An ADMM-based Distributed Optimization Method for Solving Security-Constrained AC Optimal Power Flow

In this paper, we study efficient and robust computational methods for solving the security-constrained alternating current optimal power flow (SC-ACOPF) problem, a two-stage nonlinear optimization problem with disjunctive constraints, that is central to the operation of electric power grids. The first-stage problem in SC-ACOPF determines the operation of the power grid in normal condition, while the second-stage problem responds to various contingencies of losing generators, transmission lines, and transformers. The two stages are coupled through disjunctive constraints, which model generators' active and reactive power output changes responding to system-wide active power imbalance and voltage deviations after contingencies. Real-world SC-ACOPF problems may involve power grids with more than 30k buses and 22k contingencies and need to be solved within 10-45 minutes to get a base case solution with high feasibility and reasonably good generation cost. We develop a comprehensive algorithmic framework to solve SC-ACOPF that meets the challenge of speed, solution quality, and computation robustness. In particular, we develop a smoothing technique to approximate disjunctive constraints into a smooth structure which can be handled by interior-point solvers; we design a distributed optimization algorithm to efficiently generate first-stage solutions; we propose a screening procedure to prioritize contingencies; and finally, we develop a reliable and parallel architecture that integrates all algorithmic components. Extensive tests on industry-scale systems demonstrate the superior performance of the proposed algorithms

Exploring Trust in Online Ride-sharing Platform in China: A Perspective of Time and Location

Trust is a key issue to be considered deliberately in the online ride-sharing platform to reduce risk and ensure transactions. In this paper, trust-in-platform is explored from these two perspectives to fill the research gaps. A ride-sharing platform in China was investigated. Results show that trust-in-platform in economically developing districts is slightly higher than that in economically developed districts. At the same time, trust-in-platform level differs in time, trust-in-platform levels are obviously lower between 19’o clock and 23’o clock. Moreover, machine learning is employed to predict the relationships between time/location and trust-in-platform. The result is that recall is 78.3%, precision is 57.3%, and F1 is 66.2%. The result shows trust-in-platform has an obvious correlation with time and location, thus further consolidates the findings. This study contributes to the existing knowledge on trust in the ride-sharing platforms and has practical implications for platform operators

Hybrid nodal surface and nodal line phonons in solids

Phonons have provided an ideal platform for a variety of intriguing physical states, such as non-abelian braiding and Haldane model. It is promising that phonons will realize the complicated nodal states accompanying with unusual quantum phenomena. Here, we propose the hybrid nodal surface and nodal line (NS+NL) phonons beyond the single genre nodal phonons. We categorize the NS+NL phonons into two-band and four-band situations based on symmetry analysis and compatibility relationships. Combing database screening with first-principles calculations, we identify the ideal candidate materials for realizing all categorized NS+NL phonons. Our calculations and tight-binding models further demonstrate that the interplay between NS and NL induces unique phenomena. In space group 113, the quadratic NL acts as a hub of the Berry curvature between two NSs, generating ribbon-like surface states. In space group 128, the NS serve as counterpart of Weyl NL that NS-NL mixed topological surface states are observed. Our findings extend the scope of hybrid nodal states and enrich the phononic states in realistic materials.Comment: 23+35 pages, 5+44 figures, 1+3 table

Missense VKOR mutants exhibit severe warfarin resistance but lack VKCFD via shifting to an aberrantly reduced state

Missense vitamin K epoxide reductase (VKOR) mutations in patients cause resistance to warfarin treatment but not abnormal bleeding due to defective VKOR activity. The underlying mechanism of these phenotypes remains unknown. Here we show that the redox state of these mutants is essential to their activity and warfarin resistance. Using a mass spectrometry-based footprinting method, we found that severe warfarin-resistant mutations change the VKOR active site to an aberrantly reduced state in cells. Molecular dynamics simulation based on our recent crystal structures of VKOR reveals that these mutations induce an artificial opening of the protein conformation that increases access of small molecules, enabling them to reduce the active site and generating constitutive activity uninhibited by warfarin. Increased activity also compensates for the weakened substrate binding caused by these mutations, thereby maintaining normal VKOR function. The uninhibited nature of severe resistance mutations suggests that patients showing signs of such mutations should be treated by alternative anticoagulation strategies

Inductive Meta-path Learning for Schema-complex Heterogeneous Information Networks

Heterogeneous Information Networks (HINs) are information networks with multiple types of nodes and edges. The concept of meta-path, i.e., a sequence of entity types and relation types connecting two entities, is proposed to provide the meta-level explainable semantics for various HIN tasks. Traditionally, meta-paths are primarily used for schema-simple HINs, e.g., bibliographic networks with only a few entity types, where meta-paths are often enumerated with domain knowledge. However, the adoption of meta-paths for schema-complex HINs, such as knowledge bases (KBs) with hundreds of entity and relation types, has been limited due to the computational complexity associated with meta-path enumeration. Additionally, effectively assessing meta-paths requires enumerating relevant path instances, which adds further complexity to the meta-path learning process. To address these challenges, we propose SchemaWalk, an inductive meta-path learning framework for schema-complex HINs. We represent meta-paths with schema-level representations to support the learning of the scores of meta-paths for varying relations, mitigating the need of exhaustive path instance enumeration for each relation. Further, we design a reinforcement-learning based path-finding agent, which directly navigates the network schema (i.e., schema graph) to learn policies for establishing meta-paths with high coverage and confidence for multiple relations. Extensive experiments on real data sets demonstrate the effectiveness of our proposed paradigm

Evidence for Majorana bound state in an iron-based superconductor

The search for Majorana bound state (MBS) has recently emerged as one of the most active research areas in condensed matter physics, fueled by the prospect of using its non-Abelian statistics for robust quantum computation. A highly sought-after platform for MBS is two-dimensional topological superconductors, where MBS is predicted to exist as a zero-energy mode in the core of a vortex. A clear observation of MBS, however, is often hindered by the presence of additional low-lying bound states inside the vortex core. By using scanning tunneling microscope on the newly discovered superconducting Dirac surface state of iron-based superconductor FeTe1-xSex (x = 0.45, superconducting transition temperature Tc = 14.5 K), we clearly observe a sharp and non-split zero-bias peak inside a vortex core. Systematic studies of its evolution under different magnetic fields, temperatures, and tunneling barriers strongly suggest that this is the case of tunneling to a nearly pure MBS, separated from non-topological bound states which is moved away from the zero energy due to the high ratio between the superconducting gap and the Fermi energy in this material. This observation offers a new, robust platform for realizing and manipulating MBSs at a relatively high temperature.Comment: 27 pages, 11 figures, supplementary information include

New treatment methods for myocardial infarction

For a long time, cardiovascular clinicians have focused their research on coronary atherosclerotic cardiovascular disease and acute myocardial infarction due to their high morbidity, high mortality, high disability rate, and limited treatment options. Despite the continuous optimization of the therapeutic methods and pharmacological therapies for myocardial ischemia–reperfusion, the incidence rate of heart failure continues to increase year by year. This situation is speculated to be caused by the current therapies, such as reperfusion therapy after ischemic injury, drugs, rehabilitation, and other traditional treatments, that do not directly target the infarcted myocardium. Consequently, these therapies cannot fundamentally solve the problems of myocardial pathological remodeling and the reduction of cardiac function after myocardial infarction, allowing for the progression of heart failure after myocardial infarction. Coupled with the decline in mortality caused by acute myocardial infarction in recent years, this combination leads to an increase in the incidence of heart failure. As a new promising therapy rising at the beginning of the twenty-first century, cardiac regenerative medicine provides a new choice and hope for the recovery of cardiac function and the prevention and treatment of heart failure after myocardial infarction. In the past two decades, regeneration engineering researchers have explored and summarized the elements, such as cells, scaffolds, and cytokines, required for myocardial regeneration from all aspects and various levels day and night, paving the way for our later scholars to carry out relevant research and also putting forward the current problems and directions for us. Here, we describe the advantages and challenges of cardiac tissue engineering, a contemporary innovative therapy after myocardial infarction, to provide a reference for clinical treatment