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Linking riverine discharge to shifts in temperate estuarine planktonic food web dynamics
No full textRiverine discharge plays a crucial role in shaping planktonic food web dynamics in coastal systems, though its effects can vary across estuaries. This study investigated the influence of riverine discharge on key biological variables—primary productivity, nitrogen uptake (nitrate and ammonium), biomass, community composition, and mesozooplankton feeding rates—across estuarine gradients in Gwangyang Bay, a low-turbidity temperate estuary in Korea. Principal component analysis identified riverine discharge as the main driver of environmental variation, influencing salinity, light availability, and nutrient concentrations. Microphytoplankton, particularly diatoms, dominated across the estuarine gradient, with diatom peaks in the polyhaline zone and nanophytoplankton in the oligohaline zone, reflecting size-based phytoplankton responses. Riverine nutrient inputs and low turbidity supported high nitrate uptake and primary productivity in the oligohaline zone. Chlorophyll peaks in the polyhaline zone indicated diatom transport and accumulation from upstream. Mesozooplankton feeding rates were highest in the polyhaline zone, suggesting selective grazing on diatoms, while lower feeding rates on smaller phytoplankton was likely due to trophic cascades via predation on microzooplankton. An interplay of selective grazing and trophic cascades across the estuarine–marine continuum drove spatial variations in mesozooplankton feeding. These findings demonstrate how riverine discharge drives planktonic food web dynamics shifts, affecting energy transfer and ecosystem productivity. © 2025 Elsevier B.V., All rights reserved.FALSEsciescopu
A mixed reality-based remote collaboration framework using improved pose estimation
No full textMixed Reality (MR) technology integrates digital content with the real world to enable a cohesive user experience. Accurate pose estimation is crucial for aligning virtual content with physical surroundings, ensuring the virtual elements appear naturally in the user’s environment. This paper proposes a learning-based approach for accurate pose estimation using a monocular RGB (Red-Green-Blue) image, eliminating the need for markers and depth sensors. The method leverages YOLO6D (You Only Look Once Six-Dimensional) and a RoI (Region of Interest)-based color augmentation technique combined with Principal Component Analysis to enhance the accuracy of 6-DoF (Degrees of Freedom) pose estimation, while mitigating the effects of background variations and lighting changes. The proposed pose estimation method is incorporated into an MR-based remote collaboration framework, ensuring consistent and robust information rendering onto target objects across various devices. This integration enhances the reliability and effectiveness of MR-based remote collaboration. Experimental results demonstrate the superior performance of the proposed method, establishing it as a strong foundation for future MR-based remote collaboration frameworks. © © 2025. Published by Elsevier B.V.FALSEsciescopu
Tactile Sensor-Based Body Center of Pressure Estimation System Using Supervised Deep Learning Models
No full textThe center of pressure (CoP) is a key biomechanical indicator for assessing balance and fall risk; however, force plates, the gold standard for CoP measurement, are costly and impractical for widespread use. Low-cost alternatives such as inertial units or pressure sensors are limited by drift, sparse sensor coverage, and directional performance imbalances, with previous supervised learning approaches reporting ML-AP NRMSE differences of 3.2-4.7% using 1D time-series models on sparse sensor arrays. Therefore, we propose a tactile sensor-based CoP estimation system using deep learning models that can extract 2D spatial features from each pressure distribution image with CNN/ResNet encoders followed by a Bi-LSTM for temporal patterns. Using data from 23 healthy adults performing four balance protocols, we compared ResNet-Bi-LSTM and CNN-Bi-LSTM with baseline CNN-LSTM and Bi-LSTM models used in previous studies. Model performance was validated using leave-one-out cross-validation (LOOCV) and evaluated with RMSE, NRMSE, and R2. The ResNet-Bi-LSTM with angular features achieved the best performance, with RMSE values of 18.63 +/- 4.57 mm in the mediolateral (ML) direction and 17.65 +/- 3.48 mm in the anteroposterior (AP) direction, while reducing the ML/AP NRMSE difference to 1.3% compared to 3.2-4.7% in previous studies. Under dynamic protocols, ResNet-Bi-LSTM maintained the lowest RMSE across models. These findings suggest that tactile sensor-based systems may provide a cost-effective alternative to force plates and hold potential for applications in gait analysis and real-time balance monitoring. Future work will validate clinical applicability in patient populations and explore real-time implementation.TRUEsciescopu
ROS-responsive graphene-hyaluronic acid nanomedicine for targeted therapy in renal ischemia/reperfusion injury
No full textBackground: Acute kidney injury (AKI) frequently progresses to chronic kidney disease (CKD) through the AKI-to-CKD transition; however, effective treatment strategies remain challenging due to the complex and multifactorial pathophysiology of this process. This study aims to develop a multifunctional nanoplatform for kidney-specific targeting, reactive oxygen species (ROS) scavenging, and anti-fibrotic drug delivery to mitigate AKI-to-CKD progression. Methods: Reduced graphene oxide (rGO) was conjugated with hyaluronic acid (HA) to form HA/rGO nanoparticles, enabling CD44-mediated renal targeting and ROS-responsive drug release. Paricalcitol, a hydrophobic anti-fibrotic agent, was loaded onto HA/rGO to form P/HA/rGO. The physicochemical characteristics, ROS-scavenging capacity, and oxidative stress-responsive drug release were evaluated. In vitro cytoprotection was assessed using HK-2 cells under oxidative stress. In vivo studies using ischemia/reperfusion (IR) injury mouse models assessed biodistribution, renal targeting, and therapeutic efficacy after systemic administration of P/HA/rGO. Results: HA/rGO nanoparticles demonstrated potent antioxidant activity and significantly protected HK-2 cells from ROS-induced cytotoxicity. P/HA/rGO exhibited a high paricalcitol loading efficiency (93%) and released 26% of the drug over 30 days under oxidative conditions. P/HA/rGO selectively accumulated in IR-injured kidneys via HA-CD44 interactions, decreased serum NGAL and cystatin C levels, and effectively attenuated tubular injury, fibrosis, inflammation, and apoptosis compared to vehicle-treated controls. Conclusion: The P/HA/rGO nanoplatform enables kidney-targeted delivery of paricalcitol with ROS-scavenging and ROS-responsive release properties, providing a promising therapeutic strategy to suppress the AKI-to-CKD transition via integrated targeting and microenvironment-responsive therapy.TRUEsciescopu
The dysadherin/carbonic anhydrase 9 axis shapes an acidic tumor microenvironment to promote colorectal cancer progression
No full textThe tumor microenvironment (TME) plays a central role in cancer progression and metastasis. A key feature of the TME is extracellular acidity, which promotes disease progression, immune evasion, and drug resistance. Tumor acidity is increasingly recognized as a critical factor in cancer development and a negative prognostic indicator. Here, we demonstrate that the membrane glycoprotein dysadherin promotes colorectal cancer (CRC) malignancy by modulating TME acidity. Comprehensive bioinformatics and pathological analyses of CRC patient samples revealed that increased tumor acidity is a hallmark of CRC progression and strongly correlates with high expression of dysadherin. Functional studies confirmed that dysadherin enhances malignant traits, particularly under acidic conditions. Mechanistically, dysadherin activates the integrin/FAK/STAT3 signaling pathway, leading to the upregulation of carbonic anhydrase 9 (CA9). CA9 facilitates proton export, contributing to extracellular acidification while maintaining intracellular pH homeostasis, thereby enabling cancer cells to survive and thrive in acidic environments. In a murine liver metastasis model, dysadherin deletion impaired cellular adaptation to the acidic TME and markedly attenuated metastatic colonization, whereas restoring CA9 expression effectively rescued metastatic potential. Overall, our findings identify the dysadherin/CA9 axis as a potential therapeutic target in CRC and provide new insights into how tumors exploit acidosis to drive malignant development and progression.TRUEsciescopu
Exploring Nontoxic Green Refrigerants Using Positive-Unlabeled Learning and High-Fidelity Search
No full textIdentifying environmentally sustainable refrigerants remains a challenging task, as it requires the reconciliation of thermodynamic performance with stringent safety criteria, particularly those related to low toxicity. In this study, we present a data-driven framework that emphasizes nontoxic refrigerant candidates while also considering flammability, thermal stability, and low global warming potential (GWP). Our approach integrates graph neural networks (GNNs) with positive-unlabeled (PU) learning to accurately identify refrigerants exhibiting the desired physicochemical properties, even on incomplete and biased data sets. We applied the proposed framework to a chemical library of over 33,000 compounds and identified seven promising refrigerants that satisfy all physicochemical and environmental criteria. We report detailed property predictions and uncertainty estimates for each candidate. This work introduces PU learning as a powerful tool for safer molecular design and provides a scalable alternative to traditional experimental or computational screening approaches.FALSEsciescopu
Anomalous Fraunhofer patterns in Cd3As2 Josephson junctions
No full textMajorana zero modes (MZMs) in topological superconductors are promising for quantum computing, yet their unambiguous detection remains challenging. We fabricated Josephson junctions (JJs) using Cd3As2 Dirac semimetal nanoribbons with NbTi superconducting electrodes to investigate topological supercurrents through Fraunhofer pattern analysis. The JJs exhibited excellent quality with high transparency and a large induced superconducting gap (Delta = 1.10 meV), confirmed by multiple Andreev reflection features. While node lifting at the third minimum of the Fraunhofer pattern was observed as a predicted signature of 4 pi-periodic topological supercurrents, our theoretical analysis demonstrates that asymmetric supercurrent distributions can reproduce this behavior without invoking MZMs. These findings reveal that anomalous Fraunhofer patterns alone cannot reliably confirm topological superconductivity, necessitating complementary experimental approaches for conclusive Majorana detection.FALSEsciescopuskc
Tuning ORR Activity of N-Doped Biphenylene-Based Single-Atom Catalysts via DFT and Machine Learning Synergy
No full textThe oxygen reduction reaction (ORR) is critical for sustainable energy solutions, yet noble metal catalysts' costs limit their scalability. This study investigates transition metal-doped biphenylene network (TM-BPNs) single-atom catalysts (SACs) with tailored nitrogen doping as affordable alternatives. Using density functional theory (DFT), we designed 460 TM-BPNs variants with 3d metals (Sc-Zn), evaluating their structures, electronic properties, and dual stability. Most TM-BPNs displayed quasi-metallic or semiconducting traits and robust thermodynamic and electrochemical stability, indicating synthetic viability. ORR assessments showed high potential, with V5/CCCC-Ni achieving an ultralow overpotential of 0.13 V. A novel approach combining the Extreme Gradient Boosting Regressor (XGBR) and Sure Independence Screening and Sparsifying Operator (SISSO) was developed to predict ORR performance. XGBR, with an R 2 of 0.96, identified key features such as the atomic number of TM (NA) and coordination environment influencing Delta G *OH, validated by SHAP analysis. SISSO then derived a 3D descriptor (R 2 = 0.89) that elucidates physical properties governing catalysis, enhancing interpretability. This XGBR-SISSO synergy enables rapid screening and mechanistic insight, underscoring N-doping's role in optimizing TM-BPNs. These findings provide a versatile framework for designing efficient, low-cost ORR electrocatalysts.FALSEsciescopu
Rationally designed zinc oxide nanosphere and multi-walled carbon nanotube composite with enhanced photocatalytic and photoelectrochemical performance
No full textPhotoelectrochemical (PEC) water splitting represents a promising route toward sustainable solar-to-hydrogen energy conversion. Zinc oxide (ZnO), with its wide bandgap (similar to 3.37 eV), high electron mobility and optical transparency has been intensively investigated as a photoanode material. However, its practical utilization remains limited by insufficient visible-light absorption and photocorrosion-induced instability. Here, we present a rationally engineered composite photoanode comprising ZnO nanospheres electrostatically integrated with surface-functionalized multi-walled carbon nanotube (MWCNT), forming a highly conductive and robust interfacial network. The ZnO nanospheres, assembled from quantum dots, ensure high surface area and efficient light harvesting, while the MWCNT network facilitates rapid charge transport and suppresses electron-hole recombination, as evidenced by pronounced photoluminescence quenching. This architecture delivers a remarkable photocurrent density of 417 mu A/cm(2) at 1.23 V-RHE, corresponding to a 29.7-fold enhancement compared with pristine ZnO. In addition, the composite achieves a hydrogen yield of 3.44 mu mol/cm(2) (12.3 times higher) and accelerates pollutant degradation kinetics by 21-fold, demonstrating multifunctional performance. The synergistic interplay between ZnO nanostructures and MWCNTs not only enhances charge transfer dynamics but also imparts superior photostability. These findings highlight a scalable materials design strategy for developing high-efficiency, durable photoanodes, offering broad implications for next-generation solar fuel production and environmental remediation technologies.TRUEsciescopu
Identifying a catalytic center in metal-carbon composites for O3 and persulfate activation: Active site switching between carbon and metal phases
No full textThis study demonstrated that metal-carbon composites (Me-N-C; Me = Mn, Fe, Co, Ni, and Cu) featuring sulfidated metal nanoparticles encapsulated within an N-doped carbon matrix activated both persulfate and O3, albeit through distinct mechanisms. The carbon phase, exhibiting enhanced electrical conductivity due to the presence of internal metal cores, facilitated non-radical persulfate activation. In contrast, the metallic constituent predominantly converted O3 to hydroxyl radical (center dot OH). This oxidant-dependent shift in the principal catalytic site (or degradation pathway) was substantiated by a mechanistic examination of oxidant activation by Ni-N-C that varied in structural characteristics and chemical compositions. The persulfate activation capability of Ni-N-C rose proportionally with the content of graphitic-N as the key species in the non-radical activation pathway. Conversely, center dot OH yield from O3 correlated strongly with the degree of Ni sulfidation, suggesting that sulfidated Ni functioned as the catalytic center for O3 activation. The active-site switching was further supported by the impact of H2-assisted pyrolysis, which suppressed Ni sulfidation while enriching graphitic-N, thereby enhancing persulfate activation but kinetically retarding O3-to-center dot OH conversion. UV irradiation, preventing surface organic accumulation, and thermal sulfidation, enriching metal sulfide content, effectively regenerated Ni-N-C by targeting the respective catalytic centers for persulfate and O3 activation. DFT calculations indicated that Ni3S2 displayed a preferential tendency to dissociatively adsorb and subsequently activate O3, whereas carbonencapsulated Ni promoted non-radical persulfate activation at the carbon interface. The identification of oxidant-specific catalytic sites provided a pivotal design rationale for developing metal-carbon composites as versatile catalysts for oxidant activation.FALSEsciescopu