Scientific Reports[JOURNAL]
Sun
200 papers
Risk management and operational efficiency in underground coal mining using circular Pythagorean fuzzy CRITIC WASPAS approach with prioritized weights.
Cui J
Sci Rep · 2026 Jul · PMID 42399652 · Full text
Underground coal mine operations face significant challenges due to the complex and uncertain environments in which they operate. Efficient decision-making in this context is critical for ensuring both safety and product...
Underground coal mine operations face significant challenges due to the complex and uncertain environments in which they operate. Efficient decision-making in this context is critical for ensuring both safety and productivity. This study addresses the problem of selecting the most suitable operational strategy under uncertainty by applying a multi-criteria group decision-making (MCGDM) framework. We utilize circular Pythagorean fuzzy sets (CPyFS) to better model the vagueness inherent in decision-makers' ([Formula: see text]) judgments, offering enhanced flexibility over traditional fuzzy sets (FS) through their circular membership structure. To determine the weights of criteria objectively, we employ the criteria importance through intercriteria correlation (CRITIC) method, and we integrate these weights within the weighted aggregated sum product assessment (WASPA) method for final ranking. Five alternative strategies are evaluated against five operational criteria. The proposed CRITIC-WASPAS method under the CPyFS approach identifies the second alternative as the most effective, with the highest performance score value among all options, and demonstrates competitive performance in terms of accuracy and consistency within the considered case study. A hypothetical case study demonstrates the applicability of the hybrid model in underground coal mining. Sensitivity analysis confirms the robustness of the rankings against changes in criteria weights and various parametric values. Comparative analysis shows that the proposed hybrid model yields identical rankings to other ranking methods. The study offers a methodological decision-support framework for mine managers, enhancing risk assessment and operational planning in uncertain and complex mining environments.
Heart rate and blood pressure variability differentiate hemorrhagic shock severity in rats.
Punait S, Khodadadi-Mericle F, Lewis GF
Sci Rep · 2026 Jul · PMID 42399649 · Full text
Hemorrhagic shock remains a leading cause of preventable trauma mortality, yet early identification of physiological decompensation remains challenging because conventional vital signs often remain preserved during compe...
Hemorrhagic shock remains a leading cause of preventable trauma mortality, yet early identification of physiological decompensation remains challenging because conventional vital signs often remain preserved during compensatory phases. Heart rate variability (HRV) and blood pressure variability (BPV) derived from continuous arterial waveforms reflect dynamic autonomic and hemodynamic regulation and may provide earlier indicators of cardiovascular instability. We investigated whether variability-based physiological markers could stratify hemorrhagic shock severity and whether vagal integrity influences these autonomic signatures. Male Sprague-Dawley rats underwent graded hemorrhagic shock using a delayed fluid resuscitation paradigm and were classified as moderate or severe shock. Animals were assigned to non-vagotomized and subdiaphragmatic vagotomized groups. Heart rate variability and blood pressure variability metrics, respiratory sinus arrhythmia, and indices of vagal and baroreflex regulation were derived from arterial pressure recordings obtained during steady state and the compensatory phase preceding cardiovascular decompensation. Classification performance was evaluated using discriminant and receiver operating characteristic analyses.Progressive hemorrhage was associated with reduced blood pressure variability and increased heart rate variability during compensation. In non-vagotomized animals, high-frequency diastolic blood pressure variability differentiated shock severity. In vagotomized animals, classification depended on a broader combination of autonomic and hemodynamic features. Vagotomy also altered autonomic variability responses and disrupted relationships between baseline heart rate variability and post-resuscitation vascular variability. These findings support further investigation of variability-based physiological monitoring for early detection of hemorrhagic decompensation.
Ultra-short-term photovoltaic power forecasting based on TCN contrastive encoding and xLSTM.
Zheng W, Lu Z, Peng W … +1 more , Liu B
Sci Rep · 2026 Jul · PMID 42399648 · Full text
The inherent intermittency and non-stationarity of photovoltaic (PV) power challenge high-renewable power systems. Conventional methods struggle with diurnal non-stationarity, and standard long short-term memory (LSTM) n...
The inherent intermittency and non-stationarity of photovoltaic (PV) power challenge high-renewable power systems. Conventional methods struggle with diurnal non-stationarity, and standard long short-term memory (LSTM) networks are limited by scalar hidden states. We propose CL-TCN-xLSTM, an ultra-short-term PV forecasting model that combines contrastive scene encoding with extended LSTM (xLSTM). A trend-relative power ratio decomposition decouples the raw power into a deterministic trend and a stationary relative power ratio, reducing prediction complexity. A temporal convolutional network (TCN) encoder, pre-trained via contrastive learning, extracts scene embeddings from historical weather sequences, which are used to initialize the xLSTM predictor. The xLSTM then employs matrix memory to capture multi-timescale fluctuations, forecasting the relative power ratio that is finally multiplied by the trend to obtain the power. Experiments on two-year data from eight PV plants show that CL-TCN-xLSTM achieves the lowest MAE and RMSE across all forecast horizons from 1 to 4 h. For the 4-h forecast, it also yields the best nMAE and nRMSE. Compared with the best baseline TCR-Reformer, CL-TCN-xLSTM reduces MAE by 25.8% and RMSE by 24.8%. The model exhibits the slowest error accumulation and the strongest cross-site generalization. On a highly volatile day, its forecast curve follows the actual power fluctuations reasonably well without excessive extrapolation. Semantic analysis of the learned scene embeddings reveals that the contrastively pre-trained encoder captures meaningful weather regimes with a linear probe accuracy of 92.7%, even without any labels. Furthermore, the model handles dawn and dusk transitions smoothly, showing no abrupt error spikes. Ablation studies further confirm that the trend-relative power ratio decomposition is the most critical pillar, the xLSTM memory mechanism excels at suppressing large errors, contrastive pre-training provides substantial gains, and the TCN contrastive encoder captures meteorological patterns in its scene embeddings.
Experimental sepsis causes SERCA2 expression in white adipose tissue but not classical browning.
Tidswell R, Alqallaf A, Harris J … +9 more , Falconer J, Golforoush PA, Arulkumaran N, Kleyman A, Brealey D, Rodeheffer MS, Patel K, Duchen MR, Singer M
Sci Rep · 2026 Jul · PMID 42399647 · Full text
Sepsis causes muscle wasting and cachexia but mechanisms remain unclear. Cachexia in cancer and burn injury is partly attributed to 'browning'; where white adipose tissue (WAT) develops a catabolic, thermogenic brown adi...
Sepsis causes muscle wasting and cachexia but mechanisms remain unclear. Cachexia in cancer and burn injury is partly attributed to 'browning'; where white adipose tissue (WAT) develops a catabolic, thermogenic brown adipose tissue-like phenotype. We hypothesised that sepsis-induced muscle wasting is caused by browning. 58 male Wistar rats were randomised to sham (n = 17) or experimental sepsis induced by intraperitoneal zymosan (n = 41). Tibialis anterior mass was measured on Days 3 and 14. Browning was sought using whole body and WAT respirometry, RNA-sequencing, immunoblot, thermal imaging and multi-photon microscopy of WAT. Fourteen-day mortality in rats receiving zymosan was 17%. In survivors, body mass loss peaked at day 3 and persisted to day 14 with associated tibialis anterior muscle mass loss. Zymosan peritonitis caused hypermetabolism during the late recovery phase (Days 11-14), but no difference in epididymal white adipose tissue temperature nor oxygen flux. At Day 14 transcriptomics showed inflammation but no increase in uncoupling protein (UCP)-1 at transcript or protein levels. SERCA2 protein was however increased fourfold in retroperitoneal WAT at day 14 (p = 0.016). Rats recovering from zymosan peritonitis developed muscle wasting and cachexia associated with WAT inflammation and whole-body hypermetabolism. No evidence of browning was seen at functional, transcriptomic or protein levels, therefore our data do not support the hypothesis of classical browning as a driver of sepsis-induced muscle wasting and cachexia. SERCA2 protein expression was however increased in retroperitoneal WAT at day 14.
Effects of environmental evaporation rate on desiccation cracking of a compacted expansive soil subjected to wetting-drying cycles.
Zhou R, Liu XR, Liang NH … +3 more , Han SY, Wang BT, Yu XH
Sci Rep · 2026 Jul · PMID 42399646 · Full text
Expansive soils, rich in hydrophilic clay minerals, respond sensitively to changes in ambient humidity. Repeated wetting-drying (W-D) cycles induce desiccation cracks that markedly degrade their engineering performance....
Expansive soils, rich in hydrophilic clay minerals, respond sensitively to changes in ambient humidity. Repeated wetting-drying (W-D) cycles induce desiccation cracks that markedly degrade their engineering performance. This study systematically elucidates the evolution mechanisms of desiccation cracking in compacted expansive soil through laboratory simulations of repeated W-D environments. Nine different evaporation conditions were established based on varying temperatures (30, 40, 50 °C) and humidities (25%, 55%, 85%), which were quantified by the environmental evaporation rates ([Formula: see text]). Samples under different [Formula: see text] were subjected to seven W-D cycles and crack development was quantified using automated digital image analysis, complemented by Scanning Electron Microscopy (SEM) and Mercury Intrusion Porosimetry (MIP) to capture microstructural evolution and pore-scale changes. The results indicate that the water loss in compacted soil samples follows an exponential decay process. During desiccation, crack width development lags behind crack length extension. Higher [Formula: see text] leads to faster growth in both crack length and width. As water content decreases, the crack length tends to stabilize first, while the width continues to rise. After reaching its peak, the crack width stabilizes or partially decreases depending on [Formula: see text]. The crack ratio, length, and average width display an initial increase during early W-D cycles and subsequently attain a stable state. Higher [Formula: see text] is associated with more pronounced initial growth trends. Additionally, broader water content ranges during W-D cycles aggravate internal structural deterioration, ultimately leading to higher crack lengths and widths. For narrower water content ranges, cracks tend to form from the boundaries, with crack development primarily driven by lengthening. More W-D cycles are required for cracks to reach a stage of stabilized development. SEM and MIP results further reveal that repeated W-D cycles shift pore-size distributions toward larger pores (> 1 μm) and drive the formation of multi-scale pore networks, particularly under higher [Formula: see text] and broader water content variations. This work introduces an innovative approach to elucidate the synergistic influence of environmental factors on desiccation cracks which may hold instructive significance for geotechnical engineering under repeated W-D environments.
DCFNet: dual-domain cross-modal fusion network for RGB-D mirror segmentation.
Li Z
Sci Rep · 2026 Jul · PMID 42399645 · Full text
Mirror segmentation is a fundamental task in computer vision for scene understanding in reflective environments. Existing methods still suffer from insufficient cross-modal fusion between appearance and geometric cues, l...
Mirror segmentation is a fundamental task in computer vision for scene understanding in reflective environments. Existing methods still suffer from insufficient cross-modal fusion between appearance and geometric cues, limited complementary modeling of spatial- and frequency-domain information, and inadequate multi-scale and fine-grained feature representation. To address these issues, this paper proposes DCFNet, a dual-domain cross-modal fusion network for RGB-D mirror segmentation. Specifically, the Spatial-Aware Interaction Module (SAI) is designed to promote adaptive cross-modal interaction between RGB and depth features, thereby enhancing their complementary representation. The Frequency-Guided Spatial Attention Module (FGSA) performs collaborative modeling in the spatial and frequency domains, enabling more effective integration of global structural cues and local detailed information. In addition, the Multi-Path Feature Refinement Module (MPFR) aggregates local details, multi-scale contextual information, and global structural dependencies to further improve feature discrimination. Extensive ablation studies and comparative experiments on a public benchmark dataset demonstrate the effectiveness of the proposed design. Experimental results show that DCFNet achieves highly competitive performance against existing state-of-the-art methods and yields clear improvements on several key evaluation metrics.
Cooperative search algorithm for UAV swarm based on heterogeneous sensor fusion.
Guo J, Li Z, Zhang Z … +3 more , Wang N, Zuo J, Shang Y
Sci Rep · 2026 Jul · PMID 42399644 · Full text
To address the limited robustness of single-sensor detection in complex environments, this paper proposes a cooperative search algorithm for unmanned aerial vehicle (UAV) swarm based on heterogeneous sensor fusion (HS-CS...
To address the limited robustness of single-sensor detection in complex environments, this paper proposes a cooperative search algorithm for unmanned aerial vehicle (UAV) swarm based on heterogeneous sensor fusion (HS-CS). The algorithm leverages the complementary detection capabilities of visible-light and infrared sensors as its core, and establishes a framework tailored to heterogeneous detection characteristics. Initially, the mission area is discretized into a grid, and a four-state map model-comprising undetected, visible-only, infrared-only, and heterogeneous fusion coverage-is constructed. Collaborative update and distributed fusion operators are designed to achieve accurate map updates. Subsequently, dual optimization objectives, total coverage and fusion coverage, are established, and a fast non-dominated sorting approach is employed to derive the Pareto optimal solution set. Finally, a multi-dimensional evaluation index is defined, and a four-stage adaptive evaluation function, integrated with a stochastic exploration mechanism, is developed to determine optimal actions for the UAVs. Simulation results demonstrate that, in a scenario containing 50 targets, 25 of which require fused detection as difficult targets, the proposed algorithm achieves an average fusion coverage rate of 97% and an average difficult target detection rate of 97.1% over 50 independent repeated experiments. These results indicate the potential of the HS-CS algorithm for cooperative search tasks.
Spontaneous formation of highly concentrated phenylacetylcarbinol via in situ phase separation in deep eutectic solvents using Candida magnoliae whole cells.
Htike SL, Techapun C, Phimolsiripol Y … +14 more , Gavahian M, Rachtanapun P, Khemacheewakul J, Phongthai S, Taesuwan S, Thanakkasaranee S, Sommanee S, Porninta K, Mahakuntha C, Feng J, Nunta R, Kumar A, Gao D, Leksawasdi N
Sci Rep · 2026 Jul · PMID 42399643 · Full text
Deep eutectic solvents (DESs) are promising green media for biocatalysis, yet their application in pyruvate decarboxylase (PDC)-mediated phenylacetylcarbinol (PAC) biotransformation with product separation remains limite...
Deep eutectic solvents (DESs) are promising green media for biocatalysis, yet their application in pyruvate decarboxylase (PDC)-mediated phenylacetylcarbinol (PAC) biotransformation with product separation remains limited. This study screened nine DESs using frozen-thawed whole cells (FT-WHC) of Candida magnoliae (C. mag.), followed by evaluation of water content and DES to phosphate buffer ratios. Glycerol-based DES resulted in significantly higher (p ≤ 0.05) volumetric PDC activity and PAC productivity than other DESs. Choline chloride: glycerol (ChCl: Gly (1:2) 20% (v/v) HO) achieved the highest overall [PAC] of 148.2 ± 0.3 mM. Adding 100% (v/v) water decreased stability of volumetric PDC activity, but doubled PAC productivity, and reduced solvent cost compared with a 20% (v/v) HO addition. The DES-to-phosphate buffer (Pi buffer) ratio at 1:1 was optimal, while lower ratios reduced PAC production. Spontaneous formation of PAC-enriched droplets (~ 2.5 M) as a top phase indicated simplified downstream recovery. This indicates DES-based self-separation driven by polarity and product partitioning. Overall, ChCl: Gly (1:2) with 100% (v/v) HO at a 1:1 DES: Pi buffer ratio was selected for future PAC biotransformation. These findings indicate that DESs enhance biocatalytic performance and enable integrated reaction and product separation in a single step, offering a sustainable route to biochemical production.
Application of the Multi Theory Model to improve self reported determinants of appropriate antibiotic prescribing among veterinary students.
Toghroli R, Hassani L, Baniasadi N … +5 more , Jajarmi M, Aghamolaei T, Sharma M, Sharifi H, Eftekhari Z
Sci Rep · 2026 Jul · PMID 42399639 · Full text
The present study was conducted to design, implement, and evaluate an educational program based on the Multi Theory Model (MTM) of health behaviour change to improve self-reported determinants of appropriate antibiotic p...
The present study was conducted to design, implement, and evaluate an educational program based on the Multi Theory Model (MTM) of health behaviour change to improve self-reported determinants of appropriate antibiotic prescribing among veterinary students. This mixed-methods study included qualitative interviews, questionnaire development and psychometric evaluation, a cross-sectional assessment, and a quasi-experimental intervention phase. In the intervention phase, veterinary students in the intervention and control groups completed an MTM-based questionnaire before and three months after the educational program. Descriptive statistics were reported as mean ± standard deviation, and the intervention effect in the two-group pre-post design was evaluated by comparing pre-post change scores between the intervention and control groups, corresponding to the group × time effect. Data analyses were conducted using SPSS version 22. Trial registration: IRCT20210911052432N1. There was a positive and significant relationship between MTM constructs and self-reported prescribing related behavioural outcomes among veterinary students. Significant group × time effects were observed for several MTM constructs, indicating more favourable changes over time in the intervention group than in the control group. The findings indicated that the MTM-based educational intervention improved self-reported determinants of appropriate antibiotic prescribing. These results suggest that MTM-based educational interventions may improve self-reported determinants of appropriate antibiotic prescribing among veterinary students and can inform future antimicrobial stewardship training programs.
A novel Upward-Extended Five-Zone model for overburden failure in deep coal seams with ultra-thick Cretaceous strata.
Yin HY, Xiao Y, Fan XR … +6 more , Xie DL, Wei JC, Niu HG, Zhang WJ, Han CH, Wei YQ
Sci Rep · 2026 Jul · PMID 42399638 · Full text
Preventing roof water hazards in deep coal mining under thick, weakly cemented overburden is challenging, particularly in Western China where traditional theories often fail to predict high-level water inrush caused by t...
Preventing roof water hazards in deep coal mining under thick, weakly cemented overburden is challenging, particularly in Western China where traditional theories often fail to predict high-level water inrush caused by the independent secondary fracture of massive upper strata. Using the Yingpanhao Coalfield as a case study, this research investigates overburden failure laws through a comprehensive approach involving field monitoring (including distributed optical fiber sensing), PFC numerical simulations, and theoretical analysis. The study identifies a distinct "Coal Measures-Cretaceous double-layer structure." Results show significant behavioral differences between these strata, causing a unique "secondary movement" phenomenon. Consequently, this paper proposes a new "Upward-Extended Five-Zone" model, modifying the traditional "Three-Zone" theory. The model delineates the caving zone, low-position fracture and bending zones (within Coal Measures), and high-position fracture and bending zones (within Cretaceous strata). These findings offer theoretical support for water hazard prevention in similar geological conditions.
An epitope-based peptide vaccine targeting influenza a elicits robust immune responses and induces protection in a mouse model.
Alosaimi B, Al-Rawi HZ, Alahmadi RM … +4 more , Al-Shouli ST, Alzahrani J, Alsubki R, Awadalla ME
Sci Rep · 2026 Jul · PMID 42399636 · Full text
Influenza A viruses remain a major global public health threat due to their high mutation rates, antigenic drift, and periodic antigenic shift, which collectively undermine the effectiveness of seasonal vaccines. Convent...
Influenza A viruses remain a major global public health threat due to their high mutation rates, antigenic drift, and periodic antigenic shift, which collectively undermine the effectiveness of seasonal vaccines. Conventional influenza vaccines necessitate frequent reformulation and often result in suboptimal protection. Epitope-based vaccine strategies that focus immune responses toward conserved viral regions represent a promising approach for inducing broader and durable immunity. In this study, reverse vaccinology and immunoinformatics-guided approaches were used to design multi-epitope vaccine constructs derived from conserved regions of Influenza A H3N2 and H1N1 proteins, including hemagglutinin (HA), neuraminidase (NA), nucleoprotein (NP), and matrix proteins (M1 and M2). BALB/c mice were immunized intramuscularly and evaluated for humoral and cellular immune responses. Serum IgG levels were measured by ELISA, while functional antibodies were assessed using hemagglutination inhibition (HAI) assays. Cellular immune responses were evaluated using ELISPOT assays for IFN-γ and TNF-α secretion. Protective efficacy was assessed through homologous viral challenge with H3N2 or H1N1 strains, followed by survival analysis and lung histopathological examination. Immunization with H3N2- and H1N1-derived epitopes elicited robust specific IgG responses and induced functional HAI antibodies. Notably, H3N2-derived epitopes generated higher HAI titers, consistent with enhanced humoral immunogenicity. Vaccinated mice demonstrated strong cellular immune responses, characterized by significantly elevated IFN-γ-producing CD8⁺ T cells compared with mock-immunized controls. Upon viral challenge, all vaccinated mice exhibited 100% survival against H3N2 or H1N1 infection, whereas mock-immunized mice experienced 100% mortality. Histopathological analysis revealed protective immunopathological profiles and preserved alveolar architecture. The protective efficacy of the multi-epitope vaccination was comparable to that of the seasonal quadrivalent influenza vaccine. This study demonstrates that multi-epitope vaccines derived from conserved Influenza A proteins can induce coordinated humoral and cellular immune responses and confer robust protection against H3N2 and H1N1 viral challenge in a mouse model. This suggests support for peptide-based vaccination as an alternative method to conventional strain-matched vaccines, which reduce vaccine effectiveness or universal influenza vaccine development.
Using ensemble learning and Gaussian mixture model to predict petrophysical properties and hydraulic flow units in carbonate reservoirs.
Khazaei Panah M, Khosravi R, Simjoo M … +1 more , Chahardowli M
Sci Rep · 2026 Jul · PMID 42399635 · Full text
Accurate prediction of porosity and permeability in complex carbonate reservoirs is very important for understanding reservoirs, but remains challenging due to inherent heterogeneity. This study develops a robust, machin...
Accurate prediction of porosity and permeability in complex carbonate reservoirs is very important for understanding reservoirs, but remains challenging due to inherent heterogeneity. This study develops a robust, machine learning-driven workflow to enhance the prediction of these critical petrophysical properties and the identification of Hydraulic Flow Units. The methodology integrates conventional core data and geophysical well logs, employing advanced data preprocessing, including depth matching, which significantly improved the log-core porosity correlation. A key innovation involves using a Gaussian Mixture Model for unsupervised Hydraulic Flow Unit identification, which outperformed traditional empirical methods and K-Means clustering by yielding five distinct Hydraulic Flow Units with high intra-unit porosity-permeability correlations (R up to 0.93) validated by Mercury Injection Capillary Pressure data. For predictive modeling, a comprehensive comparison of algorithms revealed that a Voting ensemble meta-algorithm with a Multi-Layer Perceptron base learner delivered superior performance for both porosity (on integrated data from three wells) and permeability (modeled per Hydraulic Flow Unit). The final models successfully estimated properties in non-cored intervals and a blind well, demonstrating high accuracy and generalizability. This integrated approach provides a reliable and theory-grounded framework for characterizing heterogeneous carbonate reservoirs, reducing dependency on extensive coring operations.
Age-related differences in processing unconventional text formats.
Alonso-Bernal N, González Alonso J, Gómez P … +1 more , Duñabeitia JA
Sci Rep · 2026 Jul · PMID 42399634 · Full text
Typographic formats influence reading efficiency; however, knowledge remains limited regarding how these effects change across the lifespan, especially for orthographic distortions in digital environments. This study exa...
Typographic formats influence reading efficiency; however, knowledge remains limited regarding how these effects change across the lifespan, especially for orthographic distortions in digital environments. This study examines how conventional formats (lowercase and uppercase) and unconventional formats (mixed-case and LEET) affect reading times and the integration of meaning while reading five-word phrases. Three hundred and three adults (18-84 years) read short sentences (five words) presented in the four formats, while reading times and memory accuracy were recorded. The results showed a graded cost pattern: conventional formats yielded the fastest reading times, mixed-case imposed moderate costs, and LEET produced the greatest slowdown and a slight reduction in accuracy. Moreover, a significant interaction between format and age was observed: although reading slowed with age in all formats, this effect was especially pronounced for LEET. These findings suggest that extreme orthographic distortions increase perceptual and pre-lexical demands, revealing limits in reading adaptation associated with aging.
Biochemical and growth responses of mungbean to actinobacterial inoculation under water stress.
Patel MM, Singh NK, Parmar RB … +2 more , Joshi BM, Yadav A
Sci Rep · 2026 Jul · PMID 42399620 · Full text
Drought severely limits mungbean growth by disrupting osmotic balance, photosynthetic function, and oxidative homeostasis. This study evaluated five actinobacterial inoculants in mungbean seedlings under water deficit to...
Drought severely limits mungbean growth by disrupting osmotic balance, photosynthetic function, and oxidative homeostasis. This study evaluated five actinobacterial inoculants in mungbean seedlings under water deficit to clarify how microbial treatments influence biomass, proline, chlorophyll, and malondialdehyde. The results showed a clear treatment-dependent physiological divergence. Among the tested isolates, Streptomyces clavuligerus PQ120343 and Streptomyces clavuligerus PQ120390 consistently produced the highest seedling dry weight together with increased proline accumulation, greater chlorophyll retention, and lower malondialdehyde relative to the uninoculated drought control. Integrative analysis indicated that biomass maintenance under drought was most strongly associated with chlorophyll retention and, within drought-exposed treatments, was further supported by higher proline and lower malondialdehyde. These findings show that effective actinobacterial drought mitigation in mungbean is not merely the reduction of stress symptoms, but a coordinated acclimation response involving osmotic adjustment, preservation of the photosynthetic apparatus, and attenuation of oxidative membrane damage. The study thus refines earlier observations by identifying chlorophyll retention as the strongest physiological link to drought-maintained biomass, while confirming S. clavuligerus PQ120343 and PQ120390 as the most promising candidates for development as drought-mitigating bioinoculants in mungbean.
Karst groundwater cycle model, hydrochemical characteristics and tectonic controls of the Shuimocao karst spring basin in the Northern Taihang Mountains, China.
Liu Y, Wen D, Zhou L … +5 more , Li W, Lv L, Zheng Y, Li S, Shi Z
Sci Rep · 2026 Jul · PMID 42399619 · Full text
To clarify the recharge sources, water cycle evolution mechanisms, and water-rock interaction patterns of typical karst spring basins in the northern Taihang Mountains, this study investigated the Shuimocao karst spring...
To clarify the recharge sources, water cycle evolution mechanisms, and water-rock interaction patterns of typical karst spring basins in the northern Taihang Mountains, this study investigated the Shuimocao karst spring group through a 1:50,000 hydrogeological survey and continuous dynamic monitoring of spring and river discharge. A total of 38 hydrochemical samples and 26 hydrogen and oxygen isotope samples were collected and tested. Integrating high-density resistivity profiling, hydrochemical identification, isotope tracing, and hydrological dynamic analysis, this study systematically explored the basin tectonic evolution, karst development features, hydrochemical signatures, and groundwater water cycle mechanisms, while elucidating the driving factors responsible for spring drying up. The results indicate that Meso-Cenozoic tectonic movements established the fundamental tectonic framework of the study basin. Highly soluble limestone of the Ordovician Majiagou Formation provides essential material conditions for karst development, whereas concealed faults and epikarst zones constitute dominant migration pathways for surface water and groundwater. Major hydrochemical ions are primarily derived from carbonate and silicate rock weathering, accompanied by staged cation exchange, while anthropogenic activities significantly disturb water quality in the spring discharge zone. Quantitative end-member mixing analysis (EMMA) identifies three groundwater recharge pathways: leakage from the Tongtian River (51.93%) serves as the primary recharge source, followed by Sanhui River leakage (28.79%) and lateral groundwater runoff from the Yebei area (19.29%). Precipitation only acts as an indirect, time-lagged driving factor rather than a direct water source. Overall, the spring system is predominantly recharged by river infiltration and secondarily by lateral groundwater inflow, forming a tectonically controlled water cycle pattern: "surface water infiltration - karst conduit migration - flow regulation by faults and aquicludes - concentrated spring discharge". The extreme spring drying event in 2020 resulted from the superposition of extreme drought and persistent groundwater overexploitation, and groundwater flow field alteration induced by water level decline was the direct cause of well water turbidity. This study reveals the surface water-groundwater coupling mechanism of typical northern karst basins, providing a representative case and scientific reference for karst groundwater exploitation, spring ecological conservation, and analogous hydrogeological studies in the Taihang Mountains.
Scalogram-CNN fusion with interactive 3D parameter exploration for inter-patient ECG classification.
Süzme NÖ, Gerek ÖN
Sci Rep · 2026 Jul · PMID 42399614 · Full text
Electrocardiogram (ECG) signals are vital for detecting cardiac anomalies but pose challenges due to their non-stationary nature. This study aims to investigate ECG classification under unseen-patient conditions by conve...
Electrocardiogram (ECG) signals are vital for detecting cardiac anomalies but pose challenges due to their non-stationary nature. This study aims to investigate ECG classification under unseen-patient conditions by converting ECG signals into 2D scalogram images. We developed an interactive 3D visualisation framework using Plotly Dash to evaluate classification performance across multiple wavelet types, feature extraction levels, and scale ranges. Scalogram images were classified using a Convolutional Neural Network (CNN). Additionally, we evaluated handcrafted statistical and wavelet-derived features on test data drawn from unseen patients to support inter-patient generalisation analysis. Wavelet choice and feature extraction strategy significantly affected accuracy. Notably, up to 89.78% accuracy was achieved across two test experiments (Complex Morlet, Experiment II), with Mexican Hat wavelets reaching 83.04% in Experiment I, with independently sampled test beats in each experiment, demonstrating relatively consistent performance across the evaluated unseen-patient test settings within the constraints of the available database. The interactive 3D dashboard not only streamlined parameter selection but also improved result exploration and facilitated parameter analysis. The proposed framework may support more efficient parameter exploration in ECG analysis workflows, with potential utility in telemedicine and remote monitoring contexts. It provides an interactive framework for small-data ECG analysis.
Phenotypic age acceleration and genetic risk synergistically increase age-related eye disease risk in the UK Biobank.
Yuan H, Hu Y
Sci Rep · 2026 Jul · PMID 42399507 · Full text
To evaluate the independent and synergistic effects of phenotypic age acceleration (PhenoAgeAccel) and genetic risk on age-related eye diseases (AREDs). We analyzed 395,322 participants from the UK Biobank to assess the...
To evaluate the independent and synergistic effects of phenotypic age acceleration (PhenoAgeAccel) and genetic risk on age-related eye diseases (AREDs). We analyzed 395,322 participants from the UK Biobank to assess the association between PhenoAgeAccel and polygenic risk scores for age-related macular degeneration (AMD) and age-related cataract (ARC). Cox proportional hazards models evaluated independent effects and potential synergistic interactions, adjusting for demographic, socioeconomic, and lifestyle factors. PhenoAgeAccel was independently associated with increased risk of AMD (HR = 1.15, 95% CI 1.10-1.21) and ARC (HR = 1.14, 95% CI 1.12-1.17). High genetic risk conferred stronger effects for AMD (HR = 1.88, 95% CI 1.78-1.98) and ARC (HR = 1.31, 95% CI 1.27-1.35). Participants with both elevated PhenoAgeAccel and high genetic risk had markedly higher risk (AMD: HR = 2.19; ARC: HR = 1.47) compared with biologically younger, low-risk individuals. A significant multiplicative interaction was observed for AMD, indicating a synergistic effect between accelerated phenotypic aging and genetic susceptibility. PhenoAgeAccel and genetic risk each contribute to the development of AREDs, and their combination exerts a synergistic effect. Integrating aging biomarkers with genetic profiling could enhance risk stratification and inform targeted prevention strategies for ocular health.
A large language model pipeline for automated citation quality scoring across engineering journal quartiles with expert validation.
Isik M, Guleryuzlu S
Sci Rep · 2026 Jul · PMID 42399491 · Full text
This study proposes and evaluates a two-stage large language model (LLM)-based pipeline for automated citation quality scoring in academic manuscripts. The pipeline operates as follows: in Stage 1, citation sentences are...
This study proposes and evaluates a two-stage large language model (LLM)-based pipeline for automated citation quality scoring in academic manuscripts. The pipeline operates as follows: in Stage 1, citation sentences are extracted from full-text PDFs and matched to their referenced articles using the Gemini 2.5 Flash model; in Stage 2, each citation-reference pair is scored for semantic relevance on a continuous 0-10 scale by a second LLM inference call operating under a structured five-tier rubric and a skeptical reviewer prompt persona. The pipeline was applied to a corpus of 121 Web of Science (WOS)-indexed engineering articles drawn from journals spanning all four Journal Citation Reports quartile strata (Q1-Q4), yielding 5,615 scored citation-reference pairs. Descriptive analysis revealed an overall mean relevance score of 7.76 (SD = 2.36), with 74.7% of citations rated as Strong or Excellent. A Kruskal-Wallis test confirmed statistically significant score differences across quartile groups (H(3) = 157.10, p < 0.001), though the overall effect size was small (ε² = 0.028). Post-hoc Mann-Whitney U tests with Bonferroni correction identified Q2 articles as recording the highest mean scores (M = 8.04), significantly outperforming Q1 (M = 7.52), Q3 (M = 7.73), and Q4 (M = 7.74). The Q3 versus Q4 comparison was the sole non-significant pairing (p = 0.756), indicating these strata are statistically indistinguishable in citation quality. Spearman correlation yielded a weak negative rank correlation (ρ = -0.105, p < 0.001), with Q1 recording the highest proportion of Irrelevant citations (10.7%). These findings challenge the assumption that citation quality improves monotonically with journal prestige. The lower mean score of Q1 coexists with one of the highest proportions of highly relevant citations, indicating a bimodal rather than uniformly weaker profile, and a systematic annotation showed that context-dependent pointer citations are disproportionately concentrated in the Q1 Irrelevant set. We therefore attribute Q1's pattern to the broader interdisciplinary scope of top-tier articles together with a measurement effect, rather than to any single cause such as AI-assisted writing. The proposed pipeline offers a scalable, content-aware complement to existing academic integrity tools, with practical applications in editorial pre-screening and automated peer review support. An inter-rater reliability study on a stratified subsample of 150 citation-reference pairs showed strong ordinal agreement between the LLM and expert majority vote (Spearman ρ = 0.643, p < 0.001), with exact-category agreement of 48.0% rising to 77.3% under ± 1 adjacent-category tolerance, and highest agreement at the Irrelevant (80.0%) and Excellent (71.0%) poles.
Failure mechanism and energy evolution of deep hard rock subjected to true triaxial unloading under different initial stress differences.
Lei B, Xie P, Qin G … +5 more , Lang D, Zhang G, Li J, Han J, Xiong P
Sci Rep · 2026 Jul · PMID 42399483 · Full text
Research on the deformation and failure mechanism of deep hard rock is of great significance for the prevention and control of rockburst in high-stress underground engineering. In this study, true triaxial single-face un...
Research on the deformation and failure mechanism of deep hard rock is of great significance for the prevention and control of rockburst in high-stress underground engineering. In this study, true triaxial single-face unloading rockburst tests were conducted on Jinchang diorite under different initial stress differences. The effect of initial stress difference on strength response, failure behavior, and energy evolution mechanism of diorite was investigated using scanning electron microscopy (SEM) and acoustic emission (AE) monitoring, and the fractal dimension of rockburst fragments and rockburst proneness were quantitatively discussed. The results demonstrated that the peak strength increases significantly with increasing initial stress difference, and the macroscopic failure pattern evolves from randomly distributed tensile-shear coupled cracking to localized tensile slabbing along the unloading free surface. The fracture surface morphology changes from rough surfaces with irregular step-like tearing features to smooth cleavage planes with river-like patterns, and AE activity changes from gradual cluster-type signals to sudden main-shock-type release. In addition, a true triaxial discrete element numerical model based on PFC3D was established and calibrated to investigate the microcrack evolution and orientation under different initial stress differences, and the numerical results were in good agreement with the experimental observations.
Whole-genome sequencing of samples from a Streptococcus parasuis infection.
Wu X, Mao H, Jin D … +1 more , Yang J
Sci Rep · 2026 Jul · PMID 42399475 · Full text
Streptococcus parasuis (S. parasuis) is a close relative of Streptococcus suis (S. suis), and they cause similar clinical symptoms. This retrospective study aimed to identify clinical phenotypic and genetic characteristi...
Streptococcus parasuis (S. parasuis) is a close relative of Streptococcus suis (S. suis), and they cause similar clinical symptoms. This retrospective study aimed to identify clinical phenotypic and genetic characteristics of a S. parasuis (namely isolate S1) isolated twice in succession from pleural effusion of an elderly patient with atypical manifestations and to further conduct a systematic literature overview for prevention and control of human S. parasuis infection. The isolate S1 was initially identified as Enterococcus raffinosus (95.5% confidence) by VITEK2COMPACT, and subsequently confirmed as S. suis by MALDI-TOF-MS (99.9% confidence). Average nucleotide identity value of isolate S1 (CP137602) showed a sequence similarity of 97.9% to S. parasuis (GCF_004283785), and 16 S rRNA gene sequence confirmed a similarity of 99.86% to S. parasuis (GenBank: No. 069079). The isolate S1 harboring 1,700 COG-annotated genes contained 1,538 predicted functional genes in six different classifications. Except for a potential virulence-associated gene responsible for production of hyaluronic acid capsule, no antimicrobial resistance gene was disclosed. The isolate S1 harboring toxin gene hasC owned an anti-phagocytosis potential, and it was susceptible to antimicrobials tested (9/10), with only intermediate susceptible to Clindamycin. Till December 2024, only 3 articles covering 4 cases of human S. parasuis infection have been reported. This is the first S. parasuis isolate from pleural effusion in a patient with atypical manifestations. Literature overview and our subsequent successful identification of its clinical phenotypic and genetic characteristics have greatly raised the awareness of potential opportunistic Zoonotic S. parasuis infection in humans, which may serve as a reference for medical professionals.
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