Targeted Demand Response: Formulation, LMP Implications, and Fast Algorithms

Demand response (DR) is regarded as a solution to the issue of high electricity prices in the wholesale market, as the flexibility of the demand can be harnessed to lower the demand level for price reductions. As an across-the-board DR in a system is impractical due to the enrollment budget for instance, it is necessary to select a small group of nodes for DR implementing. Current studies resort to intuitive yet naive approaches for DR targeting, as price is implicitly associated with demand, though optimality cannot be ensured. In this paper, we derive such a relationship in the security-constrained economic dispatch via the multi-parametric programming theory, based on which the DR targeting problem is rigorously formulated as a mixed-integer quadratic programming problem aiming at reducing the averaged price to a reference level by efficiently reducing targeted nodes' demand. A solution strategy is proposed to accelerate the computation. Numerical studies demonstrate compared with the benchmarking strategy, the proposed approach can reduce the price to the reference point with less efforts in demand reduction. Besides, we empirically show that the proposed approach is immune to inaccurate system parameters, and can be generalized to variants of DR targeting tasks.Comment: submitted to IEEE Transactions on Power System

Space and social life : morphological self-evolution of urban villages in Hangzhou

"Village in city" is a unique phenomenon in the process of China's rapid urbanization. As the concentrated embodiment of urban-rural conflicts in the period of urban transformation, urban villages have received extensive attention in the physical space and social security issues. They seem chaotic, but contain rich and colourful social life. They are vibrant communities, which provide a large number of cheap houses for the migrants. Different from modern cities or traditional villages, individuals of different classes and backgrounds constantly compete and cooperate here, forming a unique "community of social life" in urban villages. Based on the perspective of urban morphology, this paper takes Gaotang community, a typical urban village in Hangzhou as the research object, and analyses the relationship between its spatial pattern and social life through field investigation, interview and mapping. Firstly, this paper analyses the texture and public space characteristics of the self-evolution of urban villages in the context of urbanization. Then it insights the life integration of different population based on the environment-behaviour studies, which shows the daily life scenes and neighbourhood relations in a richer spatial level. The research will help to better understand the role of urban village as a social life community carrying a variety of lives. At the same time, the richness and complexity of urban village space and social life provide design strategies and reference for urban organic renewal and future community construction

Outsourcing Information Security: The Role of Information Leakage in Outsourcing Decisions

Emerging research regarding the economics of outsourcing information security recommends that firms utilize full outsourcing due to its cost advantages but ignore the risk of information leakage. In our model, we take the information leakage into account, and show that it is necessary for firm to assess the risk before outsourcing. Next, we divide a firm’s business operations into core business and non-core business operations and introduce a partial outsourcing strategy. We find that the security quality of partial outsourcing is always lower. Subsequently, we demonstrate the conditions for selecting from among three security strategies, i.e., in-house development, partial outsourcing and full outsourcing. Based on our results, in high-risk information leakage environments, we do not recommend outsourcing. We further demonstrate that outsourcing security of non-core business is an alternative strategy when the risk of information leakage is not high. A firm should shift from outsourcing to developing security protection in-house as the percentage of information assets utilized for core business increases. In addition, our results show that outsourcing information security of only core business is a strictly dominated strategy

Trifolirhizin relieves renal injury in a diabetic nephropathy model by inducing autophagy and inhibiting oxidative stress through the regulation of PI3K/AKT/mTOR pathway

Purpose: To evaluate the effects of trifolirhizin on diabetic nephropathy (DN), and the mechanism of action. Methods: Male db/db mice (8 weeks, n = 24) and age-matched control mice (n = 6) were obtained. The mice were further divided into four groups and administered increasing doses of trifolirhizin (0, 12.5, 25 and 50 mg/kg). Histological analysis of renal tissues were performed by H & E staining. Blood urea nitrogen (BUN) and creatinine were determined using enzyme-linked immunosorbent assay (ELISA). Immunoblot and TUNEL assay were performed to investigate the effect of trifolirhizin on autophagy and apoptosis, while ELISA and dihydroethidium (DHE) staining were conducted to evaluate reactive oxygen species (ROS), malondialdehyde (MDA) and superoxide dismutase (SOD) levels. The effect of trifolirhizin on PI3K/AKT/mTOR pathway was determined using Immunoblot assays. Results: Trifolirhizin alleviated renal injury in diabetic mice, and also activate autophagy and inhibited apoptosis in the renal tissues in diabetic mice (p < 0.001). In addition, trifolirhizin inhibited the oxidative stress response in the renal tissue in diabetic mice (p < 0.001). Trifolirhizin further inhibited PI3K/AKT/mTOR pathway and therefore relieved renal injury in the diabetic nephropathy model (p < 0.001). Conclusion: Trifolirhizin alleviates renal injury in diabetic mice, activates autophagy, and inhibits apoptosis in renal tissue of diabetic mice. Therefore, trifolirhizin is a promising a promising drug for the treatment of DN

Blockchain Network Analysis: A Comparative Study of Decentralized Banks

Decentralized finance (DeFi) is known for its unique mechanism design, which applies smart contracts to facilitate peer-to-peer transactions. The decentralized bank is a typical DeFi application. Ideally, a decentralized bank should be decentralized in the transaction. However, many recent studies have found that decentralized banks have not achieved a significant degree of decentralization. This research conducts a comparative study among mainstream decentralized banks. We apply core-periphery network features analysis using the transaction data from four decentralized banks, Liquity, Aave, MakerDao, and Compound. We extract six features and compare the banks' levels of decentralization cross-sectionally. According to the analysis results, we find that: 1) MakerDao and Compound are more decentralized in the transactions than Aave and Liquity. 2) Although decentralized banking transactions are supposed to be decentralized, the data show that four banks have primary external transaction core addresses such as Huobi, Coinbase, Binance, etc. We also discuss four design features that might affect network decentralization. Our research contributes to the literature at the interface of decentralized finance, financial technology (Fintech), and social network analysis and inspires future protocol designs to live up to the promise of decentralized finance for a truly peer-to-peer transaction network

Hardness of Graph-Structured Algebraic and Symbolic Problems

In this paper, we study the hardness of solving graph-structured linear systems with coefficients over a finite field $\mathbb{Z}_p$ and over a polynomial ring $\mathbb{F}[x_1,\ldots,x_t]$. We reduce solving general linear systems in $\mathbb{Z}_p$ to solving unit-weight low-degree graph Laplacians over $\mathbb{Z}_p$ with a polylogarithmic overhead on the number of non-zeros. Given the hardness of solving general linear systems in $\mathbb{Z}_p$ [Casacuberta-Kyng 2022], this result shows that it is unlikely that we can generalize Laplacian solvers over $\mathbb{R}$, or finite-element based methods over $\mathbb{R}$ in general, to a finite-field setting. We also reduce solving general linear systems over $\mathbb{Z}_p$ to solving linear systems whose coefficient matrices are walk matrices (matrices with all ones on the diagonal) and normalized Laplacians (Laplacians that are also walk matrices) over $\mathbb{Z}_p$. We often need to apply linear system solvers to random linear systems, in which case the worst case analysis above might be less relevant. For example, we often need to substitute variables in a symbolic matrix with random values. Here, a symbolic matrix is simply a matrix whose entries are in a polynomial ring $\mathbb{F}[x_1, \ldots, x_t]$. We formally define the reducibility between symbolic matrix classes, which are classified in terms of the degrees of the entries and the number of occurrences of the variables. We show that the determinant identity testing problem for symbolic matrices with polynomial degree $1$ and variable multiplicity at most $3$ is at least as hard as the same problem for general matrices over $\mathbb{R}$.Comment: 57 pages, submitted version to STOC2

HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models

Theory of Mind (ToM) is the ability to reason about one's own and others' mental states. ToM plays a critical role in the development of intelligence, language understanding, and cognitive processes. While previous work has primarily focused on first and second-order ToM, we explore higher-order ToM, which involves recursive reasoning on others' beliefs. We introduce HI-TOM, a Higher Order Theory of Mind benchmark. Our experimental evaluation using various Large Language Models (LLMs) indicates a decline in performance on higher-order ToM tasks, demonstrating the limitations of current LLMs. We conduct a thorough analysis of different failure cases of LLMs, and share our thoughts on the implications of our findings on the future of NLP.Comment: Accepted at Findings of EMNLP 202