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The high dimensionality of the modern remote sensing data of construction land makes it complicated to extract image data. This paper proposes a dimensionality reduction and extraction strategy for the remote sensing data of construction land, with the aid of building information modeling (BIM) and geographical information system (GIS). Firstly, the BIM was employed to reduce the size of the remote sensing data of construction land and to obtain the information of each element. Next, the remote sensing data of construction land were parsed, and the key BIM elements were extracted through semantic filtering. In addition, the remote sensing data were converted into a triangulated irregular network (TIN), which can be processed by the geographical information system (GIS). In the end, random projection was utilized to reduce the dimensionality and compress the remote sensing data, and realize the data extraction. Experimental results show that our approach can compress and extract the information from construction land images in the remote sensing data with a high accuracy.

Background. In recent years, immune-associated genes (IAGs) have been documented as having critical roles in the occurrence and progression of muscle-invasive bladder cancer (MIBC). Novel immune-related biomarkers and a robust prognostic signature for MIBC patients are still limited. The study is aimed at developing an IAG-based signature to predict the prognosis of MIBC patients. Methods. In the present study, we identified differentially expressed IAGs in MIBC by using transcriptomics data from The Cancer Genome Atlas (TCGA) database and proteomics data from our samples. We further constructed an IAG-based signature and evaluated its prognostic and predictive value by survival analysis and nomogram. Tumor Immune Estimation Resource (TIMER) was applied to explore the correlation between the IAG-based signature and immune cell infiltration in the microenvironment of MIBC. Results. A total of 22 differentially expressed IAGs were identified, and 2 IAGs (NR2F6 and AHNAK) were used to establish a prognostic signature. Subsequently, survival analysis showed that high-risk scores were significantly correlated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of MIBC patients. A prognostic nomogram was constructed by integrating clinical factors with the IAG-based signature risk score. In addition, the IAG-based signature risk score was positively associated with the infiltration of macrophages and dendritic cells in MIBC. Conclusions. We constructed and verified a novel IAG-based signature, which could predict the prognosis of MIBC and might reflect the status of the immune microenvironment of MIBC. Further studies in more independent clinical cohorts and further experimental exploration of the prognostic IAG-based signature are still needed.

PTPN6 (protein tyrosine phosphatase nonreceptor type 6), a tyrosine phosphatase, is known to be signaling molecules that regulate a variety of cellular processes including cell growth, differentiation, mitotic cycle, and oncogenic transformation. Previous studies have demonstrated that PTPN6 expression is relatively elevated in several malignancies. However, the role of PTPN6 in bladder cancer (BC) remains unclear. The purpose of this study was to explore the prognostic value of PTPN6 in BC. RNA-seq data from The Cancer Genome Atlas (TCGA) was used to identify the expression level of PTPN6 in BC. The relationship between clinical pathologic features and PTPN6 were analyzed with the Wilcoxon signed-rank test. The prognostic and predictive value of PTPN6 was evaluated by survival analysis and nomogram. Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential molecular mechanisms of PTPN6 in BC. Finally, Tumor Immune Estimation Resource (TIMER) was applied to investigate the relationship between PTPN6 and immune cell infiltration in the tumor microenvironment. Results indicated that PTPN6 was overexpressed in BC tissues compared with normal bladder tissues and was significantly correlated with grade, stage, T, and N. Survival analysis showed that low expression of PTPN6 was significantly related to the poor overall survival (OS) in BC patients. Coexpression analysis showed that PTPN6 and TNFRSF14 (Tumor necrosis factor receptor superfamily member 14) have a close correlation in BC. GSEA showed that multiple cancer-associated signaling pathways are differentially enriched in the PTPN6 high expression phenotype. Moreover, the expression level of PTPN6 was positively associated with the infiltration of B cells, CD4+T cells, dendritic cells, and neutrophils and negatively associated with CD8+ T cells and macrophages in BC. In conclusion, we identified that PTPN6 may be a novel prognostic biomarker in BC based on the TCGA database. Further clinical trials are needed to confirm our observations and mechanisms underlying the prognostic value of PTPN6 in BC also deserve further experimental exploration.

To solve the problems of poor performance of traditional spectrum sensing method under low signal-to-noise ratio, a new spectrum sensing method based on Empirical Mode Decomposition algorithm and K-means clustering algorithm is proposed. Firstly, the Empirical Mode Decomposition algorithm and the wavelet threshold algorithm are used to remove the noise components in the spectrum sensing signal, and K-means clustering algorithm is used to determine whether the primary user exists. The method can remove the redundant components such as noise in the nonstationary or nonlinear sampling signal in the real environment and does not need to know the prior information such as signal, channel, and noise, so it can well handle the complicated sensing signal in real environment. This method can reduce the impact of noise on the spectrum sensing system and thus can improve the sensing performance of the system. In the experimental part, the difference between maximum and minimum eigenvalues and the difference between the maximum eigenvalue and the average energy in the random matrix are selected as signal features. Experiments also show that the proposed method is better than the traditional spectrum sensing methods.

Chinese dragon’s blood, the red resin ofDracaena cochinchinensis, one of the renowned traditional medicines, has been used to facilitate blood circulation and disperse blood stasis for thousands of years. Phenolic compounds are considered to be responsible for its main biological activities. In this study, total phenolic compounds of Chinese dragon’s blood were made into capsule (Longxuetongluo Capsule, LTC) and their effects on the abnormal hemorheological properties were examined by high fat diet (HFD) induced ApoE−/− mice. Compared to the model group, LTC recovered the abnormal hemorheological parameters in HFD-induced ApoE−/− mice by reducing whole blood viscosity (WBV) at high rate and improving erythrocyte function. In conclusion, LTC could ameliorate erythrocyte deformability and osmotic fragility through the reduction of lipid peroxidation on plasma and erythrocyte membranes in HFD-induced ApoE−/− mice, which supported the traditional uses of Chinese dragon’s blood as an effective agent for improving blood microcirculation in hypercholesterolemia.

In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.

Adsorption behavior of 17α-ethinylestradiol (EE2) in northern Taihu Lake sediment was analyzed by using batch equilibrium experiment. Freundlich isotherm could describe the adsorption thermodynamic behavior of EE2 in sediment. Sediment organic matter (SOM) contents had important impacts on the adsorption capacity for EE2. The pH values also influenced the adsorption capacity for EE2. Increase of pH value could decrease the EE2 adsorption, which might be due to the electrostatic repulsion between the anionic form of EE2 and sediments with negative charge under high pH values. Competitive effects of bisphenol A (BPA) on EE2 adsorption were further analyzed. The results showed that low concentration BPA did not have significant influences on EE2 adsorption. However, high concentration BPA could reduce EE2 adsorption, which might be due to the similar molecular diameter of BPA with adsorption sites and one more benzene ring with a hydroxyl group in BPA. These results provide primary information of EE2 adsorption in sediment-water system in Taihu Lake, which is useful for the environmental risk assessment and management of EE2 in studied area.

Accurate gas turbine engine health status estimation is very important for engine applications and aircraft flight safety. Due to the fact that there are many to-be-estimated parameters, engine health status estimation is a very difficult optimization problem. Traditional gas path analysis (GPA) methods are based on the linearized thermodynamic engine performance model, and the estimation accuracy is not satisfactory on conditions that the nonlinearity of the engine model is significant. To solve this problem, a novel gas turbine engine health status estimation method has been developed. The method estimates degraded engine component parameters using quantum-behaved particle swarm optimization (QPSO) algorithm. And the engine health indices are calculated using these estimated component parameters. The new method was applied to turbine fan engine health status estimation and is compared with the other three representative methods. Results show that although the developed method is slower in computation speed than GPA methods it succeeds in estimating engine health status with the highest accuracy in all test cases and is proven to be a very suitable tool for off-line engine health status estimation.

Background.Viral hemorrhagic fevers (VHF) are a group of systemic diseases characterized by fever and bleeding, which have posed a formidable potential threat to public health with high morbidity and mortality. Traditional Chinese Medicine (TCM) formulas have been acknowledged with striking effects in treatment of hemorrhagic fever syndromes in China’s history. Nevertheless, their accurate mechanisms of action are still confusing.Objective.To systematically dissect the mechanisms of action of Chinese medicinal formula Xijiao Dihuang (XJDH) decoction as an effective treatment for VHF.Methods.In this study, a systems pharmacology method integrating absorption, distribution, metabolism, and excretion (ADME) screening, drug targeting, network, and pathway analysis was developed.Results.23 active compounds of XJDH were obtained and 118 VHF-related targets were identified to have interactions with them. Moreover, systematic analysis of drug-target network and the integrated VHF pathway indicate that XJDH probably acts through multiple mechanisms to benefit VHF patients, which can be classified as boosting immune system, restraining inflammatory responses, repairing the vascular system, and blocking virus spread.Conclusions.The integrated systems pharmacology method provides precise probe to illuminate the molecular mechanisms of XJDH for VHF, which will also facilitate the application of traditional medicine in modern medicine.

Unsaturated glycerol monooleate was considered to replace saturated glycerol monopalmitate as emulsifer in the manufacture of ice cream to improve certain properties in sensory and physical aspects. The glycerol monooleate was synthesized by glycerolysis of camellia oil using lipase Novozym 435 (from Candida Antarctica lipase B) as catalyst. A mixture of acylglycerols contained 82.42% of glycerol monooleate was obtained after purification by molecular distillation. The glycerol monooleate and glycerol monopalmitate were employed in low fat ice cream and regular fat ice cream, respectively. Sensory and physical properties such as mouthfeel, overrun, firmness and melting resistance of each ice cream were compared. The results showed that the addition of glycerol monooleate can supply the sensory gap between the low fat ice cream and regular fat ice cream. Improvement of overrun and melting resistance were also found in the ice creams that contained glycerol monooleate. This research work provides a good way that enjoying the low fat ice cream with a tasting of regular fat ice cream. PRACTICAL APPLICATIONS Premium ice creams generally have a fat content of 14–18%. It has also become desirable, however, to produce light ice creams

Soybean oil with conjugated linoleic acid (CLA) was produced by a lipase-catalyzed transesterification with soybean oil and the ethyl ester of the acid. The product, soybean oil–CLA was purified by molecular distillation, and its oxidative stability was investigated. The maximum content of the CLA in the soybean oil was 36.2% under the optimal biocatalytic conditions of 60C, 140 U Lipozyme RM IM (from Rhizomucor miehei) per gram reaction mixture and a 3:1 molar ratio of the conjugated linoleic acid ethyl ester to soybean oil. In comparison to soybean oil, the modified soybean oil with CLA was slightly decreased (P > 0.05) in oxidative stability, but it increased fivefold with the addition of tert-butylhydroquinone to a final concentration of 100 mg/Kg oil. PRACTICAL APPLICATIONS Conjugated linoleic acid (CLA) can play roles in application of anticancer and antiatherogenic. Unfortunately, CLA (and/or its ethyl ester) has an irritant effect on stomach, and studies of the sensory characteristics have revealed that the milk contained 1% or 2% CLA exhibited low intensities of a “grassy/vegetable oil” flavor. However, these problems can be easily solved by incorporating CLA into triacylglycerol. This work incorporated CLA into soybean oil by tranesterification of soybean oil and CLA-ethyl ester. The modified soybean oil enriched with CLA has potential application in milk and dairy products in supplementing of CLA.

This paper introduces the antioxidant constituents and pharmacological effects of Sijunzi decoction by looking up literatures in recent years. Sijunzi decoction is composed of Ginseng, Atractylodes, Tuckahoe, and Glycyrrhiza. The antioxidant ingredients of Sijunzi decoction include paeonol, dauricine, naringin, and isoliquiritigenin. The study has proved that it possesses wide pharmacological effects of anticardiovascular diseases, antinervous system disease, antidiabetes, antimetabolic syndrome, and antitumor. Research on the antioxidant components of Sijunzi decoction and their targets is a promising study area in the future.