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Abstract The real‐time simulation of the modular multilevel converter‐based high‐voltage direct current (MMC‐HVDC) transmission system has become a popular research topic. However, in order to meet the real‐time performance, the real‐time simulation technology will cause additional simulation errors for MMC‐HVDC, especially on its frequency characteristics. Therefore, a parallel multi‐rate simulation scheme for MMC‐HVDC is developed in this work to ensure accurate simulation of high‐frequency characteristics. Firstly, a non‐error method based on converter transformer decoupling is proposed to decouple the converter and alternating current system; direct current transmission line decoupling and arm decoupling methods are used to achieve decoupling among and within converters. A multi‐rate data synchronous mechanism is established by considering the differences among high‐frequency characteristics caused by delayed data interaction. Secondly, the computing architectures of the primary system solver and modular multilevel converter controller are designed based on a field programmable gate array (FPGA). The real‐time simulation platform for a four‐terminal true bipolar MMC‐HVDC is constructed based on the FPGA array. Thirdly, the factors in multi‐rate simulation affecting the simulation accuracy of high‐frequency characteristics are analysed. The simulator is shown to be accurate in steady and dynamic states. The authors also verify its applicability for further research on high‐frequency resonance based on control experiments.

In the process of the rapid development of big data and the Internet of Things in recent years, in order to create a "strong transportation" construction goals, intelligent transportation projects have become the key carrier of the development of China's transportation industry, the national and local transportation level, economic development and the improvement of people's living standards have an important role. However, although the construction of intelligent transportation projects around the world is in full swing, but the actual operation effect is not ideal. The comprehensive evaluation of urban smart traffic management systems (USTMS) is a classical MADM issues. In this paper, the MADM issues are studied with defined 2-tuple linguistic neutrosophic sets (2TLNSs). Then, connected traditional GRA with 2TLNSs, the 2TLNN-GRA method is elaborated for MADM. Finally, an example for comprehensive evaluation of USTMS was given and some comparisons was elaborated the 2TLNN-GRA method.

ObjectivePatients with pancreatic cancer (PC) have a poor prognosis. Radiotherapy (RT) is a standard palliative treatment in clinical practice, and there is no effective clinical prediction model to predict the prognosis of PC patients receiving radiotherapy. This study aimed to analyze PC’s clinical characteristics, find the factors affecting PC patients’ prognosis, and construct a visual Nomogram to predict overall survival (OS).MethodsSEER*Stat software was used to collect clinical data from the Surveillance, Epidemiology, and End Results (SEER) database of 3570 patients treated with RT. At the same time, the relevant clinical data of 115 patients were collected from the Affiliated Cancer Hospital of Zhengzhou University. The SEER database data were randomly divided into the training and internal validation cohorts in a 7:3 ratio, with all patients at The Affiliated Cancer Hospital of Zhengzhou University as the external validation cohort. The lasso regression was used to screen the relevant variables. All non-zero variables were included in the multivariate analysis. Multivariate Cox proportional risk regression analysis was used to determine the independent prognostic factors. The Kaplan-Meier(K-M) method was used to plot the survival curves for different treatments (surgery, RT, chemotherapy, and combination therapy) and calculate the median OS. The Nomogram was constructed to predict the survival rates at 1, 3, and 5 years, and the time-dependent receiver operating characteristic curves (ROC) were plotted with the calculated curves. Calculate the area under the curve (AUC), the Bootstrap method was used to plot the calibration curve, and the clinical efficacy of the prediction model was evaluated using decision curve analysis (DCA).ResultsThe median OS was 25.0, 18.0, 11.0, and 4.0 months in the surgery combined with chemoradiotherapy (SCRT), surgery combined with radiotherapy, chemoradiotherapy (CRT), and RT alone cohorts, respectively. Multivariate Cox regression analysis showed that age, N stage, M stage, chemotherapy, surgery, lymph node surgery, and Grade were independent prognostic factors for patients. Nomogram models were constructed to predict patients’ OS. 1-, 3-, and 5-year Time-dependent ROC curves were plotted, and AUC values were calculated. The results suggested that the AUCs were 0.77, 0.79, and 0.79 for the training cohort, 0.79, 0.82, and 0.81 for the internal validation cohort, and 0.73, 0.93, and 0.88 for the external validation cohort. The calibration curves Show that the model prediction probability is in high agreement with the actual observation probability, and the DCA curve shows a high net return.ConclusionSCRT significantly improves the OS of PC patients. We developed and validated a Nomogram to predict the OS of PC patients receiving RT.

PurposeTo compare Whole-brain radiation therapy with simultaneous integrated boost (WBRT+SIB) to stereotactic radiosurgery (SRS)for non-small cell lung cancer (NSCLC)with brain metastases (BMs)in terms of overall survival (OS), intracranial progression-free-survival(iPFS), toxicity and objective response rate (ORR)MethodsA retrospective review was performed in our hospital of 90 patients diagnosed with NSCLC- BM who received either SRS (n = 48) or WBRT+SIB (n = 42) from January 2016 to January 2022. 76 (84.44%) patients received systemic drug therapy after radiotherapy, including chemotherapy(n=53), targeted therapy(n=40), immunotherapy(n=23), and anti-vascular drug therapy(n=45). OS and iPFS were estimated by the Kaplan-Meier method and compared using the log-rank test. Univariate and Multivariate analysis of the prognostic factors was performed using the Cox proportional hazard regression model.ResultsThe WBRT+SIB cohort had a longer median iPFS (20.0 versus (VS) 12.0 months, P = 0.0069) and a similar median OS (32.0 vs 28.0 months, P = 0.195) than the SRS cohort. Intracranial objective response rates in WBRT +SIB and SRS cohorts were 76.19% and 70.09%, respectively (P = 0.566). Disease control rates were 88.09% and 83.33%, respectively (P = 0.521). Multivariate analysis showed that WBRT+SIB is the only factor affecting iPFS(hazard ratio (HR):0.597 {95%confidence interval(CI):0.370-0.966}, P=0.035). Sex, Liver metastasis and Lymph node metastasis are risk factors for NSCLC-BM.ConclusionIn the context of systemic drug therapy, WBRT+SIB may have better intracranial local control than SRS in NSCLC-BM patients.

Background: Leukoencephalopathy with cerebral calcifications and cysts (LCC) is a rare autosomal recessive cerebral microangiopathy. Recently, biallelic variants in a non-protein-coding gene SNORD118 have been discovered to cause LCC.Case Presentation: We here report a genetically confirmed childhood case of LCC. The patient was a 4-year-and-1-month-old boy with focal seizures. The age at onset of his seizure was 10 days after birth. The seizures were well-controlled by antiepileptic treatment but reoccurred twice due to a head impact accident and a fever, respectively. He suffered from a self-limited esotropia and unsteady running gait during the seizure onset. He had the typical neuroimaging triad of multifocal intracranial calcifications, cysts, and leukoencephalopathy. Genetic analysis indicated that he carried compound heterozygous variants of n.*9C>T and n.3C>T in SNORD118, which were inherited from his parents.Conclusion: We report a childhood LCC case with compound heterozygous variants in SNORD118. To the best of our knowledge, the patient reported in our case had the youngest onset age of LCC with a determined genotype. The triad cerebral-imaging findings of calcifications, cysts, and leukoencephalopathy provide a crucial diagnostic basis. Moreover, the gene assessment, together with the clinical investigations, should be considered for the diagnosis of LCC.

Background: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are two subtypes of muscular dystrophy diseases caused by pathogenic mutations in the DMD gene. Until now, more than 4,600 disease-causing mutations in DMD have been reported. However, only 33 mutations were deep intronic, cases with this type of mutations were limited.Methods: In this study, we used a combination of complementary DNA (cDNA) and target DNA sequencing analysis in addition to conventional whole-exome sequencing (WES).Results: Three novel hemizygous mutations IVS11 + 17811C > G (c.1331 + 17811C > G), IVS21 + 3252A > G (c.2803 + 3252A > G) and IVS40 + 362A > G (c.5739 + 362A > G) were identified in DMD patients, while a reported hemizygous mutation IVS62-285A > G (c.9225-285A > G) was found in the BMD patient. These DMD mutations lead to pseudoexon insertions, causing the generation of truncated and dysfunctional dystrophin.Conclusion: This study defines three novel and one reported intronic mutations, which can result in DMD/BMD. We also emphasize the need to combine WES and cDNA-based methods to detect the variant in the very large DMD gene in which the mutational spectrum is complex.

Background:BCL11B encodes B-cell lymphoma/leukemia 11B, a transcription factor that participates in the differentiation and migration of neurons and lymphocyte cells. De novo mutations of BCL11B have been associated with neurodevelopmental disorder and immunodeficiency, such as immunodeficiency 49 (IMD49) and intellectual developmental disorder with speech delay, dysmorphic facies, and T-cell abnormalities (IDDSFTA). However, the pathogenesis of the neurodevelopmental disorder and T-cell deficiency is still mysterious. The strategy to distinguish these two diseases in detail is also unclear.Methods: A patient with unique clinical features was identified. Multiple examinations were applied for evaluation. Whole-exome sequencing (WES) and Sanger sequencing were also performed for the identification of the disease-causing mutation.Results: We reported a 17-month-old girl with intellectual disability, speech impairment, and delay in motor development. She presented with mild dysmorphic facial features and weak functional movement. MRI indicated the abnormal myelination of the white matter. Immunological analysis showed normal levels of RTEs and γδT cells but a deficiency of naive T cells. Genetic sequencing identified a de novo heterozygous frameshift mutation c.1192_1196delAGCCC in BCL11B.Conclusions: An IDDSFTA patient of East Asian origin was reported. The unreported neurological display, immunophenotype, and a novel disease-causing mutation of the patient extended the spectrum of clinical features and genotypes of IDDSFTA.