mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Single NIR Laser-Activated MultifunctionalNanoparticles for Cascaded Photothermal and Oxygen-Independent Photodynamic Therapy

Inconvenient dual-laser irradiation and tumor hypoxic environment as well as limited judgment of treating region have impeded the development of combined photothermal and photodynamic therapies (PTT and PDT). Herein, Bi_2Se_3@AIPH nanoparticles (NPs) are facilely developed to overcome these problems.Through a one-step method, free radical generator (AIPH) and phase transition material (lauric acid, LA, 44–46 °C) are encapsulated in hollow bismuth selenide nanoparticles (Bi_2Se_3 NPs).Under a single 808-nm laser irradiation at the tumor area, hyperthermia produced by Bi_2Se_3 not only directly leads to cell death, but also promotes AIPH release by melting LA and triggers free radical generation, which could further eradicate tumor cells in hypoxic environments.Moreover, Bi_2Se_3 with high X-ray attenuation coefficient endows the NPs with high computed tomography (CT) imaging capability, which is important for treating area determination.The results exhibit that Bi_2Se_3@AIPH NPs possesses 31.2% photothermal conversion efficiency for enhanced PTT, ideal free radical generation for oxygen-independent PDT, and 37.77 HU mL mg–1 X-ray attenuation coefficient for CT imaging with high quality.Most importantly, the tumor growth inhibition rate by synergistic PTT, PDT, and following immunotherapy is 99.6%, and even one tumor disappears completely, which demonstrates excellent cascaded synergistic effect of Bi_2Se_3@AIPH NPs for the tumor therapy.
Perovskite/Silicon Tandem Solar Cells: FromDetailed Balance Limit Calculations to Photon Management

Energy conversion efficiency losses and limits of perovskite/silicon tandem solar cells are investigated by detailed balance calculations and photon management. An extended Shockley–Queisser model is used to identify fundamental loss mechanisms and link the losses to the optics of solar cells. Photon management is used to minimize losses and maximize the energy conversion efficiency. The influence of photon management on the solar cell parameters of a perovskite single-junction solar cell and a perovskite/silicon solar cell is discussed in greater details. An optimized solar cell design of a perovskite/silicon tandem solar cell is presented, which allows for the realization of solar cells with energy conversion efficiencies exceeding 32%.
Laser-Etched Stretchable Graphene–PolymerComposite Array for Sensitive Strain and Viscosity Sensors

The ability to control surface wettability and liquid spreading on textured surfaces is of interest for extensive applications. Soft materials have prominent advantages for producing the smart coatings with multiple functions for strain sensing. Here, we report a simple method to prepare flexible hydrophobic smart coatings using graphene–polymer films. Arrays of individual patterns in the films were created by laser engraving and controlled the contact angle of small drops by pinning the contact lines in a horizontal tensile range of 0–200%. By means of experiments and model, we demonstrate that the ductility of drops is relied on the height-to-spacing ratio of the individual pattern and the intrinsic contact angle. Moreover, the change of drop size was utilized to measure the applied strain and liquid viscosity, enabling a strain sensitivity as high as 1068 μm~2/%. The proposed laser-etched stretchable graphene–polymer composite has potential applications in DNA microarrays, biological assays, soft robots, and so on.
Availability estimation of wind power forecasting and optimization of day-ahead unit commitment

Due to the uncertainty of the accuracy of wind power forecasting, wind turbines cannot be accurately equated with dispatchable units in the preparation of a dayahead dispatching plan for power grid. A robust optimization model for the uncertainty of wind power forecasting with a given confidence level is established. Based on the forecasting value of wind power and the divergence function of forecasting error, a robust evaluation method for the availability of wind power forecasting during given load peaks is established. A simulation example is established based on a power system in Northeast China and an IEEE 39-node model. The availability estimation parameters are used to calculate the equivalent value of wind power of the conventional unit to participate in the dayahead dispatching plan. The simulation results show that the model can effectively handle the challenge of uncertainty of wind power forecasting, and enhance the consumption of wind power for the power system.
Convex optimization of virtual storage system scheduling in market environment

Due to the popularization of distributed energy resources(DERs), the aggregated prosumer effect excels a general energy storage system characteristic. Virtual energy storage system(VESS) concept is proposed hereby that mimics an actual storage unit and incorporates the same charging(consumer) and discharging(producer) modes. It is possible to provide ancillary services via VESS by exploiting the flexibility and thus much research has been proposed on the optimization of the VESS scheduling. In general, the charging and discharging efficiencies of VESS are different and there can be only one status at a time slot. To achieve the optimal schedule while considering the constraints above, binary terms should be introduced into the optimization problem which end up with a nonconvex problem. In this paper, a complimentary mathematical proof is given for the convexification of this mixed-integer linear programming(MILP) problem so that the linear programming(LP) method can be applied instead if the objective function is linear. The proposed proof is validated through a case study and the simulation results show the effectiveness of the proposed method.
Bilevel programming approach to demand response management with day-ahead tariff

This paper introduces a bilevel programming approach to electricity tariff optimization for the purpose of demand response management(DRM) in smart grids. In the multi-follower Stackelberg game model, the leader is the profit-maximizing electricity retailer, who must set a time-of-use variable energy tariff in the grid. Followers correspond to the groups of prosumers(simultaneous producers and consumers of the electricity). They respond to the observed tariff, schedule controllable loads and determine the charging/discharging policy of their batteries to minimize the cost of electricity and to maximize the utility at the same time. A bilevel programming formulation of the problem is defined, and its fundamental properties are proved. The primal-dual reformulation is proposed in this paper to convert the bilevel optimization problem into a single-level quadratically constrained quadratic program(QCQP), and a successive linear programming(SLP) algorithm is applied to solve it. It is demonstrated in computational experiments that the proposed approach outperforms earlier typical methods based on the Karush–Kuhn–Tucker(KKT) reformulation regarding both solution quality and computational efficiency on practically relevant problem sizes. Besides, it also offers more flexible modeling capabilities.
High-Performance Na-Ion Storage of S-DopedPorous Carbon Derived from Conjugated Microporous Polymers

Na-ion batteries (NIBs) have attracted considerable attention in recent years owing to the high abundance and low cost of Na. It is well known that S doping can improve the electrochemical performance of carbon materials for NIBs. However, the current methods for S doping in carbons normally involve toxic precursors or rigorous conditions. In this work, we report a creative and facile strategy for preparing S-doped porous carbons (SCs) via the pyrolysis of conjugated microporous polymers (CMPs). Briefly, thiophene-based CMPs served as the precursors and doping sources simultaneously. Simple direct carbonization of CMPs produced S-doped carbon materials with highly porous structures. When used as an anode for NIBs, the SCs exhibited a high reversible capacity of 440 mAh g–1 at 50 mA g–1 after 100 cycles, superior rate capability, and excellent cycling stability (297 mAh g–1 after 1000 cycles at 500 mA g–1), outperforming most S-doped carbon materials reported thus far. The excellent performance of the SCs is attributed to the expanded lattice distance after S doping. Furthermore, we employed ex situ X-ray photoelectron spectroscopy to investigate the electrochemical reaction mechanism of the SCs during sodiation–desodiation, which can highlight the role of doped S for Na-ion storage.
Risk assessment of microgrid aggregators considering demand response and uncertain renewable energy sources

In power market environment, the growing importance of demand response(DR) and renewable energy source(RES) attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit. Meanwhile, the intermittent natures of these alternative sources along with the competition add to the probable financial risk of the aggregators. The objective of the paper is to highlight this financial risk of aggregators in such uncertain environment while estimating DR magnitude and power generated by RES. This work develops DR modeling incorporating the effect of estimating power at different confidence levels and uncertain participation of customers. In this paper, two well-known risk assessment techniques, value at risk and conditional value at risk, are applied to predict the power from RES and DR programs at a particular level of risk in different scenarios generated by Monte Carlo method. To establish the linkage between financial risk taking ability of individuals, the aggregators are classified into risk neutral aggregator, risk averse aggregator and risk taking aggregator. The paper uses data from Indian Energy Exchange to produce realistic results and refers certain policies of Indian Energy Exchange to frame mathematical expressions for benefit function considering uncertainties for each type of three aggregators. Extensive results show the importance of assessing the risks involved with two unpredictable variables and possible impacts on technical and financial attributes of the microgrid energy market.
Stochastic optimization of cost-risk for integrated energy system considering wind and solar power correlated

Due to the growing penetration of renewable energies(REs) in integrated energy system(IES), it is imperative to assess and reduce the negative impacts caused by the uncertain REs. In this paper, an unscented transformation-based mean-standard(UT-MS) deviation model is proposed for the stochastic optimization of cost-risk for IES operation considering wind and solar power correlated. The unscented transformation(UT) sampling method is adopted to characterize the uncertainties of wind and solar power considering the correlated relationship between them. Based on the UT, a mean-standard(MS) deviation model is formulated to depict the trade-off between the cost and risk of stochastic optimization for the IES optimal operation problem. Then the UT-MS model is tackled by a multi-objective group search optimizer with adaptive covariance and Levy flights embedded with a multiple constraints handling technique(MGSO-ACL-CHT) to ensure the feasibility of Peratooptimal solutions. Furthermore, a decision making method, improved entropy weight(IEW), is developed to select a final operation point from the set of Perato-optimal solutions. In order to verify the feasibility and efficiency of the proposed UT-MS model in dealing with the uncertainties of correlative wind and solar power, simulation studies are conducted on a test IES. Simulation results show that the UT-MS model is capable of handling the uncertainties of correlative wind and solar power within much less samples and less computational burden. Moreover, the MGSOACL- CHT and IEW are also demonstrated to be effective in solving the multi-objective UT-MS model of the IES optimal operation problem.
Integrated coordination scheduling framework of electricitynatural gas systems considering electricity transmission N - 1 contingencies and gas dynamics

This paper discusses a security-constrained integrated coordination scheduling framework for an integrated electricity-natural gas system(IEGS), in which both tight interdependence between electricity and natural gas transmission networks and their distinct dynamic characteristics at different timescales are fully considered. The proposed framework includes two linear programming models. The first one focuses on hour-based steady-state coordinated economic scheduling on power outputs of electricity generators and mass flow rates of natural gas sources while considering electricity transmission N - 1 contingencies. Using the steady-state mass flow rate solutions of gas sources as the initial value, the second one studies second-based slow gas dynamics and optimizes pressures of gas sources to ensure that inlet gas pressure of gas-fired generator is within the required pressure range at any time between two consecutive steady-state scheduling. The proposed framework is validated via an IEGS consisting of an IEEE 24-bus electricity network and a 15-node 14-pipeline natural gas network coupled by gasfired generators. Numerical results illustrate the effectiveness of the proposed framework in coordinating electricity and natural gas systems as well as achieving economic and reliable operation of IEGS.
A sparse recovery model with fast decoupled solution for distribution state estimation and its performance analysis

This paper introduces a robust sparse recovery model for compressing bad data and state estimation(SE), based on a revised multi-stage convex relaxation(R-Capped- L1) model. To improve the calculation efficiency, a fast decoupled solution is adopted. The proposed method can be used for three-phase unbalanced distribution networks with both phasor measurement unit and remote terminal unit measurements. The robustness and the computational efficiency of the R-Capped-L1 model with fast decoupled solution are compared with some popular SE methods by numerical tests on several three-phase distribution networks.
Indirect Tax Burden of Regional Residents: Study on Long Term MRIO Model

Investigating the indirect tax burden of residents is an important way of understanding the effect of tax on income distribution and the tax burden transfer. In this paper, a long term MRIO model is constructed by using the regional input-output tables in China. We simulate the flow of value- added tax, consumption tax and business tax in different departments of 30 provinces(except Tibet) in mainland China from the perspective of rows in the IO table, we obtain the real burden of three indirect taxes on urban residents, and discuss the transfer of tax burden among regions. The conclusions are as follows: There are large differences in tax burden among regions. The real tax burden shifted from the eastern region to the middle and the western regions. Indirect tax aggravates the income inequality of urban residents in different regions. The indirect tax in China has a certain degree of regression. Based on the empirical analysis, we think the government should make the following policy changes: 1) Giving more consideration to the consumption terminals; 2) Adjusting preferential policies of regional taxation; 3) Increasing the amount of preferential policies for the western region.
Tung Tree (Vernicia fordii) Genome Provides A Resource for Understanding Genome Evolution and Improved Oil Production

Tung tree (Vernicia fordii) is an economically important woody oil plant that produces tung oil rich in eleostearic acid. Here, we report a high-quality chromosome-scale genome sequence of tung tree. The genome sequence was assembled by combining Illumina short reads, Pacific Biosciences single-molecule real-time long reads, and Hi-C sequencing data. The size of tung tree genome is 1.12 Gb, with 28,422 predicted genes and over 73% repeat sequences. The V. fordii underwent an ancient genome triplication event shared by core eudicots but no further wholegenome duplication in the subsequent ca. 34.55 million years of evolutionary history of the tung tree lineage. Insertion time analysis revealed that repeat-driven genome expansion might have arisen as a result of long-standing long terminal repeat retrotransposon bursts and lack of efficient DNA deletion mechanisms. The genome harbors 88 resistance genes encoding nucleotide-binding sites; 17 of these genes may be involved in early-infection stage of Fusarium wilt resistance. Further, 651 oil-related genes were identified, 88 of which are predicted to be directly involved in tung oil biosynthesis. Relatively few phosphoenolpyruvate carboxykinase genes, and synergistic effects between transcription factors and oil biosynthesis-related genes might contribute to the high oil content of tung seed. The tung tree genome constitutes a valuable resource for understanding genome evolution, as well as for molecular breeding and genetic improvements for oil production.
Technological Innovation, Regional Heterogeneity and Marine Economic Development — Analysis of Empirical Data Based on China's Coastal Provinces and Cities

In order to analyze the impact of technological innovation and regional differences in marine economy on the development of marine economy, the paper uses the regional panel data of China's total marine production value from 2006 to 2015, and uses the Theil index to measure regional differences in the marine economy based on the logarithm of the Cobb-Douglas production function. Finally, the paper establishes a random effect panel data model for empirical analysis. The research indicates that the regional differences in the marine economy show a narrowing trend, which promotes or inhibits the development of the marine economy; The extent of the impact of regional differences in the marine economy on the development of the marine economy is inconsistent; Scientific and technological innovation in various regions has promoted the development of marine economy.
高敏C反应蛋白同型半胱氨酸与胰岛素抵抗对妊娠期糖尿病并发妊娠期高血压综合征的影响

分析高敏C反应蛋白(high sensitive-C reactive protein,hs-CRP);同型半胱氨酸(homocystine, HCY);胰岛素抵抗指数(homeostasismode assessment-insulin resistance,HOMA-IR)与妊娠期糖尿病(gestational diabetes mellitus,GDM)并发妊娠期高血压综合征(pregnancy-induced hypertension,PIH)的相关性。选取2015年1月至2017年6月,绵阳市人民医院收治的妊娠期糖尿病患者273例,其中单纯GDM患者228例(Ⅰ组),GDM合并PIH患者45例(Ⅱ组),同期纳入45例正常妊娠妇女为对照组。采用自行设计的调查表收集两组患者一般资料,检测血清生化指标血糖、血脂、hs-CRP、HCY,采用稳态模式计算胰岛素抵抗指数(HOMA-IR)。结果显示,Ⅰ组、Ⅱ组体质量指数(body mass inedx,BMI);收缩压(systolic blood pressure,SBP);舒张压(diastolic blood pressccre,DBP);HCY;甘油三酯(triglyceride, TG);空腹血糖(fasting plasma glucose,FPG);空腹胰岛素(fasting serum lisulin,FINS);hs- CRP;HOMA-IR高于对照组,差异有统计学意义(F=7.181、18.851、6.591、6.775、33.364、9.055、 11.486、10.742、38.184,P<0.05)。Ⅱ组BMI、SBP、DBP、HCY、FINS、hs-CRP、HOMA-IR高于 Ⅰ组,差异有统计学意义(P<0.05)。采用logistic回归分析方法分析显示,BMI(OR=1.79,95%CI= 1.32~4.06,P<0.01);HCY(OR=1.06,95%CI=1.00~3.04,P<0.05);hs-CRP(OR=1.21, 95%CI=1.00~3.76,P<0.05);HOMA-IR(OR=1.44,95%CI=1.11~3.79,P<0.05)是GDM患者合并PIH的影响因素。妊娠糖尿病并发妊娠期高血压与BMI、HCY、hs-CRP、HOMA-IR存在相关性,指标水平越高,GDM患者合并PIH发生的风险生越大。
Linear Arboricity of NIC-Planar Graphs

A graph is NIC-planar if it admits a drawing in the plane with at most one crossing per edge and such that two pairs of crossing edges share at most one common end vertex.It is proved that every NIC-planar graph with minimum degree at least 2 (resp.3) contains either an edge with degree sum at most 23 (resp.17) or a 2-alternating cycle (resp.3-alternating quadrilateral).By applying those structural theorems, we confirm the Linear Arboricity Conjecture for NIC-planar graphs with maximum degree at least 14 and determine the linear arboricity of NIC-planar graphs with maximum degree at least 21.
Concentrated Trading and the Survival of Overconfident Traders

We build a strategic trading model where the overconfident trader earns more than the rational trader and the mechanism for this result differs from that of Kyle and Wang (1997).In this paper, discretionary and nondiscretionary liquidity traders coexist.The overconfident insider is less worried by the market maker and thus induces a lower liquidity cost.In this way, he attracts all the trading from the discretionary liquidity traders, which enables the survival of the overconfident trader.
Wolfe-Type Duality for Mathematical Programs with Equilibrium Constraints

This paper considers the mathematical programs with equilibrium constraints (MPEC).It is well-known that, due to the existence of equilibrium constraints, the Mangasarian-Fromovitz constraint qualification does not hold at any feasible point of MPEC and hence, in general, the developed numerical algorithms for standard nonlinear programming problems can not be applied to solve MPEC directly.During the past two decades, much research has been done to develop numerical algorithms and study optimality, stability, and sensitivity for MPEC.However, there are very few results on duality for MPEC in the literature.In this paper,we present a Wolfe-type duality for MPEC and, under some suitable conditions, we establish various duality theorems such as the weak duality, direct duality, converse duality, and strict converse duality theorems.We further show that a linear MPEC is equivalent to a linear programming problem in some sense.
Model assessment of nutrient removal via planting Sesuvium portulacastrum in floating beds in eutrophic marine waters: the case of aquaculture areas of Dongshan Bay

Many coastal seas are severely eutrophic and required to reduce nutrient concentrations to meet a certain water quality standard.We proposed a method for nutrient removal by planting Sesuvium portulacastrum at the water surface using the floating beds in the aquaculture area of the Dongshan Bay as an example, which is an important net-cage culture base in China and where dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphate (DIP) reach 0.75 mg/L and 0.097 mg/L, respectively far exceeding China’s Grade IV water quality standards.Numerical simulations were taken using the ecological model, field observations and field plantation experimental results to assess the environmental restoration effects of planting S.portulacastrum at some certain spatial scales.Our field experiments suggested that the herbs can absorb 377 g/m~2 nitrogen and 22.9 g/m~2 phosphorus in eight months with an inserting density of ~60 shoot/m~2.The numerical experiments show that the greater the plantation area is, the more nutrient removal.Plantation in ~12% of the study area could lower nutrients to the required Grade II standards, i.e., 0.2 mg/L
Solitonic Diffusion of Wavepackets in One-Dimensional Bose–Einstein Condensates

Solitonic characteristics are revealed in the diffusion process of a hump or a notch wave packet in a one-dimensional Bose–Einstein condensate. By numerically solving the time-dependent Gross–Pitaevskii equation, we find completely different spreading behavior for attractive or repulsive condensates. For the attractive condensate, a series of bright solitons are continuously generated one after another at the wave front and they nearly stay at the positions where they are generated in the whole diffusion process. In contrast, for the repulsive condensate, the initial wave packet splits at the beginning into a series of grey solitons that travel at different velocities. The moving velocity of the grey soliton depends on nonlinear interaction strength, as well as the shape of a particular grey soliton.