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BACKGROUND At present, the value of lipid indicators in evaluating the prognosis of colorectal cancer is still relatively limited. AIM To evaluate the value of a novel parameter for colorectal cancer (CRC) prognosis scoring based on preoperative serum lipid levels. METHODS Four key serum lipid factors, namely, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), were detected. Two representative ratios, HDL-C-LDL-C ratio (HLR) and ApoA1-ApoB ratio (ABR) were calculated. The relationship of these parameters with the prognosis of CRC patients including progression-free survival (PFS) and overall survival (OS) was analyzed by Kaplan-Meier plot and Cox proportional hazards regression. A novel lipoprotein cholesterol-apolipoprotein (LA) score based on HLR and ABR was established and its value in prognosis evaluation for CRC patients was explored. RESULTS Multivariate Cox proportional hazards regression analysis of PFS and OS showed that HDL-C, ApoA1, HLR, and ABR were positively associated with the prognosis of CRC patients. LA score was independently associated with a good prognosis in resectable CRC patients. Data processing of a dummy variable showed that the prognosis of patients with higher LA scores is better than that with lower LA scores. CONCLUSION The newly established LA score might serve as a better predictor of the prognosis of resectable CRC patients.

Motives for writing is a new research area in the field of writing motivation. Recent studies have identified important motives for students’ writing. Adding to this nascent foundation, the current study examined relationships between writing motives, writing self-efficacy and time spent on writing using a sample of grade 4 Chinese students in Shanghai (n = 619) who completed a questionnaire assessing these constructs. Four alternative models, driven separately by key motives including social recognition, curiosity, competition and grades, depicted complex relationships between motives, self-efficacy and time on writing. The grades driven model best-fitted the data. This final model showed the importance of grades as a key motive for writing and how intrinsic and extrinsic motivational pathways were originated from this performance-focused motive, connecting with writing self-efficacy and time spent on writing. Cluster analyses classified these Chinese students into seven groups of beginning writers holding contrasting profiles of writing motives. Extremely-motivated and highly-motivated writers held multiple motives in their profiles. The motive profiles of curious and averagely-motivated writers were dominated by curiosity and involvement. Performance-focused and weakly-motivated writers focused predominantly on grades as a key motive. Finally, unmotivated writers did not hold any clear motives for writing. These clusters of writers differed in writing self-efficacy but not in their time spent on writing. Complementing the findings of path analyses, cluster analyses showed grades as a dominant motive for writing among different clusters of motivated writers.

Mindfulness training has become popular among the Chinese public in recent years. However, most mindfulness related research in China has focused almost exclusively on the effects of interventions on trait, but not state mindfulness. More research and valid measures on state mindfulness are needed in this area in China. Accordingly, the present study aims to validate and assess the internal consistency and construct validity of the Chinese version of the Toronto Mindfulness Scale (TMS) in a non-clinical sample. The current study employed an international team of scholars to translate the TMS into Chinese language. Exploratory factor analysis, confirmatory factor analysis, construct validity analysis, and test–retest reliability were examined in study (sample 1 n = 220, sample 2 n = 59). Comparisons between correlation coefficients of the experienced (n = 65) and inexperienced subjects (n = 155) were explored. The Chinese TMS (Ch-TMS) demonstrated acceptable internal consistency, with confirmatory factor analysis providing support for the established two-factor model. Both subscales demonstrated significant correlations in the expected directions in relation to the FFMQ-observing, FFMQ-non-reacting, SSAS-internal state awareness, and SSAS-awareness of surroundings. Our findings suggest that the Ch-TMS has acceptable psychometric properties and is a reliable and valid instrument for assessing state mindfulness in a Chinese cultural context.

Background. Uterine fibroids are most common in women aged 30-50 and are the most common benign gynecological tumors. Relevant data suggest that about 25% of patients with uterine fibroids are at childbearing age. Uterine fibroids not only cause the discomfort symptoms, and affect the pregnancy, but also have certain malignant transformation risk, thus needed to be treated positively and promptly. Aim. This study is aimed at exploring the effect of laparoscopic myomectomy and comprehensive rehabilitation nursing on patients with uterine fibroids. Methods. The clinical data of 110 cases of uterine fibroids admitted to our hospital from August 2019 to December 2021 were analyzed retrospectively, and they were divided into two groups according to postoperative rehabilitation strategies. Both groups were treated with laparoscopic myomectomy. The A group was treated with routine rehabilitation strategy, while the B group was treated with comprehensive rehabilitation nursing strategy. The differences in operation-related indicators, stress factors, inflammatory factors, nutritional indicators, knowledge mastery, occurrence of adverse symptoms and pain scores, negative emotion scores, nursing satisfaction, and simplified comfort status scale (GCQ) scores between the two groups under nursing strategies were compared. Results. The postoperative exhaust time ( 13.14 ± 2.03 ) h, bed time ( 9.86 ± 1.94 ) h, postoperative hospital stay ( 4.37 ± 1.31 ) d, and total hospital stay ( 6.78 ± 1.69 ) d in the B group were shorter than those in the A group, and the hospitalization expenses ( 0.74 ± 0.25 ) million were less than those in the A group ( P < 0.05 ). Before operation, stress factors, inflammatory factors, and nutritional indexes were compared between the two groups ( P > 0.05 ). On the 3rd day after operation, tumor necrosis factor-α (TNF-α), cortisol (Cor), norepinephrine (NE), and interleukin-1β (IL-1β) in the two groups showed a significantly upward trend compared with those before operation, and albumin and transferrin were significantly fell compared with those before operation. However, the values of stress factor and inflammatory factor in the B group were significantly lower than those in the A group, and the values after the decrease of nutritional index were significantly higher than those in the A group ( P < 0.05 ). The pain scores at 24 h, 48 h, and 72 h after operation in the B group were significantly lower than those in the A group ( P < 0.05 ). Negative emotions, nursing satisfaction, and GCQ scores were compared between the two groups before intervention ( P > 0.05 ). After the intervention, the scores of Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA) in the two groups were significantly lower than those before the intervention, and the scores of nursing satisfaction and GCQ were higher than those before the intervention. The values of negative emotions in the B group after the decline were significantly lower than those in the A group, while the values of nursing satisfaction and GCQ after the increase were higher than those in the A group ( P < 0.05 ). The excellent and good rate of knowledge acquisition in the B group was 94.55% (52/55), which was significantly higher than 78.18% (43/55) in the A group ( P < 0.05 ). The incidence of adverse symptoms in the B group was 9.09% (5/55), which was lower than 21.82% (12/55) in the A group, while the difference was not statistically significant ( P > 0.05 ). Conclusion. Laparoscopic myomectomy combined with comprehensive rehabilitation nursing can reduce the postoperative stress state of patients with uterine fibroids, improve patient satisfaction, reduce adverse emotions, and promote rehabilitation.

The benefits of mindfulness-based interventions to alleviate anxiety and depression have been supported by many studies. Given the effectiveness of mindfulness-based interventions on anxiety and depression, the underlying mechanisms need to be explored. Using a randomized waitlist-controlled design, this study investigated whether anxiety sensitivity was a potential mechanism for the impact of mindfulness training on anxiety and depression. Participants with high psychological distress were randomly assigned to an eight-week mindfulness intervention (N = 35) or a wait-list control group (N = 34). Before and after the intervention or corresponding waitlist period, participants completed measures of anxiety and depression severity and impairment and anxiety sensitivity. Separate mixed ANOVA demonstrated significant group (intervention vs. control group) × time (pre- vs. post-test) interactions for anxiety sensitivity and overall anxiety severity and impairment and marginally significant interaction for overall depression severity and impairment. Moreover, simple mediation models showed that reductions of anxiety sensitivity from pre- to post-test mediated the impact of mindfulness training on changes in anxiety and depression severity and impairment. The findings suggest that anxiety sensitivity is a potential mechanism underlying the effect of mindfulness training on anxiety and depression, which provides a new perspective for the study of processes of change of mindfulness-based interventions.

Background As the symbolic pathological changes of Alzheimer’s disease (AD), hyperphosphorylated tau and amyloid plaque play important roles in the progression of the disease. In AD patients, the neural activity in default mode network is abnormal at different stages of the disease, and showed a hypoconnective status. Inhibition of phosphatidylinositol-3-kinase (PI3K) activates glycogen synthase kinase 3 beta (GSK-3β) and induces tau phosphorylation. Objective We speculated that inhibiting cerebral PI3K altered the glucose metabolism in DMN. We aimed to explore the impacts of PI3K inhibition on tau phosphorylation, cerebral glucose metabolism, and synaptic plasticity. Methods We injected wortmannin, an inhibitor of PI3K, lateral ventricularly in rats to mimic the pathology of AD. Immunohistochemistry was carried out to analyze the expression of phosphorylated tau. Region-specific glucose metabolism in the brain was analyzed using 18F-FDG PET imaging. In vivo long-term potentiation (LTP) in the hippocampus was detected to assess the synaptic plasticity. Results The results show that the phosphorylated tau at T231 increased and the hippocampal LTP was suppressed 24 h after wortmannin administration. In the DMN, glucose uptake was significantly high, indicating a neural activity disturbance. Conclusion We conclude that targeting PI3K-GSK-3β pathway to mimic AD tau pathology interrupted the glucose metabolism of DMN brain regions.

This paper proposes a novel and applicable approach to calculate the reactive power loss of converter transformer under dc bias. By using this proposed method, only general information of the converter transformer and the network is needed for the calculation within a certain dc current range. Specifically, a three-dimensional model of $\pm$ 800 kV converter transformer model for simulation test is established by the finite element method. Through simulation test, the electromagnetic characteristics and reactive loss characteristics of converter transformer under dc bias can be obtained, and the relationship between the bias current and the reactive loss of $\pm$ 800 kV converter transformer is quantified. Simulation results validate the feasibility of proposed algorithm.

The increasing emissions from the transportation sector pose substantial hazards to the environment and human health around the world. With the rapid development of information and communication technologies, ridesplitting, a form of ridesourcing service accessed via smartphone applications, enables passengers with similar origins and destinations to be matched to the same driver and share the ride. This is regarded as a promising travel mode that could mitigate air pollution. However, because of a lack of quantitative analysis, the environmental benefits of ridesplitting have not been rigorously justified. As vast amounts of observed data of ridesourcing have become increasingly available, this study quantifies the environmental benefits of ridesplitting based on the global positioning system (GPS) trajectory and trip order datasets of DiDi Chuxing in Chengdu, China. First, the saved distances of ridesplitting are calculated by analyzing the travel distances of both ridesplitting trips and the corresponding trips under non-ridesplitting conditions. Then, the emission factors of CO, NOx, and HC are estimated by a localized MOVES model. Combining the saved distances and emission factors, the emission reductions from each ridesplitting trip can be calculated. The results show that ridesplitting can decrease the travel distance by 22% on average compared with non-ridesplitting. As a consequence, the average emission reductions per ridesplitting trip are 10.601 g of CO, 0.691 g of NOx, and 1.424 g of HC, respectively. This study provides a better understanding of the environmental benefits of ridesplitting and theoretical guidance for the government’s decision-making in green transport planning.

Single-photon emitters based on intrinsic defects in silicon carbide (SiC) are promising as solid-state qubits for the quantum information storage, whereas defect engineering in a controllable manner still remains challenging. Herein, the thermally-driven defect dynamic reaction in the ion implanted 4H-SiC has been exploited through the optical emission spectra of defects. For the heavy-ion (Si or Ar) implanted samples with abundant Frenkel pairs, the silicon vacancies (VSi) are energetically converted into the carbon antisite-vacancy pair (CSi-VC) upon annealing till 1300 °C for 30 min, accompanied with the gradual lattice recovery and local strain relaxation. The further temperature elevation dissociates the metastable CSi-VC into carbon antisite (CSi) and carbon vacancy (VC), as supported by the consequent quenching of the (CSi-VC)-related emission at 700 nm. Thus, the whole defect reaction is probed as the vacancy interconversion from VSi to VC with the byproduct of stacking faults. In contrast, the intermediate CSi-VC complexes are not energetically favorable during the annealing of the H-implanted sample, which results from the negligible generation of Frenkel pairs, as supported by the x-ray diffraction patterns and Raman scattering analysis. These findings provide guidance for defect engineering in SiC toward the creation of reliable single photon emitters.

High-volumetric-energy-density lithium-ion batteries require anode material with a suitable redox potential, a small surface area, and facile kinetics at both single-particle and electrode level. Here a family of coarse-grained molybdenum substituted titanium niobium oxides Mo[subscript x]Ti[subscript 1−x]Nb[subscript 2]O[subscript 7+y] (single crystals with 1~2 μm size) underwent hydrogen reduction treatment to improve electronic conduction was synthesized, which is able to stably deliver a capacity of 158.5 mAh g[superscript −1] at 6,000 mA g[superscript −1] (65.2 % retention with respect to its capacity at 100 mA g[superscript −1] ) and 175 mAh g[superscript −1] (73 % capacity retention over 500 cycles) at 2,000 mA g[superscript −1], respectively. Via careful in situ electrochemical characterizations, we identified the kinetic bottleneck that limits their high-rate applications to be mainly ohmic loss at the electrode level (which mostly concerns electron transport in the composite electrodes) rather than non-ohmic loss (which mostly concerns Li+ lattice diffusion within individual particles). Such a kinetic problem was efficiently relieved by simple treatments of Mo substitution and gas-phase reduction, which enable full cells with high electrode density, and high volumetric energy/power densities. Our work highlights the importance of diagnosis, so that modifications could be made specifically to improve full-cell performance.

The test platforms of motor driver are relatively expensive, high energy consumption, complex mechanical structure, and not readily available. A three-phase power electronic load of simulated permanent magnet synchronous motor is used to eliminate the risk associated with the performance testing of motor driver, without complex mechanical system. This equipment not only can simulate a variety of load characteristics, but also has the ability to recover energy with little loss and high power factor. In this work, a novel current tracking control strategy based on dual-mode structure repetitive control (DMRC) is proposed to improve the tracking accuracy of alternating current. Compare to control strategy operated in the d-q coordinate system, the proposed control strategy can direct track sine wave commands on the stationary $\alpha $ - $\beta $ coordinate system, which is easier to implement with fewer intermediate coordinate transformation in practice. An inductor-capacitor-inductor (LCL) filter is used to interface the voltage source converter (VSC) and the tested inverter in the three-phase electronic load system. Adjusting the odd-harmonic gain and even-harmonic gain of DMRC controller can effectively suppress the current harmonics. Furthermore, the comparative evaluation of DMRC, repetitive control and conventional PI control is conducted to verify the superiority of DMRC at different AC voltage frequency of tested inverter. The simulation has been carried out on three-phase power electronic load. As a result, the proposed method can achieve low total harmonic distortion (THD) (< 1.8%) of AC current, It can provides nearly 20% reduction of THD in phase current when compared with PI controller.

Thermal decomposition of 1-hexene at temperatures 295-1410 K was conducted using a flash pyrolysis micro-reactor coupled to laser-based vacuum ultraviolet photoionization time-of-flight mass spectrometer (VUV-PI-TOFMS). The decomposition mechanism of 1-hexene was developed with the help of theoretical calculation performed at the MRCI/cc-pvtz//CASSCF/6–31+G(d,p) level. The γ-scission and diradical retro-ene reactions were determined as the main initial decomposition reactions in the temperature range 990-1240 K. Two diradical retro-ene reaction channels, 1,5-diradical and 1,6-diradical reactions, were proposed in order to interpret the appearance of the C4H8 species. The 1,5-diradical retro-ene reaction involved a 1,5-diradical intermediate that subsequently decomposed via C C β-scissions to the C2, C3 and C4 products. The 1,6-diradical retro-ene reaction proceeded via a 1,6-diradical intermediate and C C β-scissions to produce the C2 and C4 species. The proposed diradical retro-ene mechanism was evidenced indirectly by the early product distribution of 1-hexene pyrolysis in a flow reactor at 1173 K determined by synchrotron radiation VUV-PI-TOFMS. It was verified in the flash pyrolysis of 1-heptene as well.

The hydrodeoxygenation (HDO) of bio-oil has attracted considerable attention but is extremely challenging due to low yield and selectivity. In this study, we report the gas-phase hydro-deoxygenation of guaiacol, a typical model compound of lignin-derived bio-oil, into aromatic hydrocarbons with benzene yield up to 85.1% over a nitrogen-doped carbon-supported palladium (Pd/NC) catalyst under atmospheric pressure. The guaiacol HDO products are detected by an on-line VUV photoionization time-of-flight mass spectrometry (TOF-MS) in real-time. Stability evaluation based on time-on-stream profiles of typical markers (benzene and phenol) shows that the benzene selectivity and stability are kept unchanged during 6 h time-on-stream. The mechanism of guaiacol HDO over Pd/NC is also discussed. We infer that the enhanced stability of Pd/NC catalyst is attributed to the prevention of Pd particles' leaching and aggregation by nitrogen-doped carbon materials and the high activity is due to the redistribution of electron density caused by the interaction of nitrogen functionalities and Pd particles. More importantly, efficient deoxygenation of lignin model compound while preserving its aromatic nature is feasible and successfully achieved with Pd/NC catalyst, which is extremely advantageous for the concept of selective conversion of lignin into value-added aromatic chemicals.

The phenolic pool is considered to be an important intermediate during the catalytic conversion of biomass. However, no direct evidence has been reported on its full picture on a molecular level due to the huge challenges in probing the reactive and lowly volatile phenolic oligomers with state-of-the-art technologies. Herein, we report the online detection and structural identification of a phenolic pool by utilizing in-situ atmospheric-pressure photoionization mass spectrometry, demonstrating that the phenolic pool is formed through repolymerization of monomers with an equidistant group pattern and acts as a key mechanistic step for both valuable aromatic products and undesired coke. The exploration of the real reactive species is also of great importance for the rational design and synthesis of advanced catalysts with high activity.

International audience; Poly(D,L-lactide-co-glycolide)-poly(ethylene glycol) (PLGA-PEG) diblock copolymers with different compositions were synthesized by ring-opening polymerization of D,L-lactide and glycolide, using monomethoxy PEG as macro-initiator. The resulting copolymers were characterized by nuclear magnetic resonance, gel permeation chromatography, and critical micelle concentration analyses. Self-assembly of the copolymers yielded aggregates of different architectures, including spherical micelles and a mixture of spherical and worm-like micelles with Y-junctions. The self-assembled architecture depends on both the hydrophilic/hydrophobic balance and the molar mass of copolymers. Valsartan, a widely used drug in the treatment of hypertension, was loaded in micelles using a co-solvent evaporation method. High drug-loading content was obtained for worm-like micelles. in vitro drug release was performed at 37°C in pH 7.4 phosphate-buffered saline. An initial burst release is detected in all cases, followed by slower release up to 9 days. The overall release rate is strongly dependent on the degradation of micelles. Copolymers with short PLGA blocks exhibit faster drug release due to faster degradation of micelles, and worm-like micelles present slower drug release as compared to spherical ones. Therefore, PLGA-PEG copolymer micelles with high drug-loading capacity, different architectures, and variable drug release rates could be most attractive for sustained delivery of valsartan.

This paper is concerned with the problem of designing a control strategy to guarantee stability in probability for high-order stochastic systems. The control hinges on the sliding-mode scheme. We first prove that the control design can stabilize a fast terminal sliding-mode function. We further show that the stable sliding mode is able to assure the stability in probability for the high-order stochastic system. The resulting system may account nonvanishing diffusion terms, which is regarded as a novelty. The derived control strategy has implications for applications—experiments are carried out to control the pitch angle of a one-degree-of-freedom aerial device. The corresponding experimental results demonstrate the benefits and effectiveness of our approach.

We employ a regression discontinuity (RD) design to estimate the impact of air pollution on house prices across a river that demarcates regions with and without coal-fired heating resulting from th...

This article addresses the dissipativity-based asynchronous repetitive control problem for networked Markovian jump systems subject to time delays and partly accessible mode detection probabilities. A hidden Markov model is introduced to describe the asynchronous phenomenon between the system modes and controller modes. Based on this, an asynchronous repetitive controller is proposed. By utilizing the lifting technique, the 1-D delayed Markovian jump system and controller governing equations are converted into a stochastic and closed-loop 2-D delayed model to describe the control and learning actions. Utilizing a stochastic Lyapunov functional, sufficient conditions in terms of matrix inequalities are derived such that the closed-loop system is mean-square stable and achieves the specified $(\mathscr {W}_1,\mathscr {W}_2,\mathscr {W}_3)$ - $\gamma$ -dissipative performance. Under the assumption that the input matrix is full column rank in all modes of operation, a set of feasible sufficient conditions described by linear matrix inequalities is established by making use of the Schur complement. A procedure for synthesizing the controller parameters is also provided. A detailed numerical example with simulation results is presented to validate the proposed dissipativity-based asynchronous repetitive control design scheme.

The number of coronavirus disease 2019 (COVID-19) cases has exceeded 10 million. However, little is known about the epidemiology and clinical characteristics of COVID-19 infants. We collected medical information of 46 confirmed patients (, Most of the 46 infants with coronavirus disease 2019 in this study experienced moderate disease, and the most common clinical symptoms were fever and cough. Cardiac injury and liver dysfunction were prominent complications in infant patients, but none had lymphocytosis.

This paper considers the problem of asynchronous ${H}_{{\infty }}$ control for networked Markovian jump systems subject to probabilistic packet dropouts and communication delays in the measurement channel. A new dynamic output-feedback-based asynchronous controller is proposed wherein the dynamic output-feedback controller modes need not synchronize with the system modes. By utilizing results from stochastic Lyapunov–Krasovskii stability theory, sufficient conditions in terms of matrix inequalities are derived such that the closed-loop networked Markovian jump system is stochastically stable and achieves the prescribed ${H}_{{\infty }}$ performance. Using the Schur complement technique and under the assumption that the input matrix is full rank, the sufficient condition is reduced to a linear matrix inequality and the dynamic output-feedback-based asynchronous controller is synthesized. A detailed numerical example with simulation results are presented to evaluate the proposed controller design scheme.

Sepsis-associated encephalopathy (SAE) often leads to cognitive impairments in the rest life of septic survivors. The potential pathological changes of SAE are complicated and have not been fully understood. Morin, a flavone compound exhibiting neuroprotective activity and anti-inflammation effect, was employed to treat with CLP-induced septic mice in our study. The data from a novel object recognition test and tail suspension test indicated that morin treatment reversed cognitive dysfunction and relieved depressive-like behaviors in septic mice. Morin down-regulated the expressions of IL-6, MCP-1, TNF-α and IL-10 in serum and diminished microglia activation in septic mice. Additionally, Western blot results showed that morin reduced the phosphokinase GSK3β activity and elevated the phosphatase PP2A activity, which led to lower tau phosphorylation. Morin reduced Aβ deposition and protected the synapse integrity, which might be the possible mechanism of protecting cognitive functions in septic mice. In conclusion, we identified that morin exerted anti-inflammation and anti-neurodegeneration effects in septic mice, and prevented further cognitive impairments.

For a dwell time limited radar network, the achievable tracking performance can be further enhanced by adaptively tuning in the dwell time allocation strategy to accommodate the future operation scenario. In this paper, considering this dynamical resource allocation problem, a cone programming-based dwell time allocation scheme is proposed for achieving the optimal tracking performance. The basic mechanism is to exploit the feedback of its operating environment based on the interrogation of received echoes for informing the decision of future optimal dwell time allocation. To achieve this purpose, the predicted conditional Cramer-Rao lower bound (PC-CRLB) of target state estimates is developed for evaluating the tracking performance of each candidate allocation strategy conditioned on the cognitive knowledge firstly. And, its trace is chosen as a scalar allocation strategy evaluation metric. On this basis, the closed-form expression of the scalar evaluation metric is derived, which enables us to transform the dwell time allocation problem into the second-order cone program (SOCP). Extensive simulations demonstrate the efficiency and superiority of the proposed allocation scheme.

The design of irregular subarrayed planar phased arrays composed of modular tiles is a research area of increasing interest. In this article, a heuristic iterative convex relaxation programming (H-ICRP) framework is proposed. By formulating the tiling of irregular subarray as a binary programming problem, this framework is suitable for arbitrary array aperture and subarray structure. To achieve exact aperture cover, the nonconvex binary constraint is relaxed to a convex approximation and solved through multiple iterations. Furthermore, for better performance of the scanning radiation pattern, the multitask Bayesian compressive sensing (MT-BCS) solver is adopted to find a heuristic initial iteration point instead of randomizing, such that the robustness and effectiveness can be improved remarkably. Good performance and potentialities of the proposed method are verified by comparing with existing approaches in various numerical examples.

In this letter, a general framework of cognitive resource allocation for target tracking in radar networks is proposed. Firstly, an allocation strategy evaluation metric is established in this framework, i.e., the predicted conditional Cramer-Rao lower bound (PC-CRLB), for evaluating the future response of each candidate allocation strategy. Then, the optimal resource allocation strategy can be found by solving a constrained optimization problem. To specify the framework implementation details, a dwell time allocation problem is considered. For this given problem, the analytical expressions of PC-CRLB and its derived scalar strategy evaluation metric are derived, enabling us to convert the allocation problem to a second-order cone program (SOCP). Numerical results demonstrate the effectiveness of the proposed framework.

To alleviate the issues of global warming and energy crisis, countries are vigorously developing renewable energy technology. The integration of large-scale renewable energy, including wind energy, hydropower, and photovoltaic (PV), has a great impact on system operation scheduling and economic dispatch. This paper presents an economic dispatching method of wind-PV-CSP-hydro-battery system with wind and photovoltaic power generation as the main energy sources. The long short-term memory (LSTM) neural network is applied to predict wind and PV power, besides, the Latin Hypercube Sampling (LHS) method and the synchronous reduction algorithm are used to obtain 10 typical wind and PV power scenarios. A day-ahead economic dispatch model of wind-PV-CSP-hydro-battery mathematical model is established, and relevant constraints are considered. Concentrated solar power (CSP), hydropower stations, batteries, and transferable loads are used as flexible resources to increase the penetration rate of wind and photovoltaic power generation. Finally, three cases are tested to demonstrate the feasibility of the proposed model. The results show that: (1) LSTM neural network can well predict the output power of wind and photovoltaic power generation with a small root mean square error (RMSE). (2) The introduction of transferable loads and CSP power station into the renewable energy power system can effectively reduce the fluctuation and curtailment rates of wind power and PV power generation.