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Anomaly diagnosis of crude oil online near-infrared spectroscopy analysis system with ensemble ICSSOA-SVM

Synchronous spectrofluorimetric determination of tryptophan and kynurenine in human plasma using hydroxypropyl-β-cyclodextrin complexation for investigating their role in major depressive disorder

Genome-wide identification, evolutionary analysis, and expression profiling of protein phosphatase 2C genes in sweet potato (Ipomoea batatas L.)

Seasonal prokaryotic community and geochemical dynamics of an extreme environment: the Naftlije Mud Volcano, Iran

Abstract Mud volcanoes (MVs) are unique terrestrial ecosystems that serve as analogs for hydrocarbon-rich extraterrestrial environments, yet their seasonal microbial dynamics remain poorly understood. This study investigates the seasonal shifts in the prokaryotic community of the Naftlije Mud Volcano (NMV) in northeastern Iran, utilizing 16 S rDNA amplicon sequencing (849 OTUs from 2.9 million reads) alongside comprehensive geochemical analysis over three sampling seasons from 2022 to 2023. We focused on Salsa Lake, a shallow sedimentary environment associated with the NMV, revealing salinity levels between 6% and 8.2%, sulfate concentrations ranging from 170 to 940 ppm, and total petroleum hydrocarbons (TPH) fluctuating between 430 and 989 ppm. Our findings demonstrate substantial community composition changes in response to environmental factors: sulfur-oxidizing Thiomicrospira dominated during the dry season (70% of reads), Arcobacter was prevalent in the wet season (55%), and anoxygenic phototrophic Halorhodospira constituted 76% of reads during the pink summer bloom. Marinobacter remained a consistent presence year-round (2–10%). Notably, unclassified OTUs accounted for 10–20% of sequences, indicating a reservoir of novel diversity. Richness (Chao1) declined from approximately 580 to 180 OTUs as TPH increased and sulfate decreased, while Shannon diversity peaked at 3.2 under diluted spring conditions. These results illustrate that even modest seasonal changes in environmental factors are reflected in the lake’s green-to-pink transitions, actively restructuring the microbial community responsible for sulfur and hydrocarbon cycling, and generating color-linked biosignatures with potential astrobiological implications.

Genomic insights into capital-driven transmission and distance-limited outbreaks of CRAB in Zhejiang ICU networks

Abstract Carbapenem-resistant Acinetobacter baumannii (CRAB) is recognized as one of the most common pathogens responsible for nosocomial infections and mortality among patients in intensive care units (ICUs). Currently, the genomic epidemiological characteristics, transmission patterns, and influencing factors of CRAB dissemination within ICUs remain insufficiently investigated. We conducted a multicenter genomic epidemiological analysis of 138 CRAB isolates collected from ICUs of tertiary hospitals across 8 prefecture-level cities in Zhejiang province between 2018 and 2023. Antimicrobial susceptibility testing and whole-genome sequencing were performed on these isolates. By integrating genomic data from the capital city in public database, we identified population structures and reconstructed transmission events to assess dynamic changes over time. Between 2018 and 2023, CRAB isolates from tertiary hospitals in 9 prefecture-level cities in Zhejiang Province predominantly consisted of the Epidemic Super Lineage (ESL) Clade A and B. The profile of antimicrobial resistance genes was strongly associated with phylogenetic lineage. Short-term outbreaks identified using a 5-SNP threshold demonstrated a significant correlation with geographical distances within 178.7 km. Temporal phylogenetic analysis revealed that the prolonged and sustained transmission of CRAB strains across ICUs in Zhejiang originating in the 2010s, showed a temporal association with the expansion of high-speed rail infrastructure in the provincial capital starting in 2010. CRAB in ICUs from 9 hospitals in Zhejiang Province predominantly consisted of the ESL Clade A and B. Geographical distance and transportation are critical factors influencing the transmission of CRAB outbreaks among ICUs in different cities. The provincial capital appears to exert a persistent influence on non-capital cities, which should be interpreted in light of the larger sample size from Hangzhou.

Ensemble deep learning for optimizing user immersion and engagement in virtual reality

Abstract Virtual Reality (VR) is transforming various domains by providing immersive experiences, but a significant barrier still exists in the inability to recognize user immersion and involvement precisely. To address this study introduces the Adaptive Virtual Reality Design using Immersion Levels and User Engagement (AVRDIL-UEGE) algorithm, which leverages an ensemble of deep learning models to optimize VR immersion and user engagement. By employing a multi-stage approach, the model first standardizes input data using Linear Scaling Normalization (LSN) to enhance accuracy. Subsequently, it integrates Stacked Long Short-Term Memory (SLSTM), Stacked Sparse Autoencoder (SSAE), and Elman Neural Network (ENN) in an ensemble framework to capture complex temporal and spatial patterns. Hyperparameter tuning is performed using the Multi-strategy Improved Red Deer Optimization (MIRDO) algorithm, ensuring robust model performance. Experimental results on the benchmark VR dataset demonstrate the superior predictive accuracy of AVRDIL-UEGE, with a classification accuracy of 98.40% and an MCC of 0.95 compared to traditional machine learning approaches. The proposed model offers significant improvements in user immersion detection, paving the way for more responsive and personalized VR experiences. This work contributes to advancing VR analytics by providing a data-driven, scalable solution for immersive design optimization in real-time applications.

Side‐Chain Symmetry Breaking in Naphthalene Diimides Decouples High Concentration From Cycling Stability in Neutral Aqueous Organic Redox Flow Batteries

ABSTRACT Neutral aqueous organic redox flow batteries (AORFBs) offer a promising pathway for transitioning renewables from supplementary to primary energy sources. However, their advancement is constrained by the limited long‐term cycling stability and sluggish redox kinetics of materials under high‐concentration conditions. Although introducing hydrophilic groups can mitigate these issues, highly symmetric molecular architectures often impose performance penalties. In this study, a series of asymmetrically modified naphthalene diimide derivatives were synthesized via a one‐pot symmetry‐breaking strategy, which diol‐dex‐NDI achieves a high solubility of 1.82 M. Density functional theory and Molecular dynamics simulations reveal that diol‐dex‐NDI preferentially adopts a dynamic antiparallel π–π stacking mode, enhancing thermodynamic stability while effectively suppressing molecular aggregation. In situ Raman spectroscopy uncovers hydration shell dynamics during electron transfer, showing a 35% reduction in desolvation energy barrier compared to dex‐NDI. Furthermore, π–π and dipole interactions with the electrode enhance adsorption energy and accelerate electron transfer. This molecular design also strengthens the key C─N bond, as evidenced by increased bond dissociation energy, thereby intrinsically improving resistance to electrochemical degradation. Leveraging these advantages, 1.0 M (2 M e − ) diol‐dex‐NDI/MiAcNH‐TEMPO ‐based AORFB delivers stable performance over 620 cycles without notable capacity decay. This work highlights the potential of symmetry‐breaking molecular engineering for practical AORFB applications.

Comparative analysis of phase-specific plasma Epstein–Barr virus DNA signatures in Malaysian nasopharyngeal carcinoma

Upcycling Water Pollutants Into Long‐Chain Polymers via Synergistic Interfacial Dechlorination and Organic Radical Stabilization

ABSTRACT High‐entropy oxides (HEOs) offer unusual electronic structures arising from lattice distortion, multimetal synergy, and high chemical stability. Here we report nitrogen‐doped carbon‐encapsulated HEOs catalysts (HEO@NC) synthesized by in situ carbothermal reduction for efficient pollutant removal and upcycling through selective oxidative polymerization. HEO@NC activates periodate via an electron‐transfer pathway coupled with surface‐adsorbed hydroxyl radicals, enabling the selective conversion of phenolic contaminants into polymeric products under extreme pH and strong ionic interference. Relative to metal‐free nitrogen‐doped carbon, HEO@NC markedly enhances periodate activation through interfacial electronic coupling and achieves a periodate utilization efficiency of 449.2%, far exceeding that of conventional mineralization. Density functional theory and experimental analyses reveal complementary roles of the HEOs components: Co/Ni provide periodate‐binding sites, Pt lowers the barrier for electron transport, Bi/Pb promote charge delocalization to stabilize polymeric intermediates, and oxygen orbitals strengthen periodate coordination and surface charge transfer via p – d hybridization. This synergy drives dechlorination‐coupled polymerization with sustained 4‐chlorophenol removal at ultralow oxidant consumption. HEO@NC further maintained > 95% efficiency with negligible metal leaching during 20‐day treatment of real coal chemical wastewater, demonstrating the potential for sustainable and low‐chemical‐consumption remediation of industrial‐relevant wastewater.

Stress recovery effects of visual exposure to bamboo landscapes in urban parks: Evidence from physiological and psychological responses

CD163 expression in M2 macrophages of primary and metastatic head and neck squamous cell carcinoma

Association of drinking water fluoride with dental fluorosis and caries among schoolchildren in Al-Ahsa, Saudi Arabia

Knowledge, attitudes, and practices regarding avian influenza among poultry-related occupational groups in three provinces of China

Abstract The global risk of avian influenza outbreaks has increased significantly in recent years, posing substantial threats to both the poultry industry and public health due to frequent human infection cases. Occupational groups within the poultry industry face particularly high infection risks because of prolonged close contact with poultry. This study aimed to identify differences in knowledge, attitudes, and practices (KAP) regarding avian influenza among various occupational categories, pinpoint weaknesses in prevention and control, and provide scientific evidence to support targeted intervention strategies. We conducted a cross-sectional survey using stratified random sampling among 1,362 individuals engaged in poultry-related occupations in Anhui, Sichuan, and Guangxi provinces, China, from May to July 2025. Data on avian influenza-related knowledge, attitudes, and practices (KAP) were collected through electronic questionnaires. Statistical analyses were performed using SPSS 27.0, employing descriptive statistics, chi-square tests for group comparisons, and multivariate logistic regression to identify factors associated with KAP levels. A total of 1,194 valid questionnaires were collected. The overall KAP qualification rate among survey participants was 48.16%, with knowledge awareness being the lowest (33.84%), the positive attitude rate was 83.42%, and the positive practice rate was 41.46%. Multivariate analysis identified distinct factors influencing knowledge, attitude, and practice. Regarding knowledge, commercial farm workers (aOR = 1.87,95%CI:1.24–2.81) and backyard farmers(aOR = 2.40,95%CI:1.37–4.21) had higher levels than live poultry market workers, with urban residents(aOR = 1.49,95%CI:1.06–2.09), higher education, and absence of chronic disease (aOR = 1.94,95%CI:1.30–2.91) also predicting better knowledge. For attitude, commercial farm workers (aOR = 3.02,95%CI:1.67–5.46) and urban residents (aOR = 2.84,95%CI:1.79–4.51) were more positive. For practice, workers in Guangxi outperformed those in Anhui (aOR = 1.72,95%CI:1.06–2.79); commercial farm workers (aOR = 7.01,95%CI:4.55–10.80) and slaughterhouse workers (aOR = 6.33,95%CI:3.63–11.05) outperformed live poultry market workers, while backyard farmers showed poorer practices (aOR = 0.40,95%CI:0.22–0.74); females exhibited better practices than males (aOR = 1.33,95% CI:1.01–1.77). Furthermore, mobile internet (59.55%) and television/radio (50.42%) were the primary sources of information across all occupational groups. The findings reveal a pattern of superficial knowledge, and positive attitudes that do not translate into effective protective practices. Live poultry market workers, backyard farmers, individuals with lower education levels, and those residing in rural areas demonstrated poorer knowledge of avian influenza, while males exhibited lower adoption rates of protective practices. These populations should be prioritized as key targets for intervention. It is recommended to implement targeted health communication through new media platforms to enhance the coverage and effectiveness of intervention measures.

RSP-net: an effective framework for automated root cause location in wireless network optimization scene

Inside Front Cover: Side‐Chain Symmetry Breaking in Naphthalene Diimides Decouples High Concentration From Cycling Stability in Neutral Aqueous Organic Redox Flow Batteries (Angew. Chem. Int. Ed. 32/2026)

A progressive augmented reality framework for learning Arduino through physical and digital interaction

Assessing a reduced-channel algorithm for end-to-end seizure detection on multiday EEG using inter-rater agreement with epileptologists

The effect of Zataria multiflora mouthwash on the severity of chemotherapy-induced oral mucositis: a randomized controlled clinical trial

Retrieval processes, phenomenology, and importance for self-identity of unique vs. repeated events in autobiographical memory

Abstract Studies on autobiographical memory (AM) have primarily focused on unique or specific events that had happened at a particular time and place and did not last longer than 24 h. Very little is known about AMs of repeated or general events despite their prevalence and potential importance for self-identity. To address this gap in the literature, 60 participants completed a within-subjects experiment where they recalled 1880 AMs of unique and repeated events from the recent and distant past, and rated AMs on retrieval and phenomenological characteristics, and importance for self-identity and lifetime periods. Results revealed shorter retrieval latencies, lower retrieval effort ratings, and higher prevalence of direct retrieval for AMs of repeated events compared to unique events. Moreover, repeated events were rated as more important for self-identity and for defining lifetime periods. Although the phenomenological memory characteristics of unique and repeated events were similar, unique events were rated as more emotionally positive while repeated events had been more frequently rehearsed. Theoretical and practical implications of the findings are discussed primarily with respect to AM accessibility and retrieval accounts as well as how different types of events contribute to the conceptual self.

Fatigue damage behavior and structural optimisation of asphalt concrete-reinforced subgrade in ballastless tracks under extreme climates

Abstract In cold regions, extreme cold and freeze–thaw cycles cause frost heave, layer separation, and fatigue cracks in high-speed railway ballastless tracks, posing a risk to the structure and safety. This study examines CRTS III tracks with full-scale fatigue tests at − 48 °C and freeze–thaw cycles (− 50 °C to 45.8 °C), comparing three subgrade structures (with and without asphalt layers of varying thickness). A track-subgrade finite element model evaluates the impacts of asphalt thicknesses (7, 8, 10, 12 cm) on fatigue damage. The asphalt layer greatly boosts cold elastic stability, resists plastic deformation, and curbs frost heave; benefits rise with thickness. Fatigue damage mainly comes from tensile stress caused by train traction. Increasing asphalt thickness boosts fatigue resistance, but gains shrink beyond 10 cm: raising thickness from 10 to 12 cm lowers damage by just 0.83%. Balancing deformation, fatigue, and cost, 10 cm is the best asphalt layer thickness. This study offers a quantitative basis for safe ballastless track design in cold regions.