Search

The set of degrees of maps D(M,N), where M,N are closed oriented n-manifolds, always contains 0 and the set of degrees of self-maps D(M) always contains 0 and 1. Also, if a,b\in D(M), then ab\in D(M); a set A\subseteq \mathbb {Z} so that ab\in A for each a,b\in A is called multiplicative. On the one hand, not every infinite set of integers (containing 0) is a mapping degree set (Neofytidis, Wang, and Wang [Bull. Lond. Math. Soc. 55 (2023), pp. 1700–1717]) and, on the other hand, every finite set of integers (containing 0) is the mapping degree set of some 3-manifolds (Costoya, Muñoz and Viruel [ Finite sets containing zero are mapping degree sets , arXiv: 2301.13719 ]). We show the following: Not every multiplicative set A containing 0,1 is a self-mapping degree set. For each n\in \mathbb {N} and k\geq 3, every D(M,N) for n-manifolds M and N is D(P,Q) for some (n+k)-manifolds P and Q. As a consequence of (ii) and Costoya, Muñoz and Viruel, every finite set of integers (containing 0) is the mapping degree set of some n-manifolds for all n\neq 1,2,4,5. [ABSTRACT FROM AUTHOR]

This study applied the nonlinear ultrasonic method, second harmonic generation, to precisely estimate the state of charge (SoC) in lithium-ion batteries. The second harmonic of the longitudinal wave is generated on a pouch cell battery at 5 MHz with a through-transmission setup. The relative nonlinear parameter β ′ is determined by analyzing the amplitudes at the fundamental and second harmonic frequencies. To enhance the nonlinear parameter's measurement accuracy, multiple excitation amplitudes are employed. Two separate charge/discharge tests (four-cycle and eight-cycle) are conducted on the battery at a rate of C/10. The nonlinear parameter is measured periodically during the charge/discharge process, and temperature compensation is applied to the measurement. The correlation curves between the nonlinear parameter and the actual SoC align well for the four-cycle and eight-cycle tests, and a robust linear relationship is observed for both correlation curves. A linear model and a second-order polynomial model are applied to fit the correlation using all data points from both tests. The two models are employed to validate the SoC prediction on a second battery by using a four-cycle test. The results indicate that both models can predict the SoC with an accuracy of approximately 3%, whereas the polynomial model demonstrates smaller errors in the regions near 0% and 100% SoC. Therefore, the nonlinear parameter β ′ , measured through the second harmonic generation, can effectively predict lithium-ion battery SoC with an accuracy of less than 3%. [ABSTRACT FROM AUTHOR]

Nonlinear acoustic methods demonstrate high sensitivity for concrete damage evaluation. Among these methods, nonlinear resonance acoustic methods have been widely used in laboratory tests on small scale test samples. In this study, a nonlinear impact-echo (IE) method for concrete damage evaluation was introduced, in which the IE frequency shift was measured at different impact force levels. The nonlinear IE test and the nonlinear impact resonance acoustic spectroscopy (NIRAS) test share similarities in the experimental setup and analysis method. However, the nonlinear IE test excites a local thickness resonance mode of a member instead of the global resonance vibration. Therefore, the analyzed mode is unaffected by member boundary conditions and is applicable to large concrete structural members. To identify the fundamental IE frequencies, multiple impacts were applied along the members. Once the fundamental IE frequencies were determined, the effectiveness of the nonlinear IE method was evaluated by testing seven concrete beam specimens with varying levels of alkali-silica reaction (ASR) damage. The nonlinear IE test demonstrates high sensitivity to concrete damage and allows for quantitative assessment of the damage state of concrete without a baseline measurement. [ABSTRACT FROM AUTHOR]

For any closed oriented 3‐manifold M$M$ with positive simplicial volume and any closed oriented 3‐manifold N$N$, we prove that there exists a finite cover M′$M^{\prime }$ of M$M$ that admits a degree‐1 map f:M′→N$f:M^{\prime }\rightarrow N$, that is, M$M$ virtually 1‐dominates N$N$. This result generalizes previous virtual domination results with closed hyperbolic domain to more general domains. [ABSTRACT FROM AUTHOR]

This work is conducted to deal with the information security of enterprise management under the background of current global informatization, popularize the modern Internet of Things (IoT) management technology of enterprises, and maintain the information security of enterprises and provide modern upgrading means for enterprise management. In this work, it firstly introduces the application scenarios of current Internet and Artificial Intelligence (AI) technology and expounds the IoT technology. Secondly, the enterprise management platform is designed, the requirements of enterprise modern management are analyzed, and then the design requirements of system functions and the design of the information security architecture of the IoT are proposed. Furthermore, an enterprise information security management platform is designed, which covers four parts: IoT data mining management, equipment management, key management, and database management. In addition, the performance of the security management platform is tested from four parts: concurrency testing, stress testing, large data volume testing, and security testing. The research results show that the IoT-based enterprise information security management platform designed in this work under the background of AI has perfect functions and stable performance of each module. Concurrency testing, stress testing, large data volume testing, and stability testing are performed on it, and the success rate of the platform in each task reaches 100%. The average response time of concurrent testing and stress testing is about 0.13 seconds, and that of the event entry events is 0.25 seconds. The central processing unit (CPU) occupancy rate in each monitoring task is always lower than 20%. Therefore, it is determined that the performance of the IoT-based enterprise information security management platform designed in this work is sufficient to meet the daily management of enterprises. This work can provide a guarantee for enterprise information security management using AI technology, setting an example for future related research. [ABSTRACT FROM AUTHOR]

As an efficient way to integrate multiple distributed energy resources (DERs) and the user side, a microgrid is mainly faced with the problems of small-scale volatility, uncertainty, intermittency and demand-side uncertainty of DERs. The traditional microgrid has a single form and cannot meet the flexible energy dispatch between the complex demand side and the microgrid. In response to this problem, the overall environment of wind power, thermostatically controlled loads (TCLs), energy storage systems (ESSs), price-responsive loads and the main grid is proposed. Secondly, the centralized control of the microgrid operation is convenient for the control of the reactive power and voltage of the distributed power supply and the adjustment of the grid frequency. However, there is a problem in that the flexible loads aggregate and generate peaks during the electricity price valley. The existing research takes into account the power constraints of the microgrid and fails to ensure a sufficient supply of electric energy for a single flexible load. This paper considers the response priority of each unit component of TCLs and ESSs on the basis of the overall environment operation of the microgrid so as to ensure the power supply of the flexible load of the microgrid and save the power input cost to the greatest extent. Finally, the simulation optimization of the environment can be expressed as a Markov decision process (MDP) process. It combines two stages of offline and online operations in the training process. The addition of multiple threads with the lack of historical data learning leads to low learning efficiency. The asynchronous advantage actor–critic (Memory A3C, M-A3C) with the experience replay pool memory library is added to solve the data correlation and nonstatic distribution problems during training. The multithreaded working feature of M-A3C can efficiently learn the resource priority allocation on the demand side of the microgrid and improve the flexible scheduling of the demand side of the microgrid, which greatly reduces the input cost. Comparison of the researched cost optimization results with the results obtained with the proximal policy optimization (PPO) algorithm reveals that the proposed algorithm has better performance in terms of convergence and optimization economics. [ABSTRACT FROM AUTHOR]

Transmission lines' condition monitoring is an important part of smart grid construction. To ensure fast and efficient transmission of data, many mash-based wireless networks devices are adopted to collect status information. Since these nodes are exposed to the natural environment, vulnerable to damage, so it is very necessary to be predicting nodes' fault. However, these mesh nodes are affected by a variety of complex and time-series factors, and traditional models are difficult to achieve effective failure prediction. To solve this problem, this paper proposes a self-adapting multi-LSTM ensemble regression model for transmission line network's wireless mesh node failure prediction (MLSTM-FP), through establishes the corresponding relationship between similar time factors and LSTMs, the proposed model can realize multi time series data self-adapting and accurate failure prediction of transmission line network's wireless mesh nodes, The experimental results show that the proposed method has a good prediction ability than traditional methods. [ABSTRACT FROM AUTHOR]

In-memory error correction code (ECC) is a promising technique to improve the yield and reliability of high density memory design. However, the use of in-memory ECC poses a new problem to memory repair analysis algorithm, which has not been explored before. This article first makes a quantitative evaluation and demonstrates that the straightforward algorithms for memory with redundancy and in-memory ECC have serious deficiency on either repair rate or repair analysis speed. Accordingly, an optimal repair analysis algorithm that leverages preprocessing/filter algorithms, hybrid search tree, and depth-first search strategy is proposed to achieve low computational complexity and optimal repair rate in the meantime. In addition, a heuristic repair analysis algorithm that uses a greedy strategy is proposed to efficiently find repair solutions. Experimental results demonstrate that the proposed optimal repair analysis algorithm can achieve optimal repair rate and increase the repair analysis speed by up to 105 × compared with the straightforward exhaustive search algorithm. The proposed heuristic repair analysis algorithm is approximately 28 percent faster than the proposed optimal algorithm, at the expense of 5.8 percent repair rate loss. [ABSTRACT FROM AUTHOR]

Introduction: The two‐pore domain potassium channel TREK‐1 is a member of background K+ channels that are thought to provide baseline regulation of membrane excitability. Recent studies have highlighted the putative role of TREK‐1 in the action of antidepressants, and its antagonists might be potentially effective antidepressants. However, the mechanisms underlying the actions of TREK‐1 are not yet fully understood. Methods: The expression of TREK‐1 was examined in a mouse model of chronic unpredictable mild stress (CUMS) using immunoblotting. Neuron‐specific genetic manipulation of TREK‐1 was performed through adeno‐associated virus. Behavioral tests were performed to evaluate depression‐related behaviors. Electrophysiological recordings were used to evaluate synaptic plasticity. Golgi staining was used to examine neuroplasticity. Results: TREK‐1 expression was increased in the mouse hippocampus after CUMS. Knockdown of TREK‐1 in hippocampal neurons significantly attenuated depressive‐like behaviors and prevented the decrease of CUMS‐induced synaptic proteins in mice. Further examination indicated that neuron‐specific knockdown of TREK‐1 in the hippocampus prevented stress‐induced impairment of glutamatergic synaptic transmission in the CA1 region. Moreover, chronic TREK‐1 inhibition protected against CUMS‐induced depressive‐like behaviors and impairment of synaptogenesis in the hippocampus. Conclusion: Our results indicate a role for TREK‐1 in the modulation of synaptic plasticity in a mouse model of depression. These findings will provide insight into the pathological mechanism of depression and further evidence for a novel target for antidepressant treatment. [ABSTRACT FROM AUTHOR]

In this paper, we compute the subgroup distortion of all finitely generated subgroups of all finitely generated 3-manifold groups, and the subgroup distortion in this case can only be linear, quadratic, exponential and double exponential. It turns out that the subgroup distortion of a subgroup of a 3-manifold group is closely related to the separability of this subgroup. [ABSTRACT FROM AUTHOR]

This study presents a test method and its theoretical framework to determine the acoustic nonlinearity parameters (α , β , δ) of material using thermal modulation of ultrasonic waves. Temperature change-induced thermal strain excites the nonlinear response of the material and modulates the ultrasonic wave propagating in it. Experimental results showed a strong correlation between the relative wave velocity change and the temperature change. With a quadratic polynomial model, the acoustic nonlinearity parameters were obtained from the polynomial coefficients by curve fitting the experimental data. Their effects on thermal-induced velocity change were discussed. The parameters α , β , and δ govern the hysteretic gap, average slope, and curvature of the correlation curve, respectively. The proposed theory was validated on aluminum, steel, intact and damaged concrete samples. The obtained nonlinear parameters show reasonable agreement with values reported in the literature. Compared to other nonlinear acoustic methods using vibration or acoustic excitation, the thermal modulation method generates more uniform, slow changing, and larger strain field in the test sample. Employing the thermal effect as the driving force for nonlinearity instead of an undesired influencing factor, this method can measure the absolute values of α , β , and δ with good accuracy using a simple ultrasonic test setup. [ABSTRACT FROM AUTHOR]

In this paper, we give a complete characterization on which finitely generated subgroups of finitely generated 3-manifold groups are separable. Our characterization generalizes Liu's spirality character on surface subgroups of closed 3-manifold groups. A consequence of our characterization is that, for any compact, orientable, irreducible and ∂ -irreducible 3-manifold M with nontrivial torus decomposition, π1(M) is locally extended residually finite if and only if for any two adjacent pieces in the torus decomposition of M, at least one of them has a boundary component with genus at least 2. [ABSTRACT FROM AUTHOR]

Due to the private ownerships of various resource and equipment in a microgrid, it is essential to design a proper power trading strategy for a mutually satisfying partnership among suppliers and users. This paper proposes a novel discounted min-consensus algorithm to discover the optimal electrical power trading route with minimal power loss in dc microgrids. The proposed distributed algorithm only requires information exchange among neighbors based on a peer-to-peer communication protocol, which is robust to topology changes and enables parallel data processing to achieve fast decision-making. The convergence and optimality of the proposed discounted min-consensus algorithm are guaranteed by rigorous analysis. Simulation results of the 10-bus, 68-bus, and 1062-bus power systems demonstrate the effectiveness of the proposed distributed optimal routing strategy for electrical power trading. Moreover, the proposed novel distributed algorithm sheds light on applying distributed control and optimization approaches to solve problems arising in artificial intelligence. [ABSTRACT FROM AUTHOR]

Transmission–distribution coordinated energy management (TDCEM) is recognized as a promising solution to the challenge of high distributed energy resource (DER) penetration, but there is a lack of a distributed computation method that universally and effectively works for the TDCEM. To bridge this gap, this paper presents a generalized master–slave-splitting (G-MSS) method. This method is based on a general-purpose transmission–distribution coordination model called G-TDCM, which enables the G-MSS to be applicable to most of the central functions of the TDCEM. In this G-MSS method, a basic heterogeneous decomposition (HGD) algorithm is first derived from the heterogeneous decomposition of the coupling constraints in the optimality conditions of the G-TDCM. Its optimality and convergence properties are proved. Then, inspired by the sufficient conditions for convergence, a modified HGD algorithm that utilizes the subsystem's response function is developed and demonstrated to converge faster. The distributed G-MSS method is then demonstrated to successfully solve a series of central functions of the TDCEM, e.g., power flow, contingency analysis, voltage stability assessment, economic dispatch, and optimal power flow. The severe issues of over-voltage and erroneous assessment of the system security that are caused by DERs are thus resolved by the G-MSS method with modest computation cost. [ABSTRACT FROM AUTHOR]

In this paper, we review the emerging challenges and research opportunities for voltage control in smart grids. For transmission grids, the voltage control for accommodating wind and solar power, fault-induced delayed voltage recovery, and measurement-based Thévenin equivalent for voltage stability analysis are reviewed. For distribution grids, the impact of high penetration of distributed energy resources is analyzed, typical control strategies are reviewed, and the challenges for local inverter Volt–Var control is discussed. In addition, the motivation, state-of-the-art, and future directions of the coordination of transmission system operators (TSO) and distribution system operators (DSO) are also thoroughly discussed. [ABSTRACT FROM AUTHOR]

A nonlinear ultrasonic test is proposed for material damage evaluation using thermal modulation. Temperature change excites and modulates nonlinear behavior of ultrasonic waves in concrete. Coda wave interferometry was used to analyze the relative velocity change of ultrasonic wave with temperature variations. On concrete samples with different levels of thermal damage, experimental results indicate that the samples with a higher damage level demonstrated higher sensitivity to temperature variations. In addition, a slow dynamics nonlinear behavior was observed. When the temperature changed and then remained constant, the wave velocity gradually approached to its equilibrium value. [ABSTRACT FROM AUTHOR]

We prove that, for any two finite volume hyperbolic 3‐manifolds, the amalgamation of their fundamental groups along any nontrivial infinite index geometrically finite subgroup is not LERF (locally extended residually finite). This generalizes the author's previous work on nonLERFness of amalgamations of hyperbolic 3‐manifold groups along abelian subgroups. A consequence of this result is that, for all closed arithmetic hyperbolic 4‐manifolds have nonLERF fundamental groups. Along with the author's previous work, we obtain that, for any arithmetic hyperbolic manifold with dimension at least 4, with possible exceptions in seven‐dimensional manifolds defined by the octonion, its fundamental group is not LERF. [ABSTRACT FROM AUTHOR]

Large-scale datacenters are facing increasing pressure of capping their carbon emission and power cost. Many leading-edge studies have started to explore server clusters running on multiple power sources. Existing approaches do not sufficiently consider the fine-grained power delivery to satisfy diverse requirements in datacenter, especially in the multi-tenant/colocation datacenter, which may yield low energy utilization. To address the emerging trend and new requirements, this article proposes a novel Datacenter inner Power Switch Network (DiPSN) to improve datacenter power efficiency and user satisfaction.DiPSNis a reconfigurable and easy-to-scale-out power architecture, which enables datacenter to distribute various power sources in a fine-grained manner. Moreover, a tailored machine learning based power source management framework is proposed forDiPSNto dynamically optimize user customized performance metrics and maximize datacenter revenue. Compared with conventional single-switch power distribution system, ourDiPSNcan be configured to improve solar energy utilization by 39.6 percent, reduce utility power cost by 11.1 percent and improve workload performance by 33.8 percent. Meanwhile, our design can extend battery lifetime by 9.3 percent. This work could provide valuable guidelines for designing heterogeneous power distribution architecture and management methodology in datacenters for improving user-customizable efficiency, sustainability and economy. [ABSTRACT FROM AUTHOR]

The control of an islanded AC microgrid with high penetration level of renewable generations is complicated and challenging due to its low inertia and fast changing operating conditions. To address the drawbacks of traditional droop control with low-voltage AC microgrid, an adaptive virtual impedance control is proposed to improve the active/reactive power sharing accuracy. To deal with the frequency and voltage deviation caused by the primary control while satisfying the fast response requirements and various users’ preferences, a flexible distributed control strategy is proposed as the secondary control. The proposed control strategy can restore the frequency and voltage magnitude to the desired values in a finite-time manner, using only local and neighboring information. The finite-time convergence of the proposed distributed control algorithm is guaranteed through rigorous analysis. Simulation studies validate the effectiveness and scalability of the proposed distributed control strategy. [ABSTRACT FROM PUBLISHER]

Distributed generations contribute to the supply diversity as well as competitiveness of the electric market. Electric power supplies and load users all seek to optimally allocate/utilize the energy to maximize their benefits. However, maximizing the social welfare should not be the sole objective since line congestion can lead to serious problems. This paper proposes a fully distributed solution to DC optimal power flow with congestion management. The objective is to maximize the social welfare, while maintaining the supply-demand balance and relieving transmission line congestion. The proposed algorithm only requires information exchange among neighboring participants which leads to simpler realization and less expenditure for communication network and powerful central controller comparing to traditional centralized algorithms. It is adaptive to topology changes and scalable to large systems. Simulation results of the 5-& IEEE 30-bus systems demonstrate the effectiveness of the proposed distributed algorithm and indicate its promising applications to the electric market. [ABSTRACT FROM AUTHOR]

Guided image filtering (GIF) is a promising edge-preserving filtering technique that has been applied in a variety of applications. Nevertheless, an efficient very-large-scale integration (VLSI) architecture design of GIF is still very challenging for the real-time processing of full-high definition videos. Previously proposed architectures are somewhat inefficient in terms of either on-chip memory usage or off-chip memory bandwidth. This paper aims to improve the balance between on-chip memory usage and off-chip memory bandwidth through architecture exploration. Three critical architectural tradeoffs in the VLSI design of GIF are explored, and two efficient VLSI architectures, namely sequential line-based and parallel line-based architectures, are proposed. Experimental results demonstrate that the proposed VLSI design only consumes 34.1-K logic gates, 25.4-KB on-chip memories, and 373-MB/s off-chip memory bandwidth while achieving a real-time video processing of 1080P@60Hz at the maximum clock frequency of 297-MHz. Moreover, the proposed VLSI circuits are fully pipelined and synchronized to the pixel clock of output video, so can be seamlessly integrated into diverse real-time video processing systems. [ABSTRACT FROM PUBLISHER]

Energy storage devices (ESD), such as UPS batteries, have been repurposed in datacenter as a promising tuning knob for peak power shaving and power cost reducing. However, batteries progressively aging due to irregular usage patterns, which result in less effective capacity and even pose serious threat to server availability. Nevertheless, prior proposals largely ignore the aging issues of battery which may lead to low energy availability for datacenter servers. To fill this critical void, we thoroughly investigate battery aging on a heavily instrumented prototype system over an observation period of ten months. We propose Battery Anti-Aging Treatment Plus (BAAT-P ), a novel power delivery architecture included aging management algorithms from the perspective of computing system to hide, reduce, mitigate and plan the battery aging effects for high energy availability in datacenter. Our techniques exploit diverse battery aging mechanisms and dynamic aging management algorithms to provide system-level availability guarantee for datacenter. We evaluate the BAAT-P design with a real prototype. Compared with a battery powered datacenter without aging management policies, the results show that BAAT-P can extend battery lifetime by 72 percent, reduce battery cost by 33 percent and effectively improve energy availability for datacenter servers while maintaining workload performance for the performance critical workloads. [ABSTRACT FROM AUTHOR]

Recent years have seen a substantial increase in the application of machine learning (ML) for automated analysis of nondestructive examination (NDE) data. One of the applications of interest is the use of ML for the analysis of data from in-service inspection of welds in nuclear power and other industries. These types of inspections are performed in accordance with criteria described in the ASME Boiler and Pressure Vessel Code and require the use of reliable NDE techniques. The rapid growth in ML methods and the diversity of possible approaches indicate a need to assess the current capabilities of ML and automated data analysis for NDE and identify any gaps or shortcomings in current ML technologies as applied to the automated analysis of NDE data. In particular, there is a need to determine the impact of ML on the NDE reliability. This paper discusses the findings from a literature survey on the current state of ML for the automated analysis of data from ultrasonic NDE of weld flaws. It discusses an overview of ultrasonic NDE as used for weld inspections in nuclear power and other industries. Data sets and ML models used in the literature are summarized, along with a generally applicable workflow for ML. Findings on the capabilities, limitations and potential gaps in feature selection, data selection, and ML model optimization are discussed. The paper identified several needs for quantifying and validating the performance of ML methods for ultrasonic NDE, including the need for common data sets. • Literature survey of machine learning for ultrasonic NDE of welding flaws. • Capability of machine learning for ultrasonic NDE. • Recommendations for research in machine learning for ultrasonic NDE reliability. [ABSTRACT FROM AUTHOR]

This paper presents methods for assessing the statistical interdependencies between solar irradiance and the outside temperature, which are used to assess the correspondence between the operation of technologies to meet the heat demands and the PV output. It is important to be able to assess the impact of heating technology changes and increased PV penetration on power system requirements. Considering the correlation between the PV outputs and heat loads, there exist multiple effects of weather variations on the “Source-Grid-Load.” Heat load, photovoltaic (PV), electric air conditioner (EC), natural gas-fuelled combined heat and power (CHP), and central heating boiler models are established to study the influences of the solar irradiance and the temperature of the outdoors. The energy dependence impacts on the “Source-Grid-Load” are simulated in a 41-bus distribution network, and the paper's results show how the correspondence between the temperature and solar irradiance can impact the system's requirements. [ABSTRACT FROM AUTHOR]

The evaluation of early age properties of concrete is critical for ensuring construction quality. This paper presents a sensing method to use ultrasonic guided waves in a rebar for monitoring the early age properties of cementitious material. An EMAT sensor was used to excite the longitudinal mode L(0,1) wave in a rebar embedded in cement/mortar, and an ultrasonic transducer was used for receiving the echo signals. Guided wave dispersion curves were developed to select appropriate frequency range. The leakage attenuations of the L(0,1) mode wave from the rebar to the surrounding cement materials were continuously monitored for the first 10 h. The evolution of the shear wave velocity was also monitored simultaneously. The leakage attenuation from experimental measurements was compared with the theory-predicted attenuation in both time and frequency domains, and showed good agreement. Experiments were performed on three cement paste samples and three mortar samples. The results indicated that attenuation is nearly linearly related to the shear wave velocity, and shear wave velocity is linearly related to the penetration resistance (ASTM C403) in logarithmic scale. These results suggest that mechanical properties and hardening process of cement materials can be monitored by using the ultrasonic guided waves in a rebar. [ABSTRACT FROM AUTHOR]

Currently, a custom-designed configuration of different renewable technologies named the integrated energy system (IES) has become popular due to its high efficiency, benefiting from complementary multi-energy technologies. This paper proposes an information entropy approach to quantify uncertainty in an integrated energy system based on a stochastic model that drives a power system model derived from an actual network on Barry Island. Due to the complexity of co-behaviours between generators, a copula-based approach is utilized to articulate the dependency structure of the generator outputs with regard to such factors as weather conditions. Correlation coefficients and mutual information, which are effective for assessing the dependence relationships, are applied to judge whether the stochastic IES model is correct. The calculated information values can be used to analyse the impacts of the coupling of power and heat on power flows and heat flows, and this approach will be helpful for improving the operation of IES. [ABSTRACT FROM AUTHOR]

High-quality and cost-efficient image upscaling design is very important for many real-time video processing applications, especially when the display panel resolution reaches ultrahigh definition. Compared with New Edge-Directed Interpolation (NEDI) based implicit edge directional upscaling, explicit methods require less computational resource and more easily reach real-time performance, especially when the required image definition and upscaling ratio are very high. Nevertheless, the investigation of applications of explicit methods in video processing systems remains largely missing arguably because it is commonly believed that explicit edge-directed interpolation tends to introduce unexpected artifacts because of inaccurate detection and hence its image quality is relatively poor. This paper proposes an explicit edge-directed adaptive interpolation method that leverages more sophisticated edge detection and orientation estimation algorithms to avoid misinterpolation, thereby providing similar or even better image quality than those with implicit methods. Targeting the real-time 4K video display system, the proposed edge-directed image upscaling algorithm is further implemented with an efficient very-large-scale integration (VLSI) architecture. The experimental results demonstrate that the proposed interpolation algorithm outperforms previous explicit and implicit edge-directed methods in both objective and subjective tests. The presented VLSI implementation further demonstrates that the maximum output video sequence of the proposed interpolation method can reach 4\mathrm k\times 2\textk @60 Hz with a reasonable hardware cost. [ABSTRACT FROM AUTHOR]

Accurately estimating the state of charge (SoC) in battery management systems (BMSs) requires the measurement of numerous parameters and advanced algorithms. This work studies multifrequency ultrasonic waves to estimate the SoC of Li-ion batteries by sensing the material changes during charge/discharge. A pouch-type LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) | | graphite battery cell is designed and fabricated with a capacity of 2.4 Ah. Different ultrasonic testing setups are explored to determine the optimal testing parameters for the battery. An ultrasonic monitoring system is developed to monitor the battery during charge/discharge at 750 kHz, 1 MHz, and 1.5 MHz. Signal processing algorithms are proposed for extracting three ultrasonic features—amplitude, wave velocity, and attenuation. In a three-cycle test, the amplitude histories do not show clear correlations with the SoC. The wave velocities of all three frequencies have an approximately linear relationship with the SoC, which can be used for SoC estimation. Hysteresis behavior is observed for the wave velocity in terms of a larger slope in the discharge process and velocity drop after a close charge/discharge cycle. The wave attenuation is able to capture the material phase transitions during charge/discharge. [Display omitted] • Ultrasonic waves are used for monitoring charge/discharge of Li-ion battery. • Longitudinal wave velocity is linearly related to state of charge. • Temperature effect on the velocity is related to state of charge. • Wave attenuation can capture the phase transitions during battery charge/discharge. [ABSTRACT FROM AUTHOR]

Sensors used for experiments in advanced reactors must survive in harsh environments. Few material systems can be used to construct sensors viable for extreme conditions. Aluminum nitride (AlN) is one such material because it has high thermal stability and radiation resistance and sustains good piezoelectric and dielectric properties at high temperatures. In this work, the piezoelectric coefficient d 33 of the AlN single-crystal with thermal and irradiation damage was investigated using an indirect method with a laser Doppler vibrometer (LDV). Surface electrodes were deposited on the AlN samples, and the vibration response of the samples to an applied voltage was monitored using the LDV as a function of the excitation frequency. The d 33 estimation was based on the excitation voltage and the thickness-mode displacement extracted from the LDV measurements. Six AlN substrates were irradiated with 8 MeV Al2＋ at three fluences (1015, 1016, and 1017 ions/cm 2) and two temperatures (300 ° C and 500 ° C). The d 33 for the six irradiated samples and one pristine sample were measured, and the measurement uncertainty was estimated based on five repeated tests. All samples were also measured by a commercial piezometer for comparison. The experimental results demonstrate that the piezoelectric coefficients obtained by LDV were about 0.8–1.16 pm/V lower than those obtained by the piezometer. With the compensation of the clamping effect, the corrected LDV values are similar to the piezometer results. Both show similar trends in all samples, which validates the feasibility of the proposed method for d 33 measurement. Based on the LDV results, the irradiated samples show a 12%–22% decrease in d 33 compared with the pristine samples. The samples irradiated under the same fluence at a higher temperature (500 °C) demonstrated a lower d 33 than those at 300 °C. The effect of the retro-reflective tape, sample temperature, and sample size on the d 33 measurement were also studied. [Display omitted] • Laser vibrometry is used for piezoelectric coefficient (d 33) measurement of AlN. • AlN single crystals are irradiated with Al2+ at three fluences and two temperatures. • AlN irradiated at a higher temperature shows a lower d 33. • The d 33 of irradiated AlN at 1017 and 500 °C is 22% lower than that of the pristine AlN. • The d 33 measured using laser vibrometry is validated by piezometer measurement. [ABSTRACT FROM AUTHOR]

[Display omitted] Vicagrel is a novel antiplatelet drug used to mitigate clopidogrel resistance due to CYP2C19 polymorphism. This study aimed to develop a semi-mechanistic population pharmacokinetic (PopPK) model to characterize the pharmacokinetic (PK) profile of M15-2, the active metabolite of vicagrel and clopidogrel, and to evaluate the influence of CYP2C19 polymorphisms and other covariates in healthy subjects and patients with acute coronary syndrome (ACS) after oral administration. The analysis utilized data from 213 subjects, including 178 healthy subjects and 35 patients, from five clinical trials. PopPK modeling and simulation were used to estimate PopPK parameters and evaluate the impact of covariates. The M15-2 PK profiles were well characterized by a model incorporating transit compartments, two-compartment parent models and two-compartment M15-2 models for both vicagrel and clopidogrel. The parameter estimates indicated the dose fraction of vicagrel that formed M15-2 was approximately 20-fold that of clopidogrel. Covariate analysis identified a significant effect of CYP2C19 on M15-2 apparent clearance (CL/F) and apparent volume of distribution (V3/F) for clopidogrel but only CL/F for vicagrel. The analysis suggested that the nonlinear PK of M15-2 for clopidogrel was due the first-step bioactivation of clopidogrel to 2-oxoclopidogrel. The model illustrated the bioactivation of vicagrel is more efficient and less dependent on CYP2C19 than that of clopidogrel. M15-2 is formed in a linear process from vicagrel, versus a nonlinear and less predictable process from clopidogrel. Advantages in both PK and pharmacogenetics suggest that vicagrel may reduce the complexity of currently recommended CYP2C19-based dosage adjustment for clopidogrel. [ABSTRACT FROM AUTHOR]

Datacenters, the essential infrastructures for supercomputing and cloud computing, are facing increasing pressure of capping tremendous power consumption and carbon emission. Many studies have proposed to leverage energy storage devices to shave peak power or smooth intermittent power for datacenters, respectively. However, a joint energy management of peak shaving and renewable energy harvesting in datacenters is still lacking. In this paper, we propose a new power management scheme named RE-UPS, which explores the opportunity to shave datacenter peak power demand with renewable energy. RE-UPS is based on the emerging distributed energy storage architecture and existing UPS infrastructure of datacenter. It further leverages a dynamic heuristic algorithm to determine the appropriate energy storage allocation and server power sources. The proposed energy management policies can greatly optimize the design among maximizing renewable energy harvest, shaving peak power, and maintaining UPS energy availability. Compared to the baseline power management schemes, RE-UPS can averagely improve backup energy capacity by 28 %, extend battery lifetime by 42 %, increase green energy utilization by 78 %, and reduce workload performance degradation by 13 %. [ABSTRACT FROM AUTHOR]

Energy-intensive enterprises (EIEs) are typical kinds of industrial loads. They consume large amounts of electricity, and are very sensitive to electricity prices. Moreover, they have very good schedulability: they own various adjustable devices and dispatchable self-owned generation units, and have great flexibility in making production decisions. The characteristics of EIEs make them potentially ideal for coordinating with power systems and gaining a win–win situation, especially when the renewable energy penetration rate is high. However, problems still remain as to how to organize this coordination. In this paper, we design a decomposed coordinative scheduling (DCS) approach in which independent EIEs and the system exchange information iteratively to achieve final settlements. Based on a general modeling of EIEs, we introduce a mathematical formulation for DCS. The corresponding algorithm is also provided. We compare DCS to other scheduling approaches in case studies. It shows that DCS can significantly improve the benefits of the two sides without harming the privacy of EIEs. [ABSTRACT FROM AUTHOR]

Two kinds of tin oxide (SnO 2 )/titanium oxide (TiO 2 ) composite materials have been synthesized and applied as electrodes in dye-sensitized solar cells (DSSCs) with high performance. The porous SnO 2 /TiO 2 material (PSTM) consisting of SnO 2 nanosheets cluster and TiO 2 nanoparticles (P25) shows a superior dye adsorption ability due to its large specific surface area (151.1 m 2 g −1 ). The PSTM based cell exhibits the slowest electron recombination rate among the cells tested from electrochemical impedance spectra measurements, and obtains final power conversion efficiency (PCE) up to 6.80%. Another novel structure of SnO 2 @TiO 2 hollow sphere (STHS) prepared via a facile water bath process is designed to improve the light utilization efficiency with its excellent light scattering ability. Though the charge recombination resistance of STHS (25.6 Ω) is smaller than that of P25 (30.6 Ω), the PCE of the DSSCs based on the former is 5.82%, showing over 9.2% increment than the latter (5.33%). This can be mainly ascribed to the enhanced light-harvesting ability and charge collection efficiency of the macroporous hollow sphere structure, both of which contribute to a higher short current density and hence for the better photovoltaic performance. Furthermore, we demonstrate a bilayered film of PSTM (charge conduction layer) and STHS (light scattering layer) as photoanode aiming to further improve the efficiency of DSSC by engineered integration of different promising materials. The results indicate that the PSTM+STHS based cell shows an obvious 14.6% increase of PCE (7.79% with a J sc of 17.49 mA cm −2 , V oc of 0.73 V and FF of 0.61) as compared to the single layered PSTM photoelectrode with the same thickness of ∼6.9 μm, providing the specific evidence for taking full advantages of the superior dye adsorption, fast charge collection as well as strong light harvesting simultaneously. Fundamentally, this study not only provides a scheme for the guidance of effective materials surface and interfacial modification, but also highlights the significance of the ideal photoanode configuration for high-efficiency solar cells application. [ABSTRACT FROM AUTHOR]

Participant selection is a fundamental challenge to perform sensing tasks with adequate data quality in various mobile crowdsensing (MCS) applications. In this paper, we explore participant selection mechanisms with sensing-gain constraints in MCS. First, we propose a novel quality-aware participant reputation model with active factors. Second, since user density differs in various applications, we propose two kinds of sensing-gain constrained participant selection mechanisms with both sufficient and insufficient user resources. Particularly, in the case of sufficient user resources, we formulate the sensing-gain objective on recruit cost and participant scale under constraints on data quality and task coverage, and propose a M ulti-S tage D ecision mechanism via G reedy strategy (MSD-G); in the case of insufficient user resources, we formulate the sensing-gain objective on data quality, abstract it as a 0-1 knapsack problem, and devise a S ensing-G ain C onstrained D ynamic P rogramming (SGC-DP) mechanism. Extensive simulations over a real-world dataset have verified that our participant reputation model with active factors can distinguish high-quality participants with different active levels, and our MSD-G and SGC-DP algorithms can effectively select suitable participants with ideal recruit budget and guaranteed data quality. [ABSTRACT FROM AUTHOR]

Power network modeling is traditionally performed in a centralized way, where the network components and topological relationships are manually modeled at control centers. However, in large-scale power systems, this conventional modeling approach can suffer from poor efficiency and inevitable human errors, which may affect the reliability of system models. Currently, the development of distributed applications requires detailed modeling of local systems and consistency between local and global models, which is not easy with conventional modeling. This paper presents a two-level distributed modeling approach that reflects the demands of distributed applications. It describes the processes of substation modeling, model transformation, and control center modeling. Using this modeling approach, substation models can be derived in a distributive manner at substations, while system models are automatically generated at control centers. This novel modeling approach not only adapts to the future architecture of power system operation, but it also overcomes the drawbacks of conventional modeling. In addition, it has been applied to a real power system, where it demonstrated high-efficiency performance. [ABSTRACT FROM AUTHOR]

Integration of high levels of wind power penetration is an important feature of the emerging smart transmission grid. To address the dramatic voltage fluctuations and wind turbine generators (WTGs) cascading trip faults, which have been greatly challenged the wind pool area's operation, a hierarchical automatic voltage control system to support wind power integration (Wind-AVC) is designed and presented in this paper. For each wind farm, an autonomous wind farm voltage controller (WFVC), which takes the details of the wind farm side grid into account, is applied to optimize the voltage and reactive power distribution inside the wind farm. Three different control modes are implemented to consider all the terminal voltages of WTGs as well as the dynamic Var reserves. A control center voltage controller (CCVC) is designed to coordinate all the distributed WFVCs. A security-constrained optimal power flow (SCOPF) based preventive control is presented, which ensures all the wind farms’ voltage satisfying the operational constraints for all the possible N − 1 scenarios. The Wind-AVC system has been put into operation in Northern China and was found to be effective in mitigating the voltage fluctuations and reducing the cascading trip risks. [ABSTRACT FROM AUTHOR]

The power industry in China has grown significantly over the past decade, spurring the adoption of system-wide automatic voltage control (AVC) technology to meet stricter requirements for security and economical power system operation. To cope with the rapidly developing and frequently changing Chinese power grid, an AVC scheme based on adaptive zone division is introduced in this paper. Logically, this type of system has a three-level hierarchical structure, but, here, both secondary voltage control (SVC) and tertiary voltage control (TVC) are implemented via software at the same control center. The control zones are no longer fixed but are reconfigured online and updated in accordance with variations in the grid structure. The technical details of these procedures are presented here. The implementation of TVC (which is based on an online reactive optimal power flow) and SVC are also discussed, together with some technical details on improvements to their reliability and robustness. Some results obtained from field-site applications based on similar-days testing rather than simulations are employed to evaluate the performance and improvements of the AVC system. This system has been installed at over 20 control centers in China. [ABSTRACT FROM PUBLISHER]

Abstract: 1,4-Diaryl-1,3-butadiynes react with cyclic amines, such as pyrrolidine, piperidine, and morpholine in the presence of a catalytic amount of CuCl to afford amino-substituted naphthalene derivatives with good to high yields. The new catalytic procedure provides an atom-economic, one-pot synthetic method for the synthesis of naphthalene derivatives from easily available 1,4-diaryl-1,3-butadiynes. [Copyright &y& Elsevier]

Abstract: Radiation-induced soft error has become an emerging reliability threat to high performance microprocessor design. As the size of on chip cache memory steadily increased for the past decades, resilient techniques against soft errors in cache are becoming increasingly important for processor reliability. However, conventional soft error resilient techniques have significantly increased the access latency and energy consumption in cache memory, thereby resulting in undesirable performance and energy efficiency degradation. The emerging 3D integration technology provides an attractive advantage, as the 3D microarchitecture exhibits heterogeneous soft error resilient characteristics due to the shielding effect of die stacking. Moreover, the 3D shielding effect can offer several inner dies that are inherently invulnerable to soft error, as they are implicitly protected by the outer dies. To exploit the invulnerability benefit, we propose a soft error resilient 3D cache architecture, in which data blocks on the soft error invulnerable dies have no protection against soft error, therefore, access to the data block on the soft error invulnerable die incurs a considerably reduced access latency and energy. Furthermore, we propose to maximize the access on the soft error invulnerable dies by dynamically moving data blocks among different dies, thereby achieving further performance and energy efficiency improvement. Simulation results show that the proposed 3D cache architecture can reduce the power consumption by up to 65% for the L1 instruction cache, 60% for the L1 data cache and 20% for the L2 cache, respectively. In general, the overall IPC performance can be improved by 5% on average. [Copyright &y& Elsevier]

The availability of synchro-phasor data has raised the possibility of a linear state estimator if the inputs are only complex currents and voltages and if there are enough such measurements to meet observability and redundancy requirements. Moreover, the new digital substations can perform some of the computation at the substation itself resulting in a more accurate two-level state estimator. The main contribution in this paper is that this two-level processing removes the bad data and topology errors, which are major problems today, at the substation level. [ABSTRACT FROM AUTHOR]

The availability of synchro-phasor data has raised the possibility of a linear state estimator if the inputs are only complex currents and voltages and if there are enough such measurements to meet observability and redundancy requirements. Moreover, the new digital substations can perform some of the computation at the substation itself resulting in a more accurate two-level state estimator. The main contribution in this paper is that this two-level processing removes the bad data and topology errors, which are major problems today, at the substation level. [ABSTRACT FROM AUTHOR]

Abstract: BRD7 is an important protein tightly associated with Nasopharyngeal carcinoma (NPC). Overexpression of BRD7 inhibits NPC cell growth and cell cycle by transcriptionally regulating the cell cycle related genes. BRD7 contains a bromodomain that is found in many chromatin-associated proteins and in nearly all known nuclear histone acetyltransferases (HATs) and plays an important role in chromatin remodeling and transcriptional activation. Here, we report the solution structure of BRD7 bromodomain determined by NMR spectroscopy, and its binding specificity revealed by NMR titration with several acetylated histone peptides. We find that BRD7 bromodomain contains the typical left-handed four-helix bundle topology, and can bind with weak affinity to lysine-acetylated peptides derived from histone H3 with K9 or K14 acetylated and from histone H4 with K8, K12 or K16 acetylated. Our results show that BRD7 bromodomain lacks inherent binding specificity when binding to histones in vitro. [Copyright &y& Elsevier]

Some important mechanisms in neuroendocrine-immune (NEI) system are inspired to design a decentralized, evolutionary, scalable, and adaptive system for Web service composition and management. We first abstract a novel intelligent network model inspired from the NEI system. Based on this model, we then propose a method for Web service emergence by designing a bio-entity as an autonomous agent to represent Web service. As such, automatic composition and dynamic management of Web services can be achieved. Also, we build its computation platform which allows the bio-entities to cooperate over Web services and exploits capabilities of their partners. Finally, the simulation results on the platform show that Web service emergence can be achieved through self-organizing, cooperating, and compositing. The proposed method provides a novel solution for intelligent composition and management of Web services. [Copyright &y& Elsevier]

Abstract: The semi-synthesis, in vitro and in vivo biological evaluation of corosolic acid (1) and maslinic acid (2) are described. Compounds 1 and 2 represent a new class of inhibitors of glycogen phosphorylases. Both 1 and 2 inhibit the increase of fasted plasma glucose of diabetic mice induced by adrenaline. It is therefore proposed that naturally occurring pentacyclic triterpenes 1 and 2 might reduce blood glucose, at least in part, through inhibiting hepatic glycogen degradation. [Copyright &y& Elsevier]

Abstract: Compounds that simultaneously combine charge and conformational features of glycosyltransfer transition states are of interest as transition state analog inhibitors. The synthesis of a central intermediate, cis-3a,6-dihydroxy-hexahydro-cyclopenta[b]pyrrol-2-one, which yielded a family of substituted cis-3a,6-dihydroxy-hexahydro-cyclopenta[b]pyrroles that combine conformational biasing and transition state charge mimicry, is described. The key steps in this synthesis involve synthesis of (2-azido-1,3-dihydroxy-cyclopentyl)-acetic acid ethyl ester in four steps from cyclopentenone, followed by an efficient reductive cyclization of the azide to the bicyclic lactam. The lactam was subsequently converted into the corresponding bicyclic pyrrolidine, and analogs having phenyl, hydroxyl, and phosphate substituents. [Copyright &y& Elsevier]

Power systems are undergoing fundamental changes with increasing penetration of renewable energies. A reactive power ancillary service market is of significance to incentivize private providers, such as thermal power units and renewable power plants (RPPs), to participate in maintaining voltage security. Because of the local nature of reactive power, one of the recognized issues is that monopolistic participants may have great market power and strategically manipulate their costs. To pursue economic efficiency, this paper proposes an incentive-compatible mechanism based on Vickery-Clarke-Groves (VCG) auctions for the day-ahead reactive power ancillary service market. The obligations of reactive power ancillary service are quantified in the VCG-based market mechanism. Depending on the expected performance of participants compared with the corresponding obligations, payments are obtained for thermal power units, RPPs, and loads. Hence, providers have the incentive to declare their true costs and undertake obligations. Furthermore, a scarcity price is employed to reward the provision of scarce reactive power resources and ensure reliable market clearing. The proposed mechanism is illustrated using the IEEE 24-bus and 118-bus systems. The results verify the effectiveness of the proposed mechanism. Moreover, high rewards or penalties are observed for voltage weak areas, thereby inducing appropriate investments in reactive power capacities. [ABSTRACT FROM AUTHOR]