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Optimal power flow (OPF) calculation methods are important for the power system operation and mainly focus on the deterministic power flow calculation, neglecting the impact of demand response on online security calculation of power systems with renewable energy sources. Therefore, this paper proposes an OPF calculation method that considers the uncertainties of wind power, photovoltaic (PV) power generation and demand-side response. Firstly, the research focuses on the renewable energy grid, considering the uncertainties of wind power and PV power generation, and establishes uncertainty models for wind power and PV output. Secondly, based on cloud model theory, an uncertainty model for demand response is established. According to the established models, an efficient OPF model is constructed with a linearized submodels considering multiple uncertainties. By testing on the IEEE 30-bus system as a typical example, we found the effectiveness and superiority of the proposed OPF calculation method can benefit the power system economic operation and demand side resource utilization.

IntroductionNon-dystrophic myotonias (NDMs) are skeletal muscle ion channelopathies caused by CLCN1 or SCN4A mutations. This study aimed to describe the clinical, myopathological, and genetic analysis of NDM in a large Chinese cohort.MethodsWe reviewed the clinical manifestations, laboratory results, electrocardiogram, electromyography, muscle biopsy, genetic analysis, treatment, and follow-up of 20 patients (from 18 families) with NDM.ResultsCases included myotonia congenita (MC, 17/20) and paramyotonia congenita (PMC, 3/20). Muscle stiffness and hypertrophy, grip and percussion myotonia, and the warm-up phenomenon were frequently observed in MC and PMC patients. Facial stiffness, eye closure myotonia, and cold sensitivity were more common in PMC patients and could be accompanied by permanent weakness. Nine MC patients and two PMC patients had cardiac abnormalities, mainly manifested as cardiac arrhythmia, and the father of one patient died of sudden cardiac arrest. Myotonic runs in electromyography were found in all patients, and seven MC patients had mild myopathic changes. There was no difference in muscle pathology between MC and PMC patients, most of whom had abnormal muscle fiber type distribution or selective muscle fiber atrophy. Nineteen CLCN1 variants were found in 17 MC patients, among which c.795T>G (p.D265E) was a new variant, and two SCN4A variants were found in three PMC patients. The patients were treated with mexiletine and/or carbamazepine, and the symptoms of myotonia were partially improved.ConclusionsMC and PMC have considerable phenotypic overlap. Genetic investigation contributes to identifying the subtype of NDM. The muscle pathology of NDM lacks specific changes.

Abstract Background Acute liver failure (ALF) is a serious threat to the life of people all over the world. Finding an effective way to manage ALF is important. Human liver stem cells (HLSCs) are early undifferentiated cells that have been implicated in the regeneration and functional reconstruction of the liver. In this study, we aimed to evaluate the protective effects of the HLSC line HYX1 against concanavalin A (ConA)-induced acute liver injury. Methods HYX1 cells were characterized by microscopy, functional assays, gene expression, and western blot analyses. We showed that HYX1 cells can differentiate into hepatocytes. We intraperitoneally injected HYX1 cells in mice and administered ConA via caudal vein injection 3, 6, 12, 24, and 48 h later. The effects of HYX1 cell transplantation were evaluated through blood tests, histology, and flow cytometry. Results HYX1 cells reduced the levels of alanine transaminase (ALT), aspartate aminotransferase (AST), and total bilirubin (TBIL) in serum and dramatically decreased the severity of liver injuries. Mechanistically, HYX1 cells promoted myeloid-derived suppressor cell (MDSC) migration into the spleen and liver, while reducing CD4+ T cell levels in both tissues. In addition, HYX1 cells suppressed the secretion of proinflammatory cytokines, such as tumour necrosis factor-α (TNF-α) and interferon-γ (IFN-γ), but led to increased interleukin-10 (IL-10) production. Conclusions These results confirm the efficacy of HLSCs in the prevention of the ConA-induced acute liver injury through modulation of MDSCs and CD4+ T cell migration and cytokine secretion.

Our objective is to study the relationship between the regulatory proteins Bcl-2/Bax and mitochondria-mediated apoptosis during the differentiation of adipose-derived stromal cells (ADSCs) into neurons. Immunocytochemistry and western blotting showed that the cells weakly expressed neuron-specific enolase (NSE) in the non-induced group and expressed NSE more strongly in the groups induced for 1 h, 3 h, 5 h and 8 h. NSE expression peaked at 5 h (P < 0.05), although there was no significant difference between 5 and 8 h (P > 0.05). Bcl-2 expression gradually decreased over time in the non-induced group (P < 0.05). However, Bax, caspase-9, Cyt-c and caspase-3 expression gradually increased and peaked at 8 h (P < 0.05). Transmission electron microscopy revealed karyopyknosis, chromatin edge setting, mitochondria swelling and cavitation in cells at 5 h, and the mitochondrial membrane potential decreased over time, as demonstrated by laser scanning confocal microscopy. After a 5 h induction, cells differentiated into typical neurons and expressed Bcl-2, which inhibited apoptosis. Bax showed a strong apoptosis-promoting capacity, leading to changes in the mitochondrial membrane potential and structure, and then triggered the caspase-independent apoptotic response through the mitochondrial pathway. At the same time, Cyt-c was directly or indirectly released from the mitochondria to the cytoplasm to trigger the caspase-dependent apoptotic response through the mitochondrial pathway. Therefore, Bcl-2/Bax play an important role in regulating caspase-dependent and caspase-independent apoptosis mediated by the mitochondrial pathway during the differentiation of ADSCs into neurons.

The advent of novel power systems has given rise to a multitude of safety and stability concerns associated with the integration of emerging energy sources and power electronic equipment. The active support of the grid-forming control strategy represents an effective solution to the voltage and frequency stability issues associated with the weak damping and low inertia inherent to high-ratio new energy systems. Firstly, a static voltage stability index based on critical impedance is proposed for assessment of the static stability margin of a new energy grid-connected system, based on the static voltage stability theory of a traditional single-unit single-load system. Secondly, an analysis is conducted of the control principle of the grid-forming control converter and its impedance characteristics. In conclusion, a method for enhancing the static voltage stability margin of grid-connected new energy stations through parameter control of grid-forming converters is presented. The simulation verification of the single-feed and multi-feed systems demonstrates the efficacy and accuracy of the methodology presented in this study. [ABSTRACT FROM AUTHOR]

In this paper, an efficient scheme of numerical method is proposed to solve the low frequency (LF) problems, which combines the loop-tree basis functions with an efficient form of multilevel adaptive cross approximation (EFMLACA) algorithm. It utilizes the loop-tree basis functions to divide the vector part and scalar part of the impedance matrix. Meanwhile, the scalar part is frequency normalized. Through this operation, it can avoid the low frequency breakdown problem. In order to accelerate the matrix vector multiplication, the EFMLACA algorithm is applied. Meanwhile, the compressed block decomposition (CBD) preconditioner is applied to improve the condition number of poor convergence problems. The numerical results demonstrate that the memory requirement and computation time required for a matrix vector multiplication of EFMLACA algorithm is much less than that of MLACA and ACA-SVD. Moreover, the matrix vector multiplication of EFMLACA algorithm is also much more efficient than that of low-frequency multilevel fast multipole algorithm (LF-MLFMA). [ABSTRACT FROM AUTHOR]

The marching-on-in-degree (MOD) time-domain integral equation (TDIE) solver for the transient electromagnetic scattering of the graphene is presented in this paper. Graphene's dispersive surface impedance is approximated using rational function expressions of complex conjugate pole-residue pairs with the vector fitting (VF) method. Enforcing the surface impedance boundary condition, TDIE is established and solved in the MOD scheme, where the temporal surface impedance is carefully convoluted with the current. Unconditionally stable transient solution in time domain can be ensured. Wide frequency band information is obtained after the Fourier transform of the time domain solution. Numerical results validate the proposed method. [ABSTRACT FROM AUTHOR]

Background: The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database. Results: In this paper, we propose a novel protein-protein dissimilarity learning algorithm, ProDis-ContSHC. ProDis- ContSHC regularizes an existing dissimilarity measure dij by considering the contextual information of the proteins. The context of a protein is defined by its neighboring proteins. The basic idea is, for a pair of proteins (i, j), if their context N(i) and N(j) is similar to each other, the two proteins should also have a high similarity. We implement this idea by regularizing dij by a factor learned from the context N(i) and N(j) . Moreover, we divide the context to hierarchial sub-context and get the contextual dissimilarity vector for each protein pair. Using the class label information of the proteins, we select the relevant (a pair of proteins that has the same class labels) and irrelevant (with different labels) protein pairs, and train an SVM model to distinguish between their contextual dissimilarity vectors. The SVM model is further used to learn a supervised regularizing factor. Finally, with the new Supervised learned Dissimilarity measure, we update the Protein Hierarchial Context Coherently in an iterative algorithm-ProDis-ContSHC. We test the performance of ProDis-ContSHC on two benchmark sets, i.e., the ASTRAL 1.73 database and the FSSP/ DALI database. Experimental results demonstrate that plugging our supervised contextual dissimilarity measures into the retrieval systems significantly outperforms the context-free dissimilarity/similarity measures and other unsupervised contextual dissimilarity measures that do not use the class label information. Conclusions: Using the contextual proteins with their class labels in the database, we can improve the accuracy of the pairwise dissimilarity/similarity measures dramatically for the protein retrieval tasks. In this work, for the first time, we propose the idea of supervised contextual dissimilarity learning, resulting in the ProDis-ContSHC algorithm. Among different contextual dissimilarity learning approaches that can be used to compare a pair of proteins, ProDis-ContSHC provides the highest accuracy. Finally, ProDis-ContSHC compares favorably with other methods reported in the recent literature. [ABSTRACT FROM AUTHOR]

In recent yeas, there are research findings of haze formation in various fields of academic circle. It has proved that causes of haze take on diverse characteristics. Thus, from both the natural and human perspective, haze governance should be diverse. Research conclusions on causes of haze formation mainly focus on special geographical structure, and meteorological factors such a relatively stable atmosphere, high rate of calm wind, high relative humidity and temperature of air, and human factors such a industrial pollution, automotive exhaust emissions, aerosol poUution, eutrophication of soil water, and change of city underlying surface. Carbon sink mode is a new channel for haze governance. In carbon sink mode, it is feasible to reglate relative humidity and temperature in air, enhance global wind, and reduce fine particles and microorganisms of air poUution, so as to reduce haze poUution. Besides, China's special potential of carbon sink market makes it possible to govern haze on the base of carbon sink. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that threaten human health; thus, the establishment of an animal model with clinical features similar to human hepatocellular carcinoma is of important practical significance. Methods: Taking advantage of the novel microcarrier-6, human HCC cells were injected into immunocompetent mice to establish a novel human HCC patient-derived xenograft (PDX) model. Primary HCC cells were isolated from fresh hepatocellular carcinoma tissues, which were subsequently co-cultured with microcarrier-6 to construct a three-dimensional tumor cell culture model in vitro. The HCC-microcarrier complex was implanted into mice by subcutaneous inoculation, and the tumor formation time, tumor formation rate, and pathological manifestation were recorded. Changes of immune parameters in mice were detected by flow cytometry. Results: The success rate was 60% (6/10) in the establishment of hepatocellular carcinoma PDX mouse model, and the total tumor formation rate of the tumor-forming model is 90–100%. H&E staining and immunohistochemical experiments indicate that the model well retained the characteristics of the primary tumor. Interestingly, M2 macrophages in tumor-bearing mice increased significantly, and the levels of CD4+ T cells were significantly reduced. Conclusions: Through the application of the microcarrier-6 in immunocompetent mice, we successfully established a novel human HCC PDX model, which can be used to better study and further elucidate the occurrence and pathogenic mechanism of HCC, improve the predictability of toxicity and drug sensitivity in HCC. [ABSTRACT FROM AUTHOR]