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The economy of the Regional Integrated Energy System (RIES) scheduling scheme is affected by the parameter accuracy of different energy conversion equipment models. The traditional static energy hub (EH) model regards the equipment efficiency as a constant and ignores the variable condition characteristics of the equipment efficiency changing with the load rate. This paper presents an optimal scheduling method of RIES considering the characteristics of equipment under variable operating conditions. Firstly, the architecture of the integrated energy system is analyzed. Secondly, based on the DEH model, an optimal scheduling method of RIES was proposed considering the characteristics of equipment under variable operating conditions. Finally, an optimal scheduling analysis is performed for a typical RIs. The results show that the proposed method can improve the accuracy of the equipment model and reduce the cost prediction error by considering the variable operating conditions of the equipment, thus providing a more economical scheduling scheme for Ries.

Economic transformation creates a new environment for grid investment. In the situation of high quality development, the traditional investment scale prediction model is no longer applicable. Aiming at the problems of single parameter of grid-driven investment scale prediction model and poor linear fitting accuracy, a provincial medium- and long-term investment scale prediction model based on support vector machine was proposed. Aiming at the single parameter and poor line fitting accuracy of the grid-driven investment scale prediction model under the new situation, the new environment, new directions and new requirements for grid investment are analyzed. Based on the support vector machine algorithm, a medium-and long-term investment scale prediction model for provincial grids based on support vector machines is proposed. The scale of provincial grid investment is expected from 2019 to 2022. The empirical results show that the prediction model constructed in this paper is effective and feasible. It is of great significance to explore the prediction model of medium and long-term investment scale of power grid enterprises in the new situation.

2,6-Bis(5,6-dialkyl-1,2,4-triazin-3-yl)-pyridine (R-BTP) is one of the most promising classes of soft N-donor ligands for minor trivalent actinide (such as Am(iii) and Cm(iii)) separation but its complexation behavior with interfering element Pd(ii) is still unknown. The effect of substituents (R-) on the modulation of R-BTP's complexation with Pd(ii) was studied by single crystal diffractometry, 1H NMR spectroscopy, ESI-MS, and density functional theory (DFT) calculation methods. The formation of both 1 : 1 and 2 : 1 complexes of R-BTP with Pd(ii) were firstly identified, and their electronic and geometric structures were determined. It has been found that the modification of the R-BTP skeleton with substituents (R-) changing from methyl (C1) to s-butyl (C4) leads to two different coordination models with water. The structures of 2 : 1 R-BTP/Pd(ii) complexes were determined to be unusually paramagnetic, distorted six-coordinate compounds. However, the 1 : 1 species was found to have a typical square-planar geometry. The extraction properties of four R-BTPs for Pd(ii) and other fission or corrosion products were studied. This work can help to further understand the complexation behavior of Pd(ii) with R-BTP, which provides theoretical insights into the partitioning of minor actinides and Pd(ii) from high level active waste (HLW) using R-BTP type ligands. [ABSTRACT FROM AUTHOR]

A novel mesoporous polymer-based composite, C7-BTBP/XAD-7, was prepared by impregnating 6,6’-bis(5,6-diheptyl-1,2,4-triazin-3-yl)-2,2’-bipyridine (C7-BTBP) into the pores of the polymeric XAD-7 carrier. The microstructure of the material was characterized by scanning electron microscopy (SEM), nitrogen adsorption-desorption isotherms, and thermogravimetric analysis (TGA). The selective adsorption of Pd(II) onto C7-BTBP/XAD-7 from a HNO3medium containing some typical metals, including Ru(III), Fe(III), Mo(VI), Zr(IV), Li(I), Na(I), K(I), Rb(I), Cs(I), Mg(II), Ca(II), Sr(II), Ba(II), Y(III), La(III), Nd(III), and Yb(III), was investigated. The polymeric composite exhibited strong adsorption affinity, high selectivity, and fast adsorption rate for Pd(II) in 3.0 M HNO3. The adsorption isotherm fitted well with Langmuir model, with a maximum adsorption capacity of 0.412 mmol/g. The hybrid polymeric composite was very stable in HNO3solution. The kinetics of Pd(II) coordinated with C7-BTBP was discussed by Density Function Theory (DFT) calculations. [ABSTRACT FROM PUBLISHER]

Modern DRAM architectures allow a number of low-power states on individual memory ranks for advanced power management. Many previous studies have taken advantage of demotions on low-power states for energy saving. However, most of the demotion schemes are statically performed on a limited number of pre-selected low-power states, and are suboptimal for different workloads and memory architectures. Even worse, the idle periods are often too short for effective power state transitions, especially for memory intensive applications. Wrong decisions on power state transition incur significant energy and delay penalties. In this paper, we propose a novel memory system design named RAMZzz with rank-aware energy saving optimizations including dynamic page migrations and adaptive demotions. Specifically, we group the pages with similar access locality into the same rank with dynamic page migrations. Ranks have their hotness: hot ranks are kept busy for high utilization and cold ranks can have more lengthy idle periods for power state transitions. We further develop adaptive state demotions by considering all low-power states for each rank and a prediction model to estimate the power-down timeout among states. We experimentally compare our algorithm with other energy saving policies with cycle-accurate simulation. Experiments with benchmark workloads show that RAMZzz achieves significant improvement on energy-delay $^2$ and energy consumption over other energy saving techniques. [ABSTRACT FROM AUTHOR]

Main memory (or DRAM) is one of the most significant components to the computer system’s performance and energy consumption. Dynamic frequency scaling (DFS) and DRAM low-power states (Demotion ) are two main-stream techniques for DRAM power management. DFS reduces the operation frequency of memory channels and DRAM devices when the memory bandwidth is under-utilized, whereas demotion transits individual memory ranks to low-power states during long idle periods. Despite that there have been fruitful research work for DFS and demotion separately, little attention has been paid to the synergy between these two techniques. To bridge this gap, this paper conducts a comprehensive study on the synergy between DFS and demotion. In particular, we leverage queuing theory to develop analytical models for the energy consumption and performance of DRAM systems with DFS and demotion. These models provide valuable insights into the synergy between DFS and demotion. We further attempt to minimize the energy consumption by considering both DFS and demotion while keeping a pre-defined performance penalty budget. To reduce the optimization complexity, we develop simple yet effective heuristics to search near-optimum DFS-demotion configurations. We experimentally compare our design with other state-of-the-art DRAM energy saving policies using detailed simulations of a large set of workloads. Experimental results show the accuracy of our analytical models and the effectiveness of our optimizations. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the progressive loss of motor neurons (MNs) in the brain and spinal cord. It is caused by multiple factors, including mutations in any one of several specific genes. Optineurin (OPTN) mutation is an essential cause of some familial and sporadic ALS. Besides, as a multifunctional protein, OPTN is highly expressed and conserved in the central nervous system. OPTN exerts its functions by interacting with various proteins, often acting as an adaptor to provide a link between two or more core proteins related to autophagy and inflammation, etc. OPTN mutation mainly results in its function deficiency, which alters these interactions, leading to functional impairment in many processes. Meanwhile, OPTN immunopositive inclusions are also confirmed in the cases of ALS due to C9ORF72, FUS, TARDBP, and SOD1 mutations. Therefore, OPTN gene may play fundamental roles in the molecular pathology of ALS in addition to OPTN mutation. In this review, we summarize the recent advances in the ALS pathology of OPTN defect, such as mitophagy disorder, neuroinflammation, neuronal axonal degeneration, vesicular transport dysfunction, etc., which will provide a reference for research on the pathogenesis and treatment of ALS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhao, Chen, Gao, Lu, Bai and Zhang.)