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In the era of rapid development of big data,telecom operator has abundant big data assets and need to unlock the potential of huge data in pipelines through the innovation and development of big data services urgently.The construction of telecom big data ecosystem would help telecom operator solve the problems encountered in the development of big data services effectively and new value growth would be brought out.The target form and construction steps of telecom big data ecosystem were also clarified.

In many real-world applications, labeled instances are generally limited and expensively collected, while the most instances are unlabeled and the amount is often sufficient. Therefore, semi-supervised learning (SSL) has attracted much attention, since it is an effective tool to discover the unlabeled instances. However, how to safely make use of the unlabeled instances is an emerging and interesting problem in SSL. Hence, we propose DuAL Learning-based sAfe Semi-supervised learning (DALLAS), which employs dual learning to estimate the safety or risk of the unlabeled instances. To realize the safe exploitation of the unlabeled instances, our basic idea is to use supervised learning (SL) to analyze the risk of the unlabeled instances. First, DALLAS utilizes a primal model obtained by dual learning to classify each unlabeled instance and then uses a dual model to reconstruct the unlabeled instances according to the obtained classification results. The risk can be measured by analyzing the reconstruction error and predictions of the original and reconstructed unlabeled instances. If the error is small and the predictions are equal, the unlabeled instance may be safe. Otherwise, the instance may be risky and its output should be approach to be that obtained by SL. Finally, we embed a risk-based regularization term into SSL. Hence, the outputs of our algorithm are a tradeoff between those of SL and SSL. In particular, we utilize respectively regularized least squares (RLS) and Laplacian RLS for SL and SSL. To verify the effectiveness of the proposed safe mechanism in DALLAS, we carry out a series of experiments on several data sets by the comparison with the state-of-the-art supervised, semi-supervised, and safe semi-supervised learning methods and the results demonstrate that DALLAS can effectively reduce the risk of the unlabeled instances.

As one of the key components of aerospace power grid, the performance of on load tap changer (OLTC) of power transformer is very important. So it is necessary to realize real-time monitoring of its status. At present, there is no feasible monitoring scheme to carry out on-line monitoring and fault diagnosis for detecting faults of OLTC. The current waveform of the switching process will be abnormal due to the contact fault, the transition resistance fault, and most of the mechanical faults. This paper presents a fault diagnosis method for OLTC based on the current detection in the process of switching. Through on-line acquisition of current waveform in the switching process, empirical mode decomposition and Hilbert-Huang transform is used to calculate normalized time-frequency spectrum, and extract fault characteristic quantity, which can realize the comprehensive diagnosis of the running state of the equipment, and identify the early fault characteristics, and promote the process of the OLTC's maintenance, from regular test to condition based maintenance. Experiment results prove that the designed fault diagnosis instrument can effectively monitor the working condition of OLTC during the switching process and make effective fault diagnosis.

This paper proposes an improved online calibration technique for digital input electricity meters. The technique employs a double-spectral-line interpolation fast Fourier transform algorithm with four-item, three-order Nuttall window to reduce the measurement error caused by spectrum leakage, frequency fluctuation, noise pollution, and harmonic interference. A calibration system of friendly human-computer interaction is designed using LabVIEW. Simulation and practical results show that the proposed calibration system with improved Nuttall window algorithm is of high accuracy and reliability when compared with the traditional calibration algorithm currently used by industry practice.

Abstract Background The significance of PLK1 (polo-like kinase 1) has become increasingly essential as both a biomarker and a target for cancer treatment. Here, we aimed to determine the downstream genes of PLK1 and their effects on the carcinogenesis and progression of bladder cancer. Methods Specific siRNA was utilized to silence the target gene expression. The cell proliferation, invasion and migration of bladder cancer cells by MTT assay, BrdU assay and transwell assay. The differential expression genes were identified using Affymetrix HTA2.0 Array. The KEGG, GO and STRING analysis were used to analyze the signaling pathway and protein-protein interaction. Spearman analysis was used to analyze the correlation between protein and protein, between protein and clincopathologic characteristics. Results PLK1 siRNA hindered the proliferation, invasion and migration of bladder cancer cells, as determined by the MTT, BrdU and transwell assays. A total of 561 differentially expressed genes were identified using an Affymetrix HTA2.0 Array in PLK1 knockdown T24 cells. According to KEGG, GO and STRING analysis, five key genes (BUB1B, CCNB1, CDC25A, FBXO5, NDC80) were determined to be involved in cell proliferation, invasion and migration. PLK1 knockdown decreased BUB1B, CCNB1, CDC25A and NDC80 expressions but increased FBXO5 expression. BUB1B, CCNB1, CDC25A and NDC80 were positively correlated with cell proliferation, invasion, migration and PLK1 expression in tissues, but FBXO5 was negatively correlated with each of those factors. The results showed that the five genes expressions were significantly correlation with the PLK1 expression in normal bladder tissues and bladder cancer tissues. Four of them (BUB1B, CCNB1, CDC25A, NDC80) were obviously positive correlations with pT stage and metastasis. But FBXO5 was negative correlated with pT stage and metastasis. Furthermore, significant correlations were found between CCNB1 or CDC25A or NDC80 and histological grade; between BUB1B or NDC80 and recurrence. Conclusion Five downstream genes of PLK1 were associated with the regulation of cell proliferation, invasion and migration in bladder cancer. Furthermore, these genes may play important roles in bladder cancer and become important biomarkers and targets for cancer treatment.

Sorghum is the fifth most commonly used cereal worldwide and is a rich source of many bioactive compounds. We summarized phenolic compounds and carotenoids, vitamin E, amines, and phytosterols in sorghum grains. Recently, with the development of detection technology, new bioactive compounds such as formononetin, glycitein, and ononin have been detected. In addition, multiple in vitro and in vivo studies have shown that sorghum grains have extensive bio-logical activities, such as antioxidative, anticancer, antidiabetic, antiinflammatory, and antiobesity properties. Finally, with the establishment of sorghum phenolic compounds database, the bound phenolics and their biological activities and the mechanisms of biological activities of sorghum bioactive compounds using clinical trials may be researched.

Rapid and uniform seed germination improves mechanized oilseed rape production in modern agricultural cultivation practices. However, the molecular basis of seed germination is still unclear in Brassica napus. A population of recombined inbred lines of B. napus from a cross between the lower germination rate variety ‘APL01’ and the higher germination rate variety ‘Holly’ was used to study the genetics of seed germination using quantitative trait locus (QTL) mapping. A total of five QTLs for germination energy (GE) and six QTLs for germination percentage (GP) were detected across three seed lots, respectively. In addition, six epistatic interactions between the QTLs for GE and nine epistatic interactions between the QTLs for GP were detected. qGE.C3 for GE and qGP.C3 for GP were co-mapped to the 28.5–30.5 cM interval on C3, which was considered to be a novel major QTL regulating seed germination. Transcriptome analysis revealed that the differences in sugar, protein, lipid, amino acid, and DNA metabolism and the TCA cycle, electron transfer, and signal transduction potentially determined the higher germination rate of ‘Holly’ seeds. These results contribute to our knowledge about the molecular basis of seed germination in rapeseed.

The aim of this study was to assess the leaf area index (LAI) of tomato and cucumber using an AccuPAR-LP-80-ceptometer to find the influence of irrigation. LAI was also determined by destructive sampling for comparison. The research was conducted at the Liaoning Water Conservancy Institute, North China in 2016. A randomized block design was used to test the influence of four treatments corresponding to field water capacity. Full irrigation (W1.0), 15% (W0.85), 25% (W0.75) and 35% (W0.65) water deficit were applied using the drip system. Regression model was developed to estimate LAI in response to irrigation. The results show that there is no difference between the two methods. The highest LAI obtained for tomato and cucumber was 5.21 and 3.21 m2/m2, respectively, with W0.85 at 70-days after transplanting, which corresponds with destructive results. This result was found 11% higher and equal compared with W1.0 for tomato (4.62) and cucumber (3.21), respectively. For both crops, LAI was found significantly influenced at 50-days after transplanting. It also indicated that LAI significantly influenced (by 15%) deficit irrigation for both crops and methods that achieved the highest yield. The predicted LAI was obtained best-fitting with the observed values, which indicated that the AccuPAR-ceptometer is suitable to be used.

Natural isoflavones have been reported to have a potential of antineoplastic activity. However, novel and specific isoflavones are still needed to be explored, and the underlying molecular mechanisms and the intracellular targets of these compounds remain elusive. In our study, we discovered that scandenolone, a natural isoflavonoid derivative from Cudrania tricuspidata fruit, exhibited antineoplastic activity in SK-MEL-28 cells by inducing intrinsic apoptosis and blocking autophagy flux. In addition, scandenolone significantly induced G2/M cycle arrest and inhibited cell migration. The study of the intracellular molecular targets showed that scandenolone binds directly to the active kinase and ATP-binding site of EGFR, which results in downregulating the AKT/mTOR/ERK signaling pathway. Therefore, out results indicate that scandenolone from Cudrania tricuspidata fruit, significantly sensitized SK-MEL-28 cells to apoptosis and repressed the proliferation of the cells, which showed an enormous potential to treat melanoma.

Monitoring DNA binding and single-base mismatches accurately in real time is difficult, especially for miniaturized devices. Here the authors report a graphene field-effect transistor array capable of reliably measuring DNA hybridization kinetics and affinity at the picomolar level.

This paper presents a convenient approach that uses the tensor method to study the propagation of a nonuniformly correlated electromagnetic Cosine-Gaussian Schell-model (ECGSM) beam through an active gradient-index (GRIN) medium. It is shown that the initial correlation structure has a significant influence on the intensity gain; an ECGSM beam ( n = 1) experiences more gain than a conventional electromagnetic Gaussian Schell-model (EGSM) beam (n = 0). The inhomogeneous gain induced by the medium leads to a nonlinear modulation of beam parameters such as the spectral intensity, coherence, and polarization. Although the gain leads to a broadening of the beam width, the coherence gradually decreases, which yields a useful guideline for manipulating active GRIN materials to generate numerous partially coherent beams. It is found that the polarization ellipse in the center of a conventional EGSM beam gradually evolves into circular polarization. However, the state of polarization of a nonuniformly correlated ECGSM beam gradually changes into linear polarization. The ability to manipulate light beams using active GRIN materials opens an alternative avenue for the generation of complex vector beams, which promises important supports in the fields of waveguide amplifiers, beam shaping, optical sensors, and beam transformer devices.

Background: Accumulating research reports have indicated that long non-coding RNAs (lncRNAs) are abnormally expressed in many types of cancers. However, few lncRNA signatures for predicting cancer prognosis have been established. Our goal is to establish a lncRNA signature for predicting the prognosis of clear cell renal cell carcinoma (ccRCC). Methods: We downloaded KIRC lncRNA FPKM (Fragments Per Kilobase of transcript per Million Fragments) standardized expression data from The Cancer Genome Atlas (TCGA) by using the TANRIC tool. We established an 11-lncRNA signature that was clearly linked to the overall survival (OS) rates in the training and test sets. Results: The training set was divided into the high-risk and low-risk subgroups, between which the OS was disparate (HR = 1.51, 95%CI = 1.39–1.64, P

Objective. To investigate the potential therapeutic effect in a rheumatoid arthritis model of stable human CD8+ regulatory T cells (hCD8+Tregs) induced by TGF-β1 and rapamycin (RAPA) in vitro. Methods. Human CD8+T cells were isolated from human peripheral blood mononuclear cells and induced/expanded with TGF-β1 and RAPA along with anti-CD3/28 beads and IL-2 in vitro and harvested as hCD8+Tregs. The phenotypes, suppressive characteristics, and stability of the hCD8+Tregs in an inflammatory microenvironment were examined in vitro. Human CD8+Tregs were transfused into an acollagen-induced arthritis (CIA) mouse model, and their therapeutic effects and related mechanisms were investigated. Results. Human CD8+Tregs induced by TGF-β1/RAPA showed high expression of Foxp3 and CD103, exhibited vigorous suppression ability, and were stable in inflammatory microenvironments. In CIA mice, the clinical scores, levels of anti-collagen IgG antibody, and cartilage destruction were significantly reduced after adoptive transfusion with hCD8+Tregs. Moreover, hCD8+Treg treatment significantly reduced the number of Th17 cells, increased the number of CD4+IFN-γ+T cells, and produced self CD4+Foxp3+Tregs in vivo. In an in vitro cell coculture assay, hCD8+Tregs significantly inhibited mouse CD4+ effector T cell proliferation, induced mouse CD4+Foxp3+Treg and CD4+IFN-γ+Th1 cell production, reduced Th17 cell development, and downregulated CD80/86 expression on mature DCs (mDCs). Conclusion. TGF-β1/RAPA can induce hCD8+Tregs with stable suppressive characteristics, which could significantly alleviate the severity of CIA based on their stable suppressive ability in an inflammatory microenvironment and further influence the function of other downstream cell subtypes. Human CD8+Tregs might be a therapeutic strategy for rheumatoid arthritis.

Pulsed laser ablation in liquid (PLAL) is gradually becoming an attractive approach for nanomaterial fabrication because it is a chemically simple and clean method with high product purity. We studied the laser interaction with bulk target and particle products in detail, including mechanism process, target morphology and nanoparticle products. We captured three oscillations of one bubble after laser ablates the bulk target and calculated the variation of pressure and temperature inside the bubble. The results show that the first bubble oscillation has greatest impact on the nanomaterial synthesis, and the most powerful stages for the material synthesis during all the bubble oscillations are the beginning of each expansions and the end of each shrinks. Nanomaterial releases from the bubble at the end of each oscillations. In addition, based on the analysis of ablation cavity on the target, it is found that the cavity depth increases with the number of laser pulses, and then the depth tends to be under saturation status, which means it is difficult to obtain great improvement of the nanomaterial productivity just by prolonging the laser irradiation time. More importantly, the strong interaction between laser and particle products is presented clearly by time-resolved shadowgraphy, which can contributed to the modification of nanoparticle products.

Electrochemical biosensing relies on electron transport on electrode surfaces. However, electrode inactivation and biofouling caused by a complex biological sample severely decrease the efficiency of electron transfer and the specificity of biosensing. Here, we designed a three-dimensional antifouling nano-biosensing interface to improve the efficiency of electron transfer by a layer of bovine serum albumin (BSA) and multi-walled carbon nanotubes (MWCNTs) cross-linked with glutaraldehyde (GA). The electrochemical properties of the BSA/MWCNTs/GA layer were investigated using both cyclic voltammetry and electrochemical impedance to demonstrate its high-efficiency antifouling nano-biosensing interface. The BSA/MWCNTs/GA layer kept 92% of the original signal in 1% BSA and 88% of that in unprocessed human serum after a 1-month exposure, respectively. Importantly, we functionalized the BSA/MWCNTs/GA layer with HbA1c antibody (anti-HbA1c) and 3-aminophenylboronic acid (APBA) for sensitive detection of glycated hemoglobin A (HbA1c). The label-free direct electrocatalytic oxidation of HbA1c was investigated by cyclic voltammetry (CV). The linear dynamic range of 2 to 15% of blood glycated hemoglobin A (HbA1c) in non-glycated hemoglobin (HbAo) was determined. The detection limit was 0.4%. This high degree of differentiation would facilitate a label-free POCT detection of HbA1c.

Air-core coil current transformer is a key piece of equipment in the digital substation development. However, it is more vulnerable to various faults when compared with the traditional electromagnetic current transformer. Aiming at understanding the effect of various parameters on the performance of the air-core coil current transformer, this paper investigates the influence of these factors using the maximum information coefficient. The interference mechanism of influencing factors on the transformer error is also analyzed. Finally, the Stacking model fusion algorithm is used to predict transformer errors. The developed base model consists of deep learning, integrated learning and traditional learning algorithms. Compared with gated recurrent units and extreme gradient boosting algorithms, the prediction model based on stacking model fusion algorithm proposed in this paper features higher accuracy and reliability which helps improve the performance and safety of future digital substations.

While frequency response analysis (FRA) is a well matured technique widely used by current industry practice to detect the mechanical integrity of power transformers, interpretation of FRA signatures is still challenging, regardless of the research efforts in this area. This paper presents a method for reliable quantitative and qualitative analysis to the transformer FRA signatures based on a decision tree classification model and a fully connected neural network. Several levels of different six fault types are obtained using a lumped parameter-based transformer model. Results show that the proposed model performs well in the training and the validation stages, and is of good generalization ability.

Due to the rapid development of phasor measurement units (PMUs) and the wide area of interconnection of modern power systems, the security of power systems is confronted with severe challenges. A novel framework based on data for static voltage stability margin (VSM) assessment of power systems is presented. The proposed framework can select the key operation variables as input features for the assessment based on partial mutual information (PMI). Before the feature selection procedure is completed by PMI, a feature preprocessing approach is applied to remove redundant and irrelevant features to improve computational efficiency. Using the selected key variables, a voltage stability assessment (VSA) model based on iterated random forest (IRF) can rapidly provide the relative VSM results. The proposed framework is examined on the IEEE 30-bus system and a practical 1648-bus system, and a desirable assessment performance is demonstrated. In addition, the robustness and computational speed of the proposed framework are also verified. Some impact factors for power system operation are studied in a robustness examination, such as topology change, variation of peak/minimum load, and variation of generator/load power distribution.

The electronic voltage transformer (EVT) has received much attention with the recent global trend to establish smart grids and digital substations. One of the main issues of the EVT is the deterioration of its performance with long-term operation which affects the control and protection systems it is employed for and hence the overall reliability of the power grids. This calls for the essential need for a reliable technique to regularly assess the accuracy of operating EVT in real-time. Unfortunately, traditional calibration methods cannot detect the incipient EVT performance change in real-time. As such, this paper presents a new online method to evaluate the accuracy of the EVT. In this regard, the Q-statistic is calculated based on the recursive principal components analysis (RPCA) using the output data of EVT to map up the changes of metering error on the electric–physics relationship. By employing the output data of the EVT along with the power grid characteristics, the performance of the EVT is evaluated without the need for a standard transformer, as per the current industry practice. Results show that the proposed method can assess the EVT with a 0.2 accuracy class.

A novel high wear resistance hypoeutectic Fe–C–B alloy by hot rolling with isolated hard lumps distributed in matrix is reported. The effect of deformation on microstructure and properties of the alloy during hot rolling process was systematically investigated. The results showed that with the increase of deformation, the continuous hard phase network in the alloy was crushed into isolated hard lumps, and the properties of the alloy were improved significantly. The alloy with 66.7% deformation displayed excellent mechanical properties with the impact value of 12.6 J while its hardness was still kept at 58.6 HRC. And the wear resistance of the alloy with 66.7% deformation was 1.21 times as that of the commercial Cr20Mo high chromium cast iron.

For simultaneously measuring specimen’s surface morphology and material properties, multifrequency atomic force microscopy is often employed. In this kind of atomic force microscopy, if the probe’s higher-order resonance frequencies match the integer multiples of its fundamental frequency, the probe’s responses at such harmonic frequencies will be enhanced. Meanwhile, an enlarged effective slope during vibration at the probe’s tip results in an improved probe sensitivity. Moreover, increasing the probe’s natural frequency leads to a fast scanning speed. In this study, we propose to design cantilever probes that satisfy the aforementioned requirements via a structural optimization technique. A cantilever probe is represented by a three-layer symmetrical geometric model, and its width profile is continuously varied through the optimization procedure. Thereafter, an optimized design of probe considering the fifth harmonic is prepared by focused ion beam milling. Both simulation and experiment results show that the prepared probe agrees well with design requirements.

In this response, we explain the points mentioned by R. Rani and R. Bhatia in their Comment for our previous paper [AIP Advances 5, 097130 (2015)], that the high value of β obtained in Song et al. [AIP Advances 5, 097130 (2015)] is misleading because it does not corroborate with the obtained Jmax, and the obtained value of Jmax is “low” in the mentioned study as compared to the reported values [J. Appl. Phys. 111, 044307 (2012) & Appl. Phys. Lett. 102, 033102 (2013)]. For the high value of β, the obtained current Jmax is corroborated but such high value is mainly due to the multistage effect when CNTs are deposited on the rough surface of reduced graphene. For the “low” Jmax, although this is true when compared with Sameera et al. [J. Appl. Phys. 111, 044307 (2012) and Appl. Phys. Lett. 102, 033102 (2013)], but we believe that our value is a generally common value when compared with other reports [Diam. Relat. Mater. 47, 1 (2014); J. Alloys Compd. 610, 659 (2014); J. Nanomater. 2013, 5239 (2013)] using the similar method as described in our paper. Therefore, the conclusions from the experimental results on field emission performance of CNT/graphene composite materials in our paper are reliable.

This paper outlines theoretically investigations of the probability density distribution (PDD) of ranging data for the imaging laser radar (ILR) system operating at a wavelength of 905 nm under the fog condition. Based on the physical model of the reflected laser pulses from a standard Lambertian target, a theoretical approximate model of PDD of the ranging data is developed under different fog concentrations, which offer improved precision target ranging and imaging. An experimental test bed for the ILR system is developed and its performance is evaluated using a dedicated indoor atmospheric chamber under homogeneously controlled fog conditions. We show that the measured results are in good agreement with both the accurate and approximate models within a given margin of error of less than 1%.

Graphene has attracted much attention in biosensing applications due to its unique properties. In this paper, the monolayer graphene was grown by chemical vapor deposition (CVD) method. Using the graphene as the electric channel, we have fabricated a graphene field-effect transistor (G-FET) biosensor that can be used for label-free detection of RNA. Compared with conventional method, the G-FET RNA biosensor can be run in low cost, be time-saving, and be miniaturized for RNA measurement. The sensors show high performance and achieve the RNA detection sensitivity as low as 0.1 fM, which is two orders of magnitude lower than the previously reports. Moreover, the G-FET biosensor can readily distinguish target RNA from noncomplementary RNA, showing high selectivity for RNA detection. The developed G-FET RNA biosensor with high sensitivity, fast analysis speed, and simple operation may provide a new feasible direction for RNA research and biosensing.

DNA methylation is the major focus of studies on paternal epigenetic inheritance in mammals, but most previous studies about inheritable DNA methylation changes are passively induced by environmental factors. However, it is unclear whether the active changes mediated by variations in DNA methyltransferase activity are heritable. Here, we established human-derived DNMT3A (hDNMT3A) transgenic rats to study the effect of hDNMT3A overexpression on the DNA methylation pattern of rat sperm and to investigate whether this actively altered DNA methylation status is inheritable. Our results revealed that hDNMT3A was overexpressed in the testis of transgenic rats and induced genome-wide alterations in the DNA methylation pattern of rat sperm. Among 5438 reliable loci identified with 64 primer-pair combinations using a methylation-sensitive amplification polymorphism method, 28.01% showed altered amplified band types. Among these amplicons altered loci, 68.42% showed an altered DNA methylation status in the offspring of transgenic rats compared with wild-type rats. Further analysis based on loci which had identical DNA methylation status in all three biological replicates revealed that overexpression of hDNMT3A in paternal testis induced hypermethylation in sperm of both genotype-negative and genotype-positive offspring. Among the differentially methylated loci, 34.26% occurred in both positive and negative offspring of transgenic rats, indicating intergenerational inheritance of active DNA methylation changes in the absence of hDNM3A transmission. Furthermore, 75.07% of the inheritable loci were hyper-methylated while the remaining were hypomethylated. Distribution analysis revealed that the DNA methylation variations mainly occurred in introns and intergenic regions. Functional analysis revealed that genes related to differentially methylated loci were involved in a wide range of functions. Finally, this study demonstrated that active DNA methylation changes induced by hDNMT3A expression were intergenerationally inherited by offspring without transmission of the transgene, which provided evidence for the transmission of active endogenous-factors-induced epigenetic variations.

Mild hypothermia improves survival and neurological recovery after cardiac arrest (CA) and cardiopulmonary resuscitation (CPR). However, the mechanism underlying this phenomenon is not fully elucidated. The aim of this study was to determine whether mild hypothermia alleviates early blood-brain barrier (BBB) disruption. We investigated the effects of mild hypothermia on neurologic outcome, survival rate, brain water content, BBB permeability and changes in tight junctions (TJs) and adherens junctions (AJs) after CA and CPR. Pigs were subjected to 8 min of untreated ventricular fibrillation followed by CPR. Mild hypothermia (33°C) was intravascularly induced and maintained at this temperature for 12 h, followed by active rewarming. Mild hypothermia significantly reduced cortical water content, decreased BBB permeability and attenuated TJ ultrastructural and basement membrane breakdown in brain cortical microvessels. Mild hypothermia also attenuated the CPR-induced decreases in TJ (occludin, claudin-5, ZO-1) and AJ (VE-cadherin) protein and mRNA expression. Furthermore, mild hypothermia decreased the CA- and CPR-induced increases in matrix metalloproteinase-9 (MMP-9) and vascular endothelial growth factor (VEGF) expression and increased angiogenin-1 (Ang-1) expression. Our findings suggest that mild hypothermia attenuates the CA- and resuscitation-induced early brain oedema and BBB disruption, and this improvement might be at least partially associated with attenuation of the breakdown of TJ and AJ, suppression of MMP-9 and VEGF expression, and upregulation of Ang-1 expression.

Under the background of building academic big data and promoting academic sharing,the current development status of open-access repositories was investigated and domestic and foreign research were summarized on data scale,regional distribution and system software.Taking the establishment of building academic institutional repositories as an example,the data collection requirements were analyzed and the commonly used data acquisition specifications were summarized from the aspects of data attributes,metadata standards and semantic deduplication.Finally,combined with the problems and challenges faced by China in developing open-access repositories,reasonable suggestions were put forwar.

Under the background of the innovation-driven strategy,the difficulties faced by enterprises and experts in universities in the process of connecting were analyzed.Based on academic big data technology,an expert data system for industrial fields was built and a full-chain transformation system for scientific and technological achievements was established.By collecting and verifying enterprise needs online,using scholars’ portrait technology to accurately match and push,enterprise experts offline was contacted,project management,risk assessment and technology insurance services were continued to provide.At present,the system has collected tens of thousands of enterprise needs,completed a number of projects with connection of enterprises and experts,improved the accuracy and efficiency of connecting,and achieved mutual benefit and win-win between enterprises and experts.

Several window functions are currently applied to improve the performance of the discrete Fourier transform (DFT) harmonic detection method. These window functions exhibit poor accuracy in measuring the harmonic contents of a signal with high-order and weak-amplitude components when the power frequency fluctuates within a small range. In this paper, a minimum side-lobe optimization window function that is aimed at overcoming the abovementioned issue is proposed. Moreover, an improved DFT harmonic detection algorithm based on the six-term minimum side-lobe optimization window and four-spectrum-line interpolation method is proposed. In this context, the minimum side-lobe optimization window is obtained by optimizing the conventional cosine window function according to the optimization rules, and the characteristics of the new proposed window are provided to analyze its performance. Then, the proposed optimization window function is employed to improve the DFT harmonic detection algorithm based on the six-term minimum side-lobe optimization window and four-spectrum-line interpolation method. The proposed technique is used to detect harmonics of an electricity gird in which the six-term minimum side-lobe optimization window is utilized to eliminate the influence of spectrum leakage caused by nonsynchronous sampling of signal processing. The four-spectrum-line interpolation method is employed to eliminate or mitigate the fence effect caused by the inherent measurement error of the DFT method. Simulation experiments in two complex conditions and an experiment test are carried out to validate the improved performance of the proposed window. Results reveal that the six-term minimum side-lode optimization window has the smallest peak side lobe when compared with existing windows, which can effectively reduce the interaction influence of spectrum leakage, improve the measurement accuracy of the DFT harmonic detection method, and meet the standard requirement of harmonic measurement in complex situations.

In this paper, the energy method is employed to analytically investigate the influence of time delay in signal transmission on synchronization between two coupled FitzHugh-Nagumo (FHN) neurons. Unlike pre-existing methods that deal with synchronization problems, our major idea is to consider the change rate of the energy of the synchronization error system, since the original system’s synchronization is equivalent to the disappearance of the energy of the error system. In rewriting the original coupled system in the corresponding energy coordinates based on the energy method, we find that the change rate of energy of the error system can be divided into two parts (periodic and non-periodic). The synchronization criterion for the original system can then be obtained by letting the non-periodic part of the change rate of the energy be less than zero. The correctness of the analysis is illustrated with numerical simulations. Our analytical results show that time delay in signal transmission has very significant effects on the synchronization between two FHN neurons. If the time delay in signal transmission is not taken into account in the two coupled FHN neurons, synchronous spikes cannot be achieved in the system for any given coupling strength. By adjusting the value of the time delay in signal transmission, the neural system can freely switch between neural rest and synchronous spikes. This means that time delay in signal transmission is crucial for the occurrence of synchronous spikes in the FHN neural system, which contributes to our understanding of the interaction between neurons. We analytically show the influence of the time delay on the synchronization between two FHN neurons, which was seldom considered by other researchers.

A Chebyshev pseudospectral−two-step three-order boundary value coupled method is proposed and presented for handling the issue associated with complicated calculation, low precision, and poor stability in the process of transient response of transmission line. The first order differential equation in time domain is obtained via dispersing the telegraph equation in space domain by utilizing the pseudospectral method (PSM) based on Chebyshev polynomial. Then the two-step three-order boundary value method (BVM3) is presented and employed to resolve the obtained differential equation, so the numerical solution of the space discrete points can be obtained. Furthermore, the Chebyshev pseudospectral−two-step three-order boundary value coupled method (PSM-BVM3) is presented and compared with the Chebyshev pseudospectral−two-step two order boundary value coupled method (PSM-BVM2), the pseudospectral−differential quadrature method (PSM-DQM), and the pseudospectral method−trapezoid rule (PSM-TR) to validate the feasibility of the new proposed method. Theoretical analysis and numerical simulation reveal that the proposed Chebyshev PSM-BVM3 has a higher performance than the conventional method. For the proposed Chebyshev PSM-BVM3, the higher precision, efficiency, and numerical stability can be obtained and achieved only with fewer discrete points in the space domain, which is suitable for solving the transient response of transmission line. The proposed PSM-BVM3 can improve the drawback of numerical instability of the PSM and can also improve the disadvantage of the BVM as it is not easy to change the latter’s timestep size.

In order to realize rapid THz detecting and imaging, a line beam scanning-based ultra-fast THz imaging platform is designed combining simple optical components and lightweight mechanical system. The designed THz imaging platform has the resolution of 12 mm, the scanning angle range of ±10.5°, the scanning speed of 0.17 s/frame, and the scanning range of 2 m × 0.8 m; moreover, it can realize rapid human body THz imaging and distinguish metallic objects. Considering its high-quality performance in THz imaging and detecting, it is believed the proposed line beam scanning-based ultra-fast THz imaging platform can be used in the future in various safe screening applications.

This paper presents data related to the research article entitled “Effects of cell–cell contact and oxygen tension on chondrogenic differentiation of stem cells” [1]. Three sets of micropatterns were fabricated to study the influence of the cell–cell contact on the chondrogenic induction of mesenchymal stem cells (MSCs). The basic repeat units of these micropatterns were of the same area and microisland number to guarantee the same cell density in each culture well. Cells on these micropatterns experienced the same microenvironment except cell–cell contact extent. Immunofluorescent staining and quantitative real-time polymerase chain reaction (qRT-PCR) were performed, and the data are included here.

Objectives To identify risk factors, and their interactions, for suicidal ideation among the elderly in rural communities of Hunan and to provide some scientific basis for suicide prevention.Design, setting and participants A cross-sectional survey was conducted among the elderly in rural communities in China's Hunan Province. Thirteen areas were selected by multi-staged cluster random sampling, and 1887 rural elders were investigated via face-to-face interviews.Main outcome measures Measures included sociodemographic information, suicidal ideation, activities of daily living (ADL), major depression disorder (MDD), drinking, stressful life events and social support. Non-conditional logistic regression was preformed to explore the influencing factors for suicidal ideation, and additive interaction was used to analyse the interaction between risk factors.Results Incidence of suicidal ideation among the elderly was 14.5% (95% CI 12.9% to 16.1%) in rural communities of Hunan. The independent influencing factors for suicidal ideation were annual personal income (OR 3.14; 95% CI 2.15 to 4.59), MDD (OR 17.04; 95% CI 11.91 to 24.39), chronic diseases (OR 2.99; 95% CI 1.84 to 4.85) and ADL (OR 2.00; 95% CI 1.37 to 2.94). Additive interactions were detected between MDD and ADL with a relative excess risk of interaction (RERI) of 21.18 (95% CI 5.47 to 36.89), and between MDD and annual personal income with an RERI of 35.00 (95% CI 9.00 to 61.00).Conclusions The independent risk factors for suicidal ideation are annual personal income (≤2200 CNY), MDD, chronic diseases and disabled ADL status. MDD has additive interactions with ADL and annual personal income. These findings have significant implications for the prediction and prevention of suicidal behaviours.

Background and objective The growth of tumor often faced up with lackness of blood and oxygen, and it has been reported that Annexin A1 may be involved in tumor. The aim of this investigation is to explore the characteristics of expression of Annexin A1 in lung adenocarcinoma A549 cells after hypoxia. Methods A549 cells were exposured to either normoxia (21%O2) or hypoxia (1%O2) condition for 4 h, 12 h, 24 h. The expressions of Annexin A1 mRNA levels were measured by RT-PCR. The expressions of Annexin 1 protein were investigaged by Western blot. The relative content of reactive oxygen species (ROS) were assayed by special kit. The expressions of nuclear translocation of NF-κB was assayed by Western blot; After been treated with ROS scavenger NAC and PDTC, the levels of Annexin 1 protein of A549 cells were measured by Western blot. Results Compared with normoxia group, the Annexin A1 mRNA in hypoxia group increased after 4 h, and then decreased gradually; Moreover, Annexin 1 protein levels of A549 cells were also increased when treated with hypoxia. An increaing of ROS production in cells exprosed to hypoxia was detected. NAC and PDTC inhibited hypoxia-induced Annexin A1 increase. Conclusion Hypoxia upregulates the expression of Annexin A1 in lung adenocarcinoma A549 cells, in which process ROS-NF-κB may paticipate in.