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The feature diversity of different web systems in page elements, submission contents and return information makes it difficult to detect weak password automatically. To solve this problem, multi-factor correlation detection method as integrated in the DBKER algorithm is proposed to achieve automatic detection of web weak passwords and universal passwords. It generates password dictionaries based on PCFG algorithm, proposes to judge blasting result via 4 steps with traditional static keyword features and dynamic page feature information. Then the blasting failure events are discriminated and the usernames are blasted based on response time. Thereafter the weak password dictionary is dynamically adjusted according to the hints provided by the response failure page. Based on the algorithm, this paper implements a detection system named WebCrack. Experimental results of two blasting tests on DedeCMS and Discuz! systems as well as a random backend test show that the proposed method can detect weak passwords and universal passwords of various web systems with an average accuracy rate of about 93.75%, providing security advisories for users' password settings with strong practicability., Comment: 22 pages, 6 figures, 4 tables

Osteoporosis is one of the most frequent skeletal disorders and a major cause of morbidity and mortality in the expanding aging population. Evidence suggests that hesperidin may have a therapeutic impact on osteoporosis. Nevertheless, little is known about the role of hesperidin in the development of osteoporosis. Bioinformatics analyses were carried out to explore the functions and possible molecular mechanisms by which hesperidin regulates osteogenic differentiation. In the present study, we screened and harvested 12 KEGG pathways that were shared by hesperidin-targeted genes and osteoporosis. The p53 signaling pathway was considered to be a key mechanism. Our in vitro results showed that hesperidin partially reversed dexamethasone-induced inhibition of osteogenic differentiation by suppressing the activation of p53, and suggest that hesperidin may be a promising candidate for the treatment against dexamethasone-induced osteoporosis.

A simple and efficient photocatalytic method for the synthesis of dihydropyrimidinones (DHPMs) and their derivatives via porous ultrathin carbon nitride nanosheets (p-CNNs) without solvents was demonstrated. The yields of 3,4-dihydropyrimidin-2(1H)-ones/thiones and their derivatives were up to 97.0%. Furthermore, the yield of 5-ethoxycarbonyl-6-methyl-4-phenyl-3,4-dihydropyrimidin-2(1H)-one in the 10th cycle retained 98.9% of its 1st value. Considering the environmental and economic benefits, this work exhibits various merits including excellent yields, environmental friendliness, inexpensiveness, and avoiding the use of solvents and metal-based photocatalysts. In addition, the excellent performance of the p-CNNs and environmentally benign reaction system have also been checked by the photocatalytic synthesis of 12-phenyl-9,9-dimethyl-8,9,10,12-tetrahydrobenzo[a]xanthen-11-one and 5-phenyl-1(4-methoxyphenyl)-3[(4-methoxy-phenyl)-aminol]-1H-pyrrol-2(5H)-one. This work paves a new way for carrying out a three-component reaction using metal-free photocatalysts under mild reaction conditions.

Background Cysteine cathepsin C encoded by the CTSC gene is an important member of the cysteine cathepsin family that plays a key role regulation of many types of tumors. However, whether CTSC is involved in the pathological process of glioma has not yet been reported. We comprehensively analyzed data from multiple databases and for the first time revealed a role and specific mechanism of action of CTSC in glioma, identifying it as a novel and efficient biomarker for the diagnosis and treatment of this brain tumor. Methods The expression of CTSC in glioma and its relationship with clinical characteristics and prognosis of patients with glioma were analyzed at different levels by using clinical sample information from several databases. CTSC expression levels in glioma and normal brain tissues, as well as in glioma cells and normal brain cells, was validated by real-time quantitative polymerase chain reaction (RT-qPCR). Gene set enrichment analysis (GSEA) was used to reveal the signaling pathways that CTSC may participate in. The connectivity map was used to reveal small molecules that may inhibit CTSC expression in glioma, and the putative effect of these compounds was verified by RT-qPCR. Results Our analyses showed that the expression of CTSC in glioma was higher than that in non-cancerous cells. GSEA showed that CTSC expression may regulate the malignant development of glioma through Toll-like receptor signaling pathways, pathways in cancer, and extracellular matrix receptor interaction signaling pathways. And we proved piperlongumine and scopoletin could inhibit CTSC expression in glioma cells. Conclusions CTSC may serve as an efficient molecular target for the diagnosis and therapy of glioma, thereby improving the poor prognosis of patients with glioma.

Guided transport has higher transport capacity and energy efficiency in operation than other modes of transport, so there has been fast development of guided transport all over the world in the past decades. Although rail transport is the most successful guided transport system, there are still some limitations to the further development of rail transport, e.g. long travel time for long-distance travel, noise and vibration in urban areas, and rail-wheel wear and adhesion. In response, maglev and hyperloop systems which do not rely on the rails and wheels have been proposed and developed. In maglev and hyperloop systems the vehicles are levitated and propelled from the guideway by magnetic forces. There is no direct physical contact between the moving train and the guideway during operation. To achieve very high-speed operation, hyperloop systems are supposed to run inside low-pressurized tubes to reduce aerodynamic drag. In the world, there are many different types of technology developed to realize maglev and hyperloop systems. However, the technology of maglev and hyperloop systems is relatively new and still under development. Now there are only five low-speed maglev systems and one high-speed maglev system in commercial operation in the world. The maglev and hyperloop systems have different features compared to the well-developed rail transport, so it is needed to look into their core technology and follow their latest development for future development in the transport sector. In response, this work gives an overview of the maglev and hyperloop systems with respect to their history, technology and applications in the world. This work summarizes the development history of different maglev and hyperloop systems, explain the core technology used in hyperloop systems and three types of maglev systems, and describe the applications of six commercial maglev systems. This work also compares the features of different systems based on statistics. In the end, some conclusions are drawn and future work plans are sketched. QC 20220128

The dynamic interaction of pantograph and catenary in electrified railway systems has considerable research attention, both in terms of simulation and of measurements. The simulation benchmark of 2015 proved a good base of agreement between established models, but also showed that deviations between the different models increase when the simulated system approaches critical speeds. From these deviations it can be concluded that some of the models in the benchmark better depict the system behaviour around critical speed than others. Therefore, this paper analyses and compares measurement data from the Green Train project in Sweden, which includes speed at and over critical level, to simulations performed with one of the participating models, the finite element (FE) based CaPaSIM model. Based on this comparison,modelling alternatives are implemented and tested in CaPaSIM, to examine if they improve the accuracy of the model in the speed range around critical speeds. These alternative modelling approaches are to a large extent based on previous studies in thefield, such as other models that participated in the benchmark. The varied aspects include choice of element type for single components of the catenary and element mesh resolution. On the pantograph side, the effect of separately modelling independent flexible collector strips is studied. The modelling choices that prove to be most promising during the initial variation tests are presented and recommendations are given for further investigations of possible improvements. QC 20220822

As more and more artificial intelligence (AI) technologies move from the laboratory to real-world applications, the open-set and robustness challenges brought by data from the real world have received increasing attention. Data augmentation is a widely used method to improve model performance, and some recent works have also confirmed its positive effect on the robustness of AI models. However, most of the existing data augmentation methods are heuristic, lacking the exploration of their internal mechanisms. We apply the explainable artificial intelligence (XAI) method, explore the internal mechanisms of popular data augmentation methods, analyze the relationship between game interactions and some widely used robustness metrics, and propose a new proxy for model robustness in the open-set environment. Based on the analysis of the internal mechanisms, we develop a mask-based boosting method for data augmentation that comprehensively improves several robustness measures of AI models and beats state-of-the-art data augmentation approaches. Experiments show that our method can be widely applied to many popular data augmentation methods. Different from the adversarial training, our boosting method not only significantly improves the robustness of models, but also improves the accuracy of test sets. Our code is available at \url{https://github.com/Anonymous_for_submission}., Comment: 10 pages, 7 figures

Additional file 1: Table S1. Characteristics of patientswith glioma based on CGGA RNA-seqdata. Table S2. Characteristics of patientswith glioma based on CGGA microarray data. Table S3. Characteristics of patientswith glioma based on TCGA RNA-seq data

Virtual and real fusion technology is one of the key links in video enhancement of 3D geographical scene, which plays an important role in improving the real immersive visual experience. The existing video projection fusion method usually needs to traverse all the rendered objects in the new scene when the 3D scene is updated dynamically, in order to determine the objects that need to be fused in the camera range, which resulting in a long fusion process and low efficiency. A fast fusion method of multi-channel video and 3D GIS scene considering topological relationship is proposed. Firstly, a dynamic topology network model was established for video objects and rendering objects to accelerate the judgment of spatial relationship. Secondly, the topology relationship between video and rendering objects within 3D scene was established based on the topology network model, and the recorded topological relationship is used to determine and fuse the object quickly. Finally, the three-dimensional scene of Tengzhou City is verified. The experimental results show that the proposed method has the advantages of less time-consuming, high efficiency, greatly reducing the computational cost of fusion, and has good feasibility and robustness in the fusion of video and 3D GIS scene.

In recent years, studies have shown that TIMELESS, as an oncogene, is involved in progression of cancers. However, its relationship with prognosis in glioma patients is rarely reported. Our purpose was to explore the role of TIMELESS in glioma. Based on 1814 glioma samples from multiple databases such as The Cancer Genome Atlas (TCGA), The Chinese Glioma Genome Atlas (CGGA), and The Gene Expression Omnibus (GEO), we use a variety of bioinformatics methods to verify the mechanism of action of TIMELESS in glioma from mRNA to protein, from appearance to mechanism analysis, from clinical features to prognosis. Then, the connectivity map (CMap) tool was used to predict drugs that inhibit the expression of TIMELESS. First, we found TIMELESS is highly expressed in glioma at mRNA and protein levels. Second, TIMELESS is an independent risk factor in prognosis and has suitable clinical diagnostic value in glioma. It was also positively correlated with World Health Organization (WHO) grade, age, and histology, and negatively correlated with isocitrate dehydrogenase (IDH) 1 mutation and 1p19q codeletion. Third, base excision, cell cycle, and mismatch repair pathway were activated by TIMELESS in glioma. We predict small molecules to inhibit TIMELESS such as 8-azaguanine, gw8510, 6-thioguanosine, and ursodeoxycholic acid. This study is the first comprehensive analysis of TIMELESS, revealing a relationship between this novel oncogene, clinical characteristics of patients with glioma, and a mechanism leading to poor prognosis. It also provides a biomarker for diagnosis and treatment of glioma and reveal the pathologic progress of glioma at the genetic level.

This study aimed to isolate starch and evaluate its chemical and structural characteristics from six Chinese hulless barley (HB) cultivars. Starch isolated from naked barley displays A‐type crystalline packing and a regular granular shape. We measured peak viscosity values ranging from 237 to 264 cP, trough viscosity values from 305 to 380 cP, breakdown values from 390 to 535 cP, final viscosities from 357 to 523 cP, setback values from 245 to 354 cP and 383 to 460 cP, peak times from 5.53 to 5.73 min, and pasting temperatures from 93.10 to 94.65°C by RVA. Transition temperatures (T 0, T p, and T c), gelatinization temperature ranges (ΔT r), and enthalpies of gelatinization (ΔH) were measured on a differential scanning calorimeter analyzer (DSC) and ranged from 57.81 to 61.25°C, 64.36 to 67.57°C, 82.03 to 84.70°C, and 21.52 to 26.89°C and 7.14 to 10.66 J/g, respectively. The varying chemical and structural characteristics of HB starch isolated from different cultivars suggested the potential for broader applications of the cereal.

Additional file 1: Table S1. Characteristics of patients with glioma based on CGGA RNA-seq data.

Lectins are widely distributed in the natural world and are usually involved in antitumor activities. Auricularia auricula (A. auricula) is a medicinal and edible homologous fungus. A. auricula contains many active ingredients, such as polysaccharides, melanin, flavonoids, adenosine, sterols, alkaloids, and terpenes. In this study, we expected to isolate and purify lectin from A. auricula, determine the glycoside bond type and sugar-specific protein of A. auricula lectin (AAL), and finally, determine its antitumor activities. We used ammonium sulfate fractionation, ion exchange chromatography, and affinity chromatography to separate and purify lectin from A. auricula. The result was a 25 kDa AAL with a relative molecular mass of 18913.22. Protein identification results suggested that this lectin contained four peptide chains by comparing with the UniProt database. The FT-IR and β-elimination reaction demonstrated that the connection between the oligosaccharide and polypeptide of AAL was an N-glucoside bond. Analyses of its physical and chemical properties showed that AAL was a temperature-sensitive and acidic/alkaline-dependent glycoprotein. Additionally, the anticancer experiment manifested that AAL inhibited the proliferation of A549, and the I C 50 value was 28.19 ± 1.92 μ g / mL . RNA sequencing dataset analyses detected that AAL may regulate the expression of JUN, TLR4, and MYD88 to suppress tumor proliferation. Through the pulmonary flora analysis, the bacterial structure of each phylum in the lectin treatment group was more reasonable, and the colonization ability of the normal microflora was improved, indicating that lectin treatment could significantly improve the bacterial diversity characteristics.

Additional file 2: Table S2. Characteristics ofpatients with gliomabased on CGGA RNA-seq data.

Supplemental material, sj-pdf-1-pic-10.1177_09544062211027199 for Machine learning approach to improve vapor recovery: Prediction and frequency converter with a new vapor recovery system by Yajun Liu, Shenchao Zhang and Zhendong Liu in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

QC 20211220

Additional file 1: Table S1. siRNA sequences targeting GNG5.

Additional file 2: Table S2. Characteristics of patients with glioma based on CGGA microarray data.

Additional file 3: Table S3. Clinical characteristics of glioma patients based on CGGA RNA-seq data.

Additional file 2: Table S2. RNA-specific primers sequences.

QC 20220302

The performance of deep segmentation models often degrades due to distribution shifts in image intensities between the training and test data sets. This is particularly pronounced in multi-centre studies involving data acquired using multi-vendor scanners, with variations in acquisition protocols. It is challenging to address this degradation because the shift is often not known \textit{a priori} and hence difficult to model. We propose a novel framework to ensure robust segmentation in the presence of such distribution shifts. Our contribution is three-fold. First, inspired by the spirit of curriculum learning, we design a novel style curriculum to train the segmentation models using an easy-to-hard mode. A style transfer model with style fusion is employed to generate the curriculum samples. Gradually focusing on complex and adversarial style samples can significantly boost the robustness of the models. Second, instead of subjectively defining the curriculum complexity, we adopt an automated gradient manipulation method to control the hard and adversarial sample generation process. Third, we propose the Local Gradient Sign strategy to aggregate the gradient locally and stabilise training during gradient manipulation. The proposed framework can generalise to unknown distribution without using any target data. Extensive experiments on the public M\&Ms Challenge dataset demonstrate that our proposed framework can generalise deep models well to unknown distributions and achieve significant improvements in segmentation accuracy., Accepted by MICCAI-2021

Additional file 4: Figure S1. Circle diagram of co-expression analysis results.

Additional file 3: Table S3. Characteristics of patients with glioma based on TCGA RNA-seq data.

Supplemental material, sj-pdf-1-pic-10.1177_09544062211027199 for Machine learning approach to improve vapor recovery: Prediction and frequency converter with a new vapor recovery system by Yajun Liu, Shenchao Zhang and Zhendong Liu in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Additional file 4: Table S4. Characteristics ofpatients with gliomabased on TCGA RNA-seq data.

Heqing Huang, Ling Luo, Zhitao Liu, Yan Li, Zhaochen Tong, Zhendong Liu Department of Orthopaedics and Traumatology, Third Xiangya Hospital of Central South University, Changsha 410013, Hunan Province, People’s Republic of ChinaCorrespondence: Zhendong LiuDepartment of Orthopaedics and Traumatology, Third Xiangya Hospital of Central South University, No. 138 Tongzipo Road, Changsha 410013, Hunan Province, People’s Republic of ChinaTel/Fax +8673188638888Email liuzhendong001@163.comPurpose: To investigate the effect of TNF-α and FGF-2 in the fracture healing disorder of type 2 diabetes.Design/Methodology/Approach: Rat diabetes-bone traction model was established to investigate the effect of type 2 diabetes on the fracture healing and the association of TNF-α and FGF-2 with the process. Serological examination was performed to detect the related diabetes indexes. The proliferation activity of the cells was detected by MTT assay. The expressions of FGF-2 and TNF-α of osteoblasts in high glucose culture environment were detected by histochemistry and Western blotting.Findings: Serological examination showed that in rats fed with high fat and sugar diet for 8 weeks, the serum total cholesterol (TC), triglyceride (TG), fasting insulin (FINs) significantly increased, but fasting blood glucose (FBG) had no significant change. Two weeks after intraperitoneal injection of STZ, rat serum TG, TC, and FBG increased significantly, while FINs did not change obviously. Two weeks after traction osteogenesis, X-ray examination and HE staining showed that the area of osteotylus in the diabetes group was significantly smaller than that in the control group. The number of PCNA positive cells in the osteotylus of diabetes group was significantly decreased. In the osteotylus of diabetes group, the expression of TNF-α was significantly increased and the expression of FGF-2 was significantly decreased. MTT assay showed that the proliferation activity of MC3T3-E1 cells in high glucose culture medium groups was significantly decreased at 24th hour of the culture, compared with the normal culture medium group. qPCR results showed that the expression of FGF-2 was significantly decreased while the expression of TNF-α was significantly increased in high glucose culture medium groups.Originality/Value: It was concluded that type 2 diabetes mellitus affected the fracture healing by causing osteoblast proliferation disorder. TNF-α and FGF-2 were important related factors for the process.Keywords: type 2 diabetes mellitus, T2DM rat model, distraction osteogenesis, fracture healing, FGF-2, TNF-α, MC3T3-E1 cells

Highland barley starch (HBS), as a carbohydrate shell material with excellent performance in microcapsule applications, has rarely been reported. In the present study, three different microcapsules (CEO-SWSM, CEO-PM, and CEO-UM) were synthesized successfully via saturated aqueous solution method, molecular inclusion method and ultrasonic method, respectively, using HBS as shell material coupled with cinnamon essential oil (CEO) as the core material. The potential of HBS as a new shell material and the influence of synthetic methods on the performance of microcapsules, encapsulation efficiency (EE), yield, and release rate of CEO-SWSM, CEO-PM, and CEO-UM were determined, respectively. The results confirmed that CEO-PM had the most excellent EE (88.2%), yield (79.1%), as well as lowest release rate (11.5%, after 25 days of storage). Moreover, different kinetic models were applied to fit the release process of these three kinds of microcapsules: CEO-SWSM, CEO-PM, and CEO-UM had the uppermost R-squared value in the Higuchi model, the zero-order model, and the first-level model, respectively. Over all, this work put forward a novel perspective for the improved encapsulation effect of perishable core materials (e.g., essential oil) for the food industry.

Great progress has been made during the last decade in clarifying the molecular details of aroma accumulation in grape berries. However, the multigene complex controlling monoterpene accumulation in grape is not well understood. To shed light on this issue, the grapes of 149 F1 progenies from the cross 87-1 (Vitis vinifera L.) × 9-22 (Vitis vinifera L.) were characterized at the mature stage for three representative free monoterpenes during five growing seasons. A total of 202, 184 and 255 polymorphic SSR (simple sequence repeat) markers were contracted on the maternal 87-1, paternal 9-22 and consensus genetic maps, respectively. On the consensus map, we confirmed a major QTL (quantitative trait locus) for free linalool, nerol and α-terpineol content on linkage group (LG) 5, and a stable QTL for free linalool and α-terpineol was detected on LG 10. In addition, two new stable QTLs for free monoterpene (linalool, nerol and α-terpineol) contents were identified on LG 11 and LG 18 that explained up to 42.5 % of the total variance. Eleven promising candidate genes related to pentatricopeptide repeat (PPR)-containing proteins, seed maturation protein, RING finger protein, and AP2/ERF transcription factors might be potentially involved in monoterpene accumulation. The stable QTLs and candidate genes identified in this study provide new insights into free monoterpene accumulation in grape., VITIS - Journal of Grapevine Research, Vol. 59 No. 1 (2020): Vitis

Deep models often suffer from severe performance drop due to the appearance shift in the real clinical setting. Most of the existing learning-based methods rely on images from multiple sites/vendors or even corresponding labels. However, collecting enough unknown data to robustly model segmentation cannot always hold since the complex appearance shift caused by imaging factors in daily application. In this paper, we propose a novel style-invariant method for cardiac image segmentation. Based on the zero-shot style transfer to remove appearance shift and test-time augmentation to explore diverse underlying anatomy, our proposed method is effective in combating the appearance shift. Our contribution is three-fold. First, inspired by the spirit of universal style transfer, we develop a zero-shot stylization for content images to generate stylized images that appearance similarity to the style images. Second, we build up a robust cardiac segmentation model based on the U-Net structure. Our framework mainly consists of two networks during testing: the ST network for removing appearance shift and the segmentation network. Third, we investigate test-time augmentation to explore transformed versions of the stylized image for prediction and the results are merged. Notably, our proposed framework is fully test-time adaptation. Experiment results demonstrate that our methods are promising and generic for generalizing deep segmentation models., Comment: Accepted by MICCAI STACOM 2020

Additional file 1: eTable 1. Demographic and clinical characteristics of the excluded participants ≥75 years of age in the cohort study. eTable 2. Demographic and clinical characteristics of the excluded hypertensive patients ≥75 years of age in the clinical trial. eTable 3. Mean and variability in blood pressure in the cohort study and clinical trial over the follow-up period. eTable 4. Adverse effects of statins.

Improving energy efficiency and reducing CO2 emissions are becoming very essential worldwide. To encourage the development and application of energy-efficient and low-emission technologies and to increase people's awareness of energy-saving, many energy labelling systems are developed and utilized in most countries. Since energy labelling systems have a significant impact, more and more sectors are developing their energy labelling systems to have their products included. Globally, the transport sector consumes a great proportion of energy and is responsible for considerable CO2 emissions. Although rail vehicles have relatively high energy efficiency, a labelling system has not been developed in the railway sector, whereas other modes of transport have developed energy efficiency indicators or energy labelling systems. Therefore, it is necessary to develop an energy labelling system for rail vehicles to promote rail transport and develop the technology of rail vehicles. First, this paper gives a review of the existing energy labelling systems. Second, it summarizes the rail needs and rail stakeholders’ interests regarding energy efficiency and corresponding labelling. Last but not least, a proposal for an energy labelling system for rail vehicles is given. QC 20200729

In this study, apple–pear pomace dietary fibers were treated with acid, alkali, cellulase, and hemicellulase. The effects of these treatments on the chemical constitutions, structural characteristics, functional properties, and the quality of apple–pear pomace dietary fibers were investigated. The results showed that the purity of apple–pear pomace dietary fibers was 79–83%, and the fiber contained cellulose, hemicellulose, pectin, and lignin. Their monosaccharide structures included mannose, glucosamine, ribose, rhamnose, glucuronic acid, galacturonic acid, galactosamine, glucose, galactose, xylose, arabinose, and fucose. The scanning electron microscopy showed that all the apple–pear pomace dietary fibers were beehive shaped, but their functional and physico-chemical properties were different. Using the main constituents and the functional and physico-chemical properties as indicators, through a principal component analysis, we determined the main constituents and characteristics of four apple–pear pomace dietary fibers.

Since the introduction of the architecture course, the practice of surveying and mapping of ancient architecture has always been an important compulsory course in the professional course of architecture in colleges and universities in China. Against the background of the new era, the teaching methods used so far can no longer fully meet the needs of the development of the times and the construction of "Double First-Class" initiative. This paper explores deeply from the aspects of organizational planning, technical support and achievement transformation, in order to enrich the teaching methods for ancient architecture surveying and mapping practice course in architecture major, and finally improve the teaching level and improve the teaching effect.

QC 20220523

Based on the study of the application of three-dimensional laser scanning technology in ancient building surveying and mapping, this paper briefly describes the working principle and flow of three-dimensional laser scanning technology. Based on the practical application, this paper puts forward the discussion of related problems and matters needing attention. This has a certain reference significance for the study of new technology in surveying and mapping of ancient buildings.

To solve the dynamic reactive power optimization problem in the distribution network, a novel optimization algorithm (variable step size beetle antennae search algorithm, VBAS) is introduced. Meanwhile, from the economic point of view, the minimum network loss and capacitor switching cost are taken as the objective functions, and the dynamic reactive power optimization model is established. In contrast with the majority of existing traditional algorithms that are intricate in process, the conducted algorithm is of less calculate and easier achieved. Besides, the variable step size strategy is introduced to improve optimization accuracy. The effectiveness of this algorithm is verified by simulation analysis on the IEEE 33- bus system, and the results show that VBAS obtains the optimum operation point and outperforms traditional algorithms significantly.

With the expansion of power system scale, the operation of the power grid system has been greatly challenged. Reactive power optimization can make the power system operate safely and economically. In this paper, an improved differential evolutionary algorithm is applied to reactive power optimization of power system. We take the minimum power system loss as the objective function, the power balance condition as the equality constraint, the control variables and state variables as the inequality constraint conditions to establish the system model. Finally, IEEE30 bus and IEEE33 bus power system are selected to verify the effectiveness of the proposed algorithm.

Coriolis mass flowmeter is widely used in various fields due to its high accuracy, but it still needs to be improved in some special conditions. This paper proposes a deep learning-based signal processing method for Coriolis mass flowmeter. Firstly, we set up an experimental platform to collect data, taking the vibration signal as the input feature and the mass flow as the sample label. Secondly, we designed networks with different structures (including LSTM, RNN and ANN) and adopted batch normalization to speed up convergence. Finally, Bayesian model fusion and moving average were used to reduce generalization error. Experiment results prove that the model with LSTM layer is better than other single models and the mean square error of the optimized model reduces to 0.0047, which is far superior to the calibrated meter (0.1200). These findings that get rid of traditional methods are expected to break through existing bottlenecks.

Cancer is one of the most major diseases that threatens human health and life. The aim of this work was to obtain novel anticancer molecules from D. fragrans, a kind of medicinal plant. The structure of the new compound was identified using spectroscopic data (1H-NMR, 13C-NMR and two dimensions NMR). Its anticancer properties were evaluated using the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay against four human cells including lung cancer cells (A549), breast cancer cells (MCF-7), gastric cancer cells (SGC7901) and noncancerous human umbilical vein endothelial cells (HUVEC). A new phenylpropanoid—(E)-caffeic acid-9-O-β-d-xylpyranosyl-(1→2)-β-d-glucopyranosyl ester (1), with seven known compounds (2–8)—was isolated. The IC50 value of compound 1 against MCF-7 cells was 2.65 ± 0.14 µM, and the IC50 values of compound 8 against three cancer cells were below 20 µM.

Ganoderic acid D (GAD) is a highly oxygenated tetracyclic triterpenoid. This study aims to assess the effects of GAD on the energy metabolism of colon cancer through the regulation of SIRT3 expression and whether this effect is related to acetylated cyclophilin D. The results demonstrated that GAD inhibits the energy reprogramming of colon cancer cells including glucose uptake, lactate production, pyruvate and acetyl-coenzyme production in colon cancer cells. Meanwhile, GAD upregulated the protein expression of SIRT3. Furthermore, the interruption of SIRT3 expression significantly reversed all the effects of SIRT3 on the energy reprogramming of colon cancer. In addition, GAD induced the deacetylated cyclophilin D (CypD) by SIRT3, whereas SIRT3-shRNA inhibited its combining effect on CypD. The energy reprogramming effects of GAD on colon cancer seem to be mediated by SIRT3 upregulation via acetylated CypD inhibition.

The global burden of cancer continues to increase largely with the aging and growth of the world population. The purpose of the present work was to find new anticancer molecules from a natural source. We utilized chromatographic methods to isolate compounds from medicinal plant Dryopteris fragrans (L.) Schott. The structure of the new compounds was determined by spectroscopic and spectrometric data (1D NMR, 2D NMR, and EMI-MS). Their anti-proliferation effects against five human cancer cell lines including A549, MCF7, HepG2, HeLa, and PC-3 were evaluated by CCK-8 andlactate dehydrogenase (LDH) assay. A new sesquiterpene, (7S, 10S)-2,3-dihydroxy-calamenene-15-carboxylic acid methyl ester (1), and two known compounds (2 and 3) were isolated. The new sesquiterpene was named dryofraterpene A and significantly inhibited cancer cell proliferation without any obvious necrosis below a 10 μM concentration. In conclusion, a novel anticancer sesquiterpene together with two known compounds was isolated, which might be a promising lead compound for the treatment of cancer.

The pantograph-catenary system is used in railways to transfer electric power from infrastructure to trainset. As the pantograph slides against the catenary, the contact between the two surfaces is not stable due to stiffness variation, propagating wave and other environmental perturbation, especially at high speeds or in multi-pantograph operation. Heavy oscillation can result in poor power-transmission quality, electromagnetic interference, severe wear or even structural damage. So the pantograph-catenary dynamics has become one of the key issues which limits the operational speed and determines the maintenance cost. There are many types of catenary systems in Sweden, which are relatively soft and sensitive compared with the systems in other countries. They work well at low operational speed and have strict limitations to multi-pantograph operation. It is possible to achieve an operational speed of 350 km/h on newly-built high-speed lines, but there is still a large demand for higher operational speed and more capacity on the existing lines. Many researchers and engineers have made progress to improve its dynamic performance. From the research aspect, many numerical models have been built up to demonstrate the dynamics of the pantograph-catenary system and to unveil the key influencing factors. There have been many applications developed in recent years. Regarding the catenary, high-tensile loads on the catenary and low-stiffness-variation designs are widely used to improve the dynamic performance. Regarding the pantograph, aerodynamic-friendly designs and active-control technique contribute to the development of high-speed pantograph. But all these methods need not only large investment but long out-of-service. Considering the large scale and heavy service duty of the existing lines, it becomes almost impossible to completely upgrade the existing pantograph-catenary systems. So it is necessary to find practical and efficient methods to exploit the potentials of the existing systems to enhance their dynamic performances. This thesis investigates the dynamic behaviour of the Swedish pantograph-catenary systems and proposes methods for better usage. A numerical study on multi-pantograph operation is performed and the relationships between dynamic performance and some key parameters is established. By studying the multi-pantograph operation at short spacing distance, a method to use the leading pantograph as auxiliary pantograph is proposed to increase the operational speed on the soft catenary system. To ensure operational safety in abnormal conditions, numerical studies on pantograph raising/lowering processes and in catenary overlap sections are performed. By studying the influence of the lumped-mass on the dynamic performance, it shows that it is even possible to implement some artificial tuned-masses on the catenary for dynamic optimization. QC 20170915

As the heart of chemical oxygen iodine laser (COIL), the singlet oxygen generator (SOG) has been focus of research for many years. A novel eject singlet oxygen generator was designed based on research of industrial ejectors and cyclone separators. Simulations and experiments were performed on the chemical reaction of O2(1). This eject SOG can make larger gas-liquid surface area through nozzle compared with traditional SOGs, and therefore it has a high chemical efficiency. Gas and liquid were separated by a cyclone separator which was designed to fit for the high separation efficiency and low residence time. This SOG has a chlorine utilization of 97%-99% and O2(1) yield of 40%-50%.

It is important to maximize the saturated throughput of VANET broadcasting protocol for fully utilizing wireless channel. The saturated throughput of broadcasting protocol is related to contention windows valve and contending nodes in the networks. We propose a discrete markov analytic model for performance evaluation broadcasting protocol under saturation condition for VANET, and analysis the relationship between the number of vehicle nodes and the contention windows. So, the analysis results show suitable contention window value can optimize the throughput of broadcasting protocol of VANET. The results show that the proposed analytic model and optimization contention windows value can enhance the system throughput.