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The prospect of targeted therapies for advanced gastrointestinal stromal tumors (GISTs) has been dramatically transformed after encouraging results achieved in recent clinical trials. At present, the number of second- and third-line treatments are increasing, although the challenge is to take into account the differences between these interventions. Therefore, our goal is to evaluate the investigation of different regimens currently used in GISTs based on findings from phase II or phase III randomized controlled trials (RCTs), and then indirectly compare the effectiveness and safety of the available therapies. The qualified literatures in relevant sources were searched systematically. Studies to identify RCTs of which main endpoints were progression-free survival (PFS), overall survival (OS), and grade 3 or more adverse events (AEs) in patients with GISTs were considered for inclusion. Eight RCTs met our inclusion criteria, which involved 2351 patients. For PFS, compared with placebo, imatinib, and sunitinib, regorafenib (HR = 0.12, 95% CI 0.07–0.23; HR = 0.27, 95% CI 0.19–0.39; HR = 0.36, 95% CI 0.19–0.72, respectively) and ripretinib (HR = 0.15, 95% CI 0.09–0.25; HR = 0.33, 95% CI 0.16–0.68; HR = 0.44, 95% CI 0.25–0.78, respectively) were significantly correlated with the improvement of PFS, and regorafenib may be the preferred option according to the analysis of treatment rankings. For OS, compared with placebo, imatinib, and sunitinib, masitinib (HR = 0.13, 95% CI 0.04–0.44; HR = 0.13, 95% CI 0.04–0.51; HR = 0.27, 95%CI 0.09–0.84) and ripretinib (HR = 0.36, 95% CI 0.21–0.62; HR = 0.36, 95% CI 0.16–0.80; HR = 0.18, 95% CI 0.09–0.36, respectively) were significantly more effective, and masitinib may be the best choice according to treatment ranking analysis. Statistically, regorafenib can be considered to be the highest in high-grade AEs, while the rate of severe AEs of ripretinib and masitinib was likely the lowest. Our results show that ripretinib has the most favorable balance between effectiveness and tolerability among the different treatment regimens for GISTs.

Luminescent porous materials have shown various applications such as electronic devices, gas adsorption, energy materials and photocatalysis. Consequently, we designed and prepared a new type borondipyrromethene (BODIPY) based porous organic polymer (POP) by using Sonogashira coupling reaction. This POP-1 exhibits high thermal stability with moderate surface area. In addition, POP-1 is highly emissive in a solid state. Due to enrichment of different kinds of heteroatoms in the skeleton of the porous polymer, POP-1 selectively captures carbon dioxide (CO2) with relative high adsorption selectivity of CO2/N2.

With the increasing integration of wind power and demand response into power system, the complex uncertainties from supply-side and demand-side have brought great challenges to daily operation of the power system. It is essential for enabling a comprehensive and adequate consideration of the manifold uncertainties in the grid. In this study, information granule chance constraint goal programming (IGCCGP) is proposed by a combination of chance constraint goal programming and information granule to provide a uniform representation of the multifaceted uncertainties. Leveraging on IGCCGP, the reserve constraints and branch flow constraints for accommodating the complex uncertainties in the grid are developed and the economic dispatch model considering the combined uncertainties from both supply-side and demand-side is established. To accelerate model solutions without losing much of model accuracy, the deviation in the IGCCGP is transformed to a deterministic equivalent and the optimal schedule is obtained by a mixed linear integer programming. Finally, a computational study is illustrated in the IEEE 39-bus system to verify the efficiency of the proposed method.

Due to the potential of thermal storage being similar to that of the conventional battery, air conditioning (AC) has gained great popularity for its potential to provide ancillary services and emergency reserves. In order to integrate numerous inverter ACs into secondary frequency control, a hierarchical distributed control framework which incorporates a virtual battery model of inverter AC is developed. A comprehensive derivation of a second-order virtual battery model has been strictly posed to formulate the frequency response characteristics of inverter AC. In the hierarchical control scheme, a modified control performance index is utilized to evaluate the available capacity of traditional regulation generators. A coordinated frequency control strategy is derived to exploit the complementary and advantageous characteristics of regulation generators and aggregated AC. A distributed consensus control strategy is developed to guarantee the fair participation of heterogeneous AC in frequency regulation. The finite-time consensus protocol is introduced to ensure the fast convergence of power tracking and the state-of-charge (SOC) consistency of numerous ACs. The effectiveness of the proposed control strategy is validated by a variety of illustrative examples.

With the energy storage cooperatively participating in AGC of the interconnected power grid, this paper proposed energy storage acti power control performance evaluation standard. called ES (energy storage) standard, for multi-area power grid. The index was a combination of the basic ideas of both NERC's control performance standard (CPS)and unit control performance standard (UCPS). The ES standard used the energy output factor of energy storage to reflect the energy storage participation in the active control and constrained the power grids AGC behaviors with the energy storage cooperatively participating by generalized area control error. The standard evaluated two kinds of different AGC control objectives. It can be used to guide the energy storage active power control method. Finally, the comparative analysis was run for the active control guidance of the ES standard and CPS through simulation. The simulation results show that compared with the CPS, the ES standard promotes the energy storage balance the frequency fluctuations coordinately with AGC units in power grid. It is more adapt to evaluate the energy storage active power control performance.

With the development of the energy Internet, the coupling of active power and reactive power in modern power grid is increasingly inseparable, while the operation of automatic generation control (AGC) and automatic voltage control (AVC) is in the way of decoupling in the power grid. The operation of AGC and AVC will affect the control effect of each other as a result of the different targets, and even may cause the repeating regulation of equipment or other safety issues. According to the above issues, this paper establishes a coordinated control strategy of AGC and A VC based on multi agent system. By means of the establishment of three level multi agent architecture, the coordinated control of AGC and A VC is realized by classification and partition. The comprehensive coordination model of AGC and A VC is established in the organization level agent, and the AGC and A VC controls are synthesized based on the ultrashort term load forecasting for the advanced AGC optimization and the correction of AVC on account of the adjustment of active power. The independent and cooperative control strategy of voltage correction is set at the coordination level and the executive level agent to achieve the independent operation of the voltage correction, the independent cooperation between the intelligent bodies and the local compensation of reactive power. Finally, the simulation prove that, the proposed control strategy can improve the economy and security of the system operation and suppress the mutual interference between AGC and AVC.

To mitigate the impact of wind forecasting error uncertainty, a Chance-Constrained Goal Programming (CCGP) based day-ahead scheduling model is proposed in this paper. Compared with the traditional Chance Constrained Programming (CCP) method, the CCGP based model is more flexible, which allows higher violation probability than the predefined probability in necessary situations. In this way, the day-ahead scheduling and the uncertain range covered by reserves can be both optimized. Therefore, the reliability and economy of the system with wind power uncertainty can be considered in details with more flexibilities. In addition, because slack variables in CCGP model have corresponding physical meanings, they can provide more information to system operators. Furthermore, numerical tests are performed with the IEEE 118 bus system with wind power input. Results indicate that the proposed method achieves a good balance of cost and risk. And the total operation cost, especially the unit commitment cost, is reduced by the proposed method. Comparative evaluations of the proposed CCGP method and CCP method are presented in the paper.

Wind power is uncertain and fluctuating. To address its impact on system, a jointed scheduling model of wind power/thermal generation/ energy storage system (ESS) is established in this paper, based on bi-level programming (BLP). Operations of different types of power sources are optimized in the upper-level, while unit commitment of thermal generation is optimized in the lower-level. These two layers work together to yield the best results. Chance constrained programming is applied to address uncertainties of wind power. And a method to utilize the ESS as part of system reserves is introduced to reduce the total reserves required from thermal generation. A control strategy is also applied to maintain state of charge (SOC) reasonable, avoiding SOC reaching the critical area too often because of the rising utilization of ESS. Finally, results of case studies indicate that BLP is effective in optimizing ESS operation in wind power integrated system.

This paper presents a queuing theory M/G/1 model to describe the traffic flow at urban roads. Considering the lanes occupation rate, the input of the vehicle from previous road section and other influence factors, Based on the actual statistical data, Monte Carlo algorithm is used to simulate the traffic flow model M/G/1, to optimize the parameters. Compared with the actual data, the simulated results demonstrate that the proposed model can estimate the influence of carriageways occupation on urban traffic capacity accurately.