Optimal Control Strategy of Platform Load Oriented to Network and Load Cooperation

In recent years, with the continuous growth of China’s power peak load and the rapid development of renewable energy, a large number of renewable energy sources are connected to the power grid, increasing the uncertainty of power grid operation and posing new major challenges to the power system regulation capacity. Flexible load has the characteristics of wide distribution, fast response, and high economy, which is an important control resource for the future power system. Based on the flexible load of commercial buildings and residential users, this paper studies the resource characteristics and response characteristics, clarifies the resource characteristics and demand response characteristic indexes of commercial and residential users, and establishes the response characteristics model of commercial buildings and residential users. Considering the influence of weather, holidays, incentive mechanism, and other factors on the response of flexible load, the quantitative analysis method of flexible load resource regulation potential for regional power grid dispatching was studied, and the feasibility of flexible load resources directly participating in the load control system was analyzed. Based on the uncertainty and mathematical characterization method of the active response of flexible loads, the optimal combination control strategy of demand response resources was proposed to eliminate the problems of heavy load and overload of regional power grid equipment by using the active response ability of flexible loads. Finally, the IEEE 14-node system is selected for simulation verification, which provides a theoretical basis for alleviating the power grid operation pressure in the peak load period of the power grid in the urban core area, improving the safety and economic operation level of regional power grid dispatching and the utilization rate of power grid equipment assets

Application value of endoscopic submucosal dissection and endoscopic mucosal resection for treatment of rectal carcinoids

Objective: The objective of this study is to explore the clinical effect and safety of endoscopic submucosal dissection (ESD) and endoscopic mucosal resection (EMR) for treatment of rectal carcinoids. Methods: A retrospective analysis was conducted on 42 patients with rectal carcinoids who were hospitalized and subjected to surgical treatment in our hospital from January 2010 to November 2015. The patients were categorized into two groups based on treatment received: ESD (n = 22) and EMR (n = 20). The patients were analyzed and compared to determine differences in lesion size, operation time, histopathologically curative resection rate, intraoperative complications, complete lesion resection rate, and postoperative recurrence rate between the two groups. Results: Operation time (25.2 ± 20.1 min) and wound surface diameter (36.2 ± 10.1 mm) were significantly higher in the ESD group than those in the EMR group (12.6 ± 8.4 min and 18.6 ± 5.9 mm, respectively) (P < 0.05). The differences in complete lesion and histopathologically curative resection rates between the two groups were not statistically significant (P > 0.05). Delayed hemorrhage was the primary postoperative complication in both groups. Postoperative follow-up was performed for 3–71 months, and the median follow-up time was 45 months. Recurrence was noted 32 months after surgery in one patient in the EMR group (4.5%), whereas recurrence was not detected in the ESD group. Conclusion: ESD and EMR are safe and effective methods for treatment of rectal carcinoids. Moreover, ESD had less risk of recurrence, more complete resection rate which could provide more information for postoperative treatment

Knowledge Embedded Semi-Supervised Deep Learning for Detecting Non-Technical Losses in the Smart Grid

Non-technical losses (NTL) caused by fault or electricity theft is greatly harmful to the power grid. Industrial customers consume most of the power energy, and it is important to reduce this part of NTL. Currently, most work concentrates on analyzing characteristic of electricity consumption to detect NTL among residential customers. However, the related feature models cannot be adapted to industrial customers because they do not have a fixed electricity consumption pattern. Therefore, this paper starts from the principle of electricity measurement, and proposes a deep learning-based method to extract advanced features from massive smart meter data rather than artificial features. Firstly, we organize electricity magnitudes as one-dimensional sample data and embed the knowledge of electricity measurement in channels. Then, this paper proposes a semi-supervised deep learning model which uses a large number of unlabeled data and adversarial module to avoid overfitting. The experiment results show that our approach can achieve satisfactory performance even when trained by very small samples. Compared with the state-of-the-art methods, our method has achieved obvious improvement in all metrics

Analyzing an Epidemic of Human Infections with Two Strains of Zoonotic Virus

Due to the existence and variation of various viruses, an epidemic in which different strains spread at the same time will occur. here, an avian&ndash;human epidemic model with two strain viruses are established and analyzed. Both theoretical and simulation results reveal that the mixed infections intensify the epidemic and the dynamics become more complex and sensitive. There are six equilibria. The trivial equilibrium point is a high-order singular point and will undergo the transcritical bifurcations to bifurcate three equilibria. The existence and stability of equilibria mainly depend on five thresholds. A bifurcation portrait for the existence and stability of equilibria is presented. Simulations suggest that the key control measure is to develop the identification technology to eliminate the poultry infected with a high pathogenic virus preferentially, then the infected poultry with a low pathogenic virus in the recruitment and on farms. Controlling contact between human and poultry can effectively restrain the epidemic and controlling contagions in poultry can avoid great infection in humans

Decitabine plus CLAG chemotherapy as a bridge to haploidentical transplantation in the setting of acute myeloid leukemia relapse after HLA-matched sibling transplantation: a case report

Abstract Background Patients with relapsed/refractory acute myeloid leukemia after hematopoietic stem cell transplantation (HSCT) have a poor prognosis, with a 2-year survival rate of 14%. The optimal treatment for these patients remains unclear. To treat these patients, we designed a new salvage regimen consisting of decitabine, cladribine, cytarabine, and granulocyte-stimulating factor (D-CLAG). Case presentation Here, we describe a case of acute monocytic leukemia with a complex karyotype in a 38-year-old female patient who relapsed after her first HSCT, which was performed using a matched sibling donor. The patient did not respond to standard induction chemotherapy and subsequently achieved complete remission with the D-CLAG regimen. No severe hematological or extramedullary toxicity was observed. Subsequently, the patient received a second D-CLAG regimen as a bridge therapy and directly underwent haploidentical related HSCT. Following HSCT, the marrow showed complete hematologic and cytogenetic remission. Currently, 1 year after transplantation, the patient’s general condition remains good. Conclusions This case suggests that the D-CLAG regimen can be an option for reinduction in relapsed refractory AML patients as a bridge to transplantation. Nevertheless, further research will be required in the future as this report describes only a single case

Altered Genes and Biological Functions in Response to Severe Burns

Severe burns are acute wounds caused by local heat exposure, resulting in life-threatening systemic effects and poor survival. However, the specific molecular mechanisms remain unclear. First, we downloaded gene expression data related to severe burns from the GEO database (GSE19743, GSE37069, and GSE77791). Then, a gene expression analysis was performed to identify differentially expressed genes (DEGs) and construct protein-protein interaction (PPI) network. The molecular mechanism was identified by enrichment analysis and Gene Set Enrichment Analysis. In addition, STEM software was used to screen for genes persistently expressed during response to severe burns, and receiver operating characteristic (ROC) curve was used to identify key DEGs. A total of 2631 upregulated and 3451 downregulated DEGs were identified. PPI network analysis clustered these DEGs into 13 modules. Importantly, module genes mostly related with immune responses and metabolism. In addition, we identified genes persistently altered during the response to severe burns corresponding to survival and death status. Among the genes with high area under the ROC curve in the PPI network gene, CCL5 and LCK were identified as key DEGs, which may affect the prognosis of burn patients. Gene set variation analysis showed that the immune response was inhibited and several types of immune cells were decreased, while the metabolic response was enhanced. The results showed that persistent gene expression changes occur in response to severe burns, which may underlie chronic alterations in physiological pathways. Identifying the key altered genes may reveal potential therapeutic targets for mitigating the effects of severe burns