Multi-modality multi-task model for mRS prediction using diffusion-weighted resonance imaging.

This study focuses on predicting the prognosis of acute ischemic stroke patients with focal neurologic symptoms using a combination of diffusion-weighted magnetic resonance imaging (DWI) and clinical information. The primary outcome is a poor functional outcome defined by a modified Rankin Scale (mRS) score of 3-6 after 3 months of stroke. Employing nnUnet for DWI lesion segmentation, the study utilizes both multi-task and multi-modality methodologies, integrating DWI and clinical data for prognosis prediction. Integrating the two modalities was shown to improve performance by 0.04 compared to using DWI only. The model achieves notable performance metrics, with a dice score of 0.7375 for lesion segmentation and an area under the curve of 0.8080 for mRS prediction. These results surpass existing scoring systems, showing a 0.16 improvement over the Totaled Health Risks in Vascular Events score. The study further employs grad-class activation maps to identify critical brain regions influencing mRS scores. Analysis of the feature map reveals the efficacy of the multi-tasking nnUnet in predicting poor outcomes, providing insights into the interplay between DWI and clinical data. In conclusion, the integrated approach demonstrates significant advancements in prognosis prediction for cerebral infarction patients, offering a superior alternative to current scoring systems.

Very fast, high-resolution aggregation 3D detection CAM to quickly and accurately find facial fracture areas.

BACKGROUND AND OBJECTIVE: The incidence of facial fractures is on the rise globally, yet limited studies are addressing the diverse forms of facial fractures present in 3D images. In particular, due to the nature of the facial fracture, the direction in which the bone fractures vary, and there is no clear outline, it is difficult to determine the exact location of the fracture in 2D images. Thus, 3D image analysis is required to find the exact fracture area, but it needs heavy computational complexity and expensive pixel-wise labeling for supervised learning. In this study, we tackle the problem of reducing the computational burden and increasing the accuracy of fracture localization by using a weakly-supervised object localization without pixel-wise labeling in a 3D image space. METHODS: We propose a Very Fast, High-Resolution Aggregation 3D Detection CAM (VFHA-CAM) model, which can detect various facial fractures. To better detect tiny fractures, our model uses high-resolution feature maps and employs Ablation CAM to find an exact fracture location without pixel-wise labeling, where we use a rough fracture image detected with 3D box-wise labeling. To this end, we extract important features and use only essential features to reduce the computational complexity in 3D image space. RESULTS: Experimental findings demonstrate that VFHA-CAM surpasses state-of-the-art 2D detection methods by up to 20% in sensitivity/person and specificity/person, achieving sensitivity/person and specificity/person scores of 87% and 85%, respectively. In addition, Our VFHA-CAM reduces location analysis time to 76 s without performance degradation compared to a simple Ablation CAM method that takes more than 20 min. CONCLUSION: This study introduces a novel weakly-supervised object localization approach for bone fracture detection in 3D facial images. The proposed method employs a 3D detection model, which helps detect various forms of facial bone fractures accurately. The CAM algorithm adopted for fracture area segmentation within a 3D fracture detection box is key in quickly informing medical staff of the exact location of a facial bone fracture in a weakly-supervised object localization. In addition, we provide 3D visualization so that even non-experts unfamiliar with 3D CT images can identify the fracture status and location.

Tranilast treatment prevents chronic radiation-induced colitis in rats by inhibiting mast cells infiltration.

INTRODUCTION: Mast cells are the principal cells leading to acute and chronic colitis due to irradiation, radiation-induced colitis (RIC). Herein, we investigated whether pre-treatment with tranilast, mast cell inhibitor, could alleviate chronic RIC. METHODS: A total of 23 Sprague Dawley (SD) rats were randomly divided into three groups: control group (n=5, C), irradiation group (n=9, RG), and tranilast pre-treated irradiation group (n=9, TG). The rats in RG and TG were irradiated in the pelvic area (1.5cm from anus) with a single dose of 20 Gray under general anesthesia. Tranilast (100 mg/kg) was intraperitonially injected to mice of the TG for 10 days starting from the day of pelvic irradiation. Ten weeks after irradiation, the rats were euthanized. Rectal tissue samples were evaluated histologically for the total inflammation score (TIS) and mast cell count. Expression of MUC2, MUC5AC and matrix metalloproteinase 9 (MMP9) were also assessed immunohistochemically. RESULTS: Both TIS and some components of TIS, epithelial atypia, vascular sclerosis and colitis cystica profunda (CCP) were significantly higher in RG than in TG (P=0.02, 0.038, 0.025, 0.01, respectively). The number of infiltrating mast cells was significantly higher in the RG than in TG (20, 3-54 and 6, 3-25, respectively, P=0.034). Quantitatively, the number of MMP9-positive cells was significantly higher in the RG (23.67±19.00) than in the TG (10.25±8.45) (P<0.05). TIS and MMP9 exhibited strong associations (correlation coefficient r=0.56, P<0.05) Immunohistochemically, mucin-lake of CCP showed no staining for MUC5AX but positivity for MUC2. CONCLUSION: Tranilast pretreatment in RIC shows an anti-inflammatory effect on the RIC in association with the reduction of mast cell infiltration and MMP9 expression.

Identification of High Linoleic Acid Varieties in Tetraploid Perilla Through Gamma-ray Irradiation and CRISPR/Cas9.

Perilla (Perilla frutescens (L.) var frutescens) is a traditional oil crop in Asia, recognized for its seeds abundant in α-linolenic acid (18:3), a key omega-3 fatty acid known for its health benefits. Despite the known nutritional value, the reason behind the higher 18:3 content in tetraploid perilla seeds remained unexplored. Gamma irradiation yielded mutants with altered seed fatty acid composition. Among the mutants, DY-46-5 showed a 27% increase in 18:2 due to the 4 bp deletion of PfrFAD3b and NC-65-12 displayed a 16% increase in 18:2 due to the loss of function of PfrFAD3a through a large deletion. Simultaneous knockout of two copies of FATTY ACID DESATURASE 3 (PfrFAD3a and PfrFAD3b) using CRISPR/Cas9 resulted in an increase in 18:2 by up to 75% and a decrease in 18:3 to as low as 0.3% in seeds, emphasizing the pivotal roles of both genes in 18:3 synthesis in tetraploid perilla. Furthermore, diploid Perilla citriodora, the progenitor of cultivated tetraploid perilla, harbors only PfrFAD3b, with fatty acid analysis revealing lower 18:3 levels than tetraploid perilla. In conclusion, the enhanced 18:3 content in cultivated tetraploid perilla seeds can be attributed to the acquisition of two FAD3 copies through hybridization with wild-type diploid perilla.

Deep Learning-Based Real-Time Organ Localization and Transit Time Estimation in Wireless Capsule Endoscopy.

BACKGROUND: Wireless capsule endoscopy (WCE) has significantly advanced the diagnosis of gastrointestinal (GI) diseases by allowing for the non-invasive visualization of the entire small intestine. However, machine learning-based methods for organ classification in WCE often rely on color information, leading to decreased performance when obstacles such as food debris are present. This study proposes a novel model that integrates convolutional neural networks (CNNs) and long short-term memory (LSTM) networks to analyze multiple frames and incorporate temporal information, ensuring that it performs well even when visual information is limited. METHODS: We collected data from 126 patients using PillCam™ SB3 (Medtronic, Minneapolis, MN, USA), which comprised 2,395,932 images. Our deep learning model was trained to identify organs (stomach, small intestine, and colon) using data from 44 training and 10 validation cases. We applied calibration using a Gaussian filter to enhance the accuracy of detecting organ boundaries. Additionally, we estimated the transit time of the capsule in the gastric and small intestine regions using a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) designed to be aware of the sequence information of continuous videos. Finally, we evaluated the model's performance using WCE videos from 72 patients. RESULTS: Our model demonstrated high performance in organ classification, achieving an accuracy, sensitivity, and specificity of over 95% for each organ (stomach, small intestine, and colon), with an overall accuracy and F1-score of 97.1%. The Matthews Correlation Coefficient (MCC) and Geometric Mean (G-mean) were used to evaluate the model's performance on imbalanced datasets, achieving MCC values of 0.93 for the stomach, 0.91 for the small intestine, and 0.94 for the colon, and G-mean values of 0.96 for the stomach, 0.95 for the small intestine, and 0.97 for the colon. Regarding the estimation of gastric and small intestine transit times, the mean time differences between the model predictions and ground truth were 4.3 ± 9.7 min for the stomach and 24.7 ± 33.8 min for the small intestine. Notably, the model's predictions for gastric transit times were within 15 min of the ground truth for 95.8% of the test dataset (69 out of 72 cases). The proposed model shows overall superior performance compared to a model using only CNN. CONCLUSIONS: The combination of CNN and LSTM proves to be both accurate and clinically effective for organ classification and transit time estimation in WCE. Our model's ability to integrate temporal information allows it to maintain high performance even in challenging conditions where color information alone is insufficient. Including MCC and G-mean metrics further validates the robustness of our approach in handling imbalanced datasets. These findings suggest that the proposed method can significantly improve the diagnostic accuracy and efficiency of WCE, making it a valuable tool in clinical practice for diagnosing and managing GI diseases.

Chemical components and their impact on the organoleptic properties of herb-supplemented soy paste (doenjang).

Traditional Korean fermented soy paste (doenjang) has various health benefits; however, its intense umami flavor might interfere with global acceptance. Herbs-supplemented (HS) doenjang, coriander (CS), Korean mint (KMS), and peppermint (PMS), during fermentation was evaluated for its organoleptic properties. The levels of most free amino acids in HS doenjang, known to impart intense flavor, were decreased, including aspartic acid and glutamine. γ-Aminobutyric acid levels increased, whereas 2-pentylfuran levels significantly decreased in KMS and PMS doenjang (p < 0.05). The decrease in the levels of total free sugars, especially glucose, acetic acid, and fumaric acid, and the increase in lactic acid levels reflected in the desirable sour taste. Sensory evaluation corresponded to these alterations, judged superior most of sensorial attributes both by the Korean and foreigner panel particularly in KMS doenjang. Changed amount of chemical components, e.g. asparagine and glutamine of HS doenjang decreased strong umami flavor, it further affected sensory properties.

Development and validation of reverse-transcription cross-priming amplification-based lateral flow assay for the detection of infectious hematopoietic necrosis virus.

Infectious hematopoietic necrosis virus (IHNV) severely and lethally infects salmonid fish, including Atlantic salmon (Salmo salar) and rainbow trout (Oncorhynchus mykiss) worldwide. Rapid and accurate viral detection is crucial for preventing pathogen spread and minimizing damage. Although several IHNV detection assays have been developed, their analytical and diagnostic performances have not been evaluated and field usability assessments have not been completely validated. Here, we developed a reverse-transcription cross-priming amplification-based lateral flow assay (RT-CPA-LFA) and validated its diagnostic performance. To detect the IHNV, primers were designed based on the consensus sequence of the nucleocapsid (N) gene. Notably, when combined with a lateral flow dipstick, it could visualize the IHNV amplification products within 5 min and the detection limit of the developed RT-CPA-LFA was 3.28×105 copies/µL. The diagnostic sensitivity and specificity in fish samples (n=140) were 98.88 % and 96.08 %, respectively. Moreover, the IHNV detection rate by RT-CPA-LFA in dead rainbow trout artificially injected with the virus was 100 %, consistent with to the results obtained from second conventional and real-time PCR, indicating its applicability for rapid IHNV detection and presumptive IHN diagnosis during the endemic period.

Reproducibility for carotid wall segmentation using T1-weighted DANTE-SPACE sequence on high-resolution 3-T carotid MRI.

BACKGROUND: T1-weighted (T1W) magnetic resonance imaging (MRI) using the delay alternating with nutation for excitation-sampling perfection with application-optimized contrasts using different flip angle evolution (DANTE-SPACE) is the preferred imaging technique for evaluation of the vessel wall. PURPOSE: To evaluate the intra- and inter-rater reproducibility of carotid wall segmentation on T1W DANTE-SPACE in patients with symptomatic (acute stroke or transient ischemic attack) internal carotid artery (ICA) stenosis. MATERIAL AND METHODS: This prospective study included 25 patients with acute (≤3 months) stroke or transient ischemic attack and 50%-99% stenosis of the ICA. All patients underwent 3.0-T high-resolution carotid MRI. Two radiologists independently performed the manual segmentation of the vessel wall and inner lumen of the bilateral carotid artery on DANTE-SPACE. The intraclass correlation coefficient (ICC), Dice similarity coefficient (DSC), and Hausdorff distance (HD) were calculated. RESULTS: The ICCs for intra-rater reproducibility of carotid wall volume, inner lumen volume, and normalized wall index were 0.965, 0.990, and 0.962, respectively. The ICCs for inter-rater reproducibility of carotid wall volume, inner lumen, and normalized wall index were 0.856, 0.981, and 0.904. DSC and HD for intra- and inter-rater reproducibility of carotid wall segmentation were as follows: 0.873 and 0.809 (DSC); and 0.079 and 0.118 (HD), respectively. For evaluation of reproducibility only in the carotid artery with symptomatic stenosis, the ICCs for intra- and inter-rater reproducibility indicated all perfect agreement. CONCLUSION: T1W DANTE-SPACE is a reproducible sequence for evaluation of the carotid wall using carotid MRI in patients with symptomatic ICA stenosis.

Prognostic Association between Injury Severity Score and the Outcomes of Elderly Patients with Trauma in South Korea.

This study investigated the impact of the Injury Severity Score (ISS) on treatment approaches and survival outcomes in trauma patients, focusing on comparing elderly (≥65 years) with non-elderly patients. It analyzed adult trauma cases with abnormal Revised Trauma Scores from January to December 2019, categorizing patients into three severity groups based on ISS: mild (1-8), moderate (9-15), and severe (≥16). The study examined how ISS influenced therapeutic interventions and survival among elderly patients, comparing these outcomes to non-elderly patients using multivariable logistic regression analysis. In 16,336 adult trauma cases out of 52,262 patients, including 4886 elderly and 11,450 non-elderly patients, findings revealed that in the severe group, elderly patients had a lower, though not statistically significant, incidence of surgical or embolization interventions compared to the moderate group, differing from non-elderly patients. No significant differences were observed in the mild group between elderly and non-elderly patients. However, elderly patients had higher intervention rates in the moderate group and lower in the severe group, with significantly lower survival-to-discharge rates in the severe group. The ISS is insufficient for assessing trauma severity in elderly patients. Additional tools are needed for better evaluation and treatment decisions.

Simultaneous Multifocal Plane Fourier Ptychographic Microscopy Utilizing a Standard RGB Camera.

Fourier ptychographic microscopy (FPM) is a computational imaging technology that can acquire high-resolution large-area images for applications ranging from biology to microelectronics. In this study, we utilize multifocal plane imaging to enhance the existing FPM technology. Using an RGB light emitting diode (LED) array to illuminate the sample, raw images are captured using a color camera. Then, exploiting the basic optical principle of wavelength-dependent focal length variation, three focal plane images are extracted from the raw image through simple R, G, and B channel separation. Herein, a single aspherical lens with a numerical aperture (NA) of 0.15 was used as the objective lens, and the illumination NA used for FPM image reconstruction was 0.08. Therefore, simultaneous multifocal plane FPM with a synthetic NA of 0.23 was achieved. The multifocal imaging performance of the enhanced FPM system was then evaluated by inspecting a transparent organic light-emitting diode (OLED) sample. The FPM system was able to simultaneously inspect the individual OLED pixels as well as the surface of the encapsulating glass substrate by separating R, G, and B channel images from the raw image, which was taken in one shot.

Pyogenic granuloma of the hard palate leading to alveolar cleft: a case report.

This case report describes a rare occurrence of pyogenic granuloma (PG) in the hard palate deviating from its typical gingival location that led to the formation of an alveolar cleft. The aggressive growth pattern of the lesion, with atypical progression from a pedunculated nodule to an alveolar cleft, raised concern. The diagnosis was based on magnetic resonance imaging and computed tomography findings, which revealed a tadpole-shaped lesion originating from the midline hard palate. The differential diagnosis included a minor salivary gland tumor. Surgical excision was performed under general anesthesia and resulted in a mucosal defect without nasolabial fistula formation or bone exposure. The palatal defect was packed with oxidized regenerated cellulose and closed with Vicryl Rapide sutures, both of which contributed to the patient's successful outcomes. Our comprehensive approach, extending across the stages of surgical planning, execution, and postoperative care, demonstrated the advantages of a multidisciplinary strategy for the accurate diagnosis and effective treatment of palatal PGs. This report makes a meaningful contribution to the existing literature on common oral lesions by emphasizing the importance of a broad differential diagnosis and a systematic approach to oral pathologies. It also raises clinical awareness of PGs with atypical presentations and the diagnostic challenge that they pose.

One-hit kill: On the inactivation of RNA viruses by ultraviolet (UV)-C-induced genomic damage.

Large scale outbreaks of infectious respiratory disease have repeatedly plagued the globe over the last 100 years. The scope and strength of the outbreaks are getting worse as pathogenic RNA viruses are rapidly evolving and highly evasive to vaccines and anti-viral drugs. Germicidal UV-C is considered as a robust agent to disinfect RNA viruses regardless of their evolution. While genomic damage by UV-C has been known to be associated with viral inactivation, the precise relationship between the damage and inactivation remains unsettled as genomic damage has been analyzed in small areas, typically under 0.5 kb. In this study, we assessed genomic damage by the reduced efficiency of reverse transcription of regions of up to 7.2 kb. Our data seem to indicate that genomic damage was directly proportional to the size of the genome, and a single hit of damage was sufficient for inactivation of RNA viruses. The high efficacy of UV-C is already effectively adopted to inactivate airborne RNA viruses.

Generation of mouse and rat xenogeneic ovaries in vitro for production of mouse oocyte.

The system forming ovarian follicles is developed to investigate in vitro folliculogenesis in a confined environment to obtain functional oocytes. Several studies have reported the successful generation of fully functional oocytes using mouse-induced pluripotent stem cells (iPSCs) and mouse female germline stem cells (fGSCs) as sources of stem cells for in vitro gametogenesis models. In addition, human oogonia have been generated through heterologous co-culture of differentiated human primordial germ cell-like cells (hPGCLCs) with mouse germline somatic cells, although oocyte formation remains challenging. Thus, studies on in vitro ovarian formation in other species are utilized as an introductory approach for in vitro mammalian gametogenesis by understanding the differences in culture systems between species and underlying mechanisms. In this study, we optimized the method of the entire oogenesis process from rat embryonic gonads. We identified well-maturated MII oocytes from rat gonads using our constructed method. Moreover, we generated the first successful in vitro reconstitution of xenogeneic follicles from mouse primordial germ cells (PGCs) and rat somatic cells. We also established an appropriate culture medium and incubation period for xenogeneic follicles. This method will be helpful in studies of xenogeneic follicular development and oocyte generation.

Imaging Findings of Primary Acinic Cell Carcinoma of the Breast: A Case Report.

Acinic cell carcinoma is a rare malignant tumor that accounts for 2%-3% of salivary gland tumors. Acinic cell carcinoma arising from the breast is extremely rare, with only approximately 70 cases reported to date. Owing to its rarity, previous studies have primarily focused on pathological findings. Herein, we present the clinical and radiological features of acinic cell carcinoma of the breast in a 33-year-old woman.

On body and off body communication using a compact wideband and high gain wearable textile antenna.

In this paper, a compact low-profile dual-band wearable textile antenna is proposed for on-body and off-body communications. The presented antenna works efficiently in the 5G n79 frequency band (4.4 - 5 GHz) and the ISM band (5.725 - 5.875 GHz). The designed antenna has an ultra-wide impedance bandwidth of 2.01 GHz and peak realized gains of 10.5 dBi and 12 dBi at 4.5 GHz and 5.8 GHz, respectively. The antenna has a small footprint (π × 0.3λ02), which is inspired by circular fractal geometry. The performance of the presented wearable antenna is evaluated at various body parts, including the arm, wrist, and chest. The link margin is evaluated in the on-body and off-body communication scenarios, i.e., communication with the implantable antenna and the outside-body antenna, which is 80 dB and 65 dB at 4.5 GHz and 5.8 GHz, respectively. The 1 gm/10 gm specific absorption rate values at 4.5 GHz and 5.8 GHz are 0.12/0.098 and 0.11/0.082, respectively, which are significantly lower than the standard values, making the proposed antenna suitable for modern wearable applications.

Improved Diagnostic Accuracy of Thyroid Fine-Needle Aspiration Cytology with Artificial Intelligence Technology.

Background: Artificial intelligence (AI) is increasingly being applied in pathology and cytology, showing promising results. We collected a large dataset of whole slide images (WSIs) of thyroid fine-needle aspiration cytology (FNA), incorporating z-stacking, from institutions across the nation to develop an AI model. Methods: We conducted a multicenter retrospective diagnostic accuracy study using thyroid FNA dataset from the Open AI Dataset Project that consists of digitalized images samples collected from 3 university hospitals and 215 Korean institutions through extensive quality check during the case selection, scanning, labeling, and reviewing process. Multiple z-layer images were captured using three different scanners and image patches were extracted from WSIs and resized after focus fusion and color normalization. We pretested six AI models, determining Inception ResNet v2 as the best model using a subset of dataset, and subsequently tested the final model with total datasets. Additionally, we compared the performance of AI and cytopathologists using randomly selected 1031 image patches and reevaluated the cytopathologists' performance after reference to AI results. Results: A total of 10,332 image patches from 306 thyroid FNAs, comprising 78 malignant (papillary thyroid carcinoma) and 228 benign from 86 institutions were used for the AI training. Inception ResNet v2 achieved highest accuracy of 99.7%, 97.7%, and 94.9% for training, validation, and test dataset, respectively (sensitivity 99.9%, 99.6%, and 100% and specificity 99.6%, 96.4%, and 90.4% for training, validation, and test dataset, respectively). In the comparison between AI and human, AI model showed higher accuracy and specificity than the average expert cytopathologists beyond the two-standard deviation (accuracy 99.71% [95% confidence interval (CI), 99.38-100.00%] vs. 88.91% [95% CI, 86.99-90.83%], sensitivity 99.81% [95% CI, 99.54-100.00%] vs. 87.26% [95% CI, 85.22-89.30%], and specificity 99.61% [95% CI, 99.23-99.99%] vs. 90.58% [95% CI, 88.80-92.36%]). Moreover, after referring to the AI results, the performance of all the experts (accuracy 96%, 95%, and 96%, respectively) and the diagnostic agreement (from 0.64 to 0.84) increased. Conclusions: These results suggest that the application of AI technology to thyroid FNA cytology may improve the diagnostic accuracy as well as intra- and inter-observer variability among pathologists. Further confirmatory research is needed.

A Comprehensive Study on a Deep-Learning-Based Electrocardiography Analysis for Estimating the Apnea-Hypopnea Index.

This study introduces a deep-learning-based automatic sleep scoring system to detect sleep apnea using a single-lead electrocardiography (ECG) signal, focusing on accurately estimating the apnea-hypopnea index (AHI). Unlike other research, this work emphasizes AHI estimation, crucial for the diagnosis and severity evaluation of sleep apnea. The suggested model, trained on 1465 ECG recordings, combines the deep-shallow fusion network for sleep apnea detection network (DSF-SANet) and gated recurrent units (GRUs) to analyze ECG signals at 1-min intervals, capturing sleep-related respiratory disturbances. Achieving a 0.87 correlation coefficient with actual AHI values, an accuracy of 0.82, an F1 score of 0.71, and an area under the receiver operating characteristic curve of 0.88 for per-segment classification, our model was effective in identifying sleep-breathing events and estimating the AHI, offering a promising tool for medical professionals.

Compact Ultra-Wideband Wilkinson Power Divider in Parallel Stripline with Modified Isolation Branches.

An efficient design method for a compact and ultra-wideband multi-stage Wilkinson power divider in a parallel stripline (PSL) is proposed. To enhance the frequency bandwidth of the proposed power divider while reducing its size, the isolation branch is modified; that is, two capacitors are connected to both sides of a resistor at each isolation branch. For an efficient design process, the PSL power divider is equivalently represented by two microstrip power dividers, and the design equations are derived. Based on the design equations, an in-house algorithm is utilized to optimally determine the design parameters, including the line impedance, resistance, and capacitance of each stage. For example, a three-stage PSL power divider is designed with three λ/4 transmission lines at a base frequency of 5 GHz. To verify the accuracy of the design procedure, 3D EM simulations and measurements are performed, and the results show good agreement. Compared with the conventional three-stage Wilkinson power divider, the proposed PSL power divider achieves a wider frequency bandwidth of 1.16 to 6.51 GHz (139.5%) and a 23% shorter transmission line length of 207°, while exhibiting an insertion loss of 0.7 to 1.4 dB.

Double-Edged Sword? The Impact of Online Misogyny on Female College Students' Digital Activism in the Post-COVID-19 Era.

Using original surveys to investigate how online gender-based harassment marginalizes or empowers female college students, we found increased exposure to misogyny polarizes digital participation. Women aware of gender inequality in Korea encountering online hate speech were more inclined to engage in online movements, unlike women who did not recognize such inequality. This highlights distinct opportunities in relation to digital activism, showing online hate speech can sometimes be a catalyst for online political participation. This study expands current research on digital protest, highlighting the political ramifications of empowering women in the critical context of their unequal democratic rights outside the West.

Ultra-Wideband Vertical Transition in Coplanar Stripline for Ultra-High-Speed Digital Interfaces.

A design method for an ultra-wideband coplanar-stripline-based vertical transition that can be used for ultra-high-speed digital interfaces is proposed. A conventional via structure, based on a differential line (DL), inherently possesses performance limitations (<10 GHz) due to difficulties in maintaining constant line impedance and smooth electric field transformation, in addition to the effects of signal skews, FR4 fiber weave, and unbalanced EM interferences. DL-based digital interfaces may not meet the demands of ultra-high-speed digital data transmission required for the upcoming 6G communications. The use of a coplanar stripline (CPS), a type of planar balanced line (BL), for the vertical transition, along with the ultra-wideband DL-to-CPS transition, mostly removes the inherent and unfavorable issues of the DL and enables ultra-high-speed digital data transmission. The design process of the transition is simplified using the analytical design formulas, derived using the conformal mapping method, of the transition. The characteristic line impedances of the transition are calculated and found to be in close agreement with the results obtained from EM simulations. Utilizing these results, the CPS-based vertical transition, maintaining the characteristic line impedance of 100 Ω, is designed and fabricated. The measured results confirm its ultra-wideband characteristics, with a maximum of 1.6 dB insertion loss and more than 10 dB return loss in the frequency range of DC to 30 GHz. Therefore, the proposed CPS-based vertical transition offers a significantly wider frequency bandwidth, i.e., more than three times that of conventional DL-based via structures.