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In most electricity theft detection schemes, consumers' power consumption data is directly input into the detection center. Although it is valid in detecting the theft of consumers, the privacy of all consumers is at risk unless the detection center is assumed to be trusted. In fact, it is impractical. Moreover, existing schemes may result in some security problems, such as the collusion attack due to the presence of a trusted third party, and malicious data tampering caused by the system operator (SO) being attacked. Aiming at the problems above, we propose a blockchain-based privacy-preserving electricity theft detection scheme without a third party. Specifically, the proposed scheme uses an improved functional encryption scheme to enable electricity theft detection and load monitoring while preserving consumers' privacy; distributed storage of consumers' data with blockchain to resolve security problems such as data tampering, etc. Meanwhile, we build a long short-term memory network (LSTM) model to perform higher accuracy for electricity theft detection. The proposed scheme is evaluated in a real environment, and the results show that it is more accurate in electricity theft detection within acceptable communication and computational overhead. Our system analysis demonstrates that the proposed scheme can resist various security attacks and preserve consumers' privacy., Comment: 13 pages

Inspired by expert evaluation policy for urban perception, we proposed a novel inverse reinforcement learning (IRL) based framework for predicting urban safety and recovering the corresponding reward function. We also presented a scalable state representation method to model the prediction problem as a Markov decision process (MDP) and use reinforcement learning (RL) to solve the problem. Additionally, we built a dataset called SmallCity based on the crowdsourcing method to conduct the research. As far as we know, this is the first time the IRL approach has been introduced to the urban safety perception and planning field to help experts quantitatively analyze perceptual features. Our results showed that IRL has promising prospects in this field. We will later open-source the crowdsourcing data collection site and the model proposed in this paper., Comment: ACML2022 Camera-ready Version

Understanding of the complex mechanical behavior of metal-organic frameworks (MOF) beyond their elastic limit will allow the design of real-world applications in chemical engineering, optoelectronics, energy conversion apparatus, and sensing devices. Through in situ compression of micropillars, the uniaxial stress-strain curves of a copper paddlewheel MOF (HKUST-1) were determined along two unique crystallographic directions, namely the (100) and (111) facets. We show strongly anisotropic elastic response where the ratio of the Young's moduli are E(111) ~ 3.6 x E(100), followed by extensive plastic flows. Likewise, the yield strengths are considerably different, in which Y(111) ~ 2 x Y(100) because of the underlying framework anisotropy. We measure the fracture toughness using micropillar splitting. While in situ tests revealed differential cracking behavior, the resultant toughness values of the two facets are comparable, yielding Kc ~ 0.5 MPa m^1/2. This work provides new insights of porous framework ductility at the micron scale and failure by bonds breakage., Comment: 20 pages, 4 figures, Supplementary Information

Herein we employed high-resolution spectroscopic techniques in combination with periodic ab initio density functional theory (DFT) calculations to establish the different polarization processes for a porous copper-based MOF, termed HKUST-1. We used alternating current measurements to determine its dielectric response between 4 Hz and 1.5 MHz where orientational polarization is predominant, while synchrotron infrared (IR) reflectance was used to probe the far-IR, mid-IR, and near-IR dielectric response across the 1.2 THz to 150 THz range (ca. 40 - 5000 cm^-1) where vibrational and optical polarizations are principal contributors to its dielectric permittivity. We demonstrate the role of pressure on the evolution of broadband dielectric response, where THz vibrations reveal distinct blue and red shifts of phonon modes from structural deformation of the copper paddle-wheel and the organic linker, respectively. We also investigated the effect of temperature on dielectric constants in the MHz region pertinent to microelectronics, to study temperature-dependent dielectric losses via dissipation in an alternating electric field. The DFT calculations offer insights into the physical mechanisms responsible for dielectric transitions observed in the experiments and enable us to explain the frequency shifts phenomenon detected under pressure. Together, the experiments and theory have enabled us to glimpse into the complex dielectric response and mechanisms underpinning a prototypical MOF subject to pressure, temperature, and vast frequencies., Comment: 20 pages, 6 figures, plus Supporting Information

We present the frequency-dependant (dynamic) dielectric response of a group of topical polycrystalline zeolitic imidazolate-based metal-organic framework (MOF) materials in the extended infrared spectral region. Using synchrotron-based FTIR spectroscopy in specular reflectance, in conjunction with density functional theory (DFT) calculations, we have revealed detailed structure-property trends linking the THz region dielectric response to framework porosity and structural density. The work demonstrates that MOFs are promising candidate materials not only for low-\k{appa} electronics applications but could also be pioneering for terahertz (THz) applications, such as next-generation broadband communications technologies., Comment: 6 pages, 5 figures