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Abstract Focusing solely on enhancing the resilience of power systems at a systemic level would lead to a significant underestimation of the actual impact of extreme disasters. Equally vital is the assurance of livelihood security amidst such extreme conditions, which is crucial for the development of a truly resilient power system. Hence, this paper attempts to incorporate quantifiable metrics assessing public safety impacts into resilience enhancement works, thereby guiding the precise allocation of funds. Considering that the residents' intuitive feelings are the most direct reflection of the severity of the disaster, this paper employs the modified prospect theory to formulate functions representing residents' psychological risk perception and risk‐taking willingness to tolerate risks during disruptions in power, gas, and water supplies. Meanwhile, in order to accurately calculate the energy loss duration for each residential customer, a resilience enhancement method for post‐disaster collaborative dispatch of electricity‐gas‐water systems is proposed. With the objective of minimizing the public safety and economic impact of disasters, the optimal multi‐source collaborative emergency restoration strategy is developed. The significant necessity and efficiency of the proposed strategy are verified with exhaustive case studies. Numerical results evince the resilience enhancement by considering the livelihood security in the post‐disaster restoration stage.

The Traditional Chinese Medicine compound preparation known as Diwu Yanggan capsule (DWYG) can effectively hinder the onset and progression of hepatocellular carcinoma (HCC), which is recognized worldwide as a significant contributor to fatalities associated with cancer. Nevertheless, the precise mechanisms implicated have remained ambiguous. In present study, the model of HCC was set up by the 2-acetylaminofluorene (2-AAF)/partial hepatectomy (PH) in rats. To confirm the differentially expressed genes (DEGs) identified in the microarray analysis, real-time quantitative reverse transcription PCR (qRT-PCR) was conducted. In the meantime, the liquid chromatography-quadrupole time of flight mass spectrometry (LC-QTOF-MS/MS) was employed to characterize the component profile of DWYG. Consequently, the DWYG treatment exhibited the ability to reverse 51 variation genes induced by 2-AAF/PH. Additionally, there was an overlap of 54 variation genes between the normal and model groups. Upon conducting RT-qPCR analysis, it was observed that the expression levels of all genes were increased by 2-AAF/PH and subsequently reversed after DWYG treatment. Notably, the fold change of expression levels for all genes was below 0.5, with 3 genes falling below 0.25. Moreover, an investigation was conducted to determine the signaling pathway that was activated/inhibited in the HCC group and subsequently reversed in the DWYG group. Moreover, the component profile of DWYG encompassed a comprehensive compilation of 206 compounds that were identified or characterized. The findings of this study elucidated the potential alleviative mechanisms of DWYG in the context of HCC, thereby holding significant implications for its future clinical utilization and widespread adoption.

Abstract The Balanophorae are not only traditional Chinese herbal medicines but also functional foods with diverse sources. This study aimed to distinguish pharmacognostic characteristics and secondary metabolites among different species of Balanophorae. Eight species of Balanophorae herbs were harvested, including 21 batches with 209 samples. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was used to analyze secondary metabolites of Balanophorae from 21 sources. Targeted metabolomic analysis was performed to compare differences among the groups. Rhopalocnemis phalloide and B. indica can be identified by their pharmacognostic characteristics. Then, 41 secondary metabolites were identified or characterized in the mixed extracts of the 209 samples, mainly phenolic acids, flavonoids, and their derivatives. The distribution of these secondary metabolites revealed apparent differences among different species. In addition, targeted metabolomic analysis suggested that the secondary metabolite profiles of seven species of Balanophorae showed noticeable differences, and differences were also observed among different growing regions. Finally, five important metabolic markers were screened to successfully distinguish B. laxiflora, B. harlandii, and B. polyandra, including three phenolic acids and two flavonoids. This is the first study to systematically compare both the morphology and secondary metabolites among different sources of Balanophorae, which could provide effective information for identifying diverse species.

Abstract The indirect benefits of battery energy storage system (BESS) on the generation side participating in auxiliary service are hardly quantified in prior works. Nevertheless, the configuration of BESS could be affected by its indirect benefits. In this paper, the authors purpose a quantitative economic evaluation method of BESS considering the indirect benefits from the reduction in unit loss and the delay in investment. First, the authors complete further the cost model of BESS for frequency and peak regulation based on the whole life cycle theory. Second, the authors quantify the indirect benefits of BESS in thermal power plants based on the theory of rotor fatigue life loss and establish a benefits model that considers the unit loss reduction during frequency regulation and the delay in investment during peak regulation. Finally, the authors propose a set of indexes for economic evaluation of the thermal power plant with BESS. The simulation results show that the total benefits of BESS can be improved effectively by considering the indirect benefits from unit loss reduction and the delay in investment, proving the effectiveness of the proposed approach which can be meaningful for the future investment in BESS on the generation side.

Abstract The generation of chimeric antigen receptor‐modified natural killer (CAR‐NK) cells using induced pluripotent stem cells (iPSCs) has emerged as one of the paradigms for manufacturing off‐the‐shelf universal immunotherapy. However, there are still some challenges in enhancing the potency, safety, and multiple actions of CAR‐NK cells. Here, iPSCs were site‐specifically integrated at the ribosomal DNA (rDNA) locus with interleukin 24 (IL24) and CD19‐specific chimeric antigen receptor (CAR19), and successfully differentiated into iPSC‐derived NK (iNK) cells, followed by expansion using magnetic beads in vitro. Compared with the CAR19‐iNK cells, IL24 armored CAR19‐iNK (CAR19‐IL24‐iNK) cells showed higher cytotoxic capacity and amplification ability in vitro and inhibited tumor progression more effectively with better survival in a B‐cell acute lymphoblastic leukaemia (B‐ALL) (Nalm‐6 (Luc1))‐bearing mouse model. Interestingly, RNA‐sequencing analysis showed that IL24 may enhance iNK cell function through nuclear factor kappa B (NFκB) pathway‐related genes while exerting a direct effect on tumor cells. This study proved the feasibility and potential of combining IL24 with CAR‐iNK cell therapy, suggesting a novel and promising off‐the‐shelf immunotherapy strategy.

Available transfer capability (ATC) is an important measurement index to evaluate the security margin of interconnected power grids and serve as a reference for the transmission right transaction. In modern power systems, ATC is affected by the transmission network topology, renewable power output uncertainty, and load demand uncertainty. Traditional works usually model the power source-load uncertainty by using robust optimization, interval optimization, or chance-constraint optimization, which cannot fully reflect the probabilistic distribution of the daily source-load uncertainty. This paper proposes an ATC assessment methodology based on the typical stochastic scenarios of renewable output and load demand of multiarea power systems. Furthermore, the conditional generative adversarial network (CGAN) algorithm is adopted to generate and select representative scenario sets based on historical raw data, which can fully reflect the usual operating condition of a system with high renewable energy penetration. The scenario set that is fed into the ATC assessment model can fully characterize the impact of source-load uncertainty on daily ATC. Finally, the proposed method is verified by a modified three-area IEEE 9-bus system and a real-world provincial power system.

Abstract In this paper, a collaborative stochastic expansion planning model of cyber‐physical system (CPS) with resilience constraints is proposed. The model can reduce the coupling risk and enhance the resilience under extreme scenarios, from the perspective of the structural/functional coupling between the physical and cyber systems. The model is to collaboratively optimize expansion transmission line siting, expansion communication fibre siting, and service routing distribution to minimize total investment cost. Constraints are divided into conventional constraints and resilience constraints. In the resilience constraints, the impact of cyber failures on the dispatch strategy is analyzed, and the load shedding in stochastic scenarios is limited to guarantee the resilience of the planning scheme. Particularly, to reach a stable solution for the stochastic planning, a mixed scenario set is proposed based on the probabilistic typhoon model and the complex network theory. Finally, the model is solved by the progressive hedging (PH) algorithm. The case studies of the IEEE RTS‐79 test system demonstrate that, compared with the traditional independent planning model, the model proposed in this paper performs better in limiting load loss and enhancing resilience under extreme scenarios.

In this paper the authors construct estimates of electricity consumption changes at the metropolitan level across the continental U.S., during the initial two months of the COVID-19 pandemic, demonstrating variations in electricity consumption patterns based on several factors.

Background: Citrullinemia type I (CTLN1) is a rare autosomal recessive inborn error of the urea cycle caused by mutations in the gene encoding the arginosuccinate synthetase (ASS1) enzyme. Classic CTLN1 often manifests with acute hyperammonemia and neurological symptoms. Molecular genetic testing is critical for patient diagnosis.Methods: Three unrelated families with clinically suspected CTLN1 were included in this study. Potential pathogenic variants were identified using whole exome sequencing (WES) and validated using Sanger sequencing. Western blotting, quantitative PCR, immunofluorescent staining, and ELISA were used to assess functional changes in candidate ASS1 variants.Results: Five variants were identified, two of which were novel, and one has been reported, but its pathogenicity was not validated. The novel variant c.649-651del (p.P217del) and the 5′UTR variant (c.-4C>T) resulted in a decrease in ASS1 expression at both the protein and transcription levels. The other novel variant, c.1048C>T (p.Q350*), showed a marked decrease in expression at the protein level, with the formation of truncated proteins but an increased transcription. Both c.649_651del (p.P217del) and c.1048C>T (p.Q350*) showed a highly significant reduction in enzyme activity, while c.-4C>T had no effect.Conclusion: We identified two novel variants and a hypomorphic non-coding variant in ASS1 and validated the pathogenicity using functional studies. Our findings contribute to expanding the spectrum of ASS1 variants and understanding the genotype-phenotype relationships of CTLN1.

Introduction: Demand response programs are promising approaches to balance supply and demand and reduce or shift peak hour loads. However, the impacts of residents’ behavioral patterns and social–psychological factors on these programs are poorly understood.Method: We used an extended model of the theory of planned behavior to understand how social–psychological factors, demographics, and household characteristics influence the demand response behaviors (i.e., adjusting A/C and shifting the time of use) of 826 US residents who participated in our study.Results: We found that low-income households (43.7%) reported as more likely to respond to the behavior of raising A/C thermostat settings when no one is home compared to higher-income residents. Thermal comfort needs (β = 0.34) and participants’ age (β = 0.02) increased the financial incentives requested to accept higher A/C temperatures while someone is home. Thermal comfort needs (β = 0.36) and energy-saving habits (β = −0.11) are the significant predictors of increased incentives requested for higher A/C temperatures when no one is home. Older adults request higher financial incentives for shifting washer and dryer usage than younger residents. Finally, attitudes toward energy saving are the strongest predictor of electricity curtailment behavioral intention, followed by perceived behavioral control, subjective norms, cost and environmental concerns, and energy-saving habits.Discussion: This finding suggests the potential of social–psychological variables in shaping energy consumption behaviors. This study provides insights for designing effective demand response programs and broadly analyzing energy behavioral patterns.

ObjectiveMetagenomic next-generation sequencing (mNGS) technology has the potential to detect a wide range of pathogenic microorganisms. However, reports on the diagnostic value and clinical significance of different platforms of mNGS for patients with lower respiratory tract infections (LRTIs) remain scarce.MethodsA total of 306 patients with suspected LRTIs were enrolled from January 2019 to December 2021. The diagnostic performance of conventional methods and mNGS on bronchoalveolar lavage fluid (BALF) were compared. BALF mNGS was performed using a commercial and an in-house laboratory. The diagnostic value and the clinical implications of mNGS for LRTIs were analyzed for the different platforms.ResultsThe positive rate of mNGS in the in-house group was higher than that in the commercial group (85.26% vs. 70.67%, p < 0.001). mNGS significantly increased the pathogen detection rate compared with conventional methods [from 70.67% vs. 22.67% (p < 0.001) to 85.26% vs. 30.77% (p < 0.001)]. The pathogens detected using mNGS included bacteria, fungi, viruses, and atypical pathogens. The in-house platform performed well on a wider spectrum of microbial distribution. Furthermore, it showed an advantage in detecting mixed pathogens in immunocompromised patients. Among the mNGS positive cases, 34 (32.0%) cases had their antibiotics adjusted in the commercial group, while 51 (38.3%) cases had a change of treatment in the in-house group. Moreover, the turnaround time of mNGS and the time from mNGS to discharge in the in-house group were significantly shorter than those in the commercial group.ConclusionIn-house mNGS had a higher detection rate and can show a wider spectrum of pathogens, with potential benefits for the clinic by shortening the turnaround time and hospitalization, and it may be more suitable for clinical microbiology laboratories.

Abstract In the transactive energy (TE) paradigm, the devices of participative consumers, or prosumers, may be aggregated and employed to drive operational objectives at the network level. Home heating, ventilation and air‐conditioning (HVAC) systems in particular are well‐suited to modulate their behaviours based on both home thermal flexibility and requests from the utility grid. This paper develops a robust, hierarchical power dispatch scheme in the context of a residential distribution network. The formulation couples a unique, multiphase linear distribution optimal power flow (OPF) at the upper level with model predictive control (MPC)‐based HVAC fleet controllers at the lower level. The proposed approach is tested on nearly 2000 homes with a three‐phase distribution network in an intraday market setting, where two major applications are explored and analysed.

This paper proposes a learning control framework for the robotic manipulator’s dynamic tracking task demanding fixed-time convergence and constrained output. In contrast with model-dependent methods, the proposed solution deals with unknown manipulator dynamics and external disturbances by virtue of a recurrent neural network (RNN)-based online approximator. First, a time-varying tangent-type barrier Lyapunov function (BLF) is introduced to construct a fixed-time virtual controller. Then, the RNN approximator is embedded in the closed-loop system to compensate for the lumped unknown term in the feedforward loop. Finally, we devise a novel fixed-time, output-constrained neural learning controller by integrating the BLF and RNN approximator into the main framework of the dynamic surface control (DSC). The proposed scheme not only guarantees the tracking errors converge to the small neighborhoods about the origin in a fixed time, but also preserves the actual trajectories always within the prescribed ranges and thus improves the tracking accuracy. Experiment results illustrate the excellent tracking performance and verify the effectiveness of the online RNN estimate for unknown dynamics and external disturbances.

Abstract As a key component of an integrated energy system (IES), energy storage can effectively alleviate the problem of the times between energy production and consumption. Exploiting the benefits of energy storage can improve the competitiveness of multi-energy systems. This paper proposes a method for day-ahead operation optimization of a building-level integrated energy system (BIES) considering additional potential benefits of energy storage. Based on the characteristics of peak-shaving and valley-filling of energy storage, and further consideration of the changes in the system’s load and real-time electricity price, a model of additional potential benefits of energy storage is developed. Aiming at the lowest total operating cost, a bi-level optimal operational model for day-ahead operation of BIES is developed. A case analysis of different dispatch strategies verifies that the addition of the proposed battery scheduling strategy improves economic operation. The results demonstrate that the model can exploit energy storage’s potential, further optimize the power output of BIES and reduce the economic cost.

The sequential method is easy to integrate with existing large-scale alternating current (AC) power flow solvers and is therefore a common approach for solving the power flow of AC/direct current (DC) hybrid systems. In this paper, a highperformance graph computing based distributed parallel implementation of the sequential method with an improved initial estimate approach for hybrid AC/DC systems is developed. The proposed approach is capable of speeding up the entire computation process without compromising the accuracy of result. First, the AC/DC network is intuitively represented by a graph and stored in a graph database (GDB) to expedite data processing. Considering the interconnection of AC grids via high-voltage direct current (HVDC) links, the network is subsequently partitioned into independent areas which are naturally fit for distributed power flow analysis. For each area, the fast-decoupled power flow (FDPF) is employed with node-based parallel computing (NPC) and hierarchical parallel computing (HPC) to quickly identify system states. Furthermore, to reduce the alternate iterations in the sequential method, a new decoupled approach is utilized to achieve a good initial estimate for the New-ton-Raphson method. With the improved initial estimate, the sequential method can converge in fewer iterations. Consequently, the proposed approach allows for significant reduction in computing time and is able to meet the requirement of the real-time analysis platform for power system. The performance is verified on standard IEEE 300-bus system, extended large-scale systems, and a practical 11119-bus system in China.

As the penetration of renewable energy continues to increase, stochastic and intermittent generation resources gradually replace the conventional generators, bringing significant challenges in stabilizing power system frequency. Thus, aggregating demand-side resources for frequency regulation attracts attentions from both academia and industry. However, in practice, conventional aggregation approaches suffer from random and uncertain behaviors of the users such as opting out control signals. The risk-averse multi-armed bandit learning approach is adopted to learn the behaviors of the users and a novel aggregation strategy is developed for residential heating, ventilation, and air conditioning (HVAC) to provide reliable secondary frequency regulation. Compared with the conventional approach, the simulation results show that the risk-averse multi-armed bandit learning approach performs better in secondary frequency regulation with fewer users being selected and opting out of the control. Besides, the proposed approach is more robust to random and changing behaviors of the users.

Background. The incidence of polymicrobial bloodstream infections is increasing, the clinical characteristics of polymicrobial Acinetobacter baumannii bloodstream infections (AB-BSI) are unclear, and there are no reports of polymicrobial AB-BSI in mainland China. Therefore, our objective was to identify the clinical characteristics, risk factors, and outcomes of polymicrobial AB-BSI versus monomicrobial AB-BSI. Methods. A retrospective survey of all patients with AB-BSI from January 1, 2015, to December 31, 2019, and their clinical data were collected and analyzed by reviewing electronic medical records. All data were compared and analyzed between groups of monomicrobial and polymicrobial AB-BSI. Risk factors for polymicrobial AB-BSI were assessed using multivariable logistic regression analysis. Results. A total of 204 patients were included, of which 39 (19.1%) were patients with polymicrobial AB-BSI. The main sources of the pathogenicity of polymicrobial Acinetobacter baumannii bloodstream infections were skin and soft tissue (38.5% vs. 16.4%, p=0.002). Resistance to piperacillin/tazobactam as an independent factor for polymicrobial AB-BSI was found in multivariate analysis. Patients with polymicrobial AB-BSI had longer hospital stays compared to those with monomicrobial AB-BSI. However, there was no significant difference in mortality between the two groups. Conclusions. Polymicrobial AB-BSI accounted for a significant proportion among all AB-BSI, and it did not influence mortality but was related to slightly longer total hospital stays. Multidrug resistance was associated with the development of polymicrobial AB-BSI but does not directly lead to polymicrobial AB-BSI, whereas resistance to piperacillin/tazobactam was highly correlated with polymicrobial AB-BSI. Therefore, while treating A. baumannii bloodstream infections, clinicians cannot ignore the multidrug-resistant A. baumannii, especially piperacillin/tazobactam-resistant A. baumannii, which may predispose to the development of polymicrobial AB-BSI.

Cardiolipins (CLs) are involved in ATP production, mitochondria biogenesis, apoptosis and mitophagy. Their tissue distribution can provide insight into the function of mitochondria and related diseases. However, the reports on tissue distribution of CLs remain limited. In this research, CLs were identified from heart, liver, kidney, spleen, lung, skeletal muscle, and brain using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS). Then, the distribution and sex difference of CLs in seven tissues were compared by a targeted lipidomic approach. A total of 88 CLs were identified, of which 58, 51, 57, 58, 50, 61 and 52 CLs were found in heart, liver, kidney, spleen, lung, skeletal muscle, and brain, respectively. Compared with the distribution of CLs in heart, liver, kidney, and skeletal muscle, the CLs in spleen, lung, and brain showed significant differences. Moreover, the results indicated that there were sex differences of CLs in liver and kidney. A total of 16 CLs in liver tissue and 21 CLs in kidney tissue, with significant sex differences, were screened. Our findings in the targeted lipidomic analysis demonstrated that tissue distribution of CLs was essential in the dynamic states and sex differences of CLs, which might provide evidence for the mitochondrial-related mechanism under physiological and pathological conditions.

Contezolid is a novel oxazolidinone, which exhibits potent activity against gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus (VRE), and penicillin-resistant Streptococcus pneumoniae (PRSP). In this study, the in vitro activity of contezolid was compared with linezolid (LZD), tigecycline (TGC), teicoplanin (TEC), vancomycin (VA), daptomycin (DAP), and florfenicol (FFC) against MRSA and VRE strains isolated from China. Contezolid revealed considerable activity against MRSA and VRE isolates with MIC90 values of 0.5 and 1.0 μg/mL, respectively. For VRE strains with different resistance genotypes, including vanA- and vanM-type strains, contezolid did not exhibit significantly differential antibacterial activity. Furthermore, the antimicrobial activity of contezolid is similar to or slightly better than that of linezolid against MRSA and VRE strains. Subsequently, the activity of contezolid was tested against strains carrying linezolid resistance genes, including Staphylococcus capitis carrying cfr gene and Enterococcus faecalis carrying optrA gene. The results showed that contezolid exhibited similar antimicrobial efficacy to linezolid against strains with linezolid resistance genes. In general, contezolid may have potential benefits to treat the infections caused by MRSA and VRE pathogens.

The voltage stability is an essential security concern when a system is operating in peak load hours or subjected to an N-1 contingency. Among various voltage stability indices, Local Thevenin Index (LTI) has been a popular one, but mostly applied to the measurement-based framework. The reason is that it requires significant computing effort if applied to model-based approach, even though the model-based LTI calculation can provide more accurate results. In this paper, a new model-based LTI calculation is proposed using graph-computing-based power flow calculation, which is fast enough to fully utilize the advantage of model-based LTI. Then, when the voltage stability index of one or multiple buses exceeds the security limit, a demand response scheme is activated to increase the voltage security margin at the lowest cost. The simulation study of a thousand-level-bus system verifies the computation accuracy and efficiency of the proposed model-based LTI. It also demonstrates that the demand response action can enhance the system security effectively. Thus, the proposed work has advantages if applied to a large-scale Energy Management System (EMS).

Despite recent great advances in microbial culture, most microbes have not yet been cultured, and the impact of medium composition on the isolation of microbes from natural systems has not been elucidated. To optimize media for culturing marine microbes, microbial communities in three sediment samples were described using high-throughput sequencing (HTS) and culture-dependent techniques. HTS revealed communities dominated by Gammaproteobacteria, and culture-based methods revealed communities dominated by Actinobacteria. Among the total operational taxonomic units (OTUs) from the HTS dataset, 6% were recovered in the culture collection. Four potentially novel bacterial strains belonging to Oceaniovalibus, Psychrobacter and Salegentibacter were isolated. The combination of media cultured more taxa than any single medium. Nutrient-rich and single-carbon/nitrogen-source media supported the growth of relatively few taxa, and the quality of nitrogen strongly influenced the types of bacteria isolated.

Objective. There is a limited diagnosis of nonalcoholic fatty liver disease (NAFLD). Thus, the noninvasive assessments are worth exploring. We determined the associations of phase angles (PhAs) obtained from bioelectric impedance analysis (BIA) with the risk of NAFLD in an overweight population. Methods. A study involving 953 overweight participants was conducted in Wuhan city, China. The associations between PhAs (right arm, left arm, body trunk, right leg, left leg, and whole body) and the risk of NAFLD were conducted using multivariate logistic regression analyses. The associations of PhAs with the controlled attenuation parameter (CAP), a noninvasive assessment of liver steatosis and fibrosis, were also evaluated by both linear and logistic regression analyses. Results. The PhA values of the whole body, trunk, and legs were significantly lower (P

The increasing integration of renewable resources and electric vehicles (EVs) presents new requirements for the construction of a current distribution network. As an alternative of conventional distribution network, active distribution network (ADN) has gained more interest for its flexibility and interactivity. However, the unpredictable behavior of ADN participants from source-side, network-side, and demand-side brings more challenges on ADN dispatch. Thus, it is urged to design an ADN optimal scheduling approach that can comprehensively regulate the ADN participants’ behavior. In this paper, an ADN performance assessment system is first established to provide a quantitative analysis on ADN’s scheduling in terms of active controllability, active manageability, and active economy, respectively. Then, according to the ADN assessment system, a multi-stage optimal scheduling approach for ADN considering coordinated EV charging strategy is proposed. It is able to not only smooth the fluctuations caused by the integration of intermittent power sources and EVs but also reconfigure the network topology. Therefore, this approach can be applied to day-ahead dispatches to help operators effectively manage the ADN. Simulation results verify the correctness and effectiveness of the proposed approach.

Alismatis rhizoma (AR) has been used as an herbal medicine in China for over a thousand years. Crude AR, salt-processed AR (SAR), and bran-processed AR (BAR) are recorded in the Pharmacopoeia of the People′s Republic of China. However, the differences of chemical composition between crude AR and its processing products remain limited. In this study, triterpenes were identified from crude AR, SAR, and BAR by ultra-high performance liquid chromatography coupled with quadrupole time-of-flight-mass spectrometer (UHPLC-QTOF-MS/MS). Subsequently, the differences of triterpenes between the crude AR and processed ARs were compared via a targeted metabolomics approach. Finally, a total of 114 triterpenes were identified, of which 83, 100, and 103 triterpenes were found in crude AR, SAR, and BAR, respectively. After salt-processing, there were 17 triterpenes newly generated, 7 triterpenes with trends of increasing, and 37 triterpenes decreased. Meanwhile, 56 triterpenes including 21 newly generated and 35 with significant increases were observed in BAR. This study could be benefit to investigate the processing mechanism of AR, as well as support their clinical applications.

Cucurbita maxima is one of the most widely cultivated Cucurbitaceae in Heilongjiang province, China. The objectives of this study were to clarify the genetic diversity of 44 accessions from different geographical origins using morphological and molecular characteristics and to compare the consistency of these morphological and molecular characteristics. Morphological characteristics showed a large qualitative variability primarily according to fruit-related traits. Twenty-eight random-amplified polymorphic DNA (RAPD) markers produced 128 bands. Both morphological characteristics and RAPD markers grouped 44 accessions of C. maxima into four clusters, and the similarity coefficients ranged from 0.70 to 0.91 and from 0.40 to 0.98, respectively. DNA polymorphisms were highly consistent with phenotypic traits on rootstock C. maxima. The relationships between C. maxima from different origins were not clearly defined via morphological characteristics and RAPD analysis, suggesting some traits of C. maxima were specific to geographical location had disappeared or were weak in Heilongjiang province, which would not facilitate pumpkin breeding. Hybrid generations and their parent plants or sister lines were grouped into sub-clusters and showed little genetic distance according to both evaluation methods. Overall, morphological characteristics and RAPD markers were consistent and revealed high genetic diversity between C. maxima landraces from different origins.

In modern power systems, the stochastic and interactive characteristics of mixed generations have gained increasing interest, especially when more renewable energy sources are connected to the grid. The uncertainty of renewable energy has notable effects on power system security. In this paper, a set of composite security indices, which are derived from the Hyper-box and Hyper-ellipse Space theory, are extended by a Latin hypercube sampling method to model multiple probabilistic scenarios under uncertainty. Thus, the proposed approach is suitable for power system security assessment with wind power integrated. According to the indices, a security-based active demand response (DR) strategy is proposed. This strategy is able to provide expected active DR capacity based on the forecast wind power fluctuations. Therefore, it can be applied to day-ahead power system dispatches.

More renewable energy resources have been connected to the grid with the promotion of global energy strategies, which presents new opportunities for the current electricity market. However, the growing integration of renewable energy also brings more challenges, such as power system reliability and the participants’ marketable behavior. Thus, how to coordinate integrated renewable resources in the electricity market environment has gained increasing interest. In this paper, a bilevel bidding model for load serving entities (LSEs) considering grid-level energy storage (ES) and virtual power plant (VPP) is established in the day-ahead (DA) market. Then, the model is extended by considering contingencies in the intraday (ID) market. Also, according to the extended bidding model, a remedial strategic rescheduling approach for LSE’s daily profit is proposed. It provides a quantitative assessment of LSE’s loss reduction based on contingency forecasting, which can be applied to the power system dispatch to help LSEs deal with coming contingencies. Simulation results verify the correctness and effectiveness of the proposed method.