Search Results (1,506)

Since the initiation of two variants of the bootstrap method by Efron and Rubin in the late 1970s, a variety of advancements has emerged in the literature. The subsampling of blocks enabled the estimation of the actual variance of the sample mean. The equivalence of the data-level and the estimator-level resampling is easily established for the sample mean and estimators alike. For Rubin’s variant of the bootstrap we apply an algorithm by Diniz et al. which allows for the numerically stable computation of the sample-based cumulative distribution function of the estimator under investigation. No actual Monte-Carlo resampling is necessary in this setting and we demonstrate how we get access to the very small probabilities of the tails and moreover to confidence intervals. We do this at the example of a well-known test model that exhibits geometrically decaying spatial correlations. The analysis naturally applies to temporally correlated systems or to the correlations occurring in Markov chains, as well. Full article

Green ammonia is increasingly recognised as a sustainability enabler for decarbonising fertiliser production, energy storage, and maritime transport, but offshore wind-to-ammonia pathways remain subject to significant economic and operational uncertainty. This study evaluated the techno-economic and sustainability performance of integrating power-to-ammonia (PtA) with an operating offshore wind farm in Denmark under three supply-chain scenarios (SCs): SC1, a fully offshore PtA with vessel-based ammonia transport; SC2, a fully offshore PtA with pipeline export; and SC3, a hybrid offshore–onshore configuration. An hourly dispatch framework allocated wind electricity between grid export and ammonia production by comparing incremental operating margins, while accounting for minimum-load, ramping, storage, and logistics constraints. Hourly wind generation and DK1 electricity-price data for 2020–2025 are used to construct a deterministic base case and a 30-year block-bootstrap Monte Carlo analysis. Sensitivity analysis is performed by varying electrolyser rated power over 10–200 MW and ammonia selling price over 1400–3200 €/tNH3, with additional breakeven-price estimation and flexibility cases based on reduced minimum-load requirements and faster ramping. A screening-level climate indicator was additionally reported by estimating potential CO₂ emissions avoided if delivered green ammonia displaces conventional natural-gas-based ammonia. Results indicated that SC3 is the most favourable configuration under the adopted assumptions, while overall project viability remained highly sensitive to PtA sizing, ammonia market value, operational flexibility, and the assumed infrastructure cost structure. Full article

Background/Objectives: Acute myeloid leukemia (AML) comprises a heterogeneous group of diseases, with some subtypes displaying promyelocytic features and altered differentiation programs. Aberrant cytokine receptor signaling has been implicated in leukemogenesis, and IL-5Rα has recently emerged as a potential marker in selected AML subsets, including promyelocytic variants. Benralizumab is a monoclonal antibody directed against the alpha chain of the interleukin-5 receptor (CD125), which blocks IL-5Rα–mediated signaling. This proof-of-concept study aimed to explore the effects of the anti-IL-5Rα monoclonal antibody Benralizumab in an in vitro AML cell model with promyelocytic characteristics. Methods: Public transcriptomic datasets were analyzed to evaluate IL-5Rα expression in AML subtypes. HL-60 cells, an AML cell line expressing IL-5Rα, were treated with Benralizumab and analyzed for cell cycle distribution and modulation of key signaling and apoptotic pathways by flow cytometry and Western blotting. Results: IL-5Rα was highly expressed in AML, particularly in M2 and M3 subtypes. Benralizumab treatment reduced STAT3 expression, activated ERK and NF-κB signaling, induced p21 and p27 expression, altered cell cycle distribution, and induced caspase-8 cleavage, suggesting activation of extrinsic apoptotic signaling. Conclusions: These findings provide preliminary proof-of-concept evidence that IL-5Rα targeting by Benralizumab may directly affect cell survival and cell cycle regulation in AML cells with promyelocytic characteristics. When interpreted together with the in silico analyses performed on AML patient datasets, these results support the rationale for future validation in APL-oriented models carrying the PML::RARα fusion, the disease-defining oncogenic driver generated by the t(15;17) translocation that blocks myeloid differentiation. However, the in silico and in vitro datasets were not formally integrated at the patient level, and these functional results should be considered exploratory. Full article

Accurate time-domain photovoltaic (PV) models are needed to evaluate performance under outdoor variability beyond STC datasheet conditions. This paper presents a traceable modeling workflow based on the standard single-diode formulation, implemented in MATLAB/Simulink (R2023a) as a modular white-box architecture that explicitly resolves photocurrent generation and loss mechanisms (diode recombination, shunt leakage, and series resistance effects) with temperature-consistent propagation through $V_T\left(T\right)$ and saturation-current terms. The method couples optical boundary conditions to the electrical model by embedding plane-of-array (POA) excitation via the incidence angle $\theta \left(t\right)$ and roof albedo directly into the photocurrent source term, preserving the causal chain from mounting geometry to electrical response. Calibration is separated from prediction by initializing key parameters using the standard Simulink PV block and then freezing them for time-domain evaluation. The workflow is validated on a 395 W rooftop prototype using 1 min resolved POA irradiance (ISO 9060:2018 Class A radiometric chain) and module temperature (IEC 60751 Class A Pt100), synchronized with electrical measurements. Over a multi-week campaign, the model exhibits high fidelity, with a worst-case relative current error of ~1.1% and a consistently low bias and dispersion, quantified by ME, MAE, RMSE, ${\sigma }_e$, and thresholded MAPE. Full article

In blockchain–IPFS-based systems, full nodes maintain complete ledger replicas, whereas light nodes retain only essential information such as block headers to reduce storage and computation overhead. Due to the absence of full data replicas, light nodes are unable to support full-data queries, which limits their applicability in practical financial data sharing scenarios. Moreover, conventional blockchain storage mechanisms rely on synchronous confirmation across multiple nodes, resulting in limited throughput and poor responsiveness under high-concurrency and burst-traffic conditions. To address these issues, this paper proposes a blockchain–IPFS-based storage and query scheme for banking credit data that integrates multi-level caching, non-blocking asynchronous processing, and a Cuckoo filter–based lightweight query mechanism. The proposed scheme enables light nodes to efficiently verify the existence of credit files and retrieve associated metadata without maintaining complete ledger replicas, while a coordinated caching–asynchronous architecture decouples user requests from on-chain and off-chain persistence operations to improve system throughput and robustness. A prototype system is implemented and evaluated under varying file sizes and concurrency levels. Experimental results show that, for files smaller than 100 MB, the proposed scheme reduces storage latency by approximately 35–99% and improves query response time by more than 95%, compared with conventional blockchain–IPFS-based solutions. In addition, download latency is reduced by 20–31% for small and medium-sized files. The results further confirm that the proposed approach effectively supports full-data queries for light nodes and demonstrates strong resilience under burst traffic conditions, indicating its practical feasibility for secure financial credit data sharing. Full article

In classic communication systems, signals and data were mostly continuous in time, such as voice (fixed and mobile telephony, and radio systems) and video signals (Television services), Conversely, in modern communication systems, most signals are packet-based (text and images in messaging services and social media) and even continuous-time data has to be converted into a discrete-time nature data, such as video and voice services that are now discretized to be sent in packet-based communication systems. However, these classic communication systems were analyzed, studied, and designed using continuous-time analysis, such as the classic Erlang-B formula. This classic analysis can still be used in modern systems, but a discrete-based framework provides a seamless analysis and yields more accurate results. In this work, the effect of the system’s elementary time step is analyzed, and guidelines for its selection are provided to adequately analyze continuous-time systems within a discrete-time framework. To demonstrate the utility of the discretization and to consider these guidelines, we developed a mathematical analysis based on a discrete-time Markov chain to study a system with a buffer capacity under conventional and bursty traffic, which is commonly found in an Internet of Things application. The derived formulas allow us to quantify system performance under a discrete framework. This, in turn, allows us to provide some relevant guidelines for the elementary time step selection to adequately analyze continuous-time systems under a discrete-time framework. Full article

Isolated pelvic nodal metastasis from carcinoma of unknown primary origin (CUP) is rare. Evaluation should prioritize gynecological and anorectal sites based on pelvic lymphatic drainage. Although spontaneous regression of these primary lesions is exceptional, regressed lesions can present as CUP, necessitating diagnostic caution. Here, we report the case of a 40-year-old woman with a solitary, intensely fluorodeoxyglucose F-18 avid left obturator lymph node and a subtle endocervical abnormality on pelvic magnetic resonance imaging. Loop electrosurgical excision revealed a Nabothian cyst only. Excisional nodal biopsy by polymerase chain reaction revealed metastatic squamous cell carcinoma with diffuse block-type p16 and human papillomavirus (HPV) 16. Considering the potential for a primary cervical tumor along the obturator drainage pathway, the patient underwent hysterectomy with pelvic lymph node dissection. No residual invasive carcinoma was found; however, HPV16 was detected in the cervix with a low-grade squamous intraepithelial lesion, supporting a regressed cervical focus. She received adjuvant cisplatin-based chemoradiotherapy and has remained disease-free for 56 months. This case highlights the diagnostic value of integrating lymphatic anatomy with the molecular profile of HPV. Cervical squamous cell carcinoma rarely regresses and presents solely as an isolated nodal disease. Full article

This study proposed an innovative assembled blast-resistant composite structure integrating ultra-high performance concrete plates and ceramic foam layers, designed to enhance blast protection for a power valve hall hole blocking system. Based on the full-scale blast test and numerical simulation, the dynamic response of the structure under blast load was revealed. The parametric studies showed that when the thickness of the UHPC ribbed plate was increased from 30 mm to 40 mm, the maximum displacement at the edge of the hole was reduced by 60.9%. However, a further increase in thickness to 50 mm led to an increase in the inertia effect due to the high stiffness, resulting in a reduction in the maximum displacement value by only 8.61%. In addition, a machine learning framework combining generative adversarial networks (GANs) and Extremely Randomized Trees (ERT) model was constructed to predict the maximum displacement of the structure under blast loading. Furthermore, interpretability analysis by the (SHapley Additive exPlanations) SHAP algorithm verified the consistency of the decision logic of the ERT model with the physical mechanism of the explosion. This study established a full-chain design framework of structural design, mechanism research and intelligent prediction, which provided theoretical support and an intelligent tool system for protection engineering. Full article

Enhancing the solubility and processability of graphene remains a critical challenge, limiting its integration into advanced materials systems. In this work, poly(tert-butyl acrylate) (PtBA) and poly(N-isopropyl acrylamide) (PNIPAM) were grafted onto graphene via controlled atom transfer radical polymerization (ATRP) to create well-defined polymer–graphene hybrids with tunable interfacial properties. ATRP enabled the synthesis of PtBA and PNIPAM homopolymers with narrow molecular weight distributions and systematically varied chain lengths (4–18 kDa), allowing direct correlation between polymer architecture and material performance. Notably, the thermos-responsive behavior of PNIPAM was strongly dependent on chain length, highlighting the importance of controlled polymer design. Raman and FTIR spectroscopy confirmed successful grafting and chemical modification of the graphene surface. In addition, pilot studies demonstrate the ATRP synthesis of PtBA-b-PNIPAM block copolymers and their hydrolysis to PAA-b-PNIPAM, providing a platform for future development of multifunctional graphene interfaces. Overall, this study establishes a versatile and precisely controlled route for engineering polymer-grafted graphene with enhanced solubility and tunable functionality, enabling broader applications in smart materials and hybrid nanocomposites. Full article

Background: Blockchain technology has emerged as a transformative communication solution for securing distributed systems. However, several vulnerabilities exist during transactions, including latency and network congestion issues during mempool processing, topology weaknesses, cross-chain bridge exploits, and cryptographic weaknesses. These vulnerabilities have led to attacks that have threatened system integrity, including Block Extractable Value (BEV) attacks, Maximal Extractable Value (MEV) attacks, sandwich attacks, liquidation, and Decentralized Finance (DeFi) reordering attacks, among others. Thus, implementing a robust security framework based on the Confidentiality, Integrity, and Availability (CIA) triad remains critical for addressing modern blockchain technology threats. Objective: This paper examines blockchain technology, its various vulnerabilities, and attacks to determine how criminals exploit the system during transactions. Further, it evaluates its impact on users. Then, implement a blockchain attack in a “MasterChain” virtual environment to demonstrate how vulnerable spots can be practically exploited and discuss the application of the CIA security triad through modern cryptographic primitives. Methods: The approach considers Hevner’s design science framework, which emphasizes creating innovative artifacts that address identified problems while contributing to the knowledge base through rigorous evaluation. Furthermore, we developed a MasterChain tool using Python with Flask for distributed node communication, utilizing the Elliptic Curve Digital Signature Algorithm (ECDSA) with the Standards for Efficient Cryptography Prime 256-bit Koblitz curve 1 (secp256k1) for digital signatures and Secure Hash Algorithm 3 (SHA-3) (Keccak-256) hashing for block integrity. Results: show how the CIA has been implemented to provide secure communication through ECDSA-based transactions, SHA-3 chain integrity verification, and a multi-node distributed architecture, respectively. The performance analysis shows that ECDSA provides 256-bit security with 64-byte signatures compared to 2048-bit Rivest–Shamir–Adleman (RSA)’s 256-byte signatures, achieving a 75% reduction in bandwidth overhead. SHA-3 provides immunity to length extension attacks while maintaining equivalent collision resistance to SHA-256. Conclusions: The MasterChain framework provides a practical foundation for implementing blockchain security that addresses both classical and emerging vulnerabilities. The adoption of ECDSA and SHA-3 (Keccak-256) positions the system favourably for modern blockchain applications, while providing insights into the cryptographic trade-offs between performance, security, and compatibility. Full article

The development of high-performance biocomposites based on poly vinyl alcohol (PVA) and lignin is often hindered by the limited interfacial compatibility. Herein, we reporte a synchronized crosslinking strategy to seamlessly integrate lignin and PVA into a uniform and robust composite film. The vinyl groups were introduced into both lignin and PVA molecular chains, which enable the formation of dense covalent bonds through reactions between these unsaturated carbon–carbon double bonds. This dual network structure combining covalent crosslinking with hydrogen bonding effectively strengthened the interfacial compatibility between lignin and PVA, which substantially enhanced film toughness, exhibiting an elongation at break of up to 4300%. Furthermore, the prepared composite film also demonstrated outstanding UV-blocking efficiency (>90%), strong antioxidant activity (82% DPPH scavenging), enhanced hydrophobicity (water contact angle of 97.9°), and improved thermal stability. The dramatic enhancements were attributed to the homogeneous dispersion of modified lignin within the covalently bonded network, which ensured efficient stress transfer and reduced the availability of hydrophilic groups. This synchronized crosslinking approach presents a versatile and effective route for fabricating high-value lignin-based composite materials. Full article

Filled elastomers often exhibit a low-frequency power-law storage modulus (G-prime), yet quantitative links between molecular interfacial structure and macroscopic reinforcement remain unresolved. This gap is addressed using a hierarchical multiscale framework that integrates coarse-grained molecular dynamics (MD) and dynamic mechanical analysis (DMA). Overall, MD contributes transferable structural descriptors rather than direct macro-rheology prediction. MD simulations yield a bound-layer scaling relation for chain length $N=50$ in coarse-grained simulations serving as a structural probe. For EPDM master curves, the single-phase fractional Maxwell model is statistically preferred (Delta AICc > 147, n = 56), reflecting limited statistical power; larger datasets (e.g., PC/ABS, n = 952) favor the dual-phase formulation. For cross-scale prediction, an MD-derived effective-volume-fraction baseline (MAPE = 54.1%) provides a structural prior; the regime-partitioned bridge model absorbs relaxation physics not resolved at the MD scale, reducing error to 7.3% (blocked-CV MAPE = 9.5%, with a 2.3% fold-to-fold spread). Linear-viscoelastic constraints improve nonlinear PTT calibration, reducing die-swell error by 87%. Full article

This study reports the synthesis and catalytic evaluation of a series of imidazolium-based polymeric ionic liquids (PILs) for the cycloaddition of CO₂ to epichlorohydrin (ECH). The synthesized catalysts include homopolymers, poly(3-hydroxyethyl-1-vinylimidazole chloride) (p[HVIm][Cl]) and poly(3-carboxymethyl-1-vinylimidazole chloride) (p[CMVIm][Cl]), and their block copolymers with polystyrene, synthesized for the first time, pS-b-p[HVIm][Cl] and pS-b-p[CMVIm][Cl]. Structural characterization by NMR, IR spectroscopy, and gel permeation chromatography confirmed the successful synthesis. The block copolymers exhibited a low polydispersity index (PDI 1.1–1.2), which is indicative of homogeneous chain lengths and the propensity to form ordered nanostructures, whereas the homopolymers showed higher PDI (2.4–2.9). Catalytic testing at 90 °C and 1 MPa CO₂ for 4 h revealed a clear activity trend: p[CMVIm][Cl] < p[HVIm][Cl] < pS-b-p[CMVIm][Cl] < pS-b-p[HVIm][Cl], with conversions exceeding 75% for all catalysts and a maximum of 82.69% for pS-b-p[HVIm][Cl]. These results demonstrate that the catalytic performance of PILs is governed by a synergistic interplay between the local chemical functionality of the ionic moiety and the overall polymer architecture. Based on these results, the synthesized polymeric ionic liquids, particularly pS-b-p[HVIm][Cl], demonstrate strong potential for creating multifunctional materials. Their ability to self-assemble into ordered nanostructures with distinct hydrophobic and hydrophilic domains provides a foundational architecture for combined gas separation and catalysis. The observed “micellar catalytic effect”, which enhances local reagent concentration near active sites, could be leveraged in a membrane reactor to simultaneously capture and convert CO₂ directly within the membrane. This integrated “separation–reaction” approach represents a promising strategy for advancing circular carbon economy technologies. Full article

Polytetrafluoroethylene (PTFE) is attractive for high-frequency communications but adheres very poorly to other materials due to its very low surface energy. Conventionally, surface treatments of PTFE are used to increase the polarity of the PTFE surface and enable bonding to materials with increased surface free energy. However, surface treatments are difficult to scale, can damage surfaces, and often lack reproducibility. Therefore, developing a material that can make PTFE adhere well to other materials without surface treatment is highly desirable. In this study, we aimed to develop a new material with strong adhesion to PTFE. We synthesized three polymer gels from dodecyl acrylate (DA) and 2-(dimethylamino) ethyl acrylate (DMAE): the homopolymer gels PDEAE and PDA, and the copolymer gel P(DEAE-co-DA). The copolymer gel P(DEAE-co-DA) exhibited high pressure-sensitive adhesion to PTFE, recording the highest adhesive strength (F = 430.0 N/m) and the highest peel energy (G = 713.4 J/m²) compared to the homopolymer gels PDEAE and PDA. Mechanical testing showed PDEAE had the greatest strength and toughness, PDA balanced stiffness and extensibility, and P(DEAE-co-DA) was the most flexible and extensible. The P(DEAE-co-DA) with the smoothest surface (Sz ≈ 0.176 µm) showed the highest F and G, implying that surface roughness did not contribute significantly to the interfacial adhesion between the gels and the PTFE. Based on the surface free energy ${\sigma }_s$ and work of adhesion $W_a$ values, the adhesive strength to PTFE was predicted to be PDEAE > P(DEAE-co-DA) > PDA, but the measured G in peel tests contradicted this, indicating that the gels’ viscoelastic deformation and energy dissipation dominate the measured F and G. The frequency-dependent viscoelastic data and relaxation times τ and activation energies $E_a$ suggested optimal adhesion requires a balance of adhesion (mobility for energy dissipation (short τ, low $E_a$)) and sufficient cohesion (high G′). P(DEAE-co-DA) achieved this balance, explaining its high measured F and G. With precise control of polymer chain mobility, the adhesion of P(DEAE-co-DA) gels can likely be improved further. Future work will employ block copolymerization and monomer-ratio control to tune molecular motion and enhance adhesion to PTFE. Full article

Atomic oxygen in low Earth orbit erodes polyimide, increasing surface roughness and degrading performance. The reactive species scission polymer chains and remove surface material, exposing fresh sites that accelerate further attack and disrupt thermal, electrical, and mechanical functions. In this paper, we evaluate nanoscale reinforcements of polyimide with graphene and metal oxides under controlled atomic oxygen exposure equivalent to 145 days at a 550 km orbit. Graphene with a thickness of few nanometers and particle size less than 2 µm, and metal oxides zirconia, zinc oxide, and titania with particle size less than 100 nm were investigated. Hybrids containing graphene plus metal oxide at a 1:1 ratio and a total loading of 0.75 wt% increased roughness relative to neat polyimide, with graphene-zirconia showing a rise of +121 percent, graphene-zinc oxide +10 percent, and graphene–titania +20 percent. The behavior is consistent with agglomeration, incomplete dispersion, and interfacial mismatch that hinder uniform blocking of atomic oxygen and limit formation of protective oxygenated groups. In contrast, single-filler composites at 0.75 wt% reduced average roughness, with graphene lowering S_a by about 59 percent, zirconia by about 51%, titania by about 47%, and zinc oxide by about 47%. Varying graphene loading from 0.25 to 0.75 wt% diminished erosive features at the higher end, but atomic force microscopy revealed isolated tall peaks at 0.75 wt%, indicating localized restacking or agglomeration. Mechanical testing of graphene-reinforced coatings on fiberglass showed a similar trade-off, with tensile strength around 23 MPa and peak load greater than 50 N at 0.5 wt% compared to about 21 MPa and 40 N at 0.75 wt%, while strain at break remained comparable. These results define practical limits for nanoparticle reinforcement in polyimide, linking filler identity, loading, and dispersion quality to atomic oxygen response and sustained function in LEO. Full article