Search Results (2,866)

The induced polarisation (IP) technique is a geophysical method used to measure chargeability and resistivity, providing crucial insights into subsurface geological structures. Traditionally, IP measurements have been instrumental in exploring disseminated sulphide deposits, leveraging the strong polarisation response of metallic particles. It provides valuable insights about rock mineralisation, matrix composition, and formation polarizability by analysing electrical parameters. However, their potential to predict metallurgical performance remains largely unexplored. This study evaluates whether IP parameters—chargeability and resistivity—can serve as geometallurgical indicators for copper sulphide ores. The evaluation integrates IP measurements with mineralogical and flotation data. Artificial pyrite–sand mixtures and five real ore samples from Mount Isa were analysed using the sample core IP tester and mineral liberation analysis, followed by collectorless flotation tests. Statistical analysis demonstrated a strong correlation between resistivity and chalcopyrite recovery (R² = 0.90, p = 0.99), as well as a moderate correlation between chargeability and chalcopyrite selectivity (R² = 0.72, p = 0.93). These findings demonstrate that IP captures key textural and electrochemical features governing flotation behaviour, including pyrite abundance, mineral liberation, and galvanic interactions. The results highlight IP as a promising rapid-assessment tool for identifying ore variability and forecasting flotation response, with potential integration into geometallurgical models and mine-to-mill optimisation. Further validation across broader ore domains is recommended to refine the predictive capability of IP-based indicators. Full article

Representations of industrial life have long been understood to be essential to the Soviet project, and this article analyzes the distinctive, but overlooked, functions of narratives and images of women workers at the factory workbench in the 1920s, and their ramifications for understanding Soviet paradigms of gender. Examining the place of mechanized labor in Aleksandra Kollontai’s theory of women’s emancipation in conjunction with the programs of labor theorist Aleksei Gastev demonstrates the establishment of mechanized labor and its tools as essential to utopian representations of Soviet social and gender relations beyond the factory. In this light, the article traces the establishment of the stanok, or factory workbench, as a metonym for new collective labor, and an interface with other nascent Soviet institutions and the new byt, or everyday life, in the mass illustrated periodical for urban women, Rabotnitsa (The Woman Worker), in the 1920s. Full article

Faults in aero-engine rotating components account for more than 60% of total failures, and their early features are easily masked by noise under complex conditions. Traditional single-sensor diagnosis suffers from low feature utilization, poor interpretability, and weak cross-condition generalization. This paper proposes a multi-source fault diagnosis method for aero-engines based on an explainable boosted tree, integrating spatiotemporal attention (STA) and adaptive feature selection (AFS). We collect multi-domain data from four standard core sensors widely used in existing engine health management systems and extract multi-dimensional features to build a heterogeneous feature set. Adaptive feature selection is implemented using mutual information and a variance inflation factor. A spatiotemporal attention mechanism is introduced to weight and fuse features effectively. The fused features are used to train an XGBoost classifier, and SHAP values are adopted to quantify feature contributions and improve model interpretability. Uncertainty sources and sensitivity boundaries are quantitatively analyzed to support engineering acceptance. The method achieves high sensitivity to early weak faults and stable uncertainty under complex operating conditions. Tests on a fault simulation test rig show that the proposed method achieves 99.2% diagnosis accuracy and 97.5% cross-condition generalization accuracy, outperforming conventional models. It can identify early weak fault signatures, clarify key fault indicators, and provide a quantitative basis for fault tracing and maintenance decision-making. The method employs a standard sensor suite without additional hardware costs, features lightweight computation and low inference overhead, and delivers clear economic benefits by reducing false alarms, avoiding unplanned downtime, and optimizing maintenance resources. It offers a reliable, cost-effective solution for aero-engine fault diagnosis under complex operating conditions. Full article

Two-photon microscopy enables in vivo imaging of astrocytic Ca²⁺ activity, yet detecting weak, transient, and background-coupled signals remains challenging due to low signal-to-noise ratios and heterogeneous noise. Here, we propose a low-parameter, adaptive framework for detecting weak astrocytic Ca²⁺ signals in two-photon imaging. After short-window frame accumulation, static background suppression, and Gaussian smoothing to stabilize intensity statistics, signal candidates are identified via segment-wise Gaussian mixture modeling, temporal persistence masking, and adaptive threshold updates. In simulated videos, the proposed method improved the Dice coefficient from 0.06 to 0.77 and increased the reference SNR from −9.82 to 3.40 dB. In in vivo recordings, the local SNR increased from 5.58 to 7.28 dB. Compared with fixed thresholding, AQuA, and AQuA2, our method was more robust under high-noise conditions while requiring only three user-defined parameters (minimum area, minimum duration, and an initialization coefficient). This framework provides an interpretable and computationally practical front-end module for the robust extraction of astrocytic Ca²⁺ signal in low-SNR two-photon imaging. Full article

The Socialist Yugoslav Second World War memorials, works of large-scale memorial sculpture scattered across former Yugoslavia’s successor states, have gained international artistic recognition yet deteriorated significantly since the 1990s dissolution of the country. This deterioration has been particularly severe in Bosnia and Herzegovina, where ethnic and political divisions have complicated their commemorative value. This study employs the concept of “dissonant landscape” to reframe these memorials as integral components of a larger Yugoslav modernist cultural landscape rather than isolated problematic structures. By situating memorials within broader contexts of everyday heritage and collective memory, the framework enables complex interpretations that transcend simplistic ideological readings. The memorials, as dissonant heritage, are invested with multiple meanings by different ethnic–religious groups, and may function as catalysts for cultural dialogue and reconciliation. Methodologically, this study relies on conceptual analysis in the realm of critical heritage studies, combined with a case study of the Monument to the Fallen Fighters of the National Liberation War from Drvar, a relatively understudied memorial recently prioritized by local conservation efforts, and it includes analysis of previously unpublished archival material, field observation, interviews with local authorities and survey with the citizens of Drvar. This study establishes a new perspective on the heritage potential of Yugoslav memorials that may serve as bases of innovative preservation policies, grounded in reconciliation and cultural tourism. Full article

The flotation performance of a low-grade, polymetallic copper ore, dominated by chalcocite and transitional copper phases, was investigated to assess the interplay between collector chemistry, gangue mineralogy, and entrainment. QEMSCAN analysis identified chalcocite as the main copper host (62%), with minor covellite and bornite, and gangue, predominantly quartz (94%), with variable muscovite (up to 50%). Chalcocite was moderately liberated (100–200 µm), while secondary copper phases showed low exposure and strong gangue association, challenging selective recovery. Baseline flotation with potassium amyl xanthate (PAX) and sodium isobutyl xanthate (SIBX) across pH and dosage ranges showed that PAX yielded higher copper recovery but lower grade, indicating unselective gangue entrainment; SIBX offered lower recovery but higher grade, reflecting superior selectivity. Controlled muscovite doping experiments (10–50 wt.%) were employed to decouple gangue-driven selectivity loss from collector-specific interactions. Results indicate a collector-dependent sensitivity to gangue loading: PAX exhibited a pronounced decline in both copper recovery (82%–67%) and grade under increasing muscovite content, with water recovery rising by approximately 32%, whereas SIBX showed more gradual performance degradation and lower entrainment (15% increase in water recovery), highlighting its resilience in gangue-rich systems. UV-Vis and zeta potential (electrokinetic) measurements confirmed stronger PAX adsorption, consistent with its longer hydrocarbon chain, while flotation trends demonstrated a shift from true flotation-dominated recovery to entrainment-dominated regimes at high muscovite levels, particularly for PAX. This framework links mineralogy, collector chemistry, and gangue entrainment, guiding optimization of circuits for ores like Mt. Gunson while enhancing critical metal recovery, including cobalt. Full article

The global energy transition has fundamentally reshaped the conditions under which green trade generates sustainable productivity gains. This study investigates whether renewable energy adoption mediates the relationship between green trade export (GTE) and green total factor productivity (GTFP) across 37 OECD economies over 2003–2023. Employing two-way fixed-effects panel regression, dynamic System-GMM estimation, and Hansen’s panel threshold regression with 500 bootstrap iterations, we identify a nonlinear, inverted-N-shaped relationship between GTE and GTFP. Sequential threshold testing reveals a statistically significant double threshold structure: a first clean energy threshold at approximately 8.72% of total final energy consumption and a second threshold at approximately 24.63%, yielding three distinct productivity regimes. Below the first threshold, green trade suppresses GTFP through pollution displacement and insufficient absorptive capacity; between thresholds, green trade exerts a significant positive productivity effect driven by clean technology diffusion and innovation spillovers; above the second threshold, the positive effect moderates, consistent with diminishing returns to green technology absorption. Heterogeneity analysis reveals that early-stage energy transitioners bear disproportionately larger productivity penalties, while advanced transitioners capture stronger above-threshold gains. These findings underscore that trade liberalization alone is insufficient—sustainable productivity growth requires concurrent and targeted investment in renewable energy infrastructure under the post-Paris Agreement framework. Policy implications are presented as evidence-consistent hypotheses, acknowledging that the observational panel framework precludes definitive causal claims pending corroboration from quasi-experimental designs. Full article

Background: Adiponectin (ADPN) is a key adipokine with osteogenic potential, but its clinical translation for bone regeneration is hindered by poor in vivo stability. This study aimed to develop poly lactic-co-glycolic acid (PLGA) microparticles as a stable and biocompatible carrier for sustained ADPN delivery to enhance bone repair. Methods: ADPN-loaded PLGA microparticles (ADPN-MPs) were fabricated via emulsion solvent evaporation. Their physicochemical properties were characterized using scanning electron microscopy (SEM) and circular dichroism (CD) spectroscopy. Loading efficiency and drug loading were quantified. In vitro release kinetics and stability under physiological conditions were assessed. Biocompatibility was evaluated using MC3T3-E1 osteoblasts and BMSCs, and in vivo efficacy was tested in a fracture model via gait analysis. Results: Employing CD to evaluate the secondary structure of ADPN, emulsion solvent evaporation for microparticles preparation, and SEM for morphological analysis, we quantitatively assessed the loading efficiency (69.83 ± 4.24%) and drug loading (0.97 ± 0.06%) of ADPN-MPs. Results indicated that ADPN-MPs maintained significant stability under varied pH and temperature conditions and exhibited a controlled release profile, with an average initial rapid release of 14.25% within 24 h and an average cumulative release of 55.00% by day 28. Furthermore, ADPN-MPs promoted the proliferation of MC3T3-E1 and BMSCs without toxicity, demonstrating excellent biocompatibility. Notably, gait analysis in a fracture model showed improved healing in both ADPN and ADPN-MPs groups compared to controls, with ADPN-MPs demonstrating comparable efficacy to free ADPN, supporting its potential as a stable delivery system for bone regeneration. Conclusions: PLGA microparticles serve as an effective, stable, and biocompatible delivery platform for ADPN, significantly promoting bone regeneration in vitro and in vivo. This delivery system enhances the therapeutic potential of ADPN for clinical bone repair applications. Full article

Relation Extraction is crucial for knowledge graph construction, but extracting complex relations in specialized domains like Satellite Navigation Countermeasures (SNCM) remains challenging due to long semantic spans and high relational density. While Large Language Models (LLMs) possess strong semantic understanding, they often suffer from severe recall deficiency and hallucinations in high-density multi-entity contexts. Conversely, traditional small models generate excessive redundant noise. To address these limitations, this paper proposes an evaluation-model-guided relation extraction method (E-guidedRE). This framework employs a two-stage collaborative mechanism. First, a lightweight evaluation model utilizing a GlobalPointer network with Rotary Position Embedding (RoPE) and a sparse multi-label loss function acts as a structural filter to generate high-coverage candidate entity pairs. Second, these candidates guide the frozen LLM to perform deep semantic discrimination and retrospective denoising. Furthermore, we construct a dedicated SNCM dataset to fill the vertical domain data void. Extensive experiments across five heterogeneous datasets, including general, biomedical, financial, and our self-built SNCM corpus, demonstrate that E-guidedRE exhibits remarkable robustness. In ablation studies on the SNCM dataset, our method improved the F1-score from 36.54% to 54.93% compared to standalone LLM extraction, boosting recall from 27.81% to 47.13%. The proposed paradigm effectively mitigates the LLM’s attention divergence in complex contexts, dynamically balancing precision and recall, and offers a highly reliable technical pathway for knowledge extraction in specialized vertical domains. Full article

With a focus on how both traditions influence identity, memory, and lived spirituality in African contexts, this article examines the theological and cultural interactions between Christianity and African Traditional Religion (ATR). This study highlights the ongoing interaction between ATR and Christianity as two significant systems ingrained in African life, notwithstanding the continent’s religious diversity. In Africa, religion and culture are inextricably linked, influencing social customs, moral standards, and a sense of community but also constantly changing due to personal experience. African spiritual systems were frequently disregarded by missionary Christianity in the past, which led to conflicts that still exist in modern African Christianity. The importance of ancestors, rituals, and supernatural beliefs all of which are still fundamental to the worldviews of many African Christians are areas where these conflicts are especially noticeable. This article makes the case for a positive theological approach that acknowledges ATR as an essential tool for African Christian identity rather than as a rival or subpar system, drawing on the idea of inculturation. The article illustrates how African spirituality serves as a storehouse of collective memory and identity over generations by delving into issues of ancestry, ritual, and spiritual mediation. Additionally, it offers a liberative and dialogical theological concept that promotes understanding between Christianity and ATR. Such an approach not only bridges spiritual divides but also contributes to the development of a contextually grounded liberation theology that affirms indigenous knowledge systems while remaining open to global theological discourse. Full article

Explosive ordnance (EO), including AXO (abandoned explosive ordnance), IEDs (improvised explosives devices), and UXO (unexploded ordnance), are widely recognised for their blast and fragmentation hazards, but they also represent a persistent and under-addressed source of occupational chemical exposure for explosive ordnance disposal (EOD) personnel. EOD core activities liberate mixed metals and energetic chemicals, resulting in exposures that are multi-route (inhalation of dusts and fumes, dermal loading amplified by sweat and glove occlusion, and ingestion via hand-to-mouth transfer during eating, drinking, or smoking) and multi-temporal (repeated low-dose background plus task-driven spikes), as well as chemically complex. Clinically, this can present as syndromic overlap across acute and chronic domains, with symptoms that are easily misattributed to heat stress, dehydration, infection, or fatigue. Acute effects of concern include neurotoxic presentations (headache, dizziness, confusion, tremor, and seizure), respiratory and mucosal irritation following dust or fume events, gastrointestinal symptoms, and patterns suggestive of acute hepatic or renal stress, particularly when high-intensity tasks occur in hot environments that compound physiologic strain. Chronic outcomes relevant to repeatedly exposed EOD personnel include renal function decline, neurocognitive effects that can degrade operational decision making and safety, persistent haematologic abnormalities, and endocrine disruption signals, with long-latency risks requiring cautious interpretation given sparse longitudinal data and confounding co-exposures. This review synthesises the current evidence base through an EOD lens and translates it into pragmatic clinical and programmatic actions: task-based exposure characterisation; tiered biomonitoring and medical surveillance aligned to operational tempo; incident-triggered assessment pathways after high-residue events; and prevention strategies that work under field constraints, including contamination control zones, hygiene enforcement, glove and respiratory protection optimisation, tool and vehicle decontamination, and measures to prevent secondary transfer and take-home exposure. The central takeaway is practical: EOD programs can reduce morbidity and improve readiness by treating explosive ordnance as a chemical mixture exposure problem, adopting mixture-aware clinical triage, and embedding surveillance and controls that match how EOD work is actually performed. Full article

Snow water equivalent (SWE), the amount of water that will be liberated when a given snowpack melts, is considered an essential climate variable. Snowmelt drives annual run-off in snow-dominant basins. However, detecting daily SWE changes in lake-effect snowfall regions such as the Great Lakes Basin (GLB) is challenging with classical methods. We developed a Siamese U-Net (Si-UNet) model to detect and characterize daily changes and trends in SWE. Our Si-UNet detected daily changes in SWE over the GLB with an F1-score of 98.73%. To characterize the basin-wide extent of anomalies in SWE distribution, we compared SWE trends to a 35-year median (35YB) baseline and identified decadal trends in SWE. We found that the period from 1989 to 2008 was the temporal window with minimal anomalies, compared to the 35YB of ~0.5108. Positive deviations from the 35YB were prevalent over these 20 years, indicating less significant daily changes. A significant shift to daily SWE similarity below the 35YB occurred after 2009, especially in January and February. Daily changes in SWE were high in April, beginning in the second week. The strongest positive trend, likely associated with lake-effect snowfall, was observed in April 2000 (R² = 0.47). Full article

Background/Objectives: Despite high recanalization rates associated with mechanical thrombectomy (MT), disability and death remain possible for many patients. Baseline stroke severity and reperfusion status predict outcomes; however, the influence of modifiable perioperative factors during general anesthesia (GA) remains unclear. We investigated actionable perioperative determinants of functional outcomes and 90-day mortality following MT under GA. Methods: We retrospectively analyzed 166 patients with acute ischemic stroke who underwent emergency MT with GA over 10 years (2014–2024). Poor functional outcomes were defined as a 90-day modified Rankin Scale score of 3–6, with all-cause 90-day mortality as the secondary endpoint. Independent predictors were identified using multivariable logistic regression, and discrimination was assessed using receiver operating characteristic analysis. Results: At 90 days, 56.6% of patients had poor functional outcomes, and mortality was 24.1%. Independent predictors of poor outcomes included preoperative hyperglycemia ≥140 mg/dL, vasopressor requirement, incomplete reperfusion, prolonged ventilator duration, and severe post-procedural neurological deficit. Optimal anesthetic induction dosing was strongly protective. Shorter groin puncture-to-recanalization time predicted better functional recovery. Mortality was associated with hyperglycemia, National Institutes of Health Stroke Scale ≥16, poor reperfusion, and prolonged ventilation. The models demonstrated excellent discrimination (area under the curve, 0.879 for poor outcomes; 0.923 for mortality). Perioperative physiological factors remained associated with outcomes independent of procedural success. Conclusions: Beyond technical success, perioperative physiological stability strongly influenced outcomes following MT under GA. Optimization of metabolic control, hemodynamic stability, procedural efficiency, and early ventilator liberation represents a clinically actionable strategy for improving neurological recovery and survival. Full article

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) involves complex interactions between immune evasion and metabolic reprogramming. This study aimed to characterize ccRCC through integrated immunometabolic profiling, develop a prognostic signature, and investigate the functional role of the key driver gene UCN using in vitro and in vivo approaches. Methods: Integrated immunometabolic profiling was performed to identify molecular subtypes and establish a prognostic gene signature. Two distinct molecular subtypes were identified, and a 9-gene Immune Metabolic Index (IMI) was constructed. The functional role of the key driver gene UCN was investigated through in vitro functional assays and in vivo xenograft models in BALB/c mice, including combination with PD-1 blockade. Results: Two molecular subtypes with significant survival differences (p < 0.001) were identified. The established IMI demonstrated high prognostic accuracy, with Area Under the Curve (AUC) values of 0.813, 0.751, and 0.779 at 1-, 3-, and 5-year intervals, respectively. UCN was identified as the highest-risk gene in the signature. Functional assays showed that UCN silencing significantly inhibited cell proliferation and migration (p < 0.05). In BALB/c mouse xenograft models, UCN silencing remodeled the tumor microenvironment by increasing CD8+ T cell infiltration and reducing regulatory T cells (p < 0.01). Furthermore, UCN knockdown significantly suppressed tumor growth and synergized with PD-1 blockade to enhance antitumor efficacy (p < 0.001). Conclusions: The IMI is a robust tool for risk stratification in ccRCC. Targeting the UCN-driven immunometabolic axis represents a promising therapeutic strategy to overcome immune resistance in ccRCC. Full article

For power-grid applications such as transmission corridor inspection, substation asset inspection, and post-disaster emergency repair, reliable UAV self-localization under GNSS-degraded or GNSS-denied conditions is critical to ensuring operational safety and accurate defect geotagging. Due to substantial discrepancies in viewpoint, scale, and geometric structure between oblique UAV images and nadir satellite images, conventional RGB-based cross-view retrieval methods often suffer from unstable alignment and insufficient geometric modeling, particularly in scenarios with repetitive textures and partial overlap. To address these challenges, we propose a cross-view visual geo-localization model that integrates RGBD multimodal inputs with multi-scale attention enhancement. Specifically, MiDaS is used to estimate relative depth from UAV imagery, which is concatenated with RGB to form a four-channel input, while satellite images are padded with an additional zero channel to maintain dimensional consistency. A shared-weight ViTAdapter is adopted to learn joint semantic–geometric representations, and a lightweight Efficient Multi-scale Attention (EMA) module is adopted on spatial feature maps to strengthen multi-scale spatial consistency. In addition, an IoU-weighted InfoNCE loss is employed to accommodate partial matching during training, thereby improving the robustness of feature alignment. Experiments on the GTA-UAV dataset under the cross-area protocol show stable performance across both retrieval and localization metrics. Specifically, Recall@1, Recall@5, and Recall@10 reach 18.12%, 38.83%, and 49.47%, respectively; AP is 28.01 and SDM@3 is 0.53; meanwhile, the top-1 geodesic distance error Dis@1 is 1052.73 m. These results indicate that explicit geometric priors combined with multi-scale spatial enhancement can effectively improve cross-view feature alignment, leading to enhanced robustness and accuracy for localization in challenging power inspection scenarios. Full article