mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Optimal Price-maker Trading Strategy of Wind Power Producer Using Virtual Bidding

This paper proposes a stochastic optimization model for generating the optimal price-maker trading strategy for a wind power producer using virtual bidding, which is a kind of financial tool available in most electricity markets of the United States. In the proposed model, virtual bidding is used to improve the wind power producer's market power in the dayahead (DA)market by trading at multiple buses, which are not limited to the locations of the wind units. The optimal joint wind power and virtual trading strategy is generated by solving a bi-level nonlinear stochastic optimization model. The upperlevel problem maximizes the total expected profit of the wind power and virtual bidding while using the conditional value at risk (CVaR)for risk management. The lower-level problem represents the clearing process of the DA market. By using the Karush- Kuhn-Tucker (KKT)conditions, duality theory, and big-M method, the bi-level nonlinear stochastic model is firstly transferred into an equivalent single-level stochastic mathematical program with the equilibrium constraints (MPEC)model and then a mixed-integer linear programming (MILP)model, which can be solved by existing commercial solvers. To reduce the computational cost of solving the proposed stochastic optimization model for large systems, a method of reducing the number of buses considered for virtual bidding is proposed to simplify the stochastic MPEC model by reducing its decision variables and constraints related to virtual bidding. Case studies are performed to show the effectiveness of the proposed model and the method of reducing the number of buses considered for virtual bidding. The impacts of the transmission limits, wind unit location, risk aversion parameters, wind power volatility, and wind and virtual capacities on the price-maker trading strategy are also studied through case studies.
Performance Enhancement of Distribution Systems via Distribution Network Reconfiguration and Distributed Generator Allocation Considering Uncertain Environment

The emergence of dispersed generation, smart grids, and deregulated electricity markets has increased the focus on enhancing the performance of distribution systems. This paper proposes a method to reduce the energy loss and improve the reliability of distribution systems by performing distribution network reconfiguration (DNR)and distributed generator (DG)allocation. In this study, the intermittent nature of renewable- based DGs and the load profile are considered using a probabilistic method. The study investigates different annual plans based on the seasonal power profiles of DGs and the load to minimize the combined cost function of annual energy loss and annual energy not served. The proposed method is implemented using the firefly algorithm (FA), which is one of the meta- heuristic optimization algorithms. Several case studies are investigated using the IEEE 33-bus distribution system to highlight the effectiveness of the method.
Whole-lifetime Coordinated Service Strategy for Battery Energy Storage System Considering Multi-stage Battery Aging Characteristics

One battery energy storage system (BESS)can be used to provide different services, such as energy arbitrage (EA)and frequency regulation (FR)support, etc.,which have different revenues and lead to different battery degradation profiles. This paper proposes a whole-lifetime coordinated service strategy to maximize the total operation profit of BESS. A multi-stage battery aging model is developed to characterize the battery aging rates during the whole lifetime. Considering the uncertainty of electricity price in EA service and frequency deviation in FR service, the whole problem is formulated as a twostage stochastic programming problem. At the first stage, the optimal service switching scheme between the EA and FR services are formulated to maximize the expected value of the whole-lifetime operation profit. At the second stage, the output power of BESS in EA service is optimized according to the electricity price in the hourly timescale, whereas the output power of BESS in FR service is directly determined according to the frequency deviation in the second timescale. The above optimization problem is then converted as a deterministic mixed-integer nonlinear programming (MINLP)model with bilinear items. McCormick envelopes and a bound tightening algorithm are used to solve it. Numerical simulation is carried out to validate the effectiveness and advantages of the proposed strategy.
Switchable Capacitor Bank Coordination and Dynamic Network Reconfiguration for Improving Operation of Distribution Network Integrated with Renewable Energy Resources

Point of common coupling (PCC)arrays are the most prominent and widely-used intermittent distributed generations (DGs). Due to the right-of-way, environmental, economical and other restrictions, the connection of these types of DGs to the preferred point of the distribution network is very difficult or impossible in some cases. Therefore, because of non-optimal locations, they may cause a voltage rise at the PCC. In this paper, a coordinated design of switchable capacitor banks (SCBs)with dynamic reconfiguration of the distribution network is proposed to avoid low- and high-voltage violations. The distribution network reconfiguration is implemented to mitigate the voltage rise at PCCs and capacitor banks (CBs)to solve the low-voltage problem. A novel method is presented for determining the optimal size of CBs. The proposed capacitor sizing method (CSM)effectively determines the optimal values of reactive power for the given nodes. The optimal locations of SCB are determined using particle swarm optimization algorithm. The 24- hour reactive power curve optimized by the proposed method plays a pivotal role in designing SCBs. The simulation results show that the implementation of the dynamic network reconfiguration and the placement of SCB is required to maintain a standard voltage profile for better employment of DG embedded distribution networks.
ADMM-based Distributed Active and Reactive Power Control for Regional AC Power Grid with Wind Farms

A distributed active and reactive power control (DARPC)strategy based on the alternating direction method of multipliers (ADMM)is proposed for regional AC transmission system (TS)with wind farms (WFs). The proposed DARPC strategy optimizes the power distribution among the WFs to minimize the power losses of the AC TS while tracking the active power reference from the transmission system operator (TSO), and minimizes the voltage deviation of the buses inside the WF from the rated voltage as well as the power losses of the WF collection system. The optimal power flow (OPF)of the TS is relaxed by using the semidefinite programming (SDP)relaxation while the branch flow model is used to model the WF collection system. In the DARPC strategy, the large-scale strongly- coupled optimization problem is decomposed by using the ADMM, which is solved in the regional TS controller and WF controllers in parallel without loss of the global optimality. The boundary information is exchanged between the regional TS controller and WF controllers. Compared with the conventional OPF method of the TS with WFs, the optimality and accuracy of the system operation can be improved. Moreover, the proposed strategy efficiently reduces the computation burden of the TS controller and eliminates the need of a central controller. The protection of the information privacy can be enhanced. A modified IEEE 9-bus system with two WFs consisting of 64 wind turbines (WTs)is used to validate the proposed DARPC strategy.
Revisiting the period and quality factor of the Chandler wobble and its possible geomagnetic jerk excitation

The period and quality factor of the Chandler wobble (CW) are useful for constraining the Earth's internal structure properties, such as the mantle elasticity. It has been shown that the CW is mainly excited by a combination of atmospheric and oceanic processes; hence based on a deconvolution method, we can remove them from the excitation sequence of the CW to estimate its period P and quality factor Q. We finally re-estimate P = 432.3 ± 0.8 days and Q = 85 ± 15 for the CW. Based on those two estimates, we investigate the relationship between the geomagnetic jerks and the excitation sequences of the CW. The geomagnetic jerks or jerk bounds are well consistent with the sudden changes of the excitation sequences of the CW. This demonstrates that the geomagnetic jerks could be a possible excitation source of the CW. It is crucial for understanding the excitation of the CW and for deeper geophysical insights into the geomagnetic jerks.
Improving efficiency of inverted perovskite solar cells via ethanolamine-doped PEDOT:PSS as hole transport layer

In order to fabricate high-performance inverted perovskite solar cells (PeSCs), an appropriate hole transport layer (HTL) is essential since it will affect the hole extraction at perovskite/HTL interface and determine the crystallization quality of the subsequent perovskite films. Herein, a facile and simple method is developed by adding ethanolamine (ETA) into poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as HTL. The doping of a low-concentration ETA can efficiently modify the electrical properties of the PEDOT:PSS film and lower the highest occupied molecular orbital (HOMO) level, which is more suitable for the hole extraction from the perovskite to HTL. Besides, ETA-doped PEDOT:PSS will create a perovskite film with larger grain size and higher crystallinity. Hence, the results show that the open-circuit voltage of the device increases from 0.99 V to 1.06 V, and the corresponding power conversion efficiency (PCE) increases from 14.68% to 19.16%. The alkaline nature of ethanolamine greatly neutralizes the acidity of PEDOT:PSS, and plays a role in protecting the anode, leading the stability of the devices to be improved significantly. After being stored for 2000 h, the PCE of ETA-doped PEDOT:PSS devices can maintain 84.2% of the initial value, which is much higher than 67.1% of undoped devices.
Modulation of Schottky barrier in XSi_2N_4/graphene (X = Mo and W) heterojunctions by biaxial strain

Reducing the Schottky barrier height (SBH) and even achieving the transition from Schottky contacts to Ohmic contacts are key challenges of achieving high energy efficiency and high-performance power devices. In this paper, the modulation effects of biaxial strain on the electronic properties and Schottky barrier of MoSi_2N_4 (MSN)/graphene and WSi_2N_4 (WSN)/graphene heterojunctions are examined by using first principles calculations. After the construction of heterojunctions, the electronic structures of MSN, WSN, and graphene are well preserved. Herein, we show that by applying suitable external strain to a heterojunction stacked by MSN or WSN—an emerging two-dimensional (2D) semiconductor family with excellent mechanical properties—and graphene, the heterojunction can be transformed from Schottky ptype contacts into n-type contacts, even highly efficient Ohmic contacts, making it of critical importance to unleash the tremendous potentials of graphene-based van der Waals (vdW) heterojunctions. Not only are these findings invaluable for designing high-performance graphene-based electronic devices, but also they provide an effective route to realizing dynamic switching either between n-type and p-type Schottky contacts, or between Schottky contacts and Ohmic contacts.
Core structure and Peierls stress of the 90◦ dislocation and the 60◦ dislocation in aluminum investigated by the fully discrete Peierls model

The core structure, Peierls stress and core energy, etc. are comprehensively investigated for the 90◦ dislocation and the 60◦ dislocation in metal aluminum using the fully discrete Peierls model, and in particular thermal effects are included for temperature range 0 ≤ T ≤ 900 K. For the 90◦ dislocation, the core clearly dissociates into two partial dislocations with the separating distance D ~ 12 A, and the Peierls stress is very small σp < 1 kPa. The nearly vanishing Peierls stress results from the large characteristic width and a small step length of the 90◦ dislocation. The 60◦ dislocation dissociates into 30◦ and 90◦ partial dislocations with the separating distance D ~ 11 A. The Peierls stress of the 60◦ dislocation grows up from 1 MPa to 2 MPa as the temperature increases from 0 K to 900 K. Temperature influence on the core structures is weak for both the 90◦ dislocation and the 60◦ dislocation. The core structures theoretically predicted at T = 0 K are also confirmed by the first principle simulations.
Transcriptional regulator CTR9 promotes hepatocellular carcinoma progression and metastasis via increasing PEG10 transcriptional activity

Cln Three Requiring 9 (CTR9), a scaffold protein of the polymerase-associated factor-1 (PAF1) complex (PAF1c), is primarily localized in the nucleus of cells. Recent studies show that CTR9 plays essential roles in the development of various human cancers and their occurrence; however, its regulatory roles and precise mechanisms in hepatocellular carcinoma (HCC) remain unclear. In this study, we investigated the roles of CTR9 using in vitro assays and a xenograft mouse model. We found that CTR9 protein is upregulated in tumor tissues from HCC patients. Knockdown of CTR9 substantially reduced HCC cell proliferation, invasion, and migration, whereas its overexpression promoted these activities. In addition, in vitro results revealed that CTR9 silencing dramatically increased cell cycle regulators, p21 and p27, but markedly decreased matrix metalloproteinases, MMP2 and MMP9, with these outcomes reversed upon CTR9 overexpression. Furthermore, the underlying molecular mechanism suggests that CTR9 promoted the oncogene paternally expressed gene 10 (PEG10) transcription via its promoter region. Finally, the oncogenic roles of CTR9 were confirmed in a xenograft mouse model. This study confirms that CTR9, an oncoprotein that promotes HCC cell proliferation, invasion, and migration, increases tumor growth in a xenograft mouse model. CTR9 could be a novel therapeutic target. Further investigation is warranted to verify CTR9 potential in novel therapies for HCC.
Interface Modification of TiO_2 Electron Transport Layer with PbCl_2 for Perovskiote Solar Cells with Carbon Electrode

Perovskite Solar Cells (PSCs) have attracted considerable attention because of their unique features and high efficiency. However, the stability of perovskite solar cells remains to be improved. In this study, we modified the TiO_2 Electron Transport Layer (ETL) interface with PbCl_2. The efficiency of the perovskite solar cells with carbon electrodes increased from 11.28% to 13.34%, and their stability obviously improved. The addition of PbCl_2 had no effect on the morphology, crystal structure, and absorption property of the perovskite absorber layer. However, it affected the band energy level alignment of the solar cells and accelerated the electron extraction and transfer at the interface between the perovskite layer and the ETL, thus enhancing the overall photovoltaic performance. The interfacial modification of ETL with PbCl_2 is a promising way for the potential commercialization of low-cost carbon electrode-based perovskite solar cells.
An MPI+OpenACC-Based PRM Scalar Advection Scheme in the GRAPES Model over a Cluster with Multiple CPUs and GPUs

A moisture advection scheme is an essential module of a numerical weather/climate model representing the horizontal transport of water vapor. The Piecewise Rational Method (PRM) scalar advection scheme in the Global/Regional Assimilation and Prediction System (GRAPES) solves the moisture flux advection equation based on PRM. Computation of the scalar advection involves boundary exchange, and computation of higher bandwidth requirements is complicated and time-consuming in GRAPES. Recently, Graphics Processing Units (GPUs) have been widely used to solve scientific and engineering computing problems owing to advancements in GPU hardware and related programming models such as CUDA/OpenCL and Open Accelerator (OpenACC). Herein, we present an accelerated PRM scalar advection scheme with Message Passing Interface (MPI) and OpenACC to fully exploit GPUs' power over a cluster with multiple Central Processing Units (CPUs) and GPUs, together with optimization of various parameters such as minimizing data transfer, memory coalescing, exposing more parallelism, and overlapping computation with data transfers. Results show that about 3.5 times speedup is obtained for the entire model running at medium resolution with double precision when comparing the scheme's elapsed time on a node with two GPUs (NVIDIA P100) and two 16-core CPUs (Intel Gold 6142). Further, results obtained from experiments of a higher resolution model with multiple GPUs show excellent scalability.
Optimal Controller Design for Non-Affine Nonlinear Power Systems with Static Var Compensators for Hybrid UAVs

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator (SVC) or State Var System (SVS) for hybrid Unmanned Aerial Vehicles (UAVs). The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its S-Function. Combining the inverse system method and the Linear Quadratic Regulation (LQR), an optimized SVC controller is designed. The simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.
Artificial Intelligence for Edge Service Optimization in Internet of Vehicles: A Survey

The Internet of Vehicles (IoV) plays a crucial role in providing diversified services because of its powerful capability of collecting real-time information. Generally, collected information is transmitted to a centralized resourceintensive cloud platform for service implementation. Edge Computing (EC) that deploys physical resources near road-side units is involved in IoV to support real-time services for vehicular users. Additionally, many measures are adopted to optimize the performance of EC-enabled IoV, but they hardly help make dynamic decisions according to real-time requests. Artificial Intelligence (AI) is capable of enhancing the learning capacity of edge devices and thus assists in allocating resources dynamically. Although extensive research has employed AI to optimize EC performance, summaries with relative concepts or prospects are quite few. To address this gap, we conduct an exhaustive survey about utilizing AI in edge service optimization in IoV. Firstly, we establish the general condition and relative concepts about IoV, EC, and AI. Secondly, we review the edge service frameworks for IoV and explore the use of AI in edge server placement and service offloading. Finally, we discuss a number of open issues in optimizing edge services with AI.
In situ stabilization of arsenic in soil with organoclay, organozeolite, birnessite, goethite and lanthanum-doped magnetic biochar

Arsenic (As)is a known carcinogen and naturally occurring semi-metal in soils and in the Earth's crust. Contamination of soils and water with As poses a serious threat to millions of people worldwide due to its health hazards and toxicological properties. Hence, devising novel and efficient methods for remediation of contaminated areas has attracted a great deal of interest across the globe. In this study, we investigated the usefulness of synthetic birnessite, goethite, hexadecylpyridinium chloride-modified montmorillonite (HDPC-M), hexadecylpyridinium bromide-modified zeolite (HDPB-Z), and lanthanum (La)-doped magnetic biochar produced from eucalyptus bark (La-Euchar)as adsorbents at 10% dosage for As stabilization in a soil spiked with 1 000 mg kg~(-1) As. The effectiveness of the above adsorbents in As immobilization in soil was assessed using single-step extractions with 2 mol L~(-1) HNO_3 and deionized water, the simplified bioaccessibility extraction test (SBET)method, and sequential extraction with the modified Community Bureau of Reference (BCR)method. Application of the adsorbents shifted the exchangeable fraction of As to more recalcitrant fractions and dramatically reduced the exchangeable fraction by 6%-99% and the extractable amounts with HNO_3, deionized water, and SBET method by 30%-92%, 17%-95%, and 12%-90%, respectively, compared to the unamended control. The immobilizing effects of adsorbents on As decreased in the sequence of birnessite > La-Euchar > goethite > HDPB-Z > HDPC-M. Birnessite exhibited great affinity for As and drastically reduced As extractability by more than 90% in all single extractions. The results revealed that HDPC-M, HDPB-Z, La-Euchar, birnessite, and goethite are promising immobilizing agents for in situ stabilization of As in terrestrial environments.
Polyoxometalate-based metal-organic complexes constructed from a new bis-pyrimidine-amide ligand with high capacitance performance and selectivity for the detection of Cr(VI)

In this paper, three new polyoxometalates (POM)-based metal-organic complexes constructed from a new semi-rigid organic ligand N,N’-bis(4-pyrimidinecarboxamido)-1,2-cyclohexane (4-bpmah) H_2[Cu(4-bpmah)_2(SiMo_(12)O_(40))(H_2O)_2]·2H_2O (1), H[Cu(4-bpmah)_2(PMo_(12)O_(40))(H_2O)_2]·2H_2O (2) and [Cu(4-bpmah)(H_2O)_2]·[Cu_2(TeMo_6O_(24))(H_2O)_(10)]·4H_2O (3) were synthesized by hydrothermal method. Single crystal X-ray analyses showed that complexes 1 and 2 were isostructural, in which the isolated Keggin-type [SiMo_(12)O_(40)]~(4-)/[PMo_(12)O_(40)]_3-anions and [Cu(4-bpmah)_2(H_2O)_2]~(2n+) units were expanded into 3D supramolecular structures through hydrogen bond interactions. In complex 3, the 1D [Cu(4-bpmah)(H_2O)_2]~(2n+) metal-organic chains and isolated [Cu_2(TeMo_6O_(24))(H_2O)_(10)]2n-units were expanded into a 3D supramolecular framework by the hydrogen bond interactions. In this paper, carbon cloth working electrodes composited by the title complexes (1/CC, 2/CC and 3/CC) were prepared and used as electrodes for supercapacitors. The performance of supercapacitors as well as the influence of electrolyte solution and title complexes quality load on the performance of supercapacitors were studied. Furthermore, the electrochemistry and electrocatalytic behaviors of complexes 1-3 bulk-modified carbon paste electrodes (1-CPE, 2-CPE and 3-CPE) toward the reduction of KBrO_3, KNO_2, Cr(VI), as well as their sensing behaviors on Cr(VI) were investigated.
Efficient dye-sensitized solar cells based on concerted companion dyes: Systematic optimization of thiophene units in the organic dye components

To develop efficient concerted companion (CC) dyes for fabricating high-performance DSSCs, three organic dyes XL1-XL3 have been designed by varying the position and number of the β-hexylthiophene (HT) bridges, and these organic dye units are covalently linked with our previously reported porphyrin dye XW10 to construct the corresponding CC dyes XW74-XW76. Among the organic dyes, XL3 contains two β-hexylthiophene units at both the donor and acceptor parts and thus possesses stronger light-harvesting capability in the green light region. Because of the most complementary absorption between XL3 and XW10 as well as the excellent photovoltaic behavior of the individual XL3 dye, the corresponding CC dye XW76 affords the best PCE (10.78%) among all the CC dyes. Upon coadsorption with CDCA, XW76 affords a highest PCE of 11.35%, which outperforms the previous cosensitization system of XW10+WS-5. This work provides an approach for developing efficient DSSCs based on CC dyes composed of an organic dye unit with suitable π spacers inserted at appropriate positions.