Quality of Life and Associated Factors of International Students in South Korea: A Cross-Sectional Study Using the WHOQOL-BREF Instrument.

The quality of life (QoL) of an individual is affected in a complex way by the person's physical health, psychological state, social relationships, and their relationship to their environment. We assessed the QoL of international university students using the World Health Organization Quality of Life (WHOQOL-BREF) tool and explored the QoL-associated factors. We conducted a cross-sectional study between January and March 2021. The WHOQOL-BREF was summarized as a four-domain construct following the WHO guidelines and QoL scores for each domain were compared through a t-test and chi-squared test. To determine the factors associated with international students' QoL we used multiple linear regression models, with each of the domains serving as the outcome variable. In total, 261 students participated, with 52.5% being males. We reported predicted means (PM) along with 95% confidence intervals (CI). Cronbach's alpha for the overall WHOQOL-BREF tool was 0.88. Students' self-reported QoL mean score was 3.67 ± 0.71 and the mean score of their overall satisfaction with health was 3.61 ± 0.83. The social relationships domain had the highest mean score at 56.88 ± 19.55 and was significantly associated with age (>25 years: PM: 59.7; 95% CI: 56.2−63.2, p = 0.033) and region of origin (Asia: PM: 54.4; 95% CI: 42.5−64.8, p = 0.027). Students above 25 years had significantly higher scores in all domains (p < 0.05). Our results showed that the social relationships and psychological health domains have more positive impact on international students' QoL compared to the physical and environmental health domains. To cope with factors influencing international students' QoL, universities should develop and provide efficient support systems for foreign students in South Korea.

Acceptance of the COVID-19 Vaccine by Foreigners in South Korea.

Vaccination against COVID-19 is an important strategy for its control. Assessing the willingness to accept the COVID-19 vaccine in different subgroups is important for an inclusive vaccination program design. Our aim was to determine the COVID-19 vaccine acceptance rate and associated factors among foreigners in South Korea. An online cross-sectional study was carried out from May to June 2021. In this study, 710 individuals participated and most were aged between 26 and 29 (36.1%) years. Overall, 70.8% were willing to receive the vaccine. Males were less likely to accept the vaccine than females (OR: 0.5; 95% CI: 0.4-0.7, p < 0.001). Single people were more likely to receive the vaccine than those who were married (OR: 1.4; 95% CI: 0.9-2.0, p = 0.04). Other factors associated with willingness to accept COVID-19 vaccine were; vaccine convenience (OR: 1.7; 95% CI: 1.2-2.3, p = 0.002), doctors' recommendation (OR: 2.8; 95% CI: 2.0-3.9, p < 0.001), vaccine price (OR: 1.7; 95% CI: 1.2-2.3, p = 0.003), vaccine effectiveness (OR: 8.3; 95% CI: 5.8-12.1, p < 0.001), vaccine importance (OR: 7.9; 95% CI: 4.6-14.1, p < 0.001), and vaccine safety (OR: 6.9; 95% CI: 4.5-10.8, p < 0.001). Providing more information on vaccine safety and effectiveness is required to increase vaccine acceptance.

Nearly Perfect Transmissive Subtractive Coloration through the Spectral Amplification of Mie Scattering and Lattice Resonance.

Silicon has been utilized in metasurfaces to produce structural color filters due to its compatibility with mature and cost-effective methods for complementary metal oxide semiconductor devices. In this work, we propose and demonstrate efficiency- and scattering-enhanced structural color filters using all-dielectric metasurfaces made up of engineered hydrogenated amorphous silicon (a-Si:H) nanoblocks. Wavelength-dependent filtering is achieved by Mie scattering as each structure individually supports the electric dipole (ED) and magnetic dipole (MD) resonances. The ED and MD resonances are identified by observing the field profiles of the resonance calculated by finite element method (FEM) simulations. To enhance the efficiency and scattering response of the all-dielectric metasurfaces, the proposed structural color filters are designed with consideration of the lattice resonances and scattering directivity. The spectral positions of the transmission dips and peaks are rigorously analyzed in accordance with the Mie theory and multipole expansion. The transmission spectra exhibit 100% transmission where Kerker's first condition is satisfied, while the lattice resonances amplify the ED and MD scattering responses throughout the entire visible regime. Various colors are generated by varying the resonance peak, which is controlled by varying the geometric parameters of a-Si:H nanoblocks. The proposed structural color printing devices are expected to have applications in dynamic color displays, imaging devices, and photorealistic color printing.

Nanoimprint lithography for high-throughput fabrication of metasurfaces.

Metasurfaces are composed of periodic sub-wavelength nanostructures and exhibit optical properties that are not found in nature. They have been widely investigated for optical applications such as holograms, wavefront shaping, and structural color printing, however, electron-beam lithography is not suitable to produce large-area metasurfaces because of the high fabrication cost and low productivity. Although alternative optical technologies, such as holographic lithography and plasmonic lithography, can overcome these drawbacks, such methods are still constrained by the optical diffraction limit. To break through this fundamental problem, mechanical nanopatterning processes have been actively studied in many fields, with nanoimprint lithography (NIL) coming to the forefront. Since NIL replicates the nanopattern of the mold regardless of the diffraction limit, NIL can achieve sufficiently high productivity and patterning resolution, giving rise to an explosive development in the fabrication of metasurfaces. In this review, we focus on various NIL technologies for the manufacturing of metasurfaces. First, we briefly describe conventional NIL and then present various NIL methods for the scalable fabrication of metasurfaces. We also discuss recent applications of NIL in the realization of metasurfaces. Finally, we conclude with an outlook on each method and suggest perspectives for future research on the high-throughput fabrication of active metasurfaces.

Effects of Emotional Stimulations on the Online Operation of a P300-Based Brain-Computer Interface.

Using P300-based brain-computer interfaces (BCIs) in daily life should take into account the user's emotional state because various emotional conditions are likely to influence event-related potentials (ERPs) and consequently the performance of P300-based BCIs. This study aimed at investigating whether external emotional stimuli affect the performance of a P300-based BCI, particularly built for controlling home appliances. We presented a set of emotional auditory stimuli to subjects, which had been selected for each subject based on individual valence scores evaluated a priori, while they were controlling an electric light device using a P300-based BCI. There were four conditions regarding the auditory stimuli, including high valence, low valence, noise, and no sound. As a result, subjects controlled the electric light device using the BCI in real time with a mean accuracy of 88.14%. The overall accuracy and P300 features over most EEG channels did not show a significant difference between the four auditory conditions (p > 0.05). When we measured emotional states using frontal alpha asymmetry (FAA) and compared FAA across the auditory conditions, we also found no significant difference (p > 0.05). Our results suggest that there is no clear evidence to support a hypothesis that external emotional stimuli influence the P300-based BCI performance or the P300 features while people are controlling devices using the BCI in real time. This study may provide useful information for those who are concerned with the implementation of a P300-based BCI in practice.

Spectral Modulation through the Hybridization of Mie-Scatterers and Quasi-Guided Mode Resonances: Realizing Full and Gradients of Structural Color.

Metasurfaces made up of subwavelength arrays of Mie scatterers can be engineered to control the optical properties of incident light. The hybridization of the fundamental Mie resonances with lattice resonances greatly enhances the scattering cross-section of individual Mie scatterers. Through careful design of the locations of these hybridized modes using two differently engineered hydrogenated amorphous silicon nanorods, we numerically calculate and experimentally fabricate two examples of full color printing; one with spectral colors comparable to the Adobe RGB gamut, and another with gradients of color. We identify and characterize the mechanisms behind each and provide a framework that can be used to design any all-dielectric metasurfaces of subwavelength Mie scatterers for spectral modulation.

Full and gradient structural colouration by lattice amplified gallium nitride Mie-resonators.

The hybridised resonances between Mie-scatterers and lattice resonances, i.e. quasi-guided mode resonances, are investigated. The scattering of the Mie-resonators is improved by the first order of transmitted diffracted light which is coupled to the lattice formed by the Mie-resonators. The conditions of coupling are dependent on the refractive index of the substrate and the effective refractive index of the unit cell of the resonators. Based on the momentum matching conditions, the cut-off wavelength of coupling and the amount of the amplification can be controlled. As a proof-of-concept application of this framework, gallium nitride metasurfaces are designed to produce metasurfaces that display structural colour. Palettes of full spectral colour and gradients are successfully demonstrated. The hue of the colour can be controlled by changing the periodicity of the unit cell at a fixed filling ratio of Mie-scatterer radius to unit cell periodicity, since the increase in periodicity redshifts the cut-off wavelength of the lattice resonance conditions, identified as the Rayleigh anomaly. The brightness of the colour can be tuned by adjusting the filling ratio of the unit cell. Consequently, the proposed framework may provide a fundamental guideline to design spectral filters made up of low-index Mie-scatterers for various applications.

Plasmonic- and dielectric-based structural coloring: from fundamentals to practical applications.

Structural coloring is production of color by surfaces that have microstructure fine enough to interfere with visible light; this phenomenon provides a novel paradigm for color printing. Plasmonic color is an emergent property of the interaction between light and metallic surfaces. This phenomenon can surpass the diffraction limit and achieve near unlimited lifetime. We categorize plasmonic color filters according to their designs (hole, rod, metal-insulator-metal, grating), and also describe structures supported by Mie resonance. We discuss the principles, and the merits and demerits of each color filter. We also discuss a new concept of color filters with tunability and reconfigurability, which enable printing of structural color to yield dynamic coloring at will. Approaches for dynamic coloring are classified as liquid crystal, chemical transition and mechanical deformation. At the end of review, we highlight a scale-up of fabrication methods, including nanoimprinting, self-assembly and laser-induced process that may enable real-world application of structural coloring.