Search Results (1,849)

According to the U.S. Environmental Protection Agency (2024), carbon dioxide is the leading greenhouse gas driving global warming. The building sector accounts for about 39% of global energy-related carbon emissions, with 11% from embodied carbon generated during material extraction, manufacturing, transport, and assembly. This study examines embodied carbon in the Harold L. Martin Sr. Engineering Research and Innovation Complex at North Carolina A&T State University, a four-story, 130,000 square-foot facility completed in 2021. Using architectural and structural documents, verified material quantities were analyzed to calculate cradle-to-gate embodied carbon (A1–A3 stages) for major components, including concrete, steel, glazing, and finishes. Results show structural materials, especially concrete and steel, dominate embodied emissions, followed by envelope systems. Sensitivity analyses indicate that substituting materials, such as recycled steel, low-carbon concrete, and bio-based finishes, can reduce total embodied carbon by 15–30% while maintaining performance. Full article

The evaluation of building energy performance under dynamic conditions requires reliable estimates of the thermophysical properties of envelope components. In existing buildings, however, the properties of multilayer walls are often unknown or uncertain, limiting the applicability of detailed physical models. To address this issue, this study proposes an inverse modeling framework for identifying the equivalent thermophysical parameters of a multilayer wall through a simplified homogeneous one-dimensional conduction model. The equivalent parameters are determined by matching the inner-side dynamic thermal response of the homogeneous model to that of the actual multilayer structure under the same external excitation. The approach explicitly accounts for the role of inner boundary conditions, which govern both the identifiability of the equivalent parameters and the formulation of the inverse problem. Adiabatic, isothermal, and more general inner boundary conditions are analyzed to determine how many independent parameters can be reliably identified and which response variables should be used in the objective function. Synthetic datasets, generated via numerical simulations driven by real weather data, are first employed to assess the method and to quantify the effect of transient initialization. The framework is then applied to experimental measurements collected from a full-scale test room. The results show that, under adiabatic conditions, the wall dynamics can be accurately reproduced by identifying a single equivalent thermal diffusivity, whereas isothermal and near-isothermal conditions require the simultaneous estimation of thermal conductivity and volumetric heat capacity. Moreover, the analysis demonstrates that inverse formulations based on inner heat flux are significantly more robust than temperature-based formulations, particularly when the inner-surface temperature is weakly varying or tightly controlled, as commonly occurs in real buildings. In a nearly isothermal experimental case, the inverse identification failed (${EF}_T=-5.76$) when based on the inner-surface temperature, while it resulted in a better match (${EF}_q=0.63$) when based on the inner heat flux. Overall, the proposed framework provides a physically consistent and practically robust methodology for the dynamic thermal characterization of multilayer building walls using equivalent homogeneous models. Full article

The nuclear envelope (NE) functions as a barrier between the cytoplasm and nucleus. Over the past decade, NE has revealed unexpectedly divergent structural alterations. NE rupture triggers the uncontrollable exchange of macromolecules across the NE and potentially causes DNA damage. Conversely, a recent study demonstrated that DNA damage induces NE rupture and that one of the major kinases in the DNA damage response (DDR) pathway, ataxia telangiectasia and Rad3-related protein, ATR, is a key molecule in these events. Here, we review the role of the DDR pathway in NE regulation, with a focus mainly on ATR. Full article

To address the periodic impacts and amplitude-modulated high-frequency resonance phenomena caused by bearing faults in rotating machinery, this paper proposes a detection method. The core innovation lies in: firstly, constructing a composite fault feature index (CFFI) that integrates normalized kurtosis and fuzzy entropy, which synchronously quantifies the fault impact intensity and periodic structure, and serves as an optimization objective; secondly, definining a spectral energy retention rate (SERR) that includes both the full spectrum and characteristic frequency bands to evaluate the denoising effect and fault feature retention, respectively. Based on this, the method adaptively determines the Variational Mode Decomposition (VMD) parameters through the Triangular Topology Aggregation Optimizer (TTAO), and uses Dynamic Weighted Center Clustering (DWCC) to screen key IMFs containing fault-envelope information. On the IMS bearing dataset, the SERR of the reconstructed signal is 0.21356, which is higher than the actual collected signal value of 0.22465, with a relative error of 4.9%, indicating a higher reconstruction accuracy. These quantitative results indicate that CFFI-guided optimization enhances impulsive and periodic fault components while maintaining stable feature-band retention. This approach is suitable for real-world equipment monitoring and exhibits strong engineering applicability. Full article

Stock returns are a key indicator of investor confidence and capital allocation in the tourism sector, particularly during crises that compress demand and elevate liquidity risk. This study investigates firm-level determinants of stock returns among 27 Indonesian listed tourism firms over 2019–2023, covering the COVID-19 disruption and initial recovery. Operational efficiency is estimated using an input-oriented, constant returns to scale (CRS) Data Envelopment Analysis (DEA) model, and stock returns are modeled with Generalized Estimating Equations (GEE) to account for the longitudinal panel structure. The results indicate that higher DEA-based efficiency and a stronger liquidity position (current ratio) are positively and significantly associated with stock returns, whereas profitability (ROA, ROE) is not significant. Leverage, growth, and firm age also show no significant effects. In contrast, higher valuation multiples (price-to-book and price-to-sales ratios) are associated with lower subsequent returns, and larger firms exhibit lower returns over the sample horizon. The findings support signaling and resource-based interpretations, suggesting that in crisis periods investors reward operational efficiency as an indicator of disciplined resource use that helps preserve cash and sustain liquidity, while discounting firms priced at high multiples. Full article

The aerodynamic behavior of small-scale UAV propellers operating under non-axial inflow conditions poses a significant prediction challenge due to the presence of strong azimuthal asymmetries, inherently unsteady flow phenomena, and Reynolds number effects that dominate forward flight conditions. Although numerical models based on the Moving Reference Frame (MRF) formulation combined with steady RANS solvers are widely used in engineering practice because of their low computational cost, the precise limits of their applicability in crossflow configurations remain poorly defined. This work conducts a comprehensive numerical investigation that systematically compares steady RANS–MRF predictions against time-accurate URANS simulations across a wide range of advanced ratios and rotor tilt angles. Rigorous validation of the computational framework against experimental data in axial and near-axial regimes demonstrates excellent agreement, with deviations below 5% in propulsive efficiency. The results clearly identify the operational envelope within which MRF-based steady models remain valid under non-axial inflow. In particular, the steady approach exhibits robust performance for low-to-moderate advance ratios, where global errors in thrust and power remain below 10% for $\mu =0.40$. However, the fidelity of the method deteriorates sharply under extreme edgewise-flight conditions ($\mu =0.70)$, in which the crossflow component dominates the aerodynamic field, the “frozen-rotor” assumption progressively loses mathematical consistency, and the solver may converge toward steady solutions that no longer represent a physically meaningful flow state. The URANS analysis further reveals two critical phenomena that cannot be captured by steady-state models. First, at high advance ratios, the retreating blade encounters an extensive region of reverse flow, which induces negative sectional thrust and strongly anharmonic load waveforms. This behavior has direct implications for structural design: the peak-to-peak amplitude of thrust oscillation in edgewise flight can exceed the mean thrust level, implying extreme cyclic loading and a high risk of high-cycle fatigue. Second, the simulations quantify the emergence of off-axis parasitic moments (pitching and rolling), which are negligible in vertical flight but reach magnitudes comparable to the total aerodynamic torque in forward-flight conditions. Taken together, these findings highlight the need for a hybrid-fidelity strategy in UAV propulsion analysis: employing steady RANS–MRF within the validated domain for energetic assessments, while relying on time-accurate URANS for mandatory evaluation of structural loading, vibration, and control logic in critical high-speed regimes. Full article

The persistent emergence of infectious diseases has underscored the critical demand for next-generation vaccine technologies that are safe, effective, and scalable. This review explores virus biomimetic delivery systems, focusing on virus-like particles (VLPs) and virosomes as promising platforms for vaccine and therapeutic development. VLPs are self-assembled nanostructures composed of viral structural proteins that mimic native virions without carrying genetic material, while virosomes are reconstituted viral envelopes that retain functional glycoproteins but lack a nucleocapsid. Both systems provide strong immunogenicity and safety by mimicking viral architecture while eliminating the risk of replication. The paper examines various expression platforms for VLP production, including bacterial, yeast, insect, mammalian, and plant-based systems, highlighting their respective advantages, challenges, and optimization strategies. Mechanistic insights into antigen presentation, immune activation, and cellular uptake pathways are discussed to explain their superior performance in eliciting humoral and cellular immune responses. Furthermore, current applications of VLPs and virosomes in vaccines against major pathogens such as SARS-CoV-2, influenza, Newcastle disease virus, malaria, hepatitis, and respiratory syncytial virus are reviewed, demonstrating their versatility and clinical potential. By integrating molecular engineering, nanotechnology, and biofabrication strategies, virus biomimetic systems represent a transformative frontier in vaccinology, immunotherapy, and targeted drug delivery. Full article

Decarbonising the existing residential sector is a central priority of European energy policy, yet masonry buildings from the early 2000s remain significantly underrepresented in net-zero energy building (NZEB) research. This study addresses this critical gap by evaluating a holistic deep retrofit of a representative single-family house in Cracow, Poland, providing a scalable model for the Central European housing stock. The methodology integrated structural and systemic interventions: eliminating thermal bridges via balcony removal, enhancing the envelope with 0.25 m of mineral wool (λ = 0.036 W/m K), and installing innovative active triple-glazed windows (U_w = 0.85 W/m² K) with integrated electric heating foils. The energy system was transformed by replacing a coal-fired boiler with an 8 kW air-to-water heat pump and a 7 kWp photovoltaic array, complemented by a green roof on the western pitch for passive thermal buffering. Verified results demonstrate a radical reduction in the non-renewable primary energy (EP) index from 224.56 kWh/(m²·a) to 0.00 kWh/(m²·a), achieving full compliance with stringent “WT 2021” standards. Economic analysis reveals that the integrated approach is financially viable, with a simple payback time (SPBT) of 7.1 years when supported by available subsidies. This study concludes that the integration of active glazing, high-performance insulation, and nature-based solutions offers a replicable and economically sound roadmap for transforming legacy housing into zero-emission assets. Full article

The integration of Foamed Concrete (FC) into 3D Concrete Printing (3DCP) processes facilitates the design of energy-efficient building envelopes. However, strategies for optimizing material porosity and printing topology to balance winter and summer performance remain underexplored. This study presents a 2D numerical thermal analysis of an innovative 3D-printed building envelope block characterized by sinusoidal internal partitions. Through a parametric variation in porosity (ranging from 10% to 50%) and internal geometry (amplitude and period of the partitions), 45 distinct configurations were simulated. Performance was evaluated by calculating the steady-state thermal transmittance (U) and the periodic thermal transmittance (Y_ie) under dynamic climatic conditions. The results demonstrate that porosity is the governing parameter; increasing porosity from 10% to 50% reduces U by 31% and, contrary to traditional assumptions for massive structures, also improves Y_ie by 12.3%. These outcomes are physically driven by the drastic reduction in thermal conductivity, which overcompensates for the loss of thermal mass, leading to a net reduction in overall thermal diffusivity. While internal topology plays a secondary role, its optimization allows for fine-tuning dynamic damping without compromising insulation. The study confirms that 3D printing with foamed concrete enables the overcoming of the traditional trade-off between insulation and thermal inertia. High-porosity configurations (50%) with optimized internal topology emerge as the most effective solution, simultaneously guaranteeing beneficial steady-state and dynamic thermal performance for sustainable buildings. Full article

Antimicrobial resistance (AMR) was associated with 4.95 million deaths in 2019 and may cause 10 million deaths annually by 2050. We synthesize evidence on how the black soldier fly (Hermetia illucens) has evolved an expanded antimicrobial peptide (AMP) repertoire, which structural features drive family-specific activity, what mechanisms are directly demonstrated in H. illucens, and how AI contributes. PubMed, Web of Science, and Scopus (plus targeted Google Scholar) were searched from inception to 1 February 2026; studies were included when they reported BSF peptide identities, expression/proteomics, evolutionary analyses, quantitative activity, mechanistic assays, or BSF-focused computation, and claims were tiered as predicted, expression-supported, or experimentally supported. The literature supports 50–80 BSF AMP genes, plausibly shaped by gene duplication and balancing/diversifying selection in microbe-rich substrates, with marked induction plasticity across tissues, development, diet, and challenge. SAR is family-dependent: defensin-like peptides rely on disulfide-stabilized CSαβ folds and cationic surface topology; cecropin-like peptides on amphipathic α-helices with selectivity trade-offs; attacin-like peptides on β-architecture where charge-based heuristics are weak; and diptericin/proline-rich peptides remain largely inference-driven in BSF. Mechanistic evidence is strongest for membrane/envelope-centered killing by DLP4 and pore-associated envelope disruption by a recombinant attacin-like peptide, whereas pore geometry, oligomerization, intracellular targets, and broad “resistance-proof” claims remain unresolved. Key gaps include assay heterogeneity, salt/serum stability, selectivity/toxicity, resistance-risk testing, and limited in vivo validation, which must be addressed for credible AMR-relevant translation. Full article

Background/Objectives: Speech understanding in noise relies on both temporal fine structure (TFS) and temporal envelope (ENV) cues. While TFS primarily conveys interaural time differences (ITDs) at low frequencies, ENV cues can also support ITD processing, especially when TFS is unavailable or degraded. Expanding the ENV by increasing modulation depth has been proposed to improve speech perception, but its effects on spatial release from masking (SRM) and binaural temporal processing in normal-hearing listeners remain unclear. The goal of this study was to evaluate the effect of ENV enhancement on SRM in young adults with normal hearing and its influence on ITD sensitivity and interaural coherence (IC). Method: Thirty normal-hearing native Kannada speakers (19–34 years) participated. Speech stimuli consisted of Kannada sentences embedded in four-talker babble at −5, 0, and +5 dB signal to noise ratio (SNR). Target and masker were spatialized using head-related transfer functions at 0°, 15°, and 37.5° azimuths. Stimuli were presented with and without ENV enhancement (compression–expansion algorithm). Speech recognition scores were analyzed using generalized linear mixed models, and SRM was calculated as performance differences between co-located and spatially separated conditions. Cross-correlation analyses were performed to estimate ITDs and IC across SNRs. Result: ENV enhancement yielded significantly higher SRM values across all SNRs and spatial separations. Benefits were greatest at lower SNRs and wider target–masker separations. Cross-correlation analysis showed enhanced IC and more reliable ITD estimates under the expanded condition, particularly at moderate SNRs. Conclusions: Temporal ENV enhancement strengthens spatial unmasking and binaural timing cues in normal-hearing adults, especially under adverse listening conditions. These findings highlight its potential application in auditory rehabilitation and hearing technologies where ENV cues are critical. Full article

Schizophrenia is a severe neurodevelopmental disorder with a complex and largely unresolved pathogenesis. Accumulating evidence indicates that mitochondrial dysfunction is a consistent pathological hallmark of schizophrenia, suggesting that impaired mitochondrial homeostasis may represent a convergent mechanism underlying disease vulnerability. BCL2/adenovirus E1B 19 kDa interacting protein 3 (BNIP3) is a critical regulator of mitochondrial integrity and apoptosis. However, its role in schizophrenia has not yet been elucidated. Human endogenous retroviruses W family envelope (ERVWE1) has been implicated as a potential risk factor in schizophrenia, but the molecular mechanisms by which it contributes to neuronal pathology remain poorly understood. In this study, we investigated whether ERVWE1 induces mitochondrial dysfunction and neuronal apoptosis through the regulation of BNIP3. Bioinformatic analysis of the public dataset GSE53987 revealed significantly elevated BNIP3 expression in the brain tissues of patients with schizophrenia, accompanied by enrichment of mitochondria-related pathways. Consistently, BNIP3 expression was also increased in the peripheral blood of schizophrenia patients and positively correlated with ERVWE1 levels. Mechanistically, ERVWE1 upregulated BNIP3 expression by suppressing miR-27b-3p, a microRNA that directly targets BNIP3. The resulting increase in BNIP3 led to marked mitochondrial structural and functional impairment, characterized by reduced mitochondrial aspect ratio, enhanced mitochondria permeability transition pore (mPTP) opening, and decreased mitochondrial DNA (mtDNA) copy number. These mitochondrial defects subsequently triggered cytochrome c release into the cytosol, activating the intrinsic mitochondrial apoptotic pathway. Collectively, this study provides the first evidence that the ERVWE1/miR-27b-3p/BNIP3 axis contributes to mitochondrial dysfunction and neuronal apoptosis in schizophrenia. Our findings identify a previously unrecognized molecular pathway linking endogenous retroviral activity to mitochondrial pathology, offering novel insights into the mechanisms and potential therapeutic targets for schizophrenia. Full article

Background: Ports play a strategic role in the efficiency and sustainability of European transport corridors; however, empirical evidence on their performance remains limited, particularly for Eastern European countries. This study aims to assess the technical efficiency and productivity dynamics of Romanian ports along the Danube corridor in a context of structural change and evolving cargo flows. Methods: Technical efficiency is estimated using an output-oriented Data Envelopment Analysis (DEA) model under variable returns to scale, followed by bias correction and determinant analysis employing the Simar–Wilson bootstrap procedure. Productivity change is examined separately using the Malmquist Productivity Index based on original DEA distance functions. Results: The analysis reveals substantial heterogeneity in efficiency levels across ports, with bias-corrected estimates indicating that efficiency differentials are structural rather than statistical. Cargo specialization emerges as the main determinant of efficiency, while location effects are found to be asymmetric. Efficiency levels are largely stable over time, and productivity change is modest, being driven exclusively by efficiency change, with no evidence of technological progress. Conclusions: These findings suggest that the performance of ports along the Romanian Danube corridor is shaped primarily by structural and organizational factors rather than temporal dynamics, underlining the importance of targeted policy interventions focusing on traffic consolidation, port specialization, and coordinated spatial and hinterland planning to enhance inland port performance within European transport corridors. Full article

With the rapid advancement in information technology, the digital twin and smart assembly process simulation have become an integral part of the design and manufacturing of high-precision products. However, conventional Tunnel Boring Machine (TBM) cutterhead design and on-site assembly planning remain largely experience-driven and fragmented, with limited interoperability between geological characterization, structural verification, and constructability validation. This study proposes a digital twin-driven framework for TBM cutterhead design optimization and assembly process simulation that integrates geology-aware design inputs, BIM-based information modelling, FEM-based structural assessment, and immersive virtual environments within a unified virtual–physical workflow. To ensure consistent data exchange across platforms, an IFC4.3-compliant ontology is established using a non-intrusive property-set (Pset) extension strategy to represent cutterhead components, geological parameters, FEM load cases/results, and assembly tasks. Tunnel-scale stress analysis and cutter–rock interaction modelling are used to define project-representative cutter loading envelopes, which are mapped to a high-fidelity cutterhead FEM model for iterative structural refinement. The optimized configuration is then transferred to a game-engine/VR environment to support full-scale design inspection and assembly rehearsal, followed by manufacturing and field deployment with bidirectional feedback. To validate the proposed framework, an implementation case study of a deep hard-rock tunnelling project is presented where five design iterations were tracked across BIM–FEM–VR and nine constructability issues detected and resolved prior to assembly. The results indicate that the proposed digital twin approach strengthens traceability from geology to loading to structural response, reduces localized stress concentration at critical interfaces, and improves assembly readiness for complex tunnelling projects. Full article

This article examines the behavior of seismic noise fields over the Japanese islands recorded by the F-net seismic network for 1997–2025. This paper uses nonlinear noise statistics: the entropy of the wavelet coefficient distribution, the Donoho–Johnston (DJ) wavelet index, and the multifractal singularity spectrum support width. These parameters were chosen because their changes reflect the complication or simplification of the noise structure. Changes in the structure of seismic noise properties are analyzed in comparison with a sequence of strong earthquakes. Using a model of the intensity of interacting point processes, the effect of the leading of local noise property extrema relative to the seismic event times is estimated. Using the Hilbert–Huang decomposition, the synchronization of the amplitudes of the envelopes of noise property time series for different IMF levels is estimated. A sequence of weighted probability density maps of extreme values of noise properties is analyzed in comparison with the mega-earthquake of 11 March 2011 and the preparation of another possible strong seismic event. Full article