To reduce information exchange requirements in smart grids, an event-triggered communication-based distributed optimization is proposed for economic dispatch. In this work, the θ-logarithmic ...barrier-based method is employed to reformulate the economic dispatch problem, and the consensus-based approach is considered for developing fully distributed technology-enabled algorithms. Specifically, a novel distributed algorithm utilizes the minimum connected dominating set (CDS), which efficiently allocates the task of balancing supply and demand for the entire power network at the beginning of economic dispatch. Further, an event-triggered communication-based method for the incremental cost of each generator is able to reach a consensus, coinciding with the global optimality of the objective function. In addition, a fast gradient-based distributed optimization method is also designed to accelerate the convergence rate of the event-triggered distributed optimization. Simulations based on the IEEE 57-bus test system demonstrate the effectiveness and good performance of proposed algorithms.
As a promising thermoelectric material, higher manganese silicides are composed of earth‐abundant and eco‐friendly elements, and have attracted extensive attention for future commercialization. In ...this review, the authors first summarize the crystal structure, band structure, synthesis method, and pristine thermoelectric performance of different higher manganese silicides. After that, the strategies for enhancing electrical performance and reducing lattice thermal conductivity of higher manganese silicides as well as their synergism are highlighted. The application potentials including the chemical and mechanical stability of higher manganese silicides and their energy conversion efficiency of the assembled thermoelectric modules are also summarized. By analyzing the current advances in higher manganese silicides, this review proposes that potential methods of further enhancing zT of higher manganese silicides, lie in enhancing electrical performance while simultaneously reducing lattice thermal conductivity via reducing effective mass, optimizing carrier concentration, and nanostructure engineering.
Due to its nontoxicity, eco‐friendliness, and low cost, higher manganese silicide thermoelectric material shows robust potential for application in high‐performance thermoelectrics via effective strategies through carrier concentration optimization, synergistic engineering, and structure design.
Gastrointestinal cancer is the most common human malignancy characterized by high lethality and poor prognosis. Emerging evidences indicate that N6-methyladenosine (m6A), the most abundant ...post-transcriptional modification in eukaryotes, exerts important roles in regulating mRNA metabolism including stability, decay, splicing, transport, and translation. As the key component of the m6A methyltransferase complex, methyltransferase-like 14 (METTL14) catalyzes m6A methylation on mRNA or non-coding RNA to regulate gene expression and cell phenotypes. Dysregulation of METTL14 was deemed to be involved in various aspects of gastrointestinal cancer, such as tumorigenesis, progression, chemoresistance, and metastasis. Plenty of findings have opened up new avenues for exploring the therapeutic potential of gastrointestinal cancer targeting METTL14. In this review, we systematically summarize the recent advances regarding the biological functions of METTL14 in gastrointestinal cancer, discuss its potential clinical applications and propose the research forecast.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Layered antiferromagnetism is the spatial arrangement of ferromagnetic layers with antiferromagnetic interlayer coupling. The van der Waals magnet chromium triiodide (CrI3) has been shown to be a ...layered antiferromagnetic insulator in its few-layer form, opening up opportunities for various functionalities in electronic and optical devices. Here we report an emergent nonreciprocal second-order nonlinear optical effect in bilayer CrI3. The observed second-harmonic generation (SHG; a nonlinear optical process that converts two photons of the same frequency into one photon of twice the fundamental frequency) is several orders of magnitude larger than known magnetization-induced SHG and comparable to the SHG of the best (in terms of nonlinear susceptibility) two-dimensional nonlinear optical materials studied so far (for example, molybdenum disulfide). We show that although the parent lattice of bilayer CrI3 is centrosymmetric, and thus does not contribute to the SHG signal, the observed giant nonreciprocal SHG originates only from the layered antiferromagnetic order, which breaks both the spatial-inversion symmetry and the time-reversal symmetry. Furthermore, polarization-resolved measurements reveal underlying C2h crystallographic symmetry-and thus monoclinic stacking order-in bilayer CrI3, providing key structural information for the microscopic origin of layered antiferromagnetism. Our results indicate that SHG is a highly sensitive probe of subtle magnetic orders and open up possibilities for the use of two-dimensional magnets in nonlinear and nonreciprocal optical devices.
Although 5-methylcytosine (m
C) is a widespread modification in RNAs, its regulation and biological role in pathological conditions (such as cancer) remain unknown. Here, we provide the ...single-nucleotide resolution landscape of messenger RNA m
C modifications in human urothelial carcinoma of the bladder (UCB). We identify numerous oncogene RNAs with hypermethylated m
C sites causally linked to their upregulation in UCBs and further demonstrate YBX1 as an m
C 'reader' recognizing m
C-modified mRNAs through the indole ring of W65 in its cold-shock domain. YBX1 maintains the stability of its target mRNA by recruiting ELAVL1. Moreover, NSUN2 and YBX1 are demonstrated to drive UCB pathogenesis by targeting the m
C methylation site in the HDGF 3' untranslated region. Clinically, a high coexpression of NUSN2, YBX1 and HDGF predicts the poorest survival. Our findings reveal an unprecedented mechanism of RNA m
C-regulated oncogene activation, providing a potential therapeutic strategy for UCB.
Directed energy deposition (DED) is an important additive manufacturing method for producing or repairing high-end and high-value equipment. Meanwhile, the lack of reliable and uniform qualities is a ...key problem in DED applications. With the development of sensing devices and control systems, in situ monitoring (IM) and adaptive control (IMAC) technology is an effective method to enhance the reliability and repeatability of DED. In this paper, we review current IM technologies in IMAC for metal DED. First, this paper describes the important sensing signals and equipment to exhibit the research status in detail. Meanwhile, common problems that arise when gathering these signals and resolvent methods are presented. Second, process signatures obtained from sensing signals and transfer approaches from sensing signals for processing signatures are shown. Third, this work reviews the developments of the IM of product qualities and illustrates ways to realize quality monitoring. Lastly, this paper specifies the main existing problems and future research of IM in metal DED.
This tutorial review explains the emerging understanding of the surface and bulk chemistry - electrochemical performance relations in anode supports (
aka
secondary current collectors, substrates, ...templates, hosts) for lithium, sodium and potassium metal batteries (LMBs, SMBs or NMBs, and KMBs or PMBs). In relation to each section, the possible future research directions that may yield both new insight and improved cycling behavior are explored. Representative case studies from Li, Na and K metal anode literature are discussed. The tutorial starts with an overview of the solid electrolyte interphase (SEI), covering both the "classic" understanding of the SEI structure and the "modern" insights obtained by site-specific cryogenic stage TEM analysis. Next, the multiple roles of supports in promoting cycling stability are detailed. Without an optimized support architecture, the metal-electrolyte interface becomes geometrically unstable at a lower current density and cycle number. Taking into consideration the available literature on LMBs, SMBs and KMBs, it is concluded that effective architectures are geometrically complex and electrochemically lithiophilic, sodiophilic or potassiophilic, so as to promote conformal electrochemical wetting of the metal during plating/stripping. One way that philicity is achieved is through support oxygen surface chemistry, which yields a reversibly reactive metal-support interface. Examples of this include the well-known oxygen-carbon moieties in reduced graphene oxide (rGO), as well as classic ion battery reversible conversion reaction oxides such as SnO
2
. Unreactive surfaces lead to dewetted island growth of the metal, which is a precursor to dendrites, and possibly to non-uniform dissolution. Surveying the literature on various Li, Na and K metal supports, it is concluded that the key bulk thermodynamic property that will predict electrochemical wetting behavior is the enthalpy of infinite solution (Δ
sol
H
∞
) of the metal (solute) into the support (solvent). Large and negative Δ
sol
H
∞
promotes uniform metal wetting on the support surface, corresponding to relatively low plating overpotential. Positive Δ
sol
H
∞
promotes dewetted islands and a relatively high overpotential. This simple rule explains a broad range of studies on Li, Na and K metal - support interactions, including the previously reported correlation between mutual solubility and wetting.
This tutorial review explains surface and bulk chemistry - electrochemical performance relations of lithium, sodium and potassium metal anodes.
Surface plasmon resonance microscopy (SPRM) is a versatile platform for chemical and biological sensing and imaging. Great progress in exploring its applications, ranging from single‐molecule sensing ...to single‐cell imaging, has been made. In this Minireview, we introduce the principles and instrumentation of SPRM. We also summarize the broad and exciting applications of SPRM to the analysis of single entities. Finally, we discuss the challenges and limitations associated with SPRM and potential solutions.
Surface plasmon resonance microscopy has emerged as a versatile platform for single‐molecule sensing and single‐cell imaging with high spatiotemporal resolution. This Minireview highlights the recent advances in the SPRM‐based analysis of single entities. Future challenges and their limitations as well as potential research directions are discussed.
The increasing popularity of battery-limited electric vehicles puts forward an important issue of how to charge the vehicles effectively. This problem, commonly referred to as Electric Vehicle ...Charging Scheduling (EVCS), has been proven to be NP-hard. Most of the existing works formulate the EVCS problem simply as a constrained shortest path finding problem and treat it by discrete optimization. However, other variables such as the charging amount of energy and the charging option at a station need to be considered in practical use. This paper hence formulates the EVCS problem as a hierarchical mixed-variable optimization problem, considering the dependency among the station selection, the charging option at each station and the charging amount settings. To adapt to the new problem model, we specifically design a Mixed-Variable Differentiate Evolution (MVDE) as the scheduling algorithm for our proposed EVCS system. The MVDE contains several specific operators, including a charging station route construction, a hierarchical mixed-variable mutation operator and a constraint-aware evaluation operator. Experimental results validate the effectiveness of our proposed MVDE-based system on both synthetic and real-world transportation networks.
Fast and accurate airflow simulations in the built environment are critical to provide acceptable thermal comfort and air quality to the occupants. Computational Fluid Dynamics (CFD) offers detailed ...analysis on airflow motion, heat transfer, and contaminant transport in indoor environment, as well as wind flow and pollution dispersion around buildings in urban environments. However, CFD still faces many challenges mainly in terms of computational expensiveness and accuracy. With the increasing availability of large amount of data, data driven models are starting to be investigated to either replace, improve, or aid CFD simulations. More specifically, the abilities of deep learning and Artificial Neural Networks (ANN) as universal non-linear approximator, handling of high dimensionality fields, and computational inexpensiveness are very appealing. In built environment research, deep learning applications to airflow simulations shows the ANN as surrogate, replacement for expensive CFD analysis. Surrogate modeling enables fast or even real-time predictions, but usually at a cost of a degraded accuracy. The objective of this work is to critically review deep learning interactions with fluid mechanics simulations in general, to propose and inform about different techniques other than surrogate modeling for built environment applications. The literature review shows that ANNs can enhance the turbulence model in various way for coupled CFD simulations of higher accuracy, improve the efficiency of Proper Orthogonal Decomposition (POD) methods, leverage crucial physical properties and information with physics informed deep learning modeling, and even unlock new advanced methods for flow analysis such as super-resolution techniques. These promising methods are largely yet to be explored in the built environment scene. Unavoidably, deep learning models also presents challenges such as the availability of consistent large flow databases, the extrapolation task problem, and over-fitting, etc.
•In built environment ANN are only used as surrogate model for expensive CFD analysis.•New potential methods are physics informing, turbulence enhancement, super-resolution.•Challenges are the availability of large databases, extrapolation and over-fitting.
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