Nacre-Inspired,Liquid Metal-Based Ultrasensitive Electronic Skin by Spatially Regulated Cracking Strategy

The realization of liquid metal-based wearable systems will be a milestone toward high-performance, integrated electronic skin. However, despite the revolutionary progress achieved in many other components of electronic skin, liquid metal-based flexible sensors still suffer from poor sensitivity due to the insufficient resistance change of liquid metal to deformation. Herein, a nacre-inspired architecture composed of a biphasic pattern (liquid metal with Cr/Cu underlayer) as “bricks” and strain-sensitive Ag film as “mortar” is developed, which breaks the long-standing sensitivity bottleneck of liquid metal-based electronic skin. With 2 orders of magnitude of sensitivity amplification while maintaining wide (>85%) working range, for the first time, liquid metal-based strain sensors rival the state-of-art counterparts. This liquid metal composite features spatially regulated cracking behavior. On the one hand, hard Cr cells locally modulate the strain distribution, which avoids premature cut-through cracks and prolongs the defect propagation in the adjacent Ag film. On the other hand, the separated liquid metal cells prevent unfavorable continuous liquid-metal paths and create crack-free regions during strain. Demonstrated in diverse scenarios, the proposed design concept may spark more applications of ultrasensitive liquid metal-based electronic skins, and reveals a pathway for sensor development via crack engineering.     

A Voltage Control Method for a Distributed Line Feeder by means of Multiagent Approach

This paper proposes a method for the coordinated control of power factor by means of a multiagent approach. The proposed multiagent system consists of two types of agent: single feeder agent (F_AG) and bus agent (B_AG). In the proposed system, an F_AG plays as an important role, which decides the power factors of all distributed generators by executing the load flow calculations repeatedly. The voltage control strategies are implemented as the class definition of Java into the system. In order to verify the performance of the proposed method, it has been applied to a typical distribution model system. The simulation results show that the system is able to control very violent fluctuation of the demands and the photovoltaic (PV) generations.     

Magnetic Resonance Signal Amplification by Reversible Exchange of Selective PyFALGEA Oligopeptide Ligands Towards Epidermal Growth Factor Receptors

The biorelevant PyFALGEA oligopeptide ligand, which is selective towards the epidermal growth factor receptor (EGFR), has been successfully employed as a substrate in magnetic resonance signal amplification by reversible exchange (SABRE) experiments. It is demonstrated that PyFALGEA and the iridium catalyst IMes form a PyFALGEA:IMes molecular complex. The interaction between PyFALGEA:IMes and H₂ results in a ternary SABRE complex. Selective 1D EXSY experiments reveal that this complex is labile, which is an essential condition for successful hyperpolarization by SABRE. Polarization transfer from parahydrogen to PyFALGEA is observed leading to significant enhancement of the ¹H NMR signals of PyFALGEA. Different iridium catalysts and peptides are inspected to discuss the influence of their molecular structures on the efficiency of hyperpolarization. It is observed that PyFALGEA oligopeptide hyperpolarization is more efficient when an iridium catalyst with a sterically less demanding NHC ligand system such as IMesBn is employed. Experiments with shorter analogues of PyFALGEA, that is, PyLGEA and PyEA, show that the bulky phenylalanine from the PyFALGEA oligopeptide causes steric hindrance in the SABRE complex, which hampers hyperpolarization with IMes. Finally, a single-scan ¹H NMR SABRE experiment of PyFALGEA with IMesBn revealed a unique pattern of NMR lines in the hydride region, which can be treated as a fingerprint of this important oligopeptide.     

On recommendation problems beyond points of interest

Recommendation systems aim to recommend items or packages of items that are likely to be of interest to users. Previous work on recommendation systems has mostly focused on recommending points of interest (POI), to identify and suggest top-k items or packages that meet selection criteria and satisfy compatibility constraints on items in a package, where the (packages of) items are ranked by their usefulness to the users. As opposed to prior work, this paper investigates two issues beyond POI recommendation that are also important to recommendation systems. When there exist no sufficiently many POI that can be recommended, we propose (1) query relaxation recommendation to help users revise their selection criteria, or (2) adjustment recommendation to guide recommendation systems to modify their item collections, such that the users׳ requirements can be satisfied.We study two related problems, to decide (1) whether the query expressing the selection criteria can be relaxed to a limited extent, and (2) whether we can update a bounded number of items, such that the users can get desired recommendations. We establish the upper and lower bounds of these problems, all matching, for both combined and data complexity, when selection criteria and compatibility constraints are expressed in a variety of query languages, for both item recommendation and package recommendation. To understand where the complexity comes from, we also study the impact of variable sizes of packages, compatibility constraints and selection criteria on the analyses of these problems. Our results indicate that in most cases the complexity bounds of query relaxation and adjustment recommendation are comparable to their counterparts of the basic recommendation problem for testing whether a given set of (resp. packages of) items makes top-k items (resp. packages). In other words, extending recommendation systems with the query relaxation and adjustment recommendation functionalities typically does not incur extra overhead.     

Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.     

Structural Cues for Understanding eEF1A2 Moonlighting

Spontaneous mutations in the EEF1A2 gene cause epilepsy and severe neurological disabilities in children. The crystal structure of eEF1A2 protein purified from rabbit skeletal muscle reveals a post-translationally modified dimer that provides information about the sites of interaction with numerous binding partners, including itself, and maps these mutations onto the dimer and tetramer interfaces. The spatial locations of the side chain carboxylates of Glu301 and Glu374, to which phosphatidylethanolamine is uniquely attached via an amide bond, define the anchoring points of eEF1A2 to cellular membranes and interorganellar membrane contact sites. Additional bioinformatic and molecular modeling results provide novel structural insight into the demonstrated binding of eEF1A2 to SH3 domains, the common MAPK docking groove, filamentous actin, and phosphatidylinositol-4 kinase IIIβ. In this new light, the role of eEF1A2 as an ancient, multifaceted, and articulated G protein at the crossroads of autophagy, oncogenesis and viral replication appears very distant from the “canonical” one of delivering aminoacyl-tRNAs to the ribosome that has dominated the scene and much of the thinking for many decades.