Search Results (8,167)

Coal mining has historically been a central economic, cultural, and social cornerstone of Appalachian communities. The decline of the coal industry, driven by technological changes, competition from natural gas and renewable energy, environmental regulations, and evolving energy markets, has created major economic and environmental challenges for coal-dependent regions. This study examines Kentucky residents’ perceptions of coal decline and how socio-demographic factors shape environmental concern. Data was collected from 685 Kentucky residents through a statewide online survey conducted in December 2023. Ordered logistic regression was used to examine the influence of gender, age, rural residence, and political affiliation on concerns regarding climate change, environmental degradation, extinction of endangered species, air pollution, and water pollution. Respondents identified health and safety concerns, cleaner energy alternatives, government incentives, and technological changes as major contributors to coal decline, while climate change was viewed as less significant. The findings also reveal support for workforce retention and training in sectors such as construction, transportation, utility work, and renewable energy. Female respondents expressed high levels of environmental concern, while rural residents and Republicans reported lower concern regarding climate change and environmental degradation. Full article

To understand glycan–protein interactions at biological interfaces, designing surfaces modified with structurally controlled glycans is highly important. In particular, naturally occurring glycosaminoglycans (GAGs) possess periodic sugar arrangements that play important roles in protein recognition, highlighting the need for the development of periodic glycopolymer model systems that can serve as GAG mimics for quantitative interaction analysis. In this study, sequence-controlled periodic glycopolymers were synthesized by reversible addition–fragmentation chain-transfer (RAFT) polymerization and immobilized onto gold surfaces to construct glycan-modified interfaces. The synthesized material was a terminally functionalized periodic glycopolymer with the most basic structure, consisting of alternating maltose-containing vinyl ether (MalVE) units and ethyl maleimide (EtMI) units, with a trithiocarbonate group at the ω-terminal. This trithiocarbonate group was converted to a thiol group for immobilization through Au–S bond formation. Structural characterization by ¹H NMR spectroscopy, size exclusion chromatography (SEC), MALDI-TOF mass spectrometry, and UV–vis spectroscopy confirmed the structure as designed. Quartz crystal microbalance (QCM) measurements verified the stable immobilization of thiol-terminated periodic glycopolymers on the gold surface, and allowed for estimation of graft density and quantitative analysis of glycan-protein interactions at the modified interface. The periodic glycopolymer-modified surfaces exhibited selective binding behavior toward concanavalin A (ConA) compared to bovine serum albumin (BSA), with apparent binding constants on the order of 10⁶–10⁷ L mol⁻¹. This enhanced binding behavior indicated that specific and multivalent interactions with proteins also occurred at periodic pendant maltose residues along the main chain. These results demonstrate that the gold surface modified with end-functional periodic glycopolymers synthesized by RAFT polymerization provides a versatile platform for quantitative analysis of glycan-protein interactions and suggests potential applications for periodic glycopolymers as functional materials. Full article

Oncogenic viruses are responsible for between 12% and 20% of human cancers worldwide. They trigger tumorigenesis by integrating into host-cell genomes, altering cell cycle pathways, and evading immune detection. Oncoviral cancers exhibit low rates of mutation, implicating alternative splicing as an underappreciated alternative mechanism for oncogene and oncogenic pathway activation in oncoviral pathogenesis and progression. In order to create alternatively spliced viral proteins for replication and viral genome maintenance, oncoviruses take advantage of host-cell splicing machinery. Some of these proteins inhibit major host-cell tumor suppressors to promote the proliferation of DNA-damaged host-cells in order to facilitate persistent infection, whilst others interact with and de-regulate the expression and activity of host-cell splicing factors to alter host transcript splice site selection. The latter reprograms host-cell transcriptomes to express aberrant, sometimes oncogenic protein isoforms, which interact with oncoviral proteins to promote host-cell transformation and subsequent tumor progression to metastatic disease. In this article, we review oncovirus-induced alternative splicing as a fundamental, underappreciated, oncogenic and tumor-promoting mechanism. We compare how different oncoviruses hijack host-cell splicing mechanisms and how specific aberrant alternatively spliced host-cell protein isoforms, induced by different oncoviruses, influence tumor pathogenesis and progression, organized with respect to the hallmarks of cancer. We follow this with more detailed descriptions of each individual oncovirus and a section on therapeutic perspectives. This approach not only crystallizes the complexity of how oncovirus-induced host-cell alternative splicing can influence cancer pathogenesis and progression but also reveals novel potential therapeutic opportunities. Full article

Bipolar junction transistor (BJT)-based 2D temperature-sensor arrays are factory-calibrated to ±0.1 °C, but post-deployment thermal and mechanical stresses drift their per-sensor gain–offset parameters by an order of magnitude, and in-lab recalibration is impractical. We present RASC (Region-Aware Self-Calibration), a five-stage algorithm that decomposes the global ill-posed problem into local cluster-level problems, runs robust alternating estimation (trimmed-mean field reconstruction + Huber iteratively reweighted least squares (IRLS)) inside each cluster, and reconciles overlapping estimates by linear consensus on the cluster-overlap graph with provable exponential convergence. On 7632 frames from a deployed 16 × 16 array exhibiting ≈5× factory-spec non-uniformity, RASC cuts the locally non-smooth fixed-pattern residual by 71 ± 5% (10-fold cross-validation (CV)), reducing this residual to a level comparable to the ±0.1 °C factory specification (as assessed by local-smoothness residual metrics, not independent absolute-temperature validation) while perturbing the calibrated field by only 0.041 °C RMSE; reduction concentrates at the edges (78% vs. 55% interior). In simulations on 8 × 8 to 32 × 32 arrays, RASC matches an oracle centralised extended Kalman filter (EKF) within 0.10 °C with ≈4× lower bandwidth. The real-data evaluation is a single-deployment proof of concept on one array and one host PCB; broader, longitudinal validation remains future work. Full article

Biokinetic complexities (plastic sorption, protein binding, and cellular accumulation) may cause large discrepancies between nominal and biologically effective concentrations of test compounds assessed by new approach methods (NAMs). This case study was performed to explore a generally applicable workflow that addresses biokinetic complexities in the context of NAM-based hazard testing for next-generation risk assessment (NGRA). The pesticide tebufenpyrad (TEBU) is a challenging test compound, as it (i) is hydrophobic, (ii) has an intracellular target (mitochondrial respiration), and (iii) is acting at low concentrations (susceptible to biokinetic complexities). In the newly established NeuriTox-M neurotoxicity assay, based on human dopaminergic (LUHMES) neuron cultures, TEBU showed toxic effects at 20 nM. Mass spectrometric analyses of various experimental setups showed that a large fraction (75% to >90%) of TEBU was adsorbed to plastic. This effect was strongly attenuated by albumin in the medium. Cells, cultured on plastic, were considered unsuitable to assess cellular uptake. Therefore, alternatives were explored: when cells were used as suspension cultures (3% v/v) in albumin-containing medium, analysis worked best. Under such conditions, the concentration ratio (cells/medium) of TEBU was around 10. Data from an in vitro distribution (VIVD) model were in good agreement with the measurements. VIVD predicted the unbound medium TEBU concentration (C_u) to be 2–3 orders of magnitude below the nominal concentration and the total cellular concentration to be 10–100-fold above. Standard cell culture assays showed that the medium albumin content indeed altered the TEBU toxicity threshold. More such studies are needed to embed biokinetics information into NGRA. Full article

Excessive application of chemical preservatives has raised increasing concerns regarding food safety and human health, prompting the search for safer natural alternatives. Lavender essential oil (LEO), a plant-derived antimicrobial agent, has been considered a promising substitute for synthetic preservatives, but its high volatility and poor water solubility limit its practical application. In this study, LEO nanoemulsions were fabricated via high-pressure homogenization using sodium caseinate (SC) and tea polyphenols (TPs) as composite emulsifiers. The preparation process was optimized using a three-factor, three-level orthogonal design, and the physicochemical properties, storage stability, and antibacterial activity were systematically investigated. The optimal preparation conditions were determined as an SC/TP mass ratio of 2:1, homogenization pressure of 70 MPa, and 7 homogenization cycles. The optimized nanoemulsion exhibited a droplet size of 130–210 nm, zeta potential of −30.89 mV, and encapsulation efficiency of 98.61%, with typical shear-thinning behavior and excellent storage stability. The percentage of free LEO remained below 7.5% within 15 days, indicating high stability, and the release behavior followed a zero-order kinetic model. The prepared nanoemulsion showed significant antibacterial activity against Staphylococcus aureus and Escherichia coli, with a minimum inhibitory concentration (MIC) of 62.5 μg/mL for both strains. This study confirms that the SC/TP composite interface can effectively stabilize LEO nanoemulsions, providing a theoretical basis for the development of natural and efficient food preservatives. Full article

The decades-long development of curvilinear steel bar forms has relied on both physical and analytical modelling. This study integrates these complementary approaches to optimise the geometry and topology of a paraboloid-like steel bar structure, with the aim of enhancing structural performance and material efficiency. The developed method introduces a novel Discrete Catenary Model (DCM), generated through dynamic relaxation, to define the geometry of a steel bar roof suitable for flat quadrilateral (PQ) parallelogram panels. The DCMs were arranged in parallel at equal spacing, forming a bar grid supported by four corner columns. Static analyses were performed for various cladding materials—glass, polycarbonate, and metal sheets—to compare structural material demands, with serviceability limit states for nodal displacements and member deformations serving as key criteria. The proportions of structural material consumption for structures with glass, polycarbonate, and metal panels were 1.00:0.68:0.61. For the glass-clad variant, a physical prototype of a recreational shelter was developed and subjected to laboratory testing under near-real conditions. The test results confirmed the analytical predictions regarding the structural response under loading; the differences in nodal displacements were in the order of tenths of a millimetre. The findings indicate that the application of a parametric DCM makes it possible to obtain the intended and efficient geometry already at the preliminary design stage. Therefore, the generation of a DCM can serve as a practical tool for shaping efficient curvilinear steel bar structures with PQ panels. The proposed original method can be further developed through alternative DCM forms to design efficient steel bar roof systems. Full article

Autonomous artificial intelligence (AI) systems increasingly participate in decision-making processes that affect individuals, markets, and public administration. Their growing autonomy complicates the attribution of legal responsibility, particularly within regulatory frameworks that were designed around identifiable human actors and relatively stable products. Although European Union instruments such as the GDPR, the AI Act, and the revised Product Liability Directive address specific dimensions of risk and compliance, they do not fully resolve how responsibility should be allocated across the lifecycle of complex AI systems. The difficulty does not lie so much in the absence of legal rules. Rather, it reflects the structural tension between traditional liability models and the distributed architecture of contemporary AI development and deployment. By examining how existing EU regulatory instruments interact, the paper identifies fragmentation in responsibility allocation that may weaken institutional accountability. It then proposes a tiered model of legal responsibility based on meaningful control at different stages of system design, deployment, and operational oversight. Rather than introducing new forms of legal personhood, the model seeks to clarify how existing doctrines can be interpreted and coordinated in order to maintain regulatory coherence and socially intelligible accountability in digitally mediated environments. The model allocates responsibility according to meaningful control within distributed systems, offering a structurally coherent alternative for EU governance. Full article

According to data from the World Federation of Societies of Anesthesiologists, numerous countries across Asia and Africa have fewer than one anaesthesiologist per 100,000 people. Upskilling nurse anaesthetists in these regions is critical to improving clinical outcomes, and interactive virtual patient simulators offer a safe environment to explore complex clinical scenarios. This paper introduces an advanced general anaesthesia patient simulator engineered to bridge the accessibility gap left by existing platforms, which often require expert programming knowledge and restrict users to manual titration. Our simulator features an intuitive graphical user interface optimised for clinical education and natively supports both manual and closed-loop anaesthesia administration. The platform includes a suite of pre-designed controllers, specifically standard PIDs and two distinct fractional-order FO-PID variants, highlighting a novel robust FO-PID framework engineered to mitigate high patient variability. The deployment of these embedded controllers is demonstrated via a Depth of Hypnosis regulation case study and validated across a diverse cohort of 19 virtual patients. Closed-loop evaluation reveals that while the standard PID achieves a lower average mean squared error during the maintenance phase, the fractional-order alternatives deliver significantly superior robustness and inter-patient consistency. Ultimately, integrating this simulator into clinical training frameworks offers a viable pathway to reduce nursing workload and enhance patient safety through optimised automated drug delivery. Full article

An administrator-assisted CLP-SEIRS-T⁺ framework is developed to model malware propagation and urban cyber-resilience in clustered temporal communication networks. The model extends CLP-SEIRS-T by integrating community structure, predicted links, asynchronous node activation, and an endogenous defense layer in which administrator nodes remain infectable, recover faster than ordinary nodes, and trigger local patch diffusion when community-level prevalence exceeds a risk threshold. Unlike formulations that treat defense as an external or perfectly reliable safeguard, the proposed framework embeds administrator intervention directly within the epidemic state space and couples propagation dynamics with resilience-oriented performance measures, including safe functionality, absorptive capacity, spillover attenuation, recovery time, and service continuity. To keep experimental evidence scale-explicit, the validation is organized as a tiered protocol: a 48-node isolated virtual-machine cyber-range verifies safe mechanism realization; emulation-calibrated logical traces and pilot repeated comparisons examine trajectory behavior, pathway composition, and defense-component effects; and expanded numerical sweeps assess scalability, threshold sensitivity, alternative link-prediction scores, and adaptive-stress assumptions. The results show that direct links dominate local amplification, whereas predicted links contribute disproportionately to cross-community spillover. In the pilot comparison, the full CLP-SEIRS-T⁺ configuration achieves the best observed balance, reducing mean peak burden by 56.9%, shortening mean recovery time by 86.7%, increasing absorptive capacity by 37.1%, and improving service continuity by 12.0% relative to the no-intervention baseline. Larger-network sweeps over $N=48,100,150,200,$ and 500 logical hosts preserve the same qualitative mechanism ordering while keeping functionality error below 0.02. Threshold analysis indicates that intermediate trigger values provide a better burden–cost balance than either overly aggressive or delayed patching. Link-score comparisons show that local-neighborhood predictors yield consistent spillover interpretations, whereas degree-driven prediction can increase bridge exposure. Parameterized adaptive-stress tests further indicate that the mechanism remains beneficial under moderate stress but degrades under severe patch suppression, false telemetry, or intensified bridge seeking. These findings suggest that urban cyber-resilience depends jointly on network modularity, temporal availability, structurally likely bridge formation, state-dependent local defense, and the integrity of administrative response. Full article

The Easterlin paradox and recent distributional reassessments suggest that average effects obscure how subjective disadvantage is generated and reproduced over time. We propose the Social Comparison System (SCS), a framework that represents subjective well-being (SWB) as an internal state and relative income rank as an external conditioning variable within a feedback structure, with three structural properties: threshold activation, state-dependent gain, and rank-conditioned attractor displacement. The properties are recovered through a sample-isolated three-stage framework integrating tree-based machine learning, forest-based heterogeneity estimation, panel-data estimation, and hierarchical Bayesian Markov modeling on a balanced four-wave panel of the China Family Panel Studies (CFPS; 8099 individuals; 32,396 person-wave observations). Stage 1 locates a discrete predictive discontinuity in relative income rank between rank 2 and rank 3 (SHAP jump = 0.383, permutation p < 0.001). Stage 2 carries this boundary into a disjoint validation panel and recovers a negative rank-by-prior-SWB interaction (β = −0.036) and a 2.30-fold larger conditional effect in low- than in high-prior-SWB strata. Stage 3 recovers a 22.6-percentage-point gap in the rank-conditioned occupancy of the lowest within-wave SWB quartile between low- and high-rank subsystems, which under a first-order Markov approximation corresponds to a long-run stationary gap, robust to alternative state-space discretizations. Throughout this paper, relative income rank is treated as a conditioning variable, and the rank-conditioned patterns are interpreted as associational; the long-run quantities are reported under a first-order dynamical approximation rather than as identified causal or fully validated long-run effects. Persistent subjective disadvantage is therefore characterized by unequal dynamics of activation, amplification, and escape, rather than by unequal resources alone. This reframing provides a methodological template for identifying rank-conditioned feedback structures in social-systems data. Full article

Wideband direction-of-arrival (DOA) estimation is often formulated as a sparse signal recovery problem with multiple dictionaries, where the commonly adopted ℓ_2,1-norm minimization framework exploits the joint sparsity shared across different frequency bins. However, the resulting optimization problem involves a large number of variables and becomes computationally expensive as the problem scale increases. In this paper, a compact reformulation of the multi-dictionary ℓ_2,1-norm minimization problem is derived, which significantly reduces the number of optimization variables by introducing an equivalent diagonal representation. Under the special case of uniform linear arrays and harmonic sources, the proposed formulation is further extended to a gridless form, and its equivalence to wideband atomic norm minimization is discussed. For the grid-based compact formulation, an efficient block coordinate descent algorithm is developed, where each update admits a closed-form expression. For the gridless formulation, a first-order solver based on the alternating direction method of multipliers is employed to handle large-scale problems. Numerical simulations demonstrate that the proposed methods achieve substantial reductions in computational complexity, thereby enabling efficient wideband DOA estimation in large-scale scenarios. Full article

This paper presents a methodology for synthesizing static state feedback controllers utilizing a Fractional-Order Performance Index. Linear Quadratic Regulators are designed using integer-order integral weighting functions. In the proposed approach, fractional-order calculus is utilized to introduce an additional degree of freedom in controller synthesis, enabling enhanced shaping of the plant’s dynamic properties. The controller gains are obtained by solving a fractional Riccati-like equation, through which the temporal weighting properties inherent to fractional integration are embedded into a static feedback matrix. This formulation is a minimalist control structure suitable for implementation on resource-constrained hardware. The proposed method is validated via rapid control prototyping on an industrial NI PXIe platform and an analog third-order plant. Performance evaluation using Integral Absolute Error and Integral Absolute Control metrics demonstrates that the fractional order serves as a flexible tuning parameter, providing an alternative trade-off between settling time and control effort. Furthermore, frequency domain sensitivity analysis demonstrates the absence of resonant peaks and inherent attenuation of high-frequency measurement noise. As a result, the presented framework bridges fractional-order optimization techniques with industrial control platforms. Full article

Next-generation unmanned aerial vehicles require compact propulsion systems capable of providing efficient vertical lift, rapid thrust vectoring, and improved maneuverability. Cyclorotors represent a promising alternative to conventional propellers, but their aerodynamic behavior is governed by highly unsteady blade–wake interactions, making performance prediction challenging. This study investigates a four-bladed cyclorotor equipped with NACA 0012 airfoils using transient computational fluid dynamics simulations and a calibrated semi-analytical blade-element model. The numerical analysis was performed over a rotational-speed range of 368–2305 rpm and for several pitch-amplitude configurations, including 5°, 7.5°, 10°, 12.5° and 15°. The results showed that the favorable pitch amplitude decreases with increasing rotational speed, shifting from larger amplitudes at low RPM to approximately 5° at higher RPM values. The semi-analytical model reproduced the main CFD trends for lift, drag, moment, and power, providing a reduced-order tool for preliminary cyclorotor performance estimation. The comparison confirmed that pitch-amplitude selection strongly influences aerodynamic loading and efficiency and should therefore be adapted to the operating regime. The proposed CFD-based methodology, supported by semi-analytical modelling, provides a useful framework for the aerodynamic characterization and early-stage optimization of cyclorotor propulsion systems for UAV applications. Full article

This paper documents a fundamental sectoral divergence in capital–employment relationships using UK quarterly data (2014Q1–2024Q4, N = 44). While manufacturing automation studies consistently find negative employment effects, we show that information-intensive service sectors (SIC J: Information and Communication; K: Financial and Insurance; M: Professional/Scientific/Technical) exhibit robust positive co-movement between capital formation and employment. Structural vector autoregression analysis reveals persistent positive employment responses following capital shocks, with effects peaking at 5–6 quarters and remaining significant through 10 quarters. This pattern holds across eight alternative specifications with varying lag structure, variable ordering, and subsample periods. Granger causality tests reveal bidirectional temporal relationships (capital → employment: F = 3.932, p = 0.028; employment → capital: F = 5.659, p = 0.007), indicating joint determination from anticipated demand growth rather than unidirectional technology-driven dynamics. This finding—while complicating causal interpretation—strengthens the contribution by providing honest empirical characterization of coordination mechanisms in information-intensive sectors. Our capital formation proxy measures all investment in AI-intensive sectors (buildings, equipment, conventional IT, emerging AI systems) rather than AI expenditure specifically, creating measurement ambiguity we acknowledge transparently. The sectoral focus (J+K+M sectors with 22–34% AI adoption rates exceeding the 15% economy-wide average) provides indicative evidence that patterns relate to advanced technology deployment, but measurement breadth prevents definitive AI-specific conclusions. The contribution lies not in establishing AI-specific causality—which aggregate time-series methods cannot achieve—but in documenting robust sectoral heterogeneity using methodology comparable to manufacturing displacement studies. The positive association in information-intensive services contrasts sharply with manufacturing’s negative relationship, suggesting technology–employment dynamics vary fundamentally across sectors with different task structures. Three limitations constrain interpretation: (i) recursive identification cannot definitively rule out common demand shocks, (ii) the 44-quarter sample provides limited statistical power for precise magnitude estimation, and (iii) external validity to other countries, time periods, or service sectors remains uncertain. The findings motivate sector-specific rather than economy-wide technology policy approaches, recognizing that extrapolating manufacturing evidence to service-dominated economies may systematically mischaracterize employment dynamics. Full article