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Collagen, the most abundant and widely distributed functional protein in mammals, typically assembles into collagen fibrils through side-by-side packing. The purpose of this study was to comparatively investigate the fate of sea cucumber collagen fibrils in the gastrointestinal tract when interacting with different anionic polysaccharides (fucoidan (FUC), Kappa-carrageenan (K-car), sodium alginate (SA)). Results revealed that the gel properties and viscosity values of collagen fibrils were notably enhanced, and the rate of structural alteration in collagen fibrils was reduced when K-car and SA were introduced. Conversely, in the presence of FUC, collagen fibril viscosity decreased, and the secondary structure of collagen fibrils underwent changes. FUC was found to diminish the structural stability of collagen fibrils and accelerate the gastric digestion rate, which was further exacerbated by thermal treatment. All these anionic polysaccharides were observed to facilitate the formation of collagen peptide aggregates by binding to polysaccharides during intestinal digestion. This study bridged the knowledge gap regarding the impact of anionic polysaccharides on the gastrointestinal digestion of collagen fibrils, potentially paving the way for broader applications of collagen in the food industry. • The structure and digestion fate of sea cucumber collagens was investigated. • The presence of anionic polysaccharides inconsistently regulated collagen fibrils. • The presence of fucoidan (FUC) improved gastrointestinal digestion rate of fibrils. • Heat treatment increased the effect of FUC on digestion rate of collagen fibrils. • The presence of Kappa-carrageenan and sodium alginate reduced the digestion rate. [ABSTRACT FROM AUTHOR]

Collagen, the most abundant and widely distributed functional protein in mammals, typically assembles into collagen fibrils through side-by-side packing. The purpose of this study was to comparatively investigate the fate of sea cucumber collagen fibrils in the gastrointestinal tract when interacting with different anionic polysaccharides (fucoidan (FUC), Kappa-carrageenan (K-car), sodium alginate (SA)). Results revealed that the gel properties and viscosity values of collagen fibrils were notably enhanced, and the rate of structural alteration in collagen fibrils was reduced when K-car and SA were introduced. Conversely, in the presence of FUC, collagen fibril viscosity decreased, and the secondary structure of collagen fibrils underwent changes. FUC was found to diminish the structural stability of collagen fibrils and accelerate the gastric digestion rate, which was further exacerbated by thermal treatment. All these anionic polysaccharides were observed to facilitate the formation of collagen peptide aggregates by binding to polysaccharides during intestinal digestion. This study bridged the knowledge gap regarding the impact of anionic polysaccharides on the gastrointestinal digestion of collagen fibrils, potentially paving the way for broader applications of collagen in the food industry. • The structure and digestion fate of sea cucumber collagens was investigated. • The presence of anionic polysaccharides inconsistently regulated collagen fibrils. • The presence of fucoidan (FUC) improved gastrointestinal digestion rate of fibrils. • Heat treatment increased the effect of FUC on digestion rate of collagen fibrils. • The presence of Kappa-carrageenan and sodium alginate reduced the digestion rate. [ABSTRACT FROM AUTHOR]

Microbial necromass carbon (MNC) is a stable part of SOC that makes up most of the C pool in land ecosystem. However, the contribution of MNC to SOC accumulation during afforestation is still unclear, particularly in the deep soil. Based on the collection and biomarker analysis of the forest succession sequence and soil profiles with significant depth on the Loess Plateau located China, we study the vertical distribution characteristics and control of MNC. The results found that MNC content increased with succession and decreased with soil depth. On average, the MNC content of a climax forest was 2.23 times higher than that of farmland. The FNC:BNC ratio increased with vegetation succession and decreased with soil depth. Although the MNC content decreased with soil depth, the necromass accumulation coefficient increased. The contribution of MNC to SOC in deep soil (60–100 cm) of pioneer forest was more than 10 % higher than that of farmland, suggesting that afforestation had a relatively positive effect on MNC stabilization and accumulation in deep soils. The microbial biomass and soil nutrient characteristics (i.e., TN, SOC, DOC, and DON) are important factors in mediating the accumulation of MNC in the succession of farmland to forest. These findings demonstrate the potential of MNC in deep soil and provide scientific guidance for sustainable reforestation management based on the carbon pump theory at regional scales. • MNC content of climax forest was 2.23 times higher than that of farmland. • MNC/SOC was >10% higher in pioneer forest than farmland in deep soil. • FNC accumulates more rapidly than BNC with succession. • MNC accumulation decreased with depth, but the accumulation coefficient increased. [ABSTRACT FROM AUTHOR]

A smart cathode coating layer is designed to enhance the high-temperature safety of all-solid-state lithium batteries. Based on the spontaneous polarization-induced built-in electric field, ferroelectric coatings could enhance lithium ion transport at the cathode/electrolyte interface. At hazardous (high) temperatures, ferroelectric coatings transform into paraelectric phases, hindering the transport of lithium ions and slowing down the heat release caused by electrochemical reactions. [Display omitted] [ABSTRACT FROM AUTHOR]

We demonstrate in this paper a super-hydrophilic and oleophobic green porous photothermal material based on wood fiber as a novel oil-repellent photothermal material for efficient solar vapor generation (WF-SP). WF-SP is an excellent light-absorbing material with the advantages of a porous nanostructure, super-hydrophilic, low thermal conductivity, high-temperature resistance, and oleophobicity. Based on these advantages, WF-SP exhibits good solar photothermal conversion performance with solar vapor generation efficiencies of 85.4%, 75.3%, and 70.2% at 1 kW m−2, 2 kW m−2, and 3 kW m−2 radiation intensities, respectively. The results provide new possibilities for the design and preparation of low-cost, green, and pollution-free photothermal materials with high solar thermal conversion efficiency for solar photothermal conversion vapor generation. [ABSTRACT FROM AUTHOR]

The detection of complex interactions between single nucleotide polymorphisms (SNPs) plays a vital role in genome-wide association analysis (GWAS). The multi-objective evolutionary algorithm is a promising technique for SNP-SNP interaction detection. However, as the scale of SNP data further increases, the exponentially growing search space gradually becomes the dominant factor, causing evolutionary algorithm (EA)-based approaches to fall into local optima. In addition, multi-objective genetic operations consume significant amounts of time and computational resources. To this end, this study proposes a distributed multi-objective evolutionary framework (DM-EF) to identify SNP-SNP interactions on large-scale datasets. DM-EF first partitions the entire search space into several subspaces based on a space-partitioning strategy, which is nondestructive because it guarantees that each feasible solution is assigned to a specific subspace. Thereafter, each subspace is optimized using a multi-objective EA optimizer, and all subspaces are optimized in parallel. A decomposition-based multi-objective firework optimizer (DCFWA) with several problem-guided operators was designed. Finally, the final output is selected from the Pareto-optimal solutions in the historical search of each subspace. DM-EF avoids the preference for a single objective function, handles the heavy computational burden, and enhances the diversity of the population to avoid local optima. Notably, DM-EF is load-balanced and scalable because it can flexibly partition the space according to the number of available computational nodes and problem size. Experiments on both artificial and real-world datasets demonstrate that the proposed method significantly improves the search speed and accuracy. • Propose a scalable distributed multi-objective evolutionary framework for large-scale SNP-SNP interaction detection. • Design an effective space partitioning strategy to enhance the diversity and prevent local optima. • Provide a novel multi-objective fireworks optimizer based on decomposition to obtain non-dominated solutions. • Ease the heavy computational burden via distributed computing. [ABSTRACT FROM AUTHOR]

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation. • A framework was developed for field soil sampling information upscale in watershed model construction. • The framework significantly improved hydrology and non-point source simulation accuracy in regions with high heterogeneity. • Information entropy method optimized sampling locations and reduced unnecessary samplings effectively. • The integration of gridded datasets and soil sampling data has significant implications for H/NSP watershed modelling. [ABSTRACT FROM AUTHOR]

The "whitewater zone" represents a critical maritime feature intimately tied to ship identification and stealth capabilities. In this study, the large eddy simulation method is employed to analyze wake fields under varying operational conditions, and the influence of propeller turbulence and bubble wakes on the "whitewater zone" is investigated in conjunction with a self-built optical testing platform. The results indicate that an increase in propeller speed serves to stabilize the vortex structure but also results in a unimodal signal waveform. Moreover, the behavior of bubbles exerts a significant impact on the flow field structure. The coalescence and division of large bubbles play a primary role in altering the flow field structure of the "whitewater zone," consequently accelerating the mixing and diffusion of the "whitewater." The smaller bubbles exhibit prolonged retention times and a broader disturbance area within the surrounding flow field. The research conclusion has certain reference significance for the future development of ocean exploration technology. • An optical test platform for identifying the "whitewater area" is constructed. • Details on the "whitewater area" flow field characteristics is elucidated. • The effect of the "whitewater area" on the laser transmission signal is examined. [ABSTRACT FROM AUTHOR]

Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems. However, publicly available OCTA datasets remain scarce. In this paper, we introduce the largest and most comprehensive OCTA dataset dubbed OCTA-500, which contains OCTA imaging under two fields of view (FOVs) from 500 subjects. The dataset provides rich images and annotations including two modalities (OCT/OCTA volumes), six types of projections, four types of text labels (age/gender/eye/disease) and seven types of segmentation labels (large vessel/capillary/artery/vein/2D FAZ/3D FAZ/retinal layers). Then, we propose a multi-object segmentation task called CAVF, which integrates capillary segmentation, artery segmentation, vein segmentation, and FAZ segmentation under a unified framework. In addition, we optimize the 3D-to-2D image projection network (IPN) to IPN-V2 to serve as one of the segmentation baselines. Experimental results demonstrate that IPN-V2 achieves an about 10% mIoU improvement over IPN on CAVF task. Finally, we further study the impact of several dataset characteristics: the training set size, the model input (OCT/OCTA, 3D volume/2D projection), the baseline networks, and the diseases. The dataset and code are publicly available at: https://ieee-dataport.org/open-access/octa-500. • Proposed OCTA-500, which is the largest and comprehensive OCTA dataset. • The OCTA-500 includes OCTA imaging from 500 subjects and rich annotation information. • Proposed a CAVF task, which integrates multiple key segmentation tasks. • Optimized the IPN to IPN-V2 to serve as one of the competitive baselines. • The OCTA-500 dataset has great potential to promote other researches in OCTA. [ABSTRACT FROM AUTHOR]

The reservoir serves as a water source, a flood control structure, a navigational aid, and also impacts the downstream ecosystem as well as the reservoir zone. However, debate exists about effectiveness of cascade reservoirs in controlling the transportation of nutrients, particularly in the Yangtze River basin, which has been significantly affected by reservoir development. This research develops a new model X-NPSEM (X with Nitrogen and Phosphorus Steady-state Reservoir Model) based on biogeochemical processes of nitrogen and phosphorus reaction for investigating the dynamic storage capacity of cascade reservoirs at both reservoir- and watershed scales. Then the cumulative effects of cascade reservoirs and the related mechanism were investigated in Fujiang watershed, China. Based on the results, cascade reservoirs retained 16.3 % of nitrogen fluxes and 37.6 % of phosphorus fluxes annually. Downstream reservoirs have higher retention rates of phosphorus (0.48/d) compared to upstream reservoirs (0.10/d), mainly due to inflow sediment. Nitrogen retention rates show seasonal variations: wet season (0.21/d) and dry season (0.17/d). These fluctuations in nitrogen retention are primarily influenced by changes in temperature rather than other factors such as operation period, nitrogen and phosphorus concentration, or the nitrogen/phosphorus ratio. In upstream, the concentration of sediment entering the reservoir plays a decisive role in the transformation of P retention from sink to source. The X-NPSRM coupler model could be used for global reservoir operation and watershed management. • New model was developed and could be with other models for simulating reservoir processes. • Cumulative effects of cascade reservoirs were quantified with higher downstream retention rates. • It was found that nitrogen retention rate in reservoir is higher in wet season than dry season. • A transition of phosphorus from being a sink to becoming a source exists in reservoir region. [Display omitted] [ABSTRACT FROM AUTHOR]

Burst release of antibacterial agents generated by the surface antibacterial modification of Ti implants frequently results in a reduction in their biocompatibility and substantial toxic side effects. In this study, core-shelled nanoparticles namely AgNR@MSN, were synthesized successfully by mesoporous silica shell in-situ encapsulated Ag nanorods, and then co-deposited with chitosan to form a AgNR@MSN-chitosan composite coating on Ti substrate by electrophoretic deposition. The developed composite coating, due to the presence of AgNR, presented excellent photothermal effect under the irradiation of an 808 nm near-infrared laser, leading to both rapid increase of local temperature and triggered release of Ag ions for bacterial-killing effect against both E. coli and S. aureus. The addition of AgNR@MSN also improved the wettability of the coating and the MSN shell with mesoporous tunnels could barrier the contact and release rate of Ag to improve the biocompatibility. The developed photothermal responsive coating could be considered as a promising platform for achieving controlled release of Ag ions with outstanding antibacterial and biocompatible properties. AgNR was synthesized firstly by coating Ag on the surface of Au bipyramids. And the core-shell structured AgNR@MSN was synthesized then by sol-gel coating of shell MSN on the surface of AgNR. After that, the production of a composite coating on Ti substrates was then carried out via EPD as using the blend of AgNR@MSN and chitosan. The AgNR@MSN-chitosan composite coatings exhibited immediate silver release and local photothermal effect under NIR irradiation, which contributed to excellent antibacterial property, and simultaneously balanced biocompatibility. [Display omitted] • Core-shell structured AgNR@MSN was synthesized by a two-step process. • AgNR@MSN-chitosan composite coatings were co-deposited on titanium by electrophoretic deposition. • The composite coating exhibited NIR-triggered silver ion release and local temperature increase. • Balanced antibacterial and biocompatible properties of the composite coating were achieved. [ABSTRACT FROM AUTHOR]

The advent of autonomous vehicles (AVs) has complicated traffic flow and raised safety concerns, there is a pressing need to enhance traffic efficiency alongside ensuring robust safety. This paper proposes a dynamic longitudinal control strategy for AVs, based on real-time accident risk assessments. Data from traffic flow, road characteristics, and weather conditions are analyzed using a random forest algorithm, producing a real-time accident risk identification model through a support vector machine. In addition, the Perceived Risk Field Model (PRFM), a car-following model calibrated using the NGSIM dataset, considers vehicle distance, velocity, relative velocity, and acceleration. These models underpin our proposed longitudinal control strategies, tailored to variable accident risk levels. Under the normal risk control strategy, the PRFM outperforms the Intelligent Driver Model (IDM) and the Cooperative Adaptive Cruise Control Model (CACC) in stability and driving comfort. For high accident risk scenarios, our approach shows improved collision avoidance and traffic oscillation mitigation. Simulations indicate that the high accident risk control strategy offers better safety and stability than the normal risk strategy. Furthermore, traffic flow diagrams suggest an increase in road capacity as AV penetration rates rise, pointing to the promising efficiency of our proposed solution. This research provides a robust framework for AV operation, ensuring optimal traffic safety and efficiency. • A real-time accident risk identification model tailored for AVs using machine learning with high predictive accuracy. • Development of a car-following model based on safety potential field and validation using real-world datasets. • Adaptive longitudinal control strategies for AVs, capable of adjusting car-following spacing based on real-time risk. • Framework with risk identification, behavior modeling, and control strategy, providing an integrated approach to AV safety. [ABSTRACT FROM AUTHOR]

[Display omitted] • The influence of doping of trace Sm element on ferrite magnetism was studied. • Ferrite was prepared by solid phase sintering combined with high energy ball milling. • The atomic occupancy of Sm element was obtained by XRD refinement. The primary objective of this study is to enhance the overall magnetic properties of pure barium ferrite through the addition of trace amounts of the light rare earth element Sm. This approach is more cost-effective compared to using heavy rare earth elements. The M-shaped barium ferrite, denoted as Ba 1− x Sm x Fe 12 O 19 , was synthesized using a combination of solid-phase sintering method and high-energy ball milling. The high purity of samples was confirmed by determining their crystal structure using XRD. The internal structure of samples was examined using FTIR, and it was observed that the samples contained tetrahedral and octahedral clusters with corresponding bands at 599 cm−1 and 445 cm−1, respectively. The appearance of samples was examined using FESEM, and it was found that grains had hexagonal structures. EDS was used to characterize the elemental content of samples, and it was found that the content of Ba decreased with an increase in the content of Sm. The magnetic properties of samples were examined using VSM, and the coercivity reached a maximum value of 3096.22 Oe at a dopant fraction of 0.06, and the saturation magnetization reached a maximum value of 73.115 emu/g. The synthesized material has the potential for utilization in magnetic recording applications. [ABSTRACT FROM AUTHOR]