Earticle

This study focuses on isolating and characterizing novel polyhydroxybutyrate (PHB) depolymerase-producing bacteria to enable efficient PHB biodegradation. PHB is a promising biodegradable alternative to petroleum-based plastics, requires PHB depolymerase to facilitate its effective depolymerization and mineralization in the environment. We identified Janibacter terrae COS4-44 from oil contaminated tidal flat in Taean, Republic of Korea, demonstrating high PHB degradation efficiency via clear zone formation and enzymatic activity. Scanning electron microscopy (SEM) revealed increased surface roughness and porosity in degraded PHB films, while Fourier-transform infrared spectroscopy (FTIR) confirmed the cleavage of ester bonds, indicating enzymatic breakdown. The PHB depolymerase gene was successfully cloned and expressed in E. coli, yielding a functional 58 kDa enzyme. Optimal degradation conditions were 40°C, pH 8.0, and 96 h incubation, with 0.15% PHB concentration. Glucose and yeast extract enhanced enzyme activity, whereas heavy metals like Zn²⁺ and Co²⁺ slightly stimulated depolymerase production. These findings highlight Janibacter terrae COS4-44 as a potent PHB degrader, offering potential for sustainable plastic waste management. Further research on degradation metabolites and enzyme engineering could enhance industrial applications.

The term “sweet spot” is commonly used in analog/RF engineering to describe an operating region where multiple, often competing, requirements are satisfied simultaneously. This paper presents a practical sweet-spot framework that treats bias selection as a constrained multi-objective problem and explicitly connects device inversion level to distortion, noise, power/current, bandwidth-related loading, and robustness against process-voltage-temperature (PVT) drift. A step-by-step, equation-based analysis is given for IM3 shaping using a main path and an auxiliary path that controls the IM3 amplitude ratio and phase error at a combining node, clarifying how a “dip” in IM3 can be created and widened into a tunable sweet-spot region. Finally, a sweet-spot-aware parallel-path architecture is proposed to make the sweet spot tunable and repeatable under realistic excitation.

Large language models (LLMs) have demonstrated remarkable capabilities across a range of tasks, from complex reasoning to creative writing. Yet, these systems remain prone to hallucination, rely entirely on static training data, and risk homogenizing scientific thought through mode collapse. Retrieval-augmented generation (RAG) addresses these limitations by conditioning model outputs on dynamically retrieved external knowledge, tethering the immense generative capacity of LLMs to verifiable, human-curated corpora. This survey traces the development of RAG from its foundational formulations as a simple hallucination- mitigating pipeline to contemporary, highly adaptive architectures. We examine the core components—retrieval, re-ranking, and grounded generation—and survey advanced techniques including active retrieval, hierarchical memory, and multimodal extensions. Crucially, we highlight how LLM is evolving beyond a mere fact-checking mechanism into a collaborative, creative thinking partner. By feeding pluralistic evidence into the generation loop rather than relying on monolithic statistical patterns, multi-layered agentic RAG frameworks actively mitigate systemic biases, safeguard intellectual diversity, and amplify human reasoning. Ultimately, RAG represents an essential epistemological bridge for human-AI symbiosis, empowering users to make fairer and balanced decisions and accelerating the realization of co-prosperity in future society.

Emotion recognition is rapidly advancing within the realm of artificial intelligence (AI), spurred by progress in deep learning, multimodal data handling, and broader availability of large datasets. This paper offers an in-depth overview of emotion recognition strategies, focusing on bio-metric signals (e.g., audio, visual, physiological, and brain signals), conventional machine learning methods, and the latest deep learning architectures, including Transformers, two-dimensional Con-volution Neural Networks (CNNs) 2D CNNs, and three-dimensional CNNs (3D CNNs). We further examine multimodal systems and the role of Large Language Models (LLMs) in merging textual, audio, and video information for more precise emotion assessments. Key challenges such as real-time implementation, data biases, and cultural diversity are also highlighted. Ethical issues related to privacy and the potential misuse of emotion recognition technologies receive attention, as does a discussion of emerging applications in healthcare, human-computer interaction (HCI), mental health monitoring, and education. In sum, this review aims to contribute to the scholarly conversa-tion around evolving emotion recognition methodologies and their applications in practical systems.

Although systemic therapies for bone loss are well established, localized bone augmen-tation approaches remain less mature overall. This unmet need is driving a shift toward localized, minimally invasive strategies. In receptor activator of NF-κB ligand (RANKL) reverse signaling—a distinct, osteoanabolic pathway compared with the canonical receptor activator of NF-κB (RANK)–RANKL–osteoprotegerin (OPG) resorptive axis—RANKL, normally a ligand, acts as a receptor on osteoblast-lineage cells, where membrane accumulation and clustering trigger pro-osteogenic sig-naling. Peptide activators of this pathway (OP3-4, W9) are effective, but their performance depends on scaffold properties that sustain local release and provide multivalent presentation to drive RANKL membrane accumulation and clustering. This review synthesizes recent advances in scaf-fold platforms engineered to enable and amplify RANKL reverse signaling, with emphasis on gel-atin hydrogels, cholesteryl-bearing pullulan (CHP) nanogels, and injectable microparticle systems. We articulate design principles—release kinetics, porosity/architecture, and chemical modifica-tion—that govern local bioavailability and effective ligand valency, and we outline how these prin-ciples extend to RANK-bearing extracellular vesicles. Finally, we outline practical criteria for pair-ing RANKL-binding peptides with scaffolds compatible with non-surgical injectable delivery and discuss translational considerations for future clinical use.

We are trying to apply surface stress improvement process (SSIP) to the repair and maintenance of nuclear power components, mainly in the United States and Japan. A representative example is applying water jet peening (WJP) and laser peening (LP) technology to parts to extend their lifespan. The biggest problem with the lifespan of nuclear power equipment is the occurrence of stress corrosion cracking (SCC), which is directly related to safety. The SSIP is one of the good ways to mitigate SCC. The Code Case N-931 “Performance and Qualification Criteria for Mitigation of Stress Corrosion Cracking by Surface Stress Improvement: Section III, Division 1 and 3’ was developed since 2017 by the task group “Advanced Surface Stress Improvement Technology” in Korea International Working Group (KIWG) of the American Society of Mechanical Engineers (ASME). This case provides performance and qualification criteria for the pre-service application of a SSIP to items potentially susceptible to SCC, as a means to prevent crack initiation. Mitigation of items to the requirements of this case does not modify or change the in-service inspection (ISI) requirements for those items. This Code Case is to be used for SSIP such as ultrasonic nanocrystal surface modification (UNSM), WJP, LP that satisfy the performance criteria and qualification criteria defined in this case. Two major technical bases for this Code Case are “PVP2022-85151” and “EPRI Report 3002018458”. Brief summary of UNSM technology and two technical bases is introduced.

Anthraquinones are secondary metabolites of plants and are widely distributed in vari-ous species. They are known to exhibit a wide range of biological activities, including anticancer, anti-inflammation, antioxidant, antibacterial, anti-damage, and anti-osteoporosis. Anthraquinones are generally lipophilic, which results in relatively low solubility and bioavailability. These limita-tions can be addressed through enzymatic reactions such as glycosylation and hydroxylation. In this study, we attempted the glycosylation of two anthraquinone compounds, anthraflavic acid and xanthopurpurin, using microbial UDP-glycosyltransferase UGT-1. UGT-1 could catalyze the O-glu-cosylation of anthraquinones to form glucoside-type products, which were confirmed by HPLC and high-resolution LC-MS analyses. This study demonstrates that glycosyltransferase UGT-1 could be a good candidate for producing modified anthraquinones with poogical activtential biolities

Trehalose is a naturally occurring disaccharide that is abundantly present in nature. Its presence in cells as several effects, especially because it acts as a natural defender of proteins and membranes. It is utilized in food, cosmetics, and medications because of its excellent water retention properties. Following its esterification with fatty acids of different chain lengths, trehalose has also been shown to have anti-bacterial, anti-biofilm, and anti-inflammatory properties. Trehalose plays a structural part in the bacterial cell wall’s adaptive reactions to stressors including osmotic variations high temperature. Additionally, it was proposed that when bacterial cells are exposed to harsh environment challenges such as heat, cold, desiccation, or reactive oxygen species, these organisms biosynthesize high concentrations of both intra- and extracellular trehalose to help them to survive. Therefore, we analyzed Variovorax sp. PAMC28711 isolated from Antarctica, which was predicted by bioinformatics tools (RAST, Prokka, KEGG, CGView Server, and MetaCyc) to predict the enzymes involved in the different pathways of trehalose production. Furthermore, TLC analysis was carried out to characterize various trehalose biosynthesis pathways. According to the findings, it was revealed that our polar bacteria Variovorax sp. PAMC28711 have potential to produce trehalose through three (Trehalose-6 phosphate synthase/trehalose-6-phosphat phosphatase, Trehalase synthase, and Maltooligosyl-trehalose synthase/maltooligosyl-trehalose trehalohydrolase) pathways. We anticipate that this strain could be of potential use for manufacturing trehalose on the industrial scale.

X-ray thermonuclear bursts (Type I X-ray bursts) are among the most informative and intense transient phenomena associated with accreting neutron stars in low-mass X-ray binaries (LMXBs). These bursts occur due to unstable thermonuclear burning of accreted hydrogen and he-lium on the neutron star surface, and occasionally heavier fuels, producing bright, short-lived X-ray outbursts. The observed burst properties carry crucial information about nuclear synthesis pro-cesses under extreme conditions, the physics of neutron star envelopes and crusts, and the accretion environment. Over the past five decades, the field of burst research has undergone significant ad-vancements thanks to the evolution of observational facilities—from the first detectors aboard SAS-3 and ANS satellites to extensive RXTE catalogs and modern high-precision instruments such as NICER, NuSTAR, Swift, and INTEGRAL. Simultaneously, theoretical models describing ignition, flame propagation, and nuclear reaction chains, including the rp-process and carbon ignition re-sponsible for superbursts, have progressed substantially. Despite these achievements, key open questions remain regarding detailed nuclear reaction pathways, the influence of burst oscillations on surface modes and neutron star rotation, mechanisms of rare phenomena such as type II bursts and superbursts, and systematic uncertainties in using Photospheric Radius Expansion (PRE) bursts to constrain neutron star mass and radius. This review integrates the historical development, cur-rent observational data, theoretical modeling, and future prospects of X-ray burst studies. It sum-marizes major milestones, including the compilation of burst catalogs and statistical population studies, discovery and interpretation of oscillations and PRE bursts, development of multi-zone nu-merical models of thermonuclear ignition and flame spreading, as well as identification and inves-tigation of superbursts. Particular attention is given to how bursts enable constraints on nuclear physics and the equation of state of ultra-dense matter, and experimental and observational ap-proaches are proposed to address outstanding issues. The goal of this review is to provide a com-prehensive reference for researchers entering the field and to outline a roadmap for future interdis-ciplinary projects connecting high-energy astrophysics, nuclear experiments, advanced computa-tional techniques, and multi-messenger observations.