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To alleviate the 'curse of dimensionality' and speed up the calculation of the total supply capability curve (TSC curve), this paper proposes a novel critical flow-based fast algorithm for distribution networks. Firstly, the critical flow and the TSC curve are found to have good correspondence through the comparison of their concepts and models. Secondly, a critical flow-based algorithm with three phases is proposed for calculating the TSC curve: (i). Determine the equivalent flow network of the distribution network; (ii). Solve critical flows of the equivalent flow network through a dimension reduction-sampling algorithm and obtain the corresponding TSC curve operating points; (iii). Calculate the flow value of the critical flow and plot the TSC curve. Finally, the proposed algorithm is verified by the expanded IEEE RBTS BUS4 case with soft open point (SOP). The application of the TSC curve in distribution network planning is demonstrated. In addition, the correctness and rapidity of the proposed algorithm are verified by comparing it with the existing sampling algorithm, and the reasons for the performance improvement are investigated. This paper applies the network flow theory to calculating the power supply capability of distribution networks for the first time, which simplifies the calculation of the TSC curve and increases the computational efficiency significantly. [ABSTRACT FROM AUTHOR]

Herein we described the clinical characteristics of a Chinese girl with youth-onset type 2 diabetes coexisting with FRG, in whom a novel mutation (NM 003041.4:c.1129 + 2 T > C) of the I SLC5A2 i gene might explain FRG occurrence. MODY is a special type of diabetes mellitus, representing a small but very important fraction of diabetic patients (1%-5%),[[4]] and 1%-6% of cases in pediatric age.[6] In this patient, no mutations in 14 genes associated with MODY have been detected, and its diagnosis was also excluded. The pathogenesis of youth-onset type 2 diabetes is different from that of maturity-onset diabetes of the young (MODY) and from type 1 diabetes, but there are many overlapped clinical manifestations among these three types of diabetes. A young-onset type 2 diabetic Chinese girl with familial renal glycosuria caused by a novel mutation in SLC5A2: A case report. [Extracted from the article]

To reveal the complete limits of a flow network, this paper proposes the concept of critical flow. Firstly, it is found that a flow network is in a critical state when it reaches its maximum flow, and the network cannot afford any flow increase. In fact, not only maximum flow but many other network flows, i.e., blocking flows, indicate the critical states of a flow network. From a new viewpoint, the concept of critical flow is proposed, which unifies the maximum flow and the blocking flow. Secondly, the mathematical model, solution algorithms, and visualization method for critical flow are proposed. An analytical algorithm and a numerical algorithm are proposed to calculate the complete critical flows. In addition, a critical flow curve is designed to visualize the complete limits of a network, with the top point being the maximum flow. Finally, case studies are conducted to illustrate the critical flow and its typical applications in flow networks and real networks. It is concluded that the complete limits of a flow network are the range of critical flows, not a single maximum flow value. The proposed critical flows describe the complete limits of a flow network for the first time. Critical flow can be used for network monitoring and network planning. In monitoring, it reflects the margin of the flow network more accurately than maximum flow. In planning, it evaluates the flow transmission capability more accurately than maximum flow. [ABSTRACT FROM AUTHOR]

Background. Functional pancreatic neuroendocrine neoplasms (PanNENs) are very rare disorders but have complex spectrum, including insulinoma, gastrinoma, glucagonoma, somatostatinoma, and VIPoma. Patients with PanNENs usually present with characteristic symptoms caused by corresponding hormone hypersecretion. It has always been challenging in dealing with such rare but complicated disorders. In this report, we analyzed the clinical characteristics of functional PanNENs in a large cohort of Chinese patients and summarized our clinical experience in diagnosis and treatment. Methods. The retrospective analysis was performed in patients with a definite diagnosis of functional PanNENs hospitalized in Chinese PLA General Hospital between 2000 and 2020. The clinical characteristics, surgical information, and pathological findings were extracted from their medical records and were analyzed. Results. Totally, 286 patients (gender: male 103 and female 183; age: 45.55 ± 15.23 years old) were diagnosed with definite functional PanNENs. The most frequent functional PanNENs were insulinoma (266/286) followed by glucagonoma (10/286), somatostatinoma (3/286), adrenocorticotropic hormone- (ACTH-) producing tumor (3/286), gastrinoma (2/286), and VIPoma (2/286). Nine patients were diagnosed with multiple endocrine neoplasia type 1 (MEN1) in which all the associated functional PanNENs were insulinomas. The duration from symptoms' onset to confirmed diagnosis was 3.67 ± 4.28 years. Two hundred and eighty patients with tumor localized in pancreatic or with limited metastasis underwent surgery. The symptoms associated with hormonal oversecretion were improved significantly after surgery. Five patients with unresectable metastases or tumor recurrence after surgery were administrated with systemic chemotherapy or other targeted therapies. With these various therapies, the symptoms were also partially relieved. According to findings in pathological and immunochemical examination, all the functional PanNENs were categorized into NEN-G1 (41.95%), NEN-G2 (54.90%), NEN-G3 (3.15%), and NEC-G3 (0%). Conclusion. Patients with suspected functional PanNENs should have a systematic endocrine examination at diagnosis. Multidisciplinary collaborations are essential for precise diagnosis and tumor localization. A successful surgery or other targeted therapies can improve the prognosis of patients with such rare but complex disorders. [ABSTRACT FROM AUTHOR]

• Proposed the concept and mathematical model of the operational boundary (OB) for flow networks. • Developed an analytical algorithm and a sampling algorithm to calculate the OB. • Visualized the OB and demonstrated the proposed method in multi-source multi-sink networks. • Developed the OB-based safety management framework for flow networks, which specifically includes (i) identifying the security state, (ii) identifying the security margin, (iii) monitoring the security trend, and iv) developing corrective schemes for security control. Flow networks can represent complex systems and exhibit generality. The operational boundary (OB) can describe the secure operational range of complex systems. It helps to enhance network safety to determine the OB of flow networks. This paper proposes the OB for flow networks to completely represent the maximum range the network's feasible flow can reach. Firstly, the concept and mathematical model of the OB are proposed. As a subset of the feasible flows, the set of all the blocking flows is defined as the OB. The OB forms the boundary that separates the feasible flows from the infeasible flows. The feasible flows in critical states are located on the OB, and the maximum flows are located on the outermost layer of the OB. Secondly, an analytical algorithm and a sampling algorithm are proposed to calculate the OB. The former one can completely represent the OB, while the latter one better reflects the state of the boundary points. Moreover, the OB-based safety management framework, which includes security assessment and security control, has been developed to improve the safety and reliability of flow networks. Finally, the effectiveness of the proposed method is demonstrated in multiple-source multiple-sink networks. [ABSTRACT FROM AUTHOR]

Monitoring of disinfection by-products (DBPs) in water supply system is important to ensure safety of drinking water. Yet it is a laborious job. Developing predictive DBPs models using simple and easy parameters is a promising way. Yet current models could not be well applied into practice because of the improper dataset (e.g. not from real tap water) they used or involving the parameters that are difficult to measure or require expensive instruments. In this study, four simple and easy water quality parameters (temperature, pH, UVA 254 and Cl 2) were used to predict trihalomethane (THMs) occurrence in tap water. Linear/log linear regression models (LRM) and radial basis function artificial neural network (RBF ANN) were adopted to develop the THMs models. 64 observations from tap water samples were used to develop and test models. Results showed that only one or two parameters entered LRMs, and their prediction ability was very limited (testing datasets: N 25 = 46–69%, r p = 0.334–0.459). Different from LRM, the prediction accuracy of RBF ANNs developed with pH, temperature, UVA 254 and Cl 2 can be improved continuously by tweaking the maximum number of neuron (MN) and Gaussian function spread (S) until it reached best. The optimum RBF ANNs of T-THMs, TCM and BDCM were obtained when setting MN = 20, S = 100, 100.1 and 60, respectively, where the N 25 and r p values for testing datasets reached 85–92% and 0.813–0.886, respectively. Accurate predictions of THMs by RBF ANNs with these four simple and easy parameters paved an economic and convenient way for THMs monitoring in real water supply system. [Display omitted] • LRMs generated with pH, Temp, UVA 254 and Cl 2 cannot well predict THMs in tap water. • RBF ANNs developed with pH, Temp, UVA 254 and Cl 2 can be improved continuously by adjusting N and S. • RBF ANN developed with pH, Temp, UVA 254 and Cl 2 can well predict THMs in tap water. • This study gives a simple and convenient way for THMs monitoring in practice. [ABSTRACT FROM AUTHOR]

This paper proposes effective evidence on the correlation between trend and self-organized criticality (SOC) of the power outage sequence in China. Taking the data series of blackouts from 1981 to 2014 in the China power grid as the research object, the method of V / S is introduced into the analysis of the power system blackout sequence to demonstrate their prominent long-time correlations. It also verifies the probability distribution of load loss about blackout size in the China power grid has a tail feature, which shows that the time series of blackouts in the China power grid is consistent with SOC. Meanwhile, a kind of mathematical statistics analysis is presented to prove that there is a seasonal trend of blackouts, and the blackout frequency and blackout size have not decreased over time but have an upward trend in the China power grid, thereby indicating that blackout risk may be increasing with time. The last 34 years' data samples of power failure accidents in the China power grid are used to test the proposed method, and the numerical results show that the proposed self-organized criticality and trend analysis method can pave the way for further exploration of the mechanism of power failure in the China power grid. [ABSTRACT FROM AUTHOR]

Succinate is an important intermediate of the tricarboxylic acid cycle. Recently discovered roles of succinate demonstrate its involvement in immunity and cancer biology; however, the precise underlying mechanisms of its involvement in these additional roles remain to be determined. In the present study, succinate dehydrogenase (SDH) B was decreased in uterine endometrial cancer cells (UECC) under negative regulation of estrogen. This decrease was the result of lower expression levels of ubiquitin C (UBC), which was associated with the activation of peroxisome proliferator-activated receptor gamma and specificity protein 1. The decreased levels of SDHB resulted in the accumulation of succinate in UECC, and thus, a decrease in the production of fumaric acid. Succinate downregulated voltage-gated potassium channel subfamily Q member 1 (KCNQ1) levels by activating serum/glucocorticoid regulated kinase 1 and promoted the growth of UECC in vitro and in vivo. Treatment with melatonin restricted estrogen/UBC/SDHB-induced succinate accumulation and upregulated expression of KCNQ1 and reduced the succinate-mediated growth of UECC in vitro and in vivo. Furthermore, overexpression of melatonin receptor 1B amplified the inhibitory effects of melatonin on succinate-mediated UECC growth. Together, the data in the present study suggest that melatonin suppresses UECC progression by inhibiting estrogen/UBC/SDHB-induced succinate accumulation. The present study provides a scientific basis for potential therapeutic strategies and targets in UEC, particularly for patients with abnormally low levels of SDHB. [ABSTRACT FROM AUTHOR]

The clear cell (CCC), high grade serous (HGSC) and endometrioid (EC) ovarian carcinomas share overlapping histological features. The oncogene IMP3 is implicated in CCC with an elusive utility in differential diagnosis. We collected 366 cases with ovarian primary carcinomas to detect IMP3, Napsin-A and HNF-1β by immunochemistry. In 351 cases, the positive expression rate of IMP3 in CCC was significantly higher than that either in EC or HGSC ( p  < 0.01). The sensitivity of IMP3 in CCC was higher than Napsin-A but lower than HNF-1β ( p  < 0.01). The specificity of IMP3 in CCC was lower than Napsin-A but higher than HNF-1β ( p  < 0.01). The composite markers Napsin-A+/IMP3+ and the IMP3+/HNF-1β+/Napsin-A+ offered the highest odds ratio ( p  < 0.001), the highest specificity, the highest positive predictive value and the highest positive likelihood ratio. The ROC analysis showed that the combination of Napsin-A, HNF-1β and IMP3 offered the biggest AUC compared with either the singular marker performances or the other binary combinations ( p  < 0.001). In 15 cases of EC mixed with CCC, IMP3 showed a better discrimination value than the other two markers. Consequently, adding IMP3 to the diagnostic panel might provide some help with the pathological diagnosis of ovarian CCC. [ABSTRACT FROM AUTHOR]