The paper deals with the second order regularity properties of the weak solutions u∈Wloc1,ϕ(Ω,Rn) of systems of the form−divA(x,Eu)=f,in a bounded domain Ω⊂Rn, n ≥ 2, where the operator A(x, P) is Lipschitz continuous with respect to the x-variable and satisfies growth conditions with respect to the second variable expressed through a Young function Φ. We prove the Sobolev regularity of a function of the symmetric gradient Eu that takes into account the nonlinear growth of the operator A(x, P), assuming that the inhomogeneity f belongs to a suitable Orlicz-Sobolev space. The main result is achieved through some uniform higher differentiability estimates for solutions to a class of approximating problems, constructed adding singular higher order perturbations to the system.
Global use of materials has significantly increased over recent decades, causing a wide range of environmental and social concerns. In this study, we use the latest available data from the UN database on global material flows to investigate the Environmental Kuznets Curve (EKC) hypothesis for two widely used material flow indicators, Domestic Material Consumption and Material Footprint, for a dataset of 147 countries. Using both semiparametric and parametric methods over a longer period than any previous study (1970–2019), we find no evidence in support of the EKC hypothesis. A concerning result is that material-income elasticities are higher after 1989, implying that the situation has not improved. We conclude that major changes have not yet occurred in the income-material use relationship and that strong policy measures remain necessary to reduce material consumption.
Self-Sovereign Identity (SSI) is widely positioned as the decentralized future of digital identity. However, although traditional SSI literature emphasizes architecture and privacy, it largely overlooks a systematic analysis of how trust is formed, propagated, and managed. Trust is fundamental because, without it, the actions performed by key actors, including credential issuers, lose much of their practical value. In this landscape, trust is the ground on which SSI systems stand; when that ground is absent or unstable, any structure built on it crumbles. Against this backdrop, we chart the landscape of trust through a comprehensive survey of Trust Models (TMs) and Trust Management Systems (TMSs) in SSI. At the abstract level, we analyze TMs by examining the types of trust relationships among SSI actors and how trust is defined and represented. At the implementation level, we discuss TMSs in terms of how trust is represented, stored, and protected in the systems proposed in the literature. We analyzed 26 sources (24 peer-reviewed papers plus the Sovrin whitepaper and governance framework document), consolidated into 24 approaches, benchmarking 16 features across these dimensions. Based on this analysis, we identify five open challenges: enabling cross-chain trust portability; designing a hybrid TM that blends Web of Trust and hierarchies; supporting heterogeneous actors such as IoT devices and humans; implementing privacy-preserving feedback mechanisms; and TM and TMS interoperability in emerging settings, including delegated AI agents. Our analysis offers a compass to guide researchers and developers in selecting trust models and advancing SSI systems.
Growing interest in sustainable bio-lubricants as alternatives to conventional mineral oils has increased the demand for renewable feedstocks that do not compete with agricultural land use. In this study, waste cooking oil (WCO) was chemically modified through transesterification/partial hydrogenation (H-FAME), partial hydrogenation (H-WCO_l and H-WCO), estolide formation (E-WCO), and epoxidation (EOs) followed by ethanol ringopening (POs) to produce potential bio-lubricants. The thermal, physicochemical, and rheological properties of the resulting products were evaluated and compared with a commercial mineral lubricant (ISO VG 46), representative of oils used in industrial hydraulic systems. Tribological tests were performed as a preliminary comparative screening to determine friction and wear behaviour under selected pin-on-disc conditions. The WCO-derived products exhibited a broad range of properties depending on the applied chemical modification. Most samples showed thermal stability in air equal to or greater than ISO VG 46. Rheological analysis over 25-100 degrees C revealed Newtonian behaviour for H-FAME and POs, while E-WCO and EOs exhibited shearthinning behaviour, indicating fluid-like and grease-like structures, respectively. Kinematic viscosity at 40 degrees C ranged from 3.61 to 286 cSt, with polyols (POs) displaying viscosity indices between 111 and 133, exceeding that of ISO VG 46 (107). Friction coefficients were similar across all samples, although WCO, H-WCO_l, and H-WCO showed slightly lower values. Wear testing demonstrated comparable or reduced wear for E-WCO and almost fully epoxidized oil (EO_100) relative to ISO VG 46. These results highlight the potential of WCO-derived products as sustainable bio-lubricant candidates with tuneable properties, while further tribological testing under varied load, speed, and temperature conditions will be required to assess their application-specific performance.
Open-set recognition (OSR) of low-probability-of-interception (LPI) radar signals is challenging in noncooperative environments. Due to parameter variations and low signal-to-noise ratios (SNRs), LPI radar features often exhibit multimodal structures. This limits conventional single-center representations, leading to loose acceptance regions and increased false acceptance of unknown samples. To address this issue, this paper devises a feature-space multi-center framework for OSR of LPI radar signals. It represents each known class with multiple local prototypes and a shared within-class covariance matrix to capture complex intra-class distributions. A consistency-driven filtering mechanism calibrates the rejection boundary using validation data, while a class-level prototype configuration strategy adapts model complexity to heterogeneous class structures. Experiments on a simulated LPI radar signal dataset across a wide SNR range show that our solution outperforms several representative baseline approaches in terms of the area under the receiver operating characteristic curve (AU-ROC) and the false positive rate at a 95% true positive rate (FPR@95%TPR). At an SNR of-6 dB, the proposed method achieves an FPR@95%TPR of 19.09% and an AUROC of 92.11%, indicating effective discrimination under noise-dominated conditions. These results indicate the potential of the proposed method for handling complex intra-class structures in OSR of LPI radar signals under simulated non-cooperative conditions.
