Preservatives induced succession of microbial communities and proliferation of resistance genes within biofilm and plastisphere in sulfur autotrophic denitrification system.

Methylparaben (MeP), Benzethonium chloride (BZC) and microplastics (MPs) as emerging contaminants are frequently detected in the environment. Furthermore, MPs can be colonized by microorganisms to form a unique ecological niche known as the "plastisphere". In this study, three biofilm-based sulfur autotrophic denitrification (SAD) reactors were established, which were exposed to 0.

UV-promoted surface-enhanced Raman spectroscopy via heterojunction of few-layer MoS flakes on acceptor-rich β-GaO microstrips.

Surface-enhanced Raman spectroscopy (SERS) by 2D semiconductors relies on chemical (CM) enhancement driven by charge-transfer (CT) processes in bandgap alignment between molecules and substrates. Unfortunately, the low light absorption and weak conferment in the atomic-layer material limit the enhancement factor of Raman intensity (EFRI). Improving the utilization efficiency of excitation light is therefore essential for promoting SERS performance of 2D semiconductors.

Mechanistic Insights into Recovery of Partial Denitrification/Anammox under Continuous Flow: Balancing Nitrite Supply and Microbial Competition.

Partial denitrification coupled with anammox (PD/A) has emerged as a promising low-carbon strategy for energy-efficient nitrogen removal from municipal wastewater. However, the reactivation of PD/A systems following operational disturbances remains challenging, particularly under continuous-flow conditions, where microbial interactions and process stability are more complex than in sequencing batch reactors. This study systematically and first evaluated the recovery dynamics of a continuous-flow PD/A process seeded with low-activity granular sludge stored at 4 °C for three months.

Adaptive metric for knowledge distillation by deep Bregman divergence.

Knowledge distillation (KD) makes it possible to deploy high-accuracy models on devices with limited resources and is an effective means of achieving lightweight models. With the advancement of technology, the methods of knowledge distillation are also continuously developing and improving to adapt to different application scenarios and needs. To facilitate the transfer of knowledge from larger networks to smaller and lighter networks, KD has been employed to bridge the gap in probability outputs or middle-layer representations between teacher and student networks.

MSG: Stealing data from pruned neural networks via malicious sparsity guidance.

With the widespread adoption of machine learning cloud platforms, concerns over potential privacy risks in model training algorithms have grown. Attackers can exploit these platforms by deploying malicious algorithms to execute correlation value encoding attacks (CVEA). This attack mainly leverages the model's huge capacity for memorization, covertly embedding training data into the model's parameters.

V-Induced Low-Spin State Mn Suppresses Jahn-Teller Distortion for High-Performance Aqueous Zinc Ion Batteries.

The Jahn-Teller distortion caused by high-spin state Mn (t e ) is a major limiting factor for improving both the specific capacity and cycling stability of MnO cathodes in aqueous zinc-ion batteries. Thus, an intrinsic strategy for optimizing MnO involves the effective elimination of the high-spin state Mn (t e ) during electrochemical process. Herein, we focus on structural design that constructed NHVO-coated MnO (Mn@V) nanorods to achieve the low-spin state of Mn (t e ) and inhibit the Jahn-Teller distortion.

Continuous Proton Channels in Vanadium Hexacyanoferrate Enable All-Round Improved Ultra-Low-Temperature Energy Conversion.

Proton-based batteries emerge as a promising candidate for low-temperature energy conversion and storage, yet their practical implementation is constrained by cathode performance limitations. Herein, [Fe(CN)] vacancies-mediated vanadium hexacyanoferrate (VFeCN-VHCF) with contiguous proton channels is pioneered as a proton cathode material for all-round improved ultra-low-temperature energy conversion. Through operando characterization and density functional theory calculations, we reveal that the [Fe(CN)] vacancies induce the formation of V═O bonds, which serve as the active sites to store protons and endow V-VHCF to reach a high capacity.

A new deep learning model for predicting IMRT dose distributions for lung cancer with dose masks.

Purpose: 3D U-Net deep neural networks are widely used for predicting radiotherapy dose distributions. However, dose prediction for lung cancer IMRT is limited to conventional radiotherapy, with significant errors in predicting the intermediate and low-dose regions.

Methods: We included a mixed dataset of conventional radiotherapy and simultaneous integrated boost (SIB) radiotherapy with various prescription schemes.

Assessment of the safety benefits of HUD warning under high-risk pedestrian crossing event in the connected environment.

The head-up display (HUD) warning system in a connected environment is expected to improve driving behavior and enhance pedestrian crossing safety. While existing research has preliminarily examined the effectiveness of HUD warning system in avoiding pedestrian collisions, scant attention has been given to the microcosmic influence on driving behavior and a precise quantification of its overall benefits, especially in high-risk pedestrian crossing scenarios. To investigate these influences, this study employed driving simulations to construct six connected scenarios: three warning systems (Baseline/head-down display(HDD)/HUD) × two weather conditions (clear weather/foggy weather).

Defect-Engineered LaFeO Stabilizing Oxidized Pt Single-Atom Sites for Low-Temperature CO Oxidation.

The inherent trade-off between activity and stability in platinum single-atom catalysts (SACs) poses a significant challenge for catalytic oxidation reactions. High-coordination Pt sites have good stability, but their overoxidation often passivates activity. In contrast, metastable low-coordination Pt structures typically display high activity but are prone to oxidation and aggregation under harsh conditions.

Household adoption of domestic water filtration for combating waterborne diseases in developing countries.

Drinking contaminated water is a leading cause of several waterborne diseases. Domestic water filtration plants are treated as one of the possible alternative tools to combat the disease caused by contaminated drinking water. Little is known about the usage behaviour of households to use water filtration plants at the domestic level in combating waterborne disease.

Optimal design of Ru-Sn oxide catalysts for enhanced oxygen evolution reaction using the cluster-plus-glue-atom model.

Using the cluster-plus-glue-atom model, we optimized Ru-Sn oxide catalysts for the oxygen evolution reaction (OER). Optimal performance is achieved when all glue-atom sites are occupied by Sn (, Ru : Sn = 1 : 2), thereby maximizing both OER activity and stability. This work provides novel insights and a rapid strategy for designing efficient, stable Ru-based catalysts.

Improvement of optical confinement for high performance perovskite vertical-cavity surface-emitting lasers with the localized surface plasmon resonance effect.

Organic-inorganic perovskite materials have garnered widespread academic attention owing to their remarkable optical characteristics. Nonetheless, it is imperative to minimize the laser threshold and non-radiative recombination losses for developing perovskite lasers with superior performance. In this work, an innovative perovskite vertical-cavity surface-emitting laser (VCSEL) has been developed by integrating gold nanorods (Au NRs) into the resonant cavity to manipulate the light field energy distribution and optical confinement factor, significantly reducing the threshold of perovskite lasers through the localized surface plasmon resonance (LSPR) effect.

[Motor imagery classification based on dynamic multi-scale convolution and multi-head temporal attention].

Convolutional neural networks (CNNs) are renowned for their excellent representation learning capabilities and have become a mainstream model for motor imagery based electroencephalogram (MI-EEG) signal classification. However, MI-EEG exhibits strong inter-individual variability, which may lead to a decline in classification performance. To address this issue, this paper proposes a classification model based on dynamic multi-scale CNN and multi-head temporal attention (DMSCMHTA).

Temporal heterogeneity in traffic crash delays: causal inference from multi-scale time factors and sample-wise structural decomposition.

Traffic crashes remain a critical global public safety concern, exhibiting complex heterogeneity across multiple temporal scales that limits the timeliness and precision of current traffic safety management strategies. Modeling the underlying causation mechanisms across temporal scales presents several challenges, including weak sequential patterns and nonlinear interactions among temporal features. To address these issues, this research categorizes crash data into a macro-scale (annual seasonality) and micro-scale (daily peak intervals and daytime/nighttime variation), and proposes a Multi-Channel Feature Correlation Transformer (MCFformer) to systematically model the influence of multi-scale temporal factors on crash-induced delay.

Al-assisted symbolic healing for digital natives: A Jungian perspective based on the S-O-R and Fogg behavior models.

This study examines the design of emotional healing interventions for Generation Z individuals experiencing anxiety and investigates the mechanisms of AI-assisted collaborative drawing in addressing their needs for personalized and interactive emotional regulation. Drawing on Jungian theory of artistic compensation to evaluate AI-based art therapy, and integrating the S-O-R (Stimulus-Organism-Response) model and the FBM (Fogg Behavior Model), we analyzed how the intelligent mechanisms of AI collaborative painting contribute to emotional healing. We established three art therapy groups-generative AI painting, interactive AI painting, and traditional painting-for comparison.

Pulse wave-driven machine learning for the non-invasive assessment of coronary artery calcification in patients with end-stage renal disease undergoing hemodialysis.

Background: Coronary artery calcification (CAC) represents a major cardiovascular risk in patients with end-stage renal disease (ESRD) undergoing hemodialysis. Given that radial artery pulse waveforms can reflect vascular status, this study aimed to evaluate their utility in the non-invasive assessment of CAC severity.

Methods: 58 patients with ESRD undergoing hemodialysis were enrolled.

Design and Parameter Optimization of Quasi-Zero-Stiffness Structures Based on Cosine-Curve Compliant Beams.

Quasi-zero-stiffness (QZS) structures can provide a near constant force output in a certain range of displacement without force sensors and controllers. Therefore, they can be used in overload protection, vibration isolation, and biomedical application. In this paper, we propose a novel QZS structure based on cosine-curve compliant beams, which have a large QZS stoke and compact layout.

3,4-Dihydroxybenzenesulfonyl-Functionalized Polyethyleneimine for Uranium Chelation.

3,4-dihydroxybenzenesulfonyl-functionalized polyethyleneimine (PS), a novel polymeric chelator, was synthesized by conjugating 3,4-dihydroxybenzenesulfonyl (CAM) groups with branched polyethyleneimine (BPEI, MW = 600 Da) via N-acylation. PS demonstrated a high uranium adsorption capacity of 78.08% at a concentration of 4 mg/mL, accompanied by significant selectivity over competing ions such as Ca, Zn, and Cu.

Correction: Chen et al. Effects of In Situ Porous Carbon Modification on Thermal Energy Storage of Paraffin/Expanded Vermiculite Form-Stable Composite Phase Change Materials. 2025, , 870.

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Discovery of Tricyclic Aromatic Polyketides Reveals Hidden Chain-Length Flexibility in Type II Polyketide Synthases.

Type II polyketide synthases (PKSs) collectively generate polyketide intermediates of varying chain lengths, which undergo cyclization and further tailoring to produce structurally diverse aromatic polyketides. The length of the polyketide chain is a critical factor shaping the core scaffold of the final product. However, individual type II PKSs typically produce intermediates with a fixed chain length, thereby limiting the structural diversity accessible from a single biosynthetic system.

Integration of genome and transcriptome reveals core genes and allele-specific expression genetic variants associated with immune differentiation of taurine ancestry dairy cattle from indicine ancestry cattle.

Background: Disease is a key factor to shorten productive lifespan of dairy cattle. Shifting from classical 'treating existing diseases' to 'preventing diseases before they occur' is a challenge in high-producing dairy cattle. Immunity plays a crucial role in defending against disease.

Toward Lab-In-Fiber Liquid Biopsy: Graphene-Oxide Functionalized Anti-Resonant Optical Fiber for Single-Device Capture-Enrichment-Detection-Recovery of Circulating Tumor Cells.

Metastatic spread in aggressive cancers is often initiated by circulating tumor cells (CTCs) before primary tumor detection. Current CTC analysis faces fundamental limitations due to extreme cell scarcity (≈10 cells mL blood) and reliance on large sample volumes (>7.5 mL).