Analysis of Changes in Viral Load and Inflammatory Cytokines, as Well as the Occurrence of Secondary Infections, in SFTS Patients Treated with Specific Treatments: A Prospective Multicenter Cohort Study.

Severe fever with thrombocytopenia syndrome (SFTS) is an acute febrile illness caused by the SFTS virus (SFTSV). We conducted this study to propose a scientific evidence-based treatment that can improve prognosis through changes in viral load and inflammatory cytokines according to the specific treatment of SFTS patients. This prospective and observational study was conducted at 14 tertiary referral hospitals, which are located in SFTS endemic areas in Korea, from 1 May 2018 to 31 October 2020.

Chronic Hepatitis B Genotype C Mouse Model with Persistent Covalently Closed Circular DNA.

Hepatitis B virus (HBV) can cause chronic infections, significantly increasing the risk of death from cirrhosis and hepatocellular carcinoma (HCC). A key player in chronic HBV infection is covalently closed circular DNA (cccDNA), a stable episomal form of viral DNA that acts as a persistent reservoir in infected hepatocytes and drives continuous viral replication. Despite the development of several animal models, few adequately replicate cccDNA formation and maintenance, limiting our understanding of its dynamics and the evaluation of potential therapeutic interventions targeting cccDNA.

Common Chemical Plasticizer Di(2-Ethhylhexyl) Phthalate Exposure Exacerbates Coxsackievirus B3 Infection.

Unlabelled: Di(2-ethhylhexyl) phthalate (DEHP) is a common plastic rubberizer. DEHP leaches from plastic matrices and is under increasing scrutiny as numerous studies have linked it to negative human health manifestations. Coxsackievirus B3 (CVB) is a human pathogen that typically causes subclinical infections but can sometimes cause severe diseases such as pancreatitis, myocarditis, and meningoencephalitis.

Surveillance of Norovirus in Nationwide Groundwater Sources in South Korea: A Comprehensive Five-Year Study.

Groundwater is an essential drinking water source for humans. However, improper groundwater management leads to fecal contamination and waterborne diseases caused by viral pathogens. Therefore, this study aimed to investigate norovirus (NoV) contamination by conducting nationwide monitoring over five years (2019-2023).

The Impact of Genetic Variation on Duck Hepatitis A Virus (DHAV) Vaccine Efficacy: A Comparative Study of DHAV-1 and DHAV-3 Against Emerging Variant Strains.

Duck virus hepatitis (DVH), caused by duck hepatitis A virus (DHAV), poses significant challenges to duck farming due to high mortality rates in young ducklings. Despite the widespread use of live attenuated vaccines, the genetic diversity within DHAV strains has diminished their cross-protection efficacy. This study aimed to evaluate the cross-protective efficacy of current DHAV-1 and DHAV-3 vaccines against genetically divergent wild strains.

Cell-Cultured Influenza Vaccine Enhances IFN-γ+ T Cell and Memory T Cell Responses Following A/Victoria/2570/2019 IVR-215 (A/H1N1) Infection.

Background: Influenza remains a significant public health challenge, with vaccination being a substantial way to prevent it. Cell-cultured influenza vaccines have emerged to improve on the drawbacks of egg-based vaccines, but there are few studies focusing on T cell immunity with both types of vaccines. Therefore, we studied the following 2022-2023 seasonal influenza vaccines with a standard dose and high dose: cell-based (C_sd and C_hd) and egg-based (E_sd and E_hd) vaccines.

Comparison of ELISA Versus FAMA Titers in Children After Chemotherapy and Hematopoietic Stem Cell Transplantation Who Received the Live Attenuated MAV/06 Strain Varicella Vaccine.

Background: Varicella can lead to severe complications in immunocompromised children, including those undergoing hematopoietic stem cell transplantation (HSCT) or chemotherapy. Preventing primary varicella zoster virus (VZV) infection is crucial in these populations to mitigate morbidity and mortality. This study aimed to evaluate the immunogenicity and safety of the live attenuated MAV/06 varicella vaccine in pediatric patients post-HSCT and post-chemotherapy.

Association Between County-Level Social Vulnerability and Vaccine-Related Attitudes and Hesitancy Toward COVID-19 Vaccination in the United States.

Background/objectives: Understanding attitudes and behaviors related to vaccination is critical for enhancing COVID-19 vaccination acceptance and reducing disparities in vaccination coverage. This study examines disparities in vaccine-related attitudes and COVID-19 vaccine hesitancy in the United States in relation to community-level social vulnerability.

Methods: This study analyzed cross-sectional national surveys conducted repeatedly between July 2020 and August 2021 ( = 6716).

RSV Vaccine with Nanoparticle-Based Poly-Sorbitol Transporter (PST) Adjuvant Improves Respiratory Protection Against RSV Through Inducing Both Systemic and Mucosal Humoral Immunity.

Respiratory syncytial virus (RSV) causes symptoms similar to a mild cold for adults, but in case of infants, it causes bronchitis and/or pneumonia, and in some cases, mortality. Mucosal immunity within the respiratory tract includes tissue-resident memory T (T) cells and tissue-resident memory B (B) cells, which provides rapid and efficient protection against RSV re-infection. Therefore, vaccine strategies should aim to generate mucosal immune responses.

How Attribution of COVID-19 Crisis Responsibility Predicts Hong Kong Citizens' Intention to Accept Vaccination.

Background: This study aims to illuminate the role of perceived crisis responsibility in shaping vaccination intention. By using the case of Hong Kong during the COVID-19 pandemic, we examined whether and how the allocation of crisis responsibility to the government predicts the public's intention to take vaccines, particularly by investigating its underlying mechanism.

Method And Results: Based on a population-representative sample of Hong Kong adults ( = 3188), our results indicated that (1) the attribution of crisis responsibility directly led to lower vaccination intention, and (2) it also had indirect influences on vaccination intention through trust and anger; specifically, the crisis attribution resulted in less willingness to take vaccines via a decreased trust in government health agencies.

Disturbance Robust Attitude Stabilization of Multirotors with Control Moment Gyros.

This paper presents a novel control framework for enhancing the attitude stabilization of multirotor UAVs using Control Moment Gyros (CMGs) and a Disturbance Robust Drive Law (DRDL). Due to their lightweight and compact structure, multirotor UAVs are highly susceptible to disturbances such as wind, making it challenging to achieve stable attitude control using rotor thrust alone. To address this issue, we employ CMGs to provide robust attitude control and apply Fast Terminal Sliding Mode Control (FTSMC) to ensure fast and accurate convergence within a finite time.

Point Cloud Wall Projection for Realistic Road Data Augmentation.

Several approaches have been developed to generate synthetic object points using real LiDAR point cloud data for advanced driver-assistance system (ADAS) applications. The synthetic object points generated from a scene (both the near and distant objects) are essential for several ADAS tasks. However, generating points from distant objects using sparse LiDAR data with precision is still a challenging task.

The Design of a Low-Noise CMOS Image Sensor Using a Hybrid Single-Slope Analog-to-Digital Converter.

In this study, we describe a low-noise complementary metal-oxide semiconductor (CMOS) image sensor (CIS) with a 10/11-bit hybrid single-slope analog-to-digital converter (SS-ADC). The proposed hybrid SS-ADC provides a resolution of 11 bits in low-light and 10 bits in high-light. To this end, in the low-light section, the digital-correlated double sampling method using a double data rate structure was used to obtain a noise performance similar to that of the 11-bit SS-ADC under low-light conditions, while maintaining linear in-out characteristics.

A 0.73 dB Multi-Gain Low Noise Amplifier Design with Fast Mode-Switching for 5G/4G Applications.

In this paper, a sub-1dB Low Noise Amplifier (LNA) with several gain modes, including amplification and attenuation modes required for the fifth and fourth generations (5G/4G) of mobile network applications, is proposed. Its current consumption is adaptive for every gain mode and varies to lower currents for lower amplifications due to the importance of current consumption for mobile network applications. The proposed LNA features an innovative architecture with a three-core input structure supporting multi-gain modes, achieving high gain and ultra-low noise performance.

Pulse Shape Discrimination of n/γ in Liquid Scintillator at PMT Nonlinear Region Using Artificial Neural Network Technique.

Reactor-emitted electron antineutrinos can be detected via the inverse beta decay reaction, which produces a characteristic signal: a two-fold coincidence between a prompt positron event and a delayed neutron capture event within a specific time frame. While liquid scintillators are widely used for detecting neutrinos reacting with matter, detection is difficult because of the low interaction of neutrinos. In particular, it is important to distinguish between neutron (n) and gamma (γ) signals.

Damage Localization and Severity Assessment in Composite Structures Using Deep Learning Based on Lamb Waves.

In composite structures, the precise identification and localization of damage is necessary to preserve structural integrity in applications across such fields as aeronautical, civil, and mechanical engineering. This study presents a deep learning (DL)-assisted framework for simultaneous damage localization and severity assessment in composite structures using Lamb waves (LWs). Previous studies have often focused on either damage detection or localization in composite structures.

Doubly Structured Data Synthesis for Time-Series Energy-Use Data.

As the demand for efficient energy management increases, the need for extensive, high-quality energy data becomes critical. However, privacy concerns and insufficient data volume pose significant challenges. To address these issues, data synthesis techniques are employed to augment and replace real data.

Hardware-Assisted Low-Latency NPU Virtualization Method for Multi-Sensor AI Systems.

Recently, AI systems such as autonomous driving and smart homes have become integral to daily life. Intelligent multi-sensors, once limited to single data types, now process complex text and image data, demanding faster and more accurate processing. While integrating NPUs and sensors has improved processing speed and accuracy, challenges like low resource utilization and long memory latency remain.

Energy-Efficient Dynamic Enhanced Inter-Cell Interference Coordination Scheme Based on Deep Reinforcement Learning in H-CRAN.

The proliferation of 5G networks has revolutionized wireless communication by delivering enhanced speeds, ultra-low latency, and widespread connectivity. However, in heterogeneous cloud radio access networks (H-CRAN), efficiently managing inter-cell interference while ensuring energy conservation remains a critical challenge. This paper presents a novel energy-efficient, dynamic enhanced inter-cell interference coordination (eICIC) scheme based on deep reinforcement learning (DRL).

Attention-Based Malware Detection Model by Visualizing Latent Features Through Dynamic Residual Kernel Network.

In recent years, significant research has been directed towards the taxonomy of malware variants. Nevertheless, certain challenges persist, including the inadequate accuracy of sample classification within similar malware families, elevated false-negative rates, and significant processing time and resource consumption. Malware developers have effectively evaded signature-based detection methods.

Child-Centric Robot Dialogue Systems: Fine-Tuning Large Language Models for Better Utterance Understanding and Interaction.

Dialogue systems must understand children's utterance intentions by considering their unique linguistic characteristics, such as syntactic incompleteness, pronunciation inaccuracies, and creative expressions, to enable natural conversational engagement in child-robot interactions. Even state-of-the-art large language models (LLMs) for language understanding and contextual awareness cannot comprehend children's intent as accurately as humans because of their distinctive features. An LLM-based dialogue system should acquire the manner by which humans understand children's speech to enhance its intention reasoning performance in verbal interactions with children.

Time-Series Representation Feature Refinement with a Learnable Masking Augmentation Framework in Contrastive Learning.

In this study, we propose a novel framework for time-series representation learning that integrates a learnable masking-augmentation strategy into a contrastive learning framework. Time-series data pose challenges due to their temporal dependencies and feature-extraction complexities. To address these challenges, we introduce a masking-based reconstruction approach within a contrastive learning context, aiming to enhance the model's ability to learn discriminative temporal features.

Exploring Technology Acceptance of Healthcare Devices: The Moderating Role of Device Type and Generation.

The increasing adoption of healthcare devices necessitates a deeper understanding of the factors that influence user acceptance in this rapidly evolving area. Therefore, this study examined the factors influencing the technology acceptance of healthcare devices, focusing on radar sensors and wearable devices. A total of 1158 valid responses were used to test hypotheses, mediation, and moderation effects using SmartPLS 4.

Development and Evaluation of Five-in-One Vaccine Microneedle Array Patch for Diphtheria, Tetanus, Pertussis, Hepatitis B, and Type b: Immunological Efficacy and Long-Term Stability.

: The development of a five-in-one vaccine microneedle patch (five-in-one MN patch) aims to address challenges in administering vaccines against Diphtheria (DT), Tetanus (TT), Pertussis (wP), Hepatitis B (HBsAg), and type b (Hib). Combining multiple vaccines into a single patch offers a novel solution to improve vaccine accessibility, stability, and delivery efficiency, particularly in resource-limited settings. : The five-in-one MN patch consists of four distinct microneedle arrays: DT and TT vaccines are coated together on one array, while wP, HepB, and Hib vaccines are coated separately on individual arrays.

Cationic Hydroxyethyl Cellulose Nanocomplexes and RANK siRNA/Zoledronate Co-Delivery Systems for Osteoclast Inhibition.

Background/objectives: In this study, HECP2k polymer, polyethylenimine2k (PEI2k)-modified hydroxyethyl cellulose (HEC) was utilized to form the nanocomplexes with receptor activator of nuclear factor k-B (RANK) siRNA and zoledronate (Zol) for osteoclast inhibition. HECP2k/(RANK siRNA + Zol) nanocomplexes prepared by simple mixing were anticipated to overcome the low transfection efficiency of siRNA and the low bioavailability of Zol.

Methods: The characterization of both HECP2k/(pDNA + Zol) nanocomplexes and HECP2k/(RANK siRNA + Zol) nanocomplexes was performed.