Far-ultraviolet (UV) light has a wide range of global applications, including virus inactivation, bacterial disinfection, human body sterilization, communication, and sensing. Nitride semiconductors, such as AlN and AlGaN, are particularly advantageous for wavelength conversion applications because of their large energy bandgap of approximately 6 eV, which provides excellent transparency in the far-ultraviolet spectrum. In this study, we employed a transverse-quasi-matching approach to design and fabricate an AlN/AlGaN strained-layer superlattice (SLS) channel waveguide. The wavelength spectra and power dependency of the SH intensity confirm the first successful demonstration of far-UV light emission from a polarity-inversion-free SLS structure via the enhancement of the second-order nonlinear optical susceptibility by piezoelectric polarization under ultrashort pulse stimulation.
Mental health disorders pose a significant global challenge, motivating growing interest in natural language processing (NLP) methods for automated mental health assessment. In recent years, the field has evolved rapidly from traditional feature-based approaches to deep learning architectures and pre-trained foundation models. However, a comprehensive understanding of their relative strengths, limitations, and practical implications remains limited. This paper presents a survey of NLP methodologies for mental health assessment, covering commonly used data sources and representative modeling approaches, and analyzing how advances in representation learning have influenced assessment capability, interpretability, and deployment feasibility. Given that existing studies often rely on disparate datasets and metrics, a direct comparison of these methodologies remains difficult. To complement the literature synthesis, we conduct a unified empirical comparison of representative methods under a consistent experimental setting, providing an additional perspective on performance and efficiency trade-offs. Based on both the literature survey and empirical observations, we discuss key insights that shape the practical use of NLP in mental health, including trade-offs between model complexity and scalability, the role of instruction adherence in prompting-based reasoning, and persistent limitations of current datasets and benchmarks. Building on these observations, this survey outlines important challenges and future research directions toward the responsible and scalable application of NLP technologies in mental health assessment.
Noctiluca scintillans is a globally distributed harmful algal bloom (HAB) species known for potentially causing fish mortality and economic losses to fisheries. N. scintillans tends to accumulate near the sea surface, making it particularly susceptible to transport by ocean currents, however, direct evidence of long-distance dispersal has remained limited. Year-round monitoring in Kumamoto revealed that the Indonesian (Jakarta-type, K2) genotype occurs predominantly during the autumn high-abundance period, coinciding with smaller cell sizes that match Jakarta population. To evaluate the plausibility of long-distance transport, we conducted Lagrangian particle-tracking simulation using OSCAR surface currents. The results showed a plausible physical ocean connectivity between Indonesia and Japan within 600 days, with consistent patterns across different particle-release numbers indicating that arrival probabilities remained low but spatially robust. Recognizing that OSCAR provides a 0.25° satellite-derived representation of basin-scale surface circulation that does not explicitly resolve mesoscale eddies, we interpret these trajectories as possible connectivity pathways rather than literal particle tracks. Together, our genetic, morphological, and particle-tracking simulation results indicate that N. scintillans populations in Yatsushiro Bay likely consist of both regional and foreign genetic contributors, highlighting the potential for long-range connectivity under contemporary circulation patterns.
Activated carbon was prepared from Chlorella by carbonization and potassium hydroxide activation, and its structural properties and methylene blue (MB) adsorption performance were evaluated. Raw Chlorella exhibited an adsorption capacity of 287.2 mg g-1, which decreased to 214.8 mg g-1 after carbonization. Potassium hydroxide (KOH) activation increased the adsorption capacity to 329.7 mg g-1, representing an increase of approximately 15% compared with the raw material and 54% relative to the biochar. This improvement was attributed to the development of a porous structure and the increase in specific surface area induced by the activation process. Adsorption isotherms were analyzed using the Langmuir, Freundlich, and Temkin models. The Langmuir model gave a maximum monolayer adsorption capacity of 379.6 mg g-1, whereas the Freundlich model provided the best fit (R 2 = 0.93), indicating predominance of multilayer physisorption. Temkin analysis showed strong adsorption during the initial stages, followed by a gradual decrease in adsorption heat, reflecting surface heterogeneity and a partial contribution of chemisorption. These findings demonstrate that KOH activation effectively enhances the adsorption performance of Chlorella-derived carbon materials and that the adsorption mechanism involves coexistence of monolayer adsorption, multilayer adsorption, and chemisorption.
With recent advances in chemotherapy for unresectable pancreatic ductal adenocarcinoma (PDAC) with liver metastasis (LM), attempts have been made to resect the primary tumor in patients showing favorable responses to anti-cancer treatment (so-called “conversion surgery”; CS). This study aimed to clarify the outcomes of CS for PDAC with LM in a nationwide multicenter study. This retrospective, multicenter study was conducted as a project study of the Japan Pancreas Society and included patients with PDAC with LM at initial diagnosis, diagnosed radiologically or intraoperatively (occult LM), who underwent CS after at least 4 months of chemotherapy between 2010 and 2022. Survival outcomes and prognostic factors were analyzed. 90 patients were enrolled from 31 Japanese institutions. Median duration of preoperative chemotherapy was 10.4 (range, 4.2–58.5) months, and gemcitabine plus nab-paclitaxel was the most common first-line regimen, followed by folinic acid, 5-fluorouracil, irinotecan, and oxaliplatin. Liver metastasectomy was performed in 27 patients (30
