Research on Construction and Application of Individual Knowledge Management Maturity Evaluation Model

Individual knowledge management is basic component of organizational knowledge management, and the maturity of individual knowledge management has a significant impact on organizational knowledge management. This research introduces scientific idea of capability maturity model into individual knowledge management, building corresponding assessment criteria combined with features of individual knowledge management, and constructing an individual knowledge management maturity model with gray comprehensive evaluation method. In the fourth part of this paper, the validity of the model has been verified by applying the model on an instance. This research is made in order to provide references and suggestions on improving the level of individual knowledge management in knowledge-based organizations.</p

The Ageing of μPlasma Modified Polymers:the Role of Hydrophilicity

Thermoplastic polymers exhibit relatively limited surface energies and this results in poor adhesion when bonded to other materials. Plasma surface modification offers the potential to overcome this challenge through the functionalisation of the polymer surfaces. In this study, three polymers of differing hydrophobicity (HDPE, PA12, and PA6) were subjected to a novel, atmospheric, μPlasma surface treatment technique, and its effectiveness at increasing the surface energies was evaluated via measurement of the contact angle. To characterise the physical and chemical changes following μPlasma surface modification, the surface morphology was observed using atomic force microscopy (AFM), and the functionalisation of the surface was evaluated using infrared spectroscopy. Immediately after treatment, the contact angle decreased by 47.3° (HDPE), 42.6° (PA12), and 50.1° (PA6), but the effect was not permanent in that there was a pronounced relaxation or ageing phenomenon in operation. The ageing process over five hours was modelled using a modified stretched exponential function Kohlrausch–Williams–Watts (KWW) model, and it was found that the ageing rate was dependent on the hydrophilicity of polymers, with polyamides ageing more rapidly than polyethylene

Event-based pedestrian detection using dynamic vision sensors

Pedestrian detection has attracted great research attention in video surveillance, traffic statistics, and especially in autonomous driving. To date, almost all pedestrian detection solutions are derived from conventional framed-based image sensors with limited reaction speed and high data redundancy. Dynamic vision sensor (DVS), which is inspired by biological retinas, efficiently captures the visual information with sparse, asynchronous events rather than dense, synchronous frames. It can eliminate redundant data transmission and avoid motion blur or data leakage in high-speed imaging applications. However, it is usually impractical to directly apply the event streams to conventional object detection algorithms. For this issue, we first propose a novel event-to-frame conversion method by integrating the inherent characteristics of events more efficiently. Moreover, we design an improved feature extraction network that can reuse intermediate features to further reduce the computational effort. We evaluate the performance of our proposed method on a custom dataset containing multiple real-world pedestrian scenes. The results indicate that our proposed method raised its pedestrian detection accuracy by about 5.6–10.8%, and its detection speed is nearly 20% faster than previously reported methods. Furthermore, it can achieve a processing speed of about 26 FPS and an AP of 87.43% when implanted on a single CPU so that it fully meets the requirement of real-time detection

An In Vivo Screen Identifies PYGO2 as a Driver for Metastatic Prostate Cancer

Advanced prostate cancer displays conspicuous chromosomal instability and rampant copy number aberrations, yet the identity of functional drivers resident in many amplicons remain elusive. Here, we implemented a functional genomics approach to identify new oncogenes involved in prostate cancer progression. Through integrated analyses of focal amplicons in large prostate cancer genomic and transcriptomic datasets as well as genes upregulated in metastasis, 276 putative oncogenes were enlisted into an in vivo gain-of-function tumorigenesis screen. Among the top positive hits, we conducted an in-depth functional analysis on Pygopus family PHD finger 2 (PYGO2), located in the amplicon at 1q21.3. PYGO2 overexpression enhances primary tumor growth and local invasion to draining lymph nodes. Conversely, PYGO2 depletion inhibits prostate cancer cell invasion in vitro and progression of primary tumor and metastasis in vivo In clinical samples, PYGO2 upregulation associated with higher Gleason score and metastasis to lymph nodes and bone. Silencing PYGO2 expression in patient-derived xenograft models impairs tumor progression. Finally, PYGO2 is necessary to enhance the transcriptional activation in response to ligand-induced Wnt/β-catenin signaling. Together, our results indicate that PYGO2 functions as a driver oncogene in the 1q21.3 amplicon and may serve as a potential prognostic biomarker and therapeutic target for metastatic prostate cancer.Significance: Amplification/overexpression of PYGO2 may serve as a biomarker for prostate cancer progression and metastasis. Cancer Res; 78(14); 3823-33. ©2018 AACR

Changes in sulfur in soybean rhizosphere soil and the response of microbial flora in a continuous cropping system mediated by Funneliformis mosseae

Soybean is an S-loving crop, and continuous cropping might cause soil sulfur shortage. The primary objectives of this study are to determine whether Funneliformis mosseae (F. mosseae) can enhance the content of available S in S-deficient soil and thereby improve the sulfur utilization rate in soybean. The experiment used Heinong 48 (HN48), a soybean variety with a vast planting area in Heilongjiang Province, and F. mosseae was inoculated in the soil of soybean that had been continuously cropped for 0 and 3 years. The results of the barium sulfur turbidimetric assay show that the sulfur content in the soil and soybean was reduced by continuous cropping and increased by inoculation with F. mosseae; the results of the macro-genome sequencing technology, show that the diversity and abundance of bacteria in the soil was decreased by continuous cropping and increased by inoculation with F. mosseae. The sulfur-oxidizing bacteria (SOB) activity and sulfur-related gene expression levels were lower in the continuous crop group compared to the control group and higher in the F.mosseae-inoculated group compared to the control group. Continuous cropping reduced the sulfur content and ratio of soybean rhizosphere soil, affecting soil flora activity and thus soybean growth; F. mosseae inoculation increased the sulfur content of soybean root-perimeter soil and plants, increased the diversity and abundance of rhizosphere soil microorganisms, increased the expression of genes for sulfur transport systems, sulfur metabolism, and other metabolic functions related to elemental sulfur, and increased the species abundance and metabolic vigor of most SOB. In summary, continuous cropping inhibits soil sulfur uptake and utilization in soybean while the inoculation with F. mosseae can significantly improve this situation. This study offers a theoretical research foundation for using AMF as a bio-fungal agent to enhance soil sulfur use. It also supports the decrease of chemical fertilizers, their substitution, and the protection of native soil

Development and validation of polyamines metabolism-associated gene signatures to predict prognosis and immunotherapy response in lung adenocarcinoma

BackgroundPolyamines metabolism is closely related to tumor development and progression, as well as tumor microenvironment (TME). In this study, we focused on exploring whether polyamines metabolism-associated genes would provide prognosis and immunotherapy response prediction in lung adenocarcinoma (LUAD).MethodsThe expression profile data of polyamines metabolism-associated genes were acquired from the Cancer Genome Atlas (TCGA) database. Utilizing the least absolute shrinkage and selection operator (LASSO) algorithm, we created a risk score model according to polyamines metabolism-associated gene signatures. Meanwhile, an independent cohort (GSE72094) was employed to validate this model. Through the univariate and multivariate Cox regression analyses, the independent prognostic factors were identified. Subsequently, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect their expression in LUAD cells. By consensus clustering analysis, polyamines metabolism-associated subgroups were determined in LUAD patients, with differential gene expression, prognosis, and immune characteristics analyses explored.ResultsA total of 59 polyamines metabolism genes were collected for this study, of which 14 genes were identified for the construction of risk score model using LASSO method. High- and low- risk groups of LUAD patients in TCGA cohort were distinguished via this model, and high-risk group presented dismal clinical outcomes. The same prognostic prediction of this model had been also validated in GSE72094 cohort. Meanwhile, three independent prognostic factors (PSMC6, SMOX, SMS) were determined for constructing the nomogram, and they were all upregulated in LUAD cells. In addition, two distinct subgroups (C1 and C2) were identified in LUAD patients. Comparing the two subgroups, 291 differentially expressed genes (DEGs) were acquired, mainly enriching in organelle fission, nuclear division, and cell cycle. Comparing to C1 subgroup, the patients in C2 subgroup had favorable clinical outcomes, increased immune cells infiltration, and effective immunotherapy response.ConclusionThis study identified polyamines metabolism-associated gene signatures for predicting the patients’ survival, and they were also linked to immune cells infiltration and immunotherapy response in LUAD patients