Business Value of Enterprise Micro-Blogs: Empirical Study from weibo.com in Sina

The increasing use of micro-blogs as marketing tools has increased the research attention on the usage and performance of enterprise micro-blogs. Based on research on information system (IS) usage and the resource-based view (RBV) theory, this study develops a model to measure the business value of enterprise micro-blogs. The model consists of metrics on micro-blog usage, micro-blog operational performance, firm capability, and performance. Questionnaires were distributed to firms that use micro-blogs. This study collects 317 valid responses for empirical analysis. The result suggests that the extent of micro-blog usage improves the operational performance of enterprise micro-blogs directly and indirectly by increasing firm capability. The operational performance of enterprise micro-blogs significantly affects firm performance. This study reveals the mechanism of business value generation of enterprise micro-blogs and extends the stream of research that combines IS usage and the RBV theory

Probabilistic prediction of wind power based on improved Bayesian neural network

Deterministic wind power prediction can be used for long time-scale optimization of power dispatching systems, but the probability and fluctuation range of prediction results cannot be calculated. A Bayesian LSTM neural network (BNN-LSTM) is constructed based on Bayesian networks by placing a priori distributions on top of the LSTM network layer weight parameters. First, the temporal convolutional neural network (TCNN) is used to process the historical time-series data for wind power prediction, which is used to extract the correlation features of the time-series data and learn the trend changes of the time-series data. Then, the mutual information entropy method is used to analyze the meteorological dataset of wind power, which is used to eliminate the variables with small correlation and reduce the dimension of the meteorological dataset, so as to simplify the overall structure of the prediction model. At the same time, the Embedding structure is used to learn the temporal classification features of wind power. Finally, the time series data processed by TCNN, the meteorological data after dimensionality reduction, and the time classification feature data are fed into the BNN-LSTM prediction model together. Compared with a Bayesian neural network, continuous interval method, and Temporal Fusion Transformer (TFT), which is one of the most advanced time series prediction networks, the improved BNN-LSTM can respond more accurately to wind power fluctuations with better prediction results. The comprehensive index of probability prediction of pinball loss is smaller than those of the other three methods by 53.2%, 24.4%, and 11.3%, and the Winkler index is 3.5 %, 34.6 %, and 8.2 % smaller, respectively

Detection and analysis of human papillomavirus (HPV) DNA in breast cancer patients by an effective method of HPV capture

Despite an increase in the number of molecular epidemiological studies conducted in recent years to evaluate the association between human papillomavirus (HPV) and the risk of breast carcinoma, these studies remain inconclusive. Here we aim to detect HPV DNA in various tissues from patients with breast carcinoma using the method of HPV capture combined with massive paralleled sequencing (MPS). To validate the confidence of our methods, 15 cervical cancer samples were tested by PCR and the new method. Results showed that there was 100% consistence between the two methods.DNA from peripheral blood, tumor tissue, adjacent lymph nodes and adjacent normal tissue were collected from seven malignant breast cancer patients, and HPV type 16(HPV16) was detected in 1/7, 1/7, 1/7and 1/7 of patients respectively. Peripheral blood, tumor tissue and adjacent normal tissue were also collected from two patients with benign breast tumor, and 1/2, 2/2 and 2/2 was detected to have HPV16 DNA respectively. MPS metrics including mapping ratio, coverage, depth and SNVs were provided to characterize HPV in samples. The average coverage was 69% and 61.2% for malignant and benign samples respectively. 126 SNVs were identified in all 9 samples. The maximum number of SNVs was located in the gene of E2 and E4 among all samples. Our study not only provided an efficient method to capture HPV DNA, but detected the SNVS, coverage, SNV type and depth. The finding has provided further clue of association between HPV16 and breast cancer

Reflective plasmonic color filters based on lithographically patterned silver nanorod arrays

10.1039/c3nr01419cNanoscale5146243-624

Analysis of the elements and healing effects of animation based on big data

The big data method is used in this study to examine the relationship between the elements and healing effects of animation. On the basis of the relationship between animation and movies, we analyze the warmth healing animation as well as its history and current situation. Theories in psychology are used to study this type of animation in detail. Warmth healing animation is investigated from different angles. First, we analyze warmth healing animation based on theories of narrative psychology. Subsequently, we investigate it based on theories of visual arts and via big data analysis. Finally, on the basis of analysis results, the emergence of warmth healing animation is found to be inevitable

Antioxidant Enzymatic Activities and Gene Expression Associated with Heat Tolerance in the Stems and Roots of Two Cucurbit Species (“Cucurbita maxima” and “Cucurbita moschata”) and Their Interspecific Inbred Line “Maxchata”

The elucidation of heat tolerance mechanisms is required to combat the challenges of global warming. This study aimed to determine the antioxidant enzyme responses to heat stress, at the enzymatic activity and gene expression levels, and to investigate the antioxidative alterations associated with heat tolerance in the stems and roots of squashes using three genotypes differing in heat tolerance. Plants of heat-tolerant “C. moschata”, thermolabile “C. maxima” and moderately heat-tolerant interspecific inbred line “Maxchata” genotypes were exposed to moderate (37 °C) and severe (42 °C) heat shocks. “C. moschata” exhibited comparatively little oxidative damage, with the lowest hydrogen peroxide (H2O2), superoxide (O2−) and malondialdehyde (MDA) contents in the roots compared to stems, followed by “Maxchata”. The enzyme activities of superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT) and peroxidase (POD) were found to be increased with heat stress in tolerant genotypes. The significant inductions of FeSOD, MnSOD, APX2, CAT1 and CAT3 isoforms in tolerant genotypes suggested their participation in heat tolerance. The differential isoform patterns of SOD, APX and CAT between stems and roots also indicated their tissue specificity. Furthermore, despite the sequence similarity of the studied antioxidant genes among “C. maxima” and “Maxchata”, most of these genes were highly induced under heat stress in “Maxchata”, which contributed to its heat tolerance. This phenomenon also indicated the involvement of other unknown genetic and/or epigenetic factors in controlling the expression of these antioxidant genes in squashes, which demands further exploration

Influence of temperature on sludge settleability and bacterial community structure in enhanced biological phosphorus removal systems

<p>In this study, the influence of temperature on sludge settleability and bacterial community structure was investigated in two EBPR systems for a better understanding of the seasonally variable settleability. The results indicated that settleability depended both on the filament content and on the non-soluble phosphorus (Pns) and non-volatile suspended solids (NVSS) contents at varying temperatures. When the temperature was increased, settleability was significantly improved because of the substantial reduction in the filaments. When the temperature was decreased, settleability changed slightly in the long run and was mainly determined by Pns/VSS and NVSS/VSS (<i>p</i> < 0.05). Canonical correspondence analysis results indicated that bacterial community structure was significantly correlated with temperature and settleability (<i>p</i> < 0.01). At a high temperature (25°C), 21 species mostly affiliated with <i>Proteobacteria</i>, followed by <i>Bacteroidetes</i>, were stimulated greatly. The proliferation of <i>Bacteroidetes</i> might have a close relation with the improvement of settleability. At a low temperature (15°C), 25 species which were different from that at a high temperature proliferated in the system. These species mostly affiliated with <i>Proteobacteria,</i> followed by <i>Actinobacteria.</i> The large population of <i>Actinobacteria</i> was closely correlated with poor settleability. This work provides a valuable basis for the control of seasonal sludge bulking in EBPR systems.</p

Synergistic improvement of strength and electrical conductivity in Cu–Cr–Zr alloys through prestrain-assisted friction stir processing

The objective of this study is to investigate the effects of prestrain-assisted friction stir processing and subsequent aging heat treatment on the microstructural evolution and performance of copper-chromium-zirconium alloys. The findings indicated that prestrain, generated through cold rolling before friction stir processing, considerably affected grain refinement and enhanced the mechanical properties and electrical conductivity in the processing zone. The prestrain not only decreased the activation energy of dynamic restoration and precipitation in the processing zone, but also strengthened the “constraint effect” of the base metals to the processing zone. This effectively reduced the width of micro-bands and promoted nanocrystalline formation in the processing zone. Furthermore, dynamic precipitation resulted in higher thermal stability of the microstructure in the processing zone during subsequent aging heat treatment. Thus, the synergistic improvement of the mechanical properties and electrical conductivity of copper-chromium-zirconium alloys was successfully achieved

Melodinhenine B attenuates NLRP3 expression in a cerebral ischemia/reperfusion-induced neuronal injury rat model

This investigation evaluated the neuroprotective effect of melodinhenine B in a cerebral ischemia/reperfusion (I/R)-induced neuronal injury rat model. The effect of melodinhenine B was determined by evaluating the neurological deficit score, cerebral infarcted area, and blood-brain barrier (BBB) permeability. Moreover, the level of inflammatory cytokines and expression of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κβ), interleukin-1β (IL-1β), NLRP3, zonula occludens-1 (ZO-1), and occluding proteins were estimated by Western blotting. Histopathological changes and immunohistochemical analysis were performed to estimate the effect of melodinhenine B on neuronal injury. The neurological deficit score, percentage of infarcted area, and BBB permeability were improved in the melodinhenine B-treated group of rats. Treatment with melodinhenine B attenuated the altered expression of NF-κβ, IL-1β, NLRP3, ZO-1, and occluding proteins in the brain tissue of I/R-induced neuronal injury rats. The inflammatory cytokine levels were reduced in the melodinhenine B-treated group. Histopathologically, melodinhenine B reversed the pathological changes in the brain tissues of I/R-induced neuronal injury rats. In conclusion, melodinhenine B protects against neuronal injury in cerebral ischemia-reperfusion injury rats by regulating the inflammasomes