Business organizations often need to manage creative work. An important way of promoting creative work is to use idea generation techniques (IGTs). Numerous IGTs have been developed, and choosing from such a big pool of candidates can be demanding, which is further complicated by the elusiveness of the mechanisms of these IGTs. This study aims at developing a taxonomy for IGTs based on their underlying mechanisms of supporting ideation. First, the current literature for the classification of IGTs is reviewed. Then some related creativity theories are consulted and a new classification system is proposed based on these theories and previous studies. Eighty seven IGTs are classified according to the system. The implications for research and practice are discussed.
Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’ learning situation, which provides the necessary theoretical basis for following revision of teaching plans. To improve the accuracy of topic-sentiment analysis, a novel model for topic sentiment analysis is proposed that outperforms other state-of-art models.
We aim at highlighting the identification and visualization of topic sentiment based on learning topic mining and sentiment clustering at various granularity-levels. The proposed method comprised data preprocessing, topic detection, sentiment analysis, and visualization.
The proposed model can effectively perceive students’ sentiment tendencies on different topics, which provides powerful practical reference for improving the quality of information services in teaching practice.
The model obtains the topic-terminology hybrid matrix and the document-topic hybrid matrix by selecting the real user’s comment information on the basis of LDA topic detection approach, without considering the intensity of students’ sentiments and their evolutionary trends.
The implication and association rules to visualize the negative sentiment in comments or reviews enable teachers and administrators to access a certain plaint, which can be utilized as a reference for enhancing the accuracy of learning content recommendation, and evaluating the quality of their services.
The topic-sentiment analysis model can clarify the hierarchical dependencies between different topics, which lay the foundation for improving the accuracy of teaching content recommendation and optimizing the knowledge coherence of related courses.
The essence of low-carbon logistics is to make logistics capacity grow moderately to meet the requirements of social and economic developments and the goals of energy conservation and carbon reduction through logistics planning and policies, logistics rationalization and standardization, logistics informationization, low-carbon logistics technologies, etc. This study evaluates the performances of human resources in low-carbon logistics enterprises from three assessment facets: work ability, work performance, and work attitude. It adopts the AHP method to reasonably determine an indicator system of performance evaluation and its weight to avoid certain human-caused bias. According to the results herein, the low-carbon work attitude of the case company in recent years has produced good performance, but its low-carbon work performance and low-carbon work ability are both poor. The case company should practically implement and strengthen these indicators so as to enhance human resource performance in low-carbon logistics enterprises. This study establishes a human resources performance evaluation system for low-carbon logistics enterprises to measure the low-carbon working ability, work performance, and working attitude of their general staff. In this way, enterprises may understand their development status, improve development plans, and formulate the best human resources management and development decisions, thus positively guiding their future development.
Collecting ideas through crowdsourcing has become a common practice for companies to benefit from external ideas and innovate. It is desirable that crowd members build on each other's ideas to achieve synergy. This study proposes and verifies a new method for idea combination which can result in combined ideas that are both novel and useful. The domain-specific knowledge of crowd members does not influence the effectiveness of such idea combination. The new method can be used for collecting highly creative ideas from the crowd. The implications for future research are discussed.
Polygonum orientale with beautiful red flowers can be found as one dominant species in the vicinity of most water bodies and wetlands in China. However, its phytoremediation potential has not been sufficiently explored because little is known about its resistance to inorganic or organic pollutants. We investigated P. orientale response to low and moderate levels of phenol stress (≤ 80 mg L-1). Endpoints included phenol tolerance of P. orientale and the removal of the pollutant, antioxidant enzyme activities, damage to the cell membrane, osmotic regulators and photosynthetic pigments. In plant leaves, phenol stress significantly increased the activities of peroxidase (POD) and catalase (CAT), as well as the contents of proline, soluble sugars and carotenoids, whereas superoxide dismutase (SOD), H2O2 and electrolyte leakage (EL) levels remained unaltered. On the other hand, there were significant decreases of soluble protein and chlorophyll contents. We demonstrated that, in combination with phenol tolerance and its removal, P. orientale has efficient protection mechanisms against phenol-induced oxidative damage (≤ 80 mg L-1). We propose that P. orientale could be used as an alternative and interesting material in the phytoremediation of phenol.
Bee pollen has been used for many years in traditional medicine and supplementary nutrients. Bee pollen is mainly composed of nutrients and bioactive substances which might act as potential antioxidants and tyrosinase inhibitors. In this study, 14 species of monofloral bee pollen from China were collected to analyse their antioxidant and tyrosinase inhibitory properties. Our results revealed that virtually all the bee pollen samples possessed powerful antioxidant or tyrosinase inhibitory activities. These properties varied greatly depending on the fl oral species and extraction solvents. To extract phenolics of various species of bee pollen, the most effective solvent may be a solvent which is a 75 wt. % ethanol/water. Extracts of wuweizi, rape, phellodendron, apricot, and dandelion pollen had stronger antioxidant activities; on the other hand, those of apricot, camellia, and sunflower presented excellent tyrosinase inhibitory activities. In addition, we may have found a novel discovery: that apricot pollen exhibits both powerful antioxidant and strong tyrosinase inhibitory activities.
Introduction: The aim of the experiment was to establish the enterotoxigenic Escherichia coli K88 (ETEC K88)-induced BALB/c mouse duodenum inflammation model. Material and Methods: Mice were administered different concentrations of E. coli K88 (1.0 × 107-109 CFU/mL) for 3 d by means of an esophageal catheter. Results: The results showed that the treated group expressed several significant clinical symptoms, such as reduced dietary demands and weight loss, an increased presence of IL-1α, TNF-α, and MPO in the peripheral blood, and some pathological changes in the duodenum. On the 6th-8th days, the body weight of the mice was the lowest. On the 8th day, there were significant differences in IL-1α, TNF-α, and MPO levels compared to the control group (P < 0.05), the gap between the duodenum mucous layer and the muscular layer had widened, the number of goblet cells was increased, and the inflammatory infiltrate and inflammation changes in the lamina propria and the mucous layer were the most obvious. Conclusion: The duodenum inflammation was the most severe on day 8; thus, the model was successfully established. In addition, varying concentrations of ETEC K88 did not significantly influence the duodenum inflammation (P > 0.05).
Differentially Expressed Proteins between Esophageal Squamous Cell Carcinoma and Adjacent Normal Esophageal Tissue
Proteomics was employed to identify the differentially expressed proteins between esophageal squamous cell carcinoma (ESCC) and adjacent normal esophageal tissues. ESCC tissues and adjacent normal tissues were obtained from 10 patients with ESCC and the proteins were extracted and subjected to two-dimensional gel electrophoresis (2-DE). The differentially expressed proteins were identified after image analysis, and matrix assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF-MS) was used to confirm these proteins. Immunohistochemistry was then performed to detect the expressions of HSP27 and ANX1 in ESCC tissues and adjacent normal tissues. A total of 6 differentially expressed proteins were identified by peptide mass fingerprinting, among which SCCA1, KRT4 and ANX1 were down-regulated and TIM1, MnSOD and HSP27 up-regulated in the ESCC. Immunohistochemistry showed HSP27 was highly expressed in the ESCC which, however, had a low expression of ANX1. These findings were consistent with those in proteomics. There were differentially expressed proteins between ESCC and adjacent normal tissues. The investigation of differentially expressed proteins between ESCC and normal esophageal tissue may provide evidence for the molecular pathogenesis of ESCC.
Traditional image contrast enhancement methods originally cannot improve the quality of vein images and may also import some unknown noise resulting in low recognition rate. To overcome the abovementioned disadvantages, the paper proposes an enhancement method based on the morphological filtering theory including three main procedures. Firstly, the algorithm extract the vein Region Of Interest (ROI), and then adopting the improved White Top-Hat transform (WTH) and Black Top-Hat transform (BTH) methods to get the features of vein in detail in both white and black pattern (vein information and background information); Secondly, to construct the filtering function with the self-designed controlling operator, representing the gradient changes of the vein edges, which well reflects the importance of local detail in multi-scale pattern; Finally, traditional nonlinear gray-level transformation function is imported with modality to the parameters to realize the gray normalization. We perform rigorous experiments with the proposed method and other state-of-the-art enhancement methods on the self-built dorsal vein image databases, and the experimental results illustrate that the multiscale top-hat theory-based enhancement methods improve the contrast of hand vein images with restrictions on the possibility of enhancement on existing noise information.
In order to improve the performance of the shell and tube heat exchanger, a porous baffle and a splitter bar are employed in this research. Through the arrangement of the porous baffle in the tube-side inlet and the splitter bar in the tube, the flow distribution of liquid in the heat exchanger is improved. PIV technology is used to investigate the unsteady flow in the tube-side inlet and the outlet of different models. The porous baffle significantly improves the flow of fluid in the shell and tube heat exchanger, especially by eliminating/minimizing the maldistribution of fluid flow in the tube-side inlet. The performance of the arc baffle is better than that of the straight baffle. The splitter bar has a minimal effect on the flow field of the tube-side inlet, but it effectively improves the flow in the tube bundle and restrains the vortex generation in the tube-side outlet.