Journal articles on the topic 'An quan gong cheng'

Reviewing his long reign in 1792, the Qianlong Emperor (r. 1736–1795) hailed his military triumphs as one of its central accomplishments. To underscore the importance he ascribed to these successes, he began to style himself ‘Old Man of the Ten Complete Victories’ (Shi Quan Lao Ren), after an essay in which he boldly declared he had surpassed, in ‘Ten Complete Military Victories’ (Shi Quan Wu Gong), the far-reaching westward expansions of the great Han (206 BCE–220 CE) and Tang (618–907) empires. Such an assertion, together with the program of commemoration discussed below, served to justify the immense expense incurred by frequent long-distance campaigning; to elevate all these wars to an unimpeachable level of splendor even though some were distinctly less glorious than others; and to align the Manchu Qing dynasty (16–191 i) with two of the greatest native dynasties of Chinese history and the Qianlong Emperor personally with some of the great figures of the past.

Abstract Objective: To observe the expression levels of serum high mobility group box 1 (HMGB1) , nicotinic acetylcholine receptor α7 (α7 nAChR) and nuclear factor kappa-B mRNA(NF-κB mRNA) in colon tissue after electroacupuncture (EA) on Shangjuxu, Zusanli, Xiajuxu,Yanglingquan and Chengjin points, by comparison of the different effects we could thus explore the relative specificity of Shangjuxu on treating its corresponding viscera’ s disease. Methods: Seventy SD rats were randomly assigned to seven groups labeled by blank control (A), Model (B), Shang Ju Xu (C), Zu San Li (D), Xia Ju Xu (E), Yang Ling Quan (F), Cheng Jin (G), ten (half males and half females) in each group. Except for the blank control group, animals in other groups were modeled to ulcerative colitis (UC) by lavation of 2-4-6 trinitro-benzene-sulfonic acid (TNBS)/ethanol solution. After successful modeling animals in the five treatment groups were respectively treated with electroaccupuncture at corresponding acupoint for 10 consecutive days. Then histological changes in the colon were observed by light microscopy. ELISA method was used to check models’serum HMGB1 content, and α7 nAChR in the colon were detected by western blot , RT-PCR was used to detecte NF-κB mRNA. Results: ① Compared with the model group, the tissue injury changes in 5 treatment groups improved to a certain extent, and the colon tissue NF-κB mRNA expression of them decreasd signifcantly（P<0.01),as well, the α7 nAChR expression of Shang Ju Xu group, Zu San Li group and Xia Ju Xu group increased signifcantly (P<0.01 or P<0.05), and their serum HMGB1 content made obvious decrease(P<0.01 or P<0.05), the α7 nAChR expression in Yang Ling Quan group was also increased significantly（P<0.01). ② Compared with Shang Ju Xu group, the tissue injury changes of groups including Xia Ju Xu,Yang Ling Quan and Cheng Jin are much severe under light microscope, and the α7 nAChR expression of them decreased with significance（P<0.01),both serum HMGB1 content and colon tissue NF-κB mRNA expression increased significantly as well（P<0.01),the serum HMGB1 content of Zu San Li group also increased significantly（P<0.01). Conclusion: ① Electroacupuncture on all five different acupoints can improve the UC through regulating HMGB1, α7 nAChR and NF-κB mRNA, and effectively inhibiting the immune response, reducing inflammatory response of colon and improving pathological changes of colonic mucosa. ②The effect of treating UC inflammation in rats when electroacupuncture at Shang Ju Xu was better than Zu San Li, Xiajuxu, Yang Ling Quan and Cheng Jin, which demonstrated that Shangjuxu treating UC has some relative specificity.

A total of 50 (43 known and seven new) species in the subgenus Phortica (sensu stricto) were surveyed and (re)described from China: P. bicornuta (Chen & Toda, 1997); P. bipartita (Toda & Peng, 1992); P. biprotrusa (Chen & Toda, 1998); P. cardua (Okada, 1977); P. chi (Toda & Sidorenko, 1996); P. conifera (Okada, 1977); P. eparmata (Okada, 1977); P. eugamma (Toda & Peng, 1990); P. excrescentiosa (Toda & Peng, 1990); P. fangae (Máca, 1993); P. flexuosa (Zhang & Gan, 1986); P. foliata (Chen & Toda, 1997); P. gamma (Toda & Peng, 1990); P. gigas (Okada, 1977); P. glabtabula Chen & Gao, 2005; P. hainanensis (Chen & Toda, 1998); P. hongae (Máca, 1993); P. huazhii Cheng & Chen, 2008; P. iota (Toda & Sidorenko, 1996); P. jadete Zhu, Cao & Chen, 2018; P. kappa (Máca, 1977); P. lambda (Toda & Peng, 1990); P. latifoliacea Chen & Watabe, 2008; P. magna (Okada, 1960); P. okadai (Máca, 1977); P. omega (Okada, 1977); P. orientalis (Hendel, 1914); P. pangi Chen & Wen, 2005; P. paramagna (Okada, 1971); P. perforcipata (Máca & Lin, 1993); P. pi (Toda & Peng, 1990); P. protrusa (Zhang & Shi, 1997); P. pseudopi (Toda & Peng, 1990); P. pseudotau (Toda & Peng, 1990); P. psi (Zhang & Gan, 1986); P. rhagolobos Chen & Gao, 2008; P. saeta (Zhang & Gan, 1986); P. setitabula Chen & Gao, 2005; P. subradiata (Okada, 1977); P. tau (Toda & Peng, 1990); P. uncinata Chen & Gao, 2005; P. unipetala Chen & Wen, 2005; P. allomega Gong & Chen, sp. nov.; P. archikappa Gong & Chen, sp. nov.; P. dianzangensis Gong & Chen, sp. nov.; P. imbacilia Gong & Chen, sp. nov.; P. liukuni Gong & Chen, sp. nov.; P. tibeta Gong & Chen, sp. nov.; and P. xianfui Gong & Chen, sp. nov. In addition, seven new synonyms were recognized: P. acongruens (Zhang & Shi, 1997), syn. nov.; P. antillaria (Chen & Toda, 1997), syn. nov.; P. kukuanensis Máca, 2003, syn. nov.; P. linae (Máca & Chen, 1993), syn. nov.; P. shillongensis (Singh & Gupta, 1979), syn. nov.; P. takadai (Okada, 1977), syn. nov.; and P. watanabei (Máca & Lin, 1993), syn. nov. A key to all Asian species (except for the eparmata species complex) of this subgenus was provided. All currently available DNA barcode (partial mitochondrial cytochrome c oxidase subunit I (COI) gene) sequences of this subgenus (217 sequences of 54 species) are employed in a molecular analysis using different species delimitation methods. The results indicate that approximately 68.5% (37 of 54 spp.) of Phortica (s. str.) species could be clearly distinguished from closely related morphospecies or cryptic species.

Nghiên cứu được tiến hành để làm rõ tính liên quan giữa hành vi đồng tạo sinh giá trị, sự hài lòng và lòng trung thành của khách hang trong lĩnh vực y tế. Hành vi đồng tạo sinh giá trị là khái niệm về hành vi tham gia của khách hàng, trong đó đề cập đến hành vi bắt buộc (trong vai trò) để đồng sáng tạo giá trị thành công (Yi & Gong, 2013). Sự hài lòng của khách hàng là một thái độ tổng thể của khách hàng đối với một nhà cung cấp dịch vụ. Lòng trung thành khách hàng có thể được xem là lòng tin của khách hàng, sự ưu tiên lựa chọn sản phẩm và lặp lại trong những lần sử dụng sau đó, đồng thời thông qua truyền miệng tích cực. Dữ liệu nghiên cứu là dữ liệu sơ cấp được khảo sát trực tiếp 405 bệnh nhân tại bệnh viện Thủ Đức. Nghiên cứu sử dụng phân tích mô hình phương trình cấu trúc (SEM) để ước lượng mối quan hệ. Kết quả nghiên cứu chứng minh hành vi tham gia của người bệnh hay các thành phần của nó (hành vi có trách nhiệm, hành vi giao tiếp, hành vi tìm kiếm thông tin và hành vi chia sẻ thông tin) đều có mối quan hệ thuận chiều đến sự hài lòng và lòng trung thành của khách hàng.

AbstractThis article investigates the formation of the Shatan scholarly group and the contribution of its leader, Zheng Zhen. Zheng benefitted from a vigorous trans-regional cultural network of returned local scholars such as Li Xun and Mo Yuchou and prominent scholar-officials from outside such as Cheng Enze and He Changling. Zheng Zhen remained true to the approaches and research topics of evidential research, i.e., historical philology and exegesis of pre-Qin classics, bibliography, and an inquiry into ancient institutions and technology, in an era when the general intellectual trend turned toward statecraft studies and the politicized Modern Text School, promoted by scholars like Gong Zizhen and Kang Youwei. The contribution of the Shatan group, Zheng Zhen in particular, embodies the rise of evidential research, a passion for facts, as well as concerns about society. More importantly, it prompts us to rethink Guizhou as an active agent in the late Qing Chinese cultural landscape.

Carpinus langaoensis Z. Qiang Lu & J. Quan Liu, a new hornbeam species from the Daba Mountains in the Shanxi province of China, is described and illustrated in this study. Morphological comparisons show that this species is similar to C. tientaiensis W. C. Cheng and C. mianningensis Yi, with which it shares the presence of the long bract with lobes at bases of both inner and outer margins and large glabrescent nutlet. However, it is distinct from both in the dense pubescence on the abaxial leaf, and the long infructescence bract. Phylogenetic analyses of ITS sequence variation indicates that these three species form a well-supported monophyletic group, but all examined individuals of the new species are separated from all others by three fixed nucleotide mutations. The new species is also geographically isolated from these two closely related ones. Therefore, all available evidence suggests that a new species (C. langaoensis) should be established for this evolutionarily independent lineage. The new species is known from only a single small population, and so should be treated as a critically endangered species according to the IUCN categories and criteria.

Abstract: Semarang as a multicultural city which there is a mixture of three ethnics groups, namely Javanese ethnics, Arab ethnics and Chinese ethnics. Semarang has a cultural acculturation that comes from three etnics. Semarang has a special food called “Lunpia”. Semarang has a variety of festival’s such as the Chinese New Year, Cheng Ho Festival, Dugderan Festival. One example : Dugderan festival is held welcoming ramadhan. Warag ngendog is a mythological animal with carrying eggs on its back, this creature celebrated during the dugderan festival held annualy a few days before the Ramadhan. Represent three different etnics groups in Semarang city is a Javanese ethnics, Arabian ethnics, and Chinese ethnics. Its head is like a dragon, the body is the combination of  camel and the legs is teh combination of goat. Gambang Semarang is one of traditional dance in Semarang. Gambang Semarang dance is showed to be enjoyed from its moving, appearance and rhythm and the dance is a reflection of someone action which enjoy their life, joyful and thankfull to God (Allah SWT), because we have been given grace through beautiful dance. Gambang Semarang dance using gamelan instrument including Kendang, kempul, bonang, gong, kecrek and tohyan (chinese). Song in Gambang Semarang dance exhivition feels happy and fresh, in January 2020 tourist arrivals in Semarang decreased until 6 percen, because in Jauary is not a period holiday (low season period). Ahmad Yani International Airport in Semarang i sthe entrance point for foreign. In January 2020, Malaysia were the highest number of tourist in Semarang (849people), Singapore (279 people) and Chinese (113 people).Keywords: cultural, acculturation, food, festival

Gao, Bao-Xi, Gong Cheng, and Lea Ziskind-Conhaim. Development of spontaneous synaptic transmission in the rat spinal cord. J. Neurophysiol. 79: 2277–2287, 1998. Dorsal root afferents form synaptic connections on motoneurons a few days after motoneuron clustering in the rat lumbar spinal cord, but frequent spontaneous synaptic potentials are detected only after birth. To increase our understanding of the mechanisms underlying the differentiation of synaptic transmission, we examined the developmental changes in properties of spontaneous synaptic transmission at early stages of synapse formation. Spontaneous postsynaptic currents (PSCs) and tetrodotoxin (TTX)-resistant miniature PSCs (mPSCs) were measured in spinal motoneurons of embryonic and postnatal rats using whole cell patch-clamp recordings. Spontaneous PSC frequencies were higher than mPSC frequencies in both embryonic and postnatal motoneurons, suggesting that even at embryonic stages, when action-potential firing rate was low, presynaptic action potentials played an important role in triggering spontaneous PSCs. After birth, the twofold increase in spontaneous PSC frequency was attributed to an increase in action-potential–independent quantal release rather than to a higher rate of action-potential firing. In embryonic motoneurons, the fluctuations in peak amplitude of spontaneous PSCs were normally distributed around single peaks with modal values similar to those of mPSCs. These data indicated that early in synapse differentiation spontaneous PSCs were primarily composed of currents generated by quantal release. After birth, mean mPSC amplitude increased by 50% but mean quantal current amplitude did not change. Synchronous, multiquantal release was apparent in postnatal motoneurons only in high-K+ extracellular solution. Comparison of the properties of miniature excitatory and inhibitory postsynaptic currents (mEPSCs and mIPSCs) demonstrated that mean mEPSC frequency was higher than mIPSC frequency, suggesting that either excitatory synapses outnumbered inhibitory synapses or that the probability of excitatory transmitter release was higher than the release of inhibitory neurotransmitters. The finding that mIPSC duration was several-fold longer than mEPSC duration implied that despite their lower frequency, inhibitory currents could modulate motoneuron synaptic integration by shunting incoming excitatory inputs for prolonged time intervals.

We presented a numerical investigation of a metamaterial narrowband perfect absorber conducted via a finite element method based on commercially available COMSOL software. The periodic array of silicon meta-atoms (MAs) are placed on 80 nm thick gold layer. The broadband light at normal incidence is blocked by the gold layer and silicon MAs are used to excite the surface plasmon by scattering light through it. Maximum absorption of 95.7 % is obtained at the resonance wavelength of 1137.5 nm due to the perfect impedance matching of the electric and magnetic dipoles. The absorption is insensitive to the wide-angle of incidence ranging from 0 to 80 degrees. We believe that the proposed metamaterial device can be utilized in solar photovoltaic and biochemical sensing applications. Full Text: PDF ReferencesY. Cheng, X.S. Mao, C. Wu, L. Wu, R.Z. Gong, "Infrared non-planar plasmonic perfect absorber for enhanced sensitive refractive index sensing", Optical Materials, 53, 195-200 (2016). CrossRef S. S. Mirshafieyan, D.A. Gregory, "Electrically tunable perfect light absorbers as color filters and modulators", Scientific Reports,8, 2635 (2018). CrossRef D.M. Nguyen, D. Lee, J. Rho, "Control of light absorbance using plasmonic grating based perfect absorber at visible and near-infrared wavelengths", Scientific Reports, 7, 2611 (2017). CrossRef Y. Sun, Y. Ling, T. Liu, L. Huang, "Electro-optical switch based on continuous metasurface embedded in Si substrate", AIP Advances, 5, 117221 (2015). CrossRef H. Chu, Q. Li, B. Liu, J. Luo, S. Sun, Z. H. Hang, L. Zhou, Y. Lai, "A hybrid invisibility cloak based on integration of transparent metasurfaces and zero-index materials", Light: Science & Applications, 7, 50 (2018). CrossRef S. K. Patel, S. Charola, J. Parmar, M. Ladumor, "Broadband metasurface solar absorber in the visible and near-infrared region", Materials Research Express, 6, 086213 (2019). CrossRef Q. Qian, S. Ti, C. Wang, "All-dielectric ultra-thin metasurface angular filter", Optics Letters, 44, 3984 (2019). CrossRef P. Yu et al., "Broadband Metamaterial Absorbers", Advanced Optical Materials, 7, 1800995 (2019). CrossRef Y. J. Kim et al., "Flexible ultrathin metamaterial absorber for wide frequency band, based on conductive fibers", Science and Technology of advanced materials, 19, 711-717 (2018). CrossRef N.L. Kazanskiy, S.N. Khonina, M.A. Butt, "Plasmonic sensors based on Metal-insulator-metal waveguides for refractive index sensing applications: A brief review", Physica E, 117, 113798 (2020). CrossRef H. E. Nejad, A. Mir, A. Farmani, "Supersensitive and Tunable Nano-Biosensor for Cancer Detection", IEEE Sensors Journal, 19, 4874-4881 (2019). CrossRef

Rapid urbanization rates impact significantly on the nature of Land Cover patterns of the environment, which has been evident in the depletion of vegetal reserves and in general modifying the human climatic systems (Henderson, et al., 2017; Kumar, Masago, Mishra, & Fukushi, 2018; Luo and Lau, 2017). This study explores remote sensing classification technique and other auxiliary data to determine LULCC for a period of 50 years (1967-2016). The LULCC types identified were quantitatively evaluated using the change detection approach from results of maximum likelihood classification algorithm in GIS. Accuracy assessment results were evaluated and found to be between 56 to 98 percent of the LULC classification. The change detection analysis revealed change in the LULC types in Minna from 1976 to 2016. Built-up area increases from 74.82ha in 1976 to 116.58ha in 2016. Farmlands increased from 2.23 ha to 46.45ha and bared surface increases from 120.00ha to 161.31ha between 1976 to 2016 resulting to decline in vegetation, water body, and wetlands. The Decade of rapid urbanization was found to coincide with the period of increased Public Private Partnership Agreement (PPPA). Increase in farmlands was due to the adoption of urban agriculture which has influence on food security and the environmental sustainability. The observed increase in built up areas, farmlands and bare surfaces has substantially led to reduction in vegetation and water bodies. The oscillatory nature of water bodies LULCC which was not particularly consistent with the rates of urbanization also suggests that beyond the urbanization process, other factors may influence the LULCC of water bodies in urban settlements. Keywords: Minna, Niger State, Remote Sensing, Land Surface Characteristics References Akinrinmade, A., Ibrahim, K., & Abdurrahman, A. (2012). Geological Investigation of Tagwai Dams using Remote Sensing Technique, Minna Niger State, Nigeria. Journal of Environment, 1(01), pp. 26-32. Amadi, A., & Olasehinde, P. (2010). Application of remote sensing techniques in hydrogeological mapping of parts of Bosso Area, Minna, North-Central Nigeria. International Journal of Physical Sciences, 5(9), pp. 1465-1474. Aplin, P., & Smith, G. (2008). Advances in object-based image classification. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B7), pp. 725-728. Ayele, G. T., Tebeje, A. K., Demissie, S. S., Belete, M. A., Jemberrie, M. A., Teshome, W. M., . . . Teshale, E. Z. (2018). Time Series Land Cover Mapping and Change Detection Analysis Using Geographic Information System and Remote Sensing, Northern Ethiopia. Air, Soil and Water Research, 11, p 1178622117751603. Azevedo, J. A., Chapman, L., & Muller, C. L. (2016). Quantifying the daytime and night-time urban heat island in Birmingham, UK: a comparison of satellite derived land surface temperature and high resolution air temperature observations. Remote Sensing, 8(2), p 153. Blaschke, T., Hay, G. J., Kelly, M., Lang, S., Hofmann, P., Addink, E., . . . van Coillie, F. (2014). Geographic object-based image analysis–towards a new paradigm. ISPRS Journal of Photogrammetry and Remote Sensing, 87, pp. 180-191. Bukata, R. P., Jerome, J. H., Kondratyev, A. S., & Pozdnyakov, D. V. (2018). Optical properties and remote sensing of inland and coastal waters: CRC press. Camps-Valls, G., Tuia, D., Bruzzone, L., & Benediktsson, J. A. (2014). Advances in hyperspectral image classification: Earth monitoring with statistical learning methods. IEEE signal processing magazine, 31(1), pp. 45-54. Chen, J., Chen, J., Liao, A., Cao, X., Chen, L., Chen, X., . . . Lu, M. (2015). Global land cover mapping at 30 m resolution: A POK-based operational approach. ISPRS Journal of Photogrammetry and Remote Sensing, 103, pp. 7-27. Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile networks and applications, 19(2), pp. 171-209. Cheng, G., Han, J., Guo, L., Liu, Z., Bu, S., & Ren, J. (2015). Effective and efficient midlevel visual elements-oriented land-use classification using VHR remote sensing images. IEEE transactions on geoscience and remote sensing, 53(8), pp. 4238-4249. Cheng, G., Han, J., Zhou, P., & Guo, L. (2014). Multi-class geospatial object detection and geographic image classification based on collection of part detectors. ISPRS Journal of Photogrammetry and Remote Sensing, 98, pp. 119-132. Coale, A. J., & Hoover, E. M. (2015). Population growth and economic development: Princeton University Press. Congalton, R. G., & Green, K. (2008). Assessing the accuracy of remotely sensed data: principles and practices: CRC press. Corner, R. J., Dewan, A. M., & Chakma, S. (2014). Monitoring and prediction of land-use and land-cover (LULC) change Dhaka megacity (pp. 75-97): Springer. Coutts, A. M., Harris, R. J., Phan, T., Livesley, S. J., Williams, N. S., & Tapper, N. J. (2016). Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning. Remote Sensing of Environment, 186, pp. 637-651. Debnath, A., Debnath, J., Ahmed, I., & Pan, N. D. (2017). Change detection in Land use/cover of a hilly area by Remote Sensing and GIS technique: A study on Tropical forest hill range, Baramura, Tripura, Northeast India. International journal of geomatics and geosciences, 7(3), pp. 293-309. Desheng, L., & Xia, F. (2010). Assessing object-based classification: advantages and limitations. Remote Sensing Letters, 1(4), pp. 187-194. Dewan, A. M., & Yamaguchi, Y. (2009). Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied Geography, 29(3), pp. 390-401. Dronova, I., Gong, P., Wang, L., & Zhong, L. (2015). Mapping dynamic cover types in a large seasonally flooded wetland using extended principal component analysis and object-based classification. Remote Sensing of Environment, 158, pp. 193-206. Duro, D. C., Franklin, S. E., & Dubé, M. G. (2012). A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery. Remote Sensing of Environment, 118, pp. 259-272. Elmhagen, B., Destouni, G., Angerbjörn, A., Borgström, S., Boyd, E., Cousins, S., . . . Hambäck, P. (2015). Interacting effects of change in climate, human population, land use, and water use on biodiversity and ecosystem services. Ecology and Society, 20(1) Farhani, S., & Ozturk, I. (2015). Causal relationship between CO 2 emissions, real GDP, energy consumption, financial development, trade openness, and urbanization in Tunisia. Environmental Science and Pollution Research, 22(20), pp. 15663-15676. Feng, L., Chen, B., Hayat, T., Alsaedi, A., & Ahmad, B. (2017). The driving force of water footprint under the rapid urbanization process: a structural decomposition analysis for Zhangye city in China. Journal of Cleaner Production, 163, pp. S322-S328. Fensham, R., & Fairfax, R. (2002). Aerial photography for assessing vegetation change: a review of applications and the relevance of findings for Australian vegetation history. Australian Journal of Botany, 50(4), pp. 415-429. Ferreira, N., Lage, M., Doraiswamy, H., Vo, H., Wilson, L., Werner, H., . . . Silva, C. (2015). Urbane: A 3d framework to support data driven decision making in urban development. Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on. Garschagen, M., & Romero-Lankao, P. (2015). Exploring the relationships between urbanization trends and climate change vulnerability. Climatic Change, 133(1), pp. 37-52. Gokturk, S. B., Sumengen, B., Vu, D., Dalal, N., Yang, D., Lin, X., . . . Torresani, L. (2015). System and method for search portions of objects in images and features thereof: Google Patents. Government, N. S. (2007). Niger state (The Power State). Retrieved from http://nigerstate.blogspot.com.ng/ Green, K., Kempka, D., & Lackey, L. (1994). Using remote sensing to detect and monitor land-cover and land-use change. Photogrammetric engineering and remote sensing, 60(3), pp. 331-337. Gu, W., Lv, Z., & Hao, M. (2017). Change detection method for remote sensing images based on an improved Markov random field. Multimedia Tools and Applications, 76(17), pp. 17719-17734. Guo, Y., & Shen, Y. (2015). Quantifying water and energy budgets and the impacts of climatic and human factors in the Haihe River Basin, China: 2. Trends and implications to water resources. Journal of Hydrology, 527, pp. 251-261. Hadi, F., Thapa, R. B., Helmi, M., Hazarika, M. K., Madawalagama, S., Deshapriya, L. N., & Center, G. (2016). Urban growth and land use/land cover modeling in Semarang, Central Java, Indonesia: Colombo-Srilanka, ACRS2016. Hagolle, O., Huc, M., Villa Pascual, D., & Dedieu, G. (2015). A multi-temporal and multi-spectral method to estimate aerosol optical thickness over land, for the atmospheric correction of FormoSat-2, LandSat, VENμS and Sentinel-2 images. Remote Sensing, 7(3), pp. 2668-2691. Hegazy, I. R., & Kaloop, M. R. (2015). Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1), pp. 117-124. Henderson, J. V., Storeygard, A., & Deichmann, U. (2017). Has climate change driven urbanization in Africa? Journal of development economics, 124, pp. 60-82. Hu, L., & Brunsell, N. A. (2015). A new perspective to assess the urban heat island through remotely sensed atmospheric profiles. Remote Sensing of Environment, 158, pp. 393-406. Hughes, S. J., Cabral, J. A., Bastos, R., Cortes, R., Vicente, J., Eitelberg, D., . . . Santos, M. (2016). A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive. Science of the Total Environment, 565, pp. 427-439. Hussain, M., Chen, D., Cheng, A., Wei, H., & Stanley, D. (2013). Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS Journal of Photogrammetry and Remote Sensing, 80, pp. 91-106. Hyyppä, J., Hyyppä, H., Inkinen, M., Engdahl, M., Linko, S., & Zhu, Y.-H. (2000). Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes. Forest Ecology and Management, 128(1-2), pp. 109-120. Jiang, L., Wu, F., Liu, Y., & Deng, X. (2014). Modeling the impacts of urbanization and industrial transformation on water resources in China: an integrated hydro-economic CGE analysis. Sustainability, 6(11), pp. 7586-7600. Jin, S., Yang, L., Zhu, Z., & Homer, C. (2017). A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011. Remote Sensing of Environment, 195, pp. 44-55. Joshi, N., Baumann, M., Ehammer, A., Fensholt, R., Grogan, K., Hostert, P., . . . Mitchard, E. T. (2016). A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring. Remote Sensing, 8(1), p 70. Kaliraj, S., Chandrasekar, N., & Magesh, N. (2015). Evaluation of multiple environmental factors for site-specific groundwater recharge structures in the Vaigai River upper basin, Tamil Nadu, India, using GIS-based weighted overlay analysis. Environmental earth sciences, 74(5), pp. 4355-4380. Koop, S. H., & van Leeuwen, C. J. (2015). Assessment of the sustainability of water resources management: A critical review of the City Blueprint approach. Water Resources Management, 29(15), pp. 5649-5670. Kumar, P., Masago, Y., Mishra, B. K., & Fukushi, K. (2018). Evaluating future stress due to combined effect of climate change and rapid urbanization for Pasig-Marikina River, Manila. Groundwater for Sustainable Development, 6, pp. 227-234. Lang, S. (2008). Object-based image analysis for remote sensing applications: modeling reality–dealing with complexity Object-based image analysis (pp. 3-27): Springer. Li, M., Zang, S., Zhang, B., Li, S., & Wu, C. (2014). A review of remote sensing image classification techniques: The role of spatio-contextual information. European Journal of Remote Sensing, 47(1), pp. 389-411. Liddle, B. (2014). Impact of population, age structure, and urbanization on carbon emissions/energy consumption: evidence from macro-level, cross-country analyses. Population and Environment, 35(3), pp. 286-304. Lillesand, T., Kiefer, R. W., & Chipman, J. (2014). Remote sensing and image interpretation: John Wiley & Sons. Liu, Y., Wang, Y., Peng, J., Du, Y., Liu, X., Li, S., & Zhang, D. (2015). Correlations between urbanization and vegetation degradation across the world’s metropolises using DMSP/OLS nighttime light data. Remote Sensing, 7(2), pp. 2067-2088. López, E., Bocco, G., Mendoza, M., & Duhau, E. (2001). Predicting land-cover and land-use change in the urban fringe: a case in Morelia city, Mexico. Landscape and urban planning, 55(4), pp. 271-285. Luo, M., & Lau, N.-C. (2017). Heat waves in southern China: Synoptic behavior, long-term change, and urbanization effects. Journal of Climate, 30(2), pp. 703-720. Mahboob, M. A., Atif, I., & Iqbal, J. (2015). Remote sensing and GIS applications for assessment of urban sprawl in Karachi, Pakistan. Science, Technology and Development, 34(3), pp. 179-188. Mallinis, G., Koutsias, N., Tsakiri-Strati, M., & Karteris, M. (2008). Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site. ISPRS Journal of Photogrammetry and Remote Sensing, 63(2), pp. 237-250. Mas, J.-F., Velázquez, A., Díaz-Gallegos, J. R., Mayorga-Saucedo, R., Alcántara, C., Bocco, G., . . . Pérez-Vega, A. (2004). Assessing land use/cover changes: a nationwide multidate spatial database for Mexico. International Journal of Applied Earth Observation and Geoinformation, 5(4), pp. 249-261. Mathew, A., Chaudhary, R., Gupta, N., Khandelwal, S., & Kaul, N. (2015). Study of Urban Heat Island Effect on Ahmedabad City and Its Relationship with Urbanization and Vegetation Parameters. International Journal of Computer & Mathematical Science, 4, pp. 2347-2357. Megahed, Y., Cabral, P., Silva, J., & Caetano, M. (2015). Land cover mapping analysis and urban growth modelling using remote sensing techniques in greater Cairo region—Egypt. ISPRS International Journal of Geo-Information, 4(3), pp. 1750-1769. Metternicht, G. (2001). Assessing temporal and spatial changes of salinity using fuzzy logic, remote sensing and GIS. Foundations of an expert system. Ecological modelling, 144(2-3), pp. 163-179. Miller, R. B., & Small, C. (2003). Cities from space: potential applications of remote sensing in urban environmental research and policy. Environmental Science & Policy, 6(2), pp. 129-137. Mirzaei, P. A. (2015). Recent challenges in modeling of urban heat island. Sustainable Cities and Society, 19, pp. 200-206. Mohammed, I., Aboh, H., & Emenike, E. (2007). A regional geoelectric investigation for groundwater exploration in Minna area, north west Nigeria. Science World Journal, 2(4) Morenikeji, G., Umaru, E., Liman, S., & Ajagbe, M. (2015). Application of Remote Sensing and Geographic Information System in Monitoring the Dynamics of Landuse in Minna, Nigeria. International Journal of Academic Research in Business and Social Sciences, 5(6), pp. 320-337. Mukherjee, A. B., Krishna, A. P., & Patel, N. (2018). Application of Remote Sensing Technology, GIS and AHP-TOPSIS Model to Quantify Urban Landscape Vulnerability to Land Use Transformation Information and Communication Technology for Sustainable Development (pp. 31-40): Springer. Myint, S. W., Gober, P., Brazel, A., Grossman-Clarke, S., & Weng, Q. (2011). Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Remote Sensing of Environment, 115(5), pp. 1145-1161. Nemmour, H., & Chibani, Y. (2006). Multiple support vector machines for land cover change detection: An application for mapping urban extensions. ISPRS Journal of Photogrammetry and Remote Sensing, 61(2), pp. 125-133. Niu, X., & Ban, Y. (2013). Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach. International journal of remote sensing, 34(1), pp. 1-26. Nogueira, K., Penatti, O. A., & dos Santos, J. A. (2017). Towards better exploiting convolutional neural networks for remote sensing scene classification. Pattern Recognition, 61, pp. 539-556. Oguz, H., & Zengin, M. (2011). Analyzing land use/land cover change using remote sensing data and landscape structure metrics: a case study of Erzurum, Turkey. Fresenius Environmental Bulletin, 20(12), pp. 3258-3269. Pohl, C., & Van Genderen, J. L. (1998). Review article multisensor image fusion in remote sensing: concepts, methods and applications. International journal of remote sensing, 19(5), pp. 823-854. Price, O., & Bradstock, R. (2014). Countervailing effects of urbanization and vegetation extent on fire frequency on the Wildland Urban Interface: Disentangling fuel and ignition effects. Landscape and urban planning, 130, pp. 81-88. Prosdocimi, I., Kjeldsen, T., & Miller, J. (2015). Detection and attribution of urbanization effect on flood extremes using nonstationary flood‐frequency models. Water resources research, 51(6), pp. 4244-4262. Rawat, J., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), pp. 77-84. Rokni, K., Ahmad, A., Solaimani, K., & Hazini, S. (2015). A new approach for surface water change detection: Integration of pixel level image fusion and image classification techniques. International Journal of Applied Earth Observation and Geoinformation, 34, pp. 226-234. Sakieh, Y., Amiri, B. J., Danekar, A., Feghhi, J., & Dezhkam, S. (2015). Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran. Journal of Housing and the Built Environment, 30(4), pp. 591-611. Santra, A. (2016). Land Surface Temperature Estimation and Urban Heat Island Detection: A Remote Sensing Perspective. Remote Sensing Techniques and GIS Applications in Earth and Environmental Studies, p 16. Shrivastava, L., & Nag, S. (2017). MONITORING OF LAND USE/LAND COVER CHANGE USING GIS AND REMOTE SENSING TECHNIQUES: A CASE STUDY OF SAGAR RIVER WATERSHED, TRIBUTARY OF WAINGANGA RIVER OF MADHYA PRADESH, INDIA. Shuaibu, M., & Sulaiman, I. (2012). Application of remote sensing and GIS in land cover change detection in Mubi, Adamawa State, Nigeria. J Technol Educ Res, 5, pp. 43-55. Song, B., Li, J., Dalla Mura, M., Li, P., Plaza, A., Bioucas-Dias, J. M., . . . Chanussot, J. (2014). Remotely sensed image classification using sparse representations of morphological attribute profiles. IEEE transactions on geoscience and remote sensing, 52(8), pp. 5122-5136. Song, X.-P., Sexton, J. O., Huang, C., Channan, S., & Townshend, J. R. (2016). Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover. Remote Sensing of Environment, 175, pp. 1-13. Tayyebi, A., Shafizadeh-Moghadam, H., & Tayyebi, A. H. (2018). Analyzing long-term spatio-temporal patterns of land surface temperature in response to rapid urbanization in the mega-city of Tehran. Land Use Policy, 71, pp. 459-469. Teodoro, A. C., Gutierres, F., Gomes, P., & Rocha, J. (2018). Remote Sensing Data and Image Classification Algorithms in the Identification of Beach Patterns Beach Management Tools-Concepts, Methodologies and Case Studies (pp. 579-587): Springer. Toth, C., & Jóźków, G. (2016). Remote sensing platforms and sensors: A survey. ISPRS Journal of Photogrammetry and Remote Sensing, 115, pp. 22-36. Tuholske, C., Tane, Z., López-Carr, D., Roberts, D., & Cassels, S. (2017). Thirty years of land use/cover change in the Caribbean: Assessing the relationship between urbanization and mangrove loss in Roatán, Honduras. Applied Geography, 88, pp. 84-93. Tuia, D., Flamary, R., & Courty, N. (2015). Multiclass feature learning for hyperspectral image classification: Sparse and hierarchical solutions. ISPRS Journal of Photogrammetry and Remote Sensing, 105, pp. 272-285. Tzotsos, A., & Argialas, D. (2008). Support vector machine classification for object-based image analysis Object-Based Image Analysis (pp. 663-677): Springer. Wang, L., Sousa, W., & Gong, P. (2004). Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery. International journal of remote sensing, 25(24), pp. 5655-5668. Wang, Q., Zeng, Y.-e., & Wu, B.-w. (2016). Exploring the relationship between urbanization, energy consumption, and CO2 emissions in different provinces of China. Renewable and Sustainable Energy Reviews, 54, pp. 1563-1579. Wang, S., Ma, H., & Zhao, Y. (2014). Exploring the relationship between urbanization and the eco-environment—A case study of Beijing–Tianjin–Hebei region. Ecological Indicators, 45, pp. 171-183. Weitkamp, C. (2006). Lidar: range-resolved optical remote sensing of the atmosphere: Springer Science & Business. Wellmann, T., Haase, D., Knapp, S., Salbach, C., Selsam, P., & Lausch, A. (2018). Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing. Ecological Indicators, 85, pp. 190-203. Whiteside, T. G., Boggs, G. S., & Maier, S. W. (2011). Comparing object-based and pixel-based classifications for mapping savannas. International Journal of Applied Earth Observation and Geoinformation, 13(6), pp. 884-893. Willhauck, G., Schneider, T., De Kok, R., & Ammer, U. (2000). Comparison of object oriented classification techniques and standard image analysis for the use of change detection between SPOT multispectral satellite images and aerial photos. Proceedings of XIX ISPRS congress. Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., . . . Young, S. A. (2009). Overview of the CALIPSO mission and CALIOP data processing algorithms. Journal of Atmospheric and Oceanic Technology, 26(11), pp. 2310-2323. Yengoh, G. T., Dent, D., Olsson, L., Tengberg, A. E., & Tucker III, C. J. (2015). Use of the Normalized Difference Vegetation Index (NDVI) to Assess Land Degradation at Multiple Scales: Current Status, Future Trends, and Practical Considerations: Springer. Yu, Q., Gong, P., Clinton, N., Biging, G., Kelly, M., & Schirokauer, D. (2006). Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery. Photogrammetric Engineering & Remote Sensing, 72(7), pp. 799-811. Zhou, D., Zhao, S., Zhang, L., & Liu, S. (2016). Remotely sensed assessment of urbanization effects on vegetation phenology in China's 32 major cities. Remote Sensing of Environment, 176, pp. 272-281. Zhu, Z., Fu, Y., Woodcock, C. E., Olofsson, P., Vogelmann, J. E., Holden, C., . . . Yu, Y. (2016). Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014). Remote Sensing of Environment, 185, pp. 243-257.

Các kỹ thuật nâng cao tương phản ảnh đã thu hút nhiều sự quan tâm của cộng đồng xử lý ảnh vì chúng giúp cải thiện khả năng phân tích hình ảnh, thị lực máy tính, v.v. Trong các phương pháp nâng cao độ tương phản ảnh, các phương pháp trực tiếp thiết lập một độ đo tương phản và nâng cao chất lượng hình ảnh bằng cách cải thiện độ đo tương phản. Tuy nhiên, hiện có rất ít các nghiên cứu theo phương pháp trực tiếp, chỉ có các nghiên cứu của Cheng và Xu là đề xuất một phương pháp thay đổi độ tương phản tại mỗi điểm ảnh sử dụng độ đo tương phản được tính dựa trên độ thuần nhất của điểm ảnh. Trong bài báo này, chúng tôi đề xuất một phương pháp xây dựng độ thuần nhất mới dựa trên đại số gia tử. Các kết quả thực nghiệm cho thấy phương pháp nâng cao độ tương phản trực tiếp được thực hiện tốt với nhiều loại ảnh màu khác nhau khi áp dụng phép đo độ thuần nhất đề xuất. DOI: 10.32913/rd-ict.vol2.no38.381

Red bayberry (Myrica rubra (Lour.) Siebold & Zucc.), small trees, evergreen, dioecious, natively grows in evergreen broad-leaved forests at elevation of 1580-1875 m a.s.l., and can survive in low nutrient soil at Cao Ma Po commune, Quan Ba district, Ha Giang province. Some data on morphology, phenology, population structure, natural regeneration and distribution of Red baybery, climatic characteristics, physical and chemical properties of soil, and vegetation structure of forests having Myrica rubra occurrence are presented in this paper. Keywords Red bayberry, Myrica rubra, biology, ecology, conservation, Ha Giang, Vietnam References [1] Lu A. & Bornstein A. J., Myricaceae in Wu Z. Y. & Raven P. H. (eds.). Flora of China Vol. 4, Science Press & Missouri Botanical Garden Press, Beijing & St. Louis, 1999, pp. 275-276.[2] He X. H., Chen L. G., Asghar S. & Chen Y., Red Bayberry (Myrica rubra), a Promising Fruit and Forest Tree in China, Journal of the American Pomological Society, 58(3), 2004, pp. 163- 168.[3] Joyce D., Khurshid T., Liu S., McGregor G., Li J. & Jiang Y., Red Bayberry-A New and Exciting Crop for Australia? An investigation of the potential for commercialisation of Myrica rubra Sieb. and Zucc. (Yang mei) in Australia, RIRDC Publication No. 05/081, 2005, 26 pp. [4] Sharpe R. H. & Knapp F. W., The Straberry tree, Myrica rubra Sieb. and Zucc., Florida State Horticultural Society, 1972, pp. 326-328. [5] Chai C. Y. & Chen Y. F., Introduction of Yangmei Elite Varieties in California, World Journal of Forestry, 5(1), 2016, pp. 1-6.[6] Fang Z. X., Zhang M., Tao G. J., Sun Y. F. & Sun J. C., Chemical composition of clarified bayberry (Myrica rubra Sieb et Zucc.) juice sediment, Journal of Agriculture and Food Chemistry, 54(20), 2006, pp. 7710-7716.[7] Cheng J. Y., Ye X. Q., Chen J. C., Liu D. H. & Zhou S. H., Nutritional composition of underutilized bayberry (Myrica rubra Sieb. et Zucc.) kernels, Food Chemistry, 107(4), 2008, pp. 1674-1680.[8] Joyce D. & Sanewski G., The Commercial Potential of Red Bayberry in Australia, RIRDC Publication No. 10/200, 2010, 36 pp.[9] Zhang X. N., Huang H. Z., Zhao X. Y., Lu Q., Sun C. D., Li X., Chen K. S., Effects of flavonoids-rich Chinese bayberry (Myrica rubra Sieb. et Zucc.) pulp extracts on glucose consumption in human HepG2 cells, Journal of Functional Foods, 14, 2015, pp. 144-153.[10] Tong Y., Zhou X. M., Wang S. J., Yang Y. & Cao Y. L., Analgesic activity of myricetin isolated from Myrica rubra Sieb. et Zucc. leaves, Archives of Pharmacal Research, 2(4), 2009, pp. 527-533. [11] Zhang Y., Zhou X. Z., Tao W. Y., Li L. Q., Wei C. Y., Duan J., Chen S. G. & Ye X. Q., Antioxidant and antiproliferative activities of proanthocyanidins from Chinese bayberry (Myrica rubra Sieb. et Zucc.) leaves, Journal of Functional Foods, 27, 2016, pp. 645-654.[12] Kim H. H., Kim D. H., Kim M. H., Oh M. H., Kim S. R., et al., Flavonoid constituents in the leaves of Myrica rubra Sieb. et Zucc. with anti-inflammatory activity, Archives of Pharmacal Research, 36(12), 2013, pp. 1533-1540.[13] Kuo P. L., Hsu Y. L., Lin T. C., Lin L. T. & Lin C. C., Induction of apoptosis in human breast adenocarcinoma MCF-7 cells by prodelphinidin B-2 3,3'-di-O-gallate from Myrica rubra via Fas-mediated pathway, Journal of Pharmacy and Pharmacology 56(11), 2004, pp. 1399-1406.[14] Sun C. D., Zheng Y. X., Chen Q. J., Tang X. L., Jiang M., Zhang J. K., Li X. & Chen K. S., Purification and anti-tumour activity of cyanidin-3-O-glucoside from Chinese bayberry fruit, Food Chemistry, 131(4), 2012, pp. 1287-1294.[15] Sun C. D., Huang H. Z., Xu C. J., Li X. & Chen K. S., Biological activities of extracts from Chinese bayberry (Myrica rubra Sieb. et Zucc.): A review, Plant Foods for Human Nutrition, 68(2), 2013, pp. 97-106.[16] Langhansova L., Hanusova V., Rezek J., Stohanslova B., Ambroz M., et al., Essential oil from Myrica rubra leaves inhibits cancer cell proliferation and induces apoptosis in several human intestinal lines, Industrial Crops Products ,59, 2014, pp. 20-26.[17] Ambrǒz M., Bousǒvá I., Skarka A., Hanusǒvá V., Králová V., et al., The Influence of Sesquiterpenes from Myrica rubra on the Antiproliferative and Pro-Oxidative Effects of Doxorubicin and Its Accumulation in Cancer Cells, Molecules, 20(8), 2015, pp. 15343-15358.[18] Lê Mộng Chân và Lê Thị Huyền, Thực Vật Rừng, Nxb Nông nghiệp, Hà Nội, 2000, tr. 149-150.[19] Xia N. H., Myricaceae in Hu Q. M. & Wu D. L. (eds.), Flora of Hong Kong Vol. 1, Agriculture, Fisheries and Conservation Department, Hong Kong, 2007, pp. 125-126.[20] Nguyễn Sinh Khang, Bùi Hồng Quang, Vũ Tiến Chính, Nguyễn Tiến Hiệp, Nguyễn Quang Hiếu, Nguyễn Thành Sơn, Xia Nian He & Davidson Christopher, Myrica rubra (Lour.) Siebold & Zucc. (Myricaceae): A useful plant resource in Vietnam, Hội nghị Khoa học toàn quốc lần thứ 7 về Sinh thái và Tài nguyên sinh vật, Viện Sinh thái và Tài nguyên sinh vật, Nxb Nông nghiệp, Hà Nội, 2017, pp. 226-232. [21] Nguyễn Nghĩa Thìn, Các phương pháp nghiên cứu thực vật, Nxb. Đại học Quốc gia Hà Nội, Hà Nội, 2007.[22] Liesner R., Field Techniques Used by Missouri Botanical Garden, 2018, http://www.mobot.org/MOBOT/molib/fieldtechbook/welcome.shtml [23] Bộ Khoa học và Công nghệ, Tiêu chuẩn Việt Nam TCVN 7538-2:2005 (ISO 10381 - 2 : 2002) về Chất lượng đất - Lấy mẫu - Phần 2: Hướng dẫn kỹ thuật lấy mẫu.[24] Phạm Hoàng Hộ, Cây cỏ Việt Nam, tập 1, Nxb Trẻ, TP. Hồ Chí Minh, 1999.[25] Phạm Hoàng Hộ, Cây cỏ Việt Nam, tập 2, Nxb Trẻ, TP. Hồ Chí Minh, 2003.[26] Phạm Hoàng Hộ, Cây cỏ Việt Nam, tập 3, Nxb Trẻ, TP. Hồ Chí Minh, 2000.[27] http://www.efloras.org/flora_page.aspx?flora_id=2 [28] http://www.theplantlist.org/[29] http://www.iucnredlist.org/ [30] Bộ Khoa học và Công nghệ, Viện Khoa học và Công nghệ Việt Nam, Sách Đỏ Việt Nam. Phần II: Thực vật, Nxb. Khoa học Tự nhiên và Công nghệ, Hà Nội, 2007, 612 tr.[31] Nguyễn Khánh Vân, Nguyễn Thị Hiền, Phan Kế Lộc và Nguyễn Tiến Hiệp, Các biểu đồ sinh khí hậu Việt Nam, Nxb. Đại học Quốc gia Hà Nội, 2000, tr. 45, 48, 120, 121.[32] Averyanov L. V., Lộc P. K., Hiệp N. T. & Harder D. K., Phytogeographic Review of Vietnam and Adjacent Areas of Eastern Indochina, Komarovia, 3, 2003, pp. 1-83.[33] Tsujino R. & Yumoto T., Topography-specific seed dispersal by Japanese macaques in a lowland forest on Yakushima Island, Japan, Journal of Animal Ecology, 78, 2009, pp. 119-125.[34] Đỗ Đình Sâm, Ngô Đình Quế, Nguyễn Tử Siêm và Nguyễn Ngọc Bình, Cẩm nang ngành Lâm nghiệp, Chương Đất và Dinh dưỡng đất, Bộ NN&PTNT, Chương trình hỗ trợ ngành Lâm nghiệp và đối tác, 2006, 143 tr.[35] Li Z. L., Zhang S. L. & Chen D. M., Red bayberry (Myrica rubra Sieb. & Zucc.): A valuable evergreen tree fruit for tropical and subtropical areas, Acta Horticulture 321, 1992, pp.112-121.[36] Sasakawa H., 1995: Effect of Frankia Inoculation on Growth and Nitrogen-Fixing Activity of Myrica rubra Seedlings Prepared Aseptically, Soil Science and Plant Nutrition 41(4): 691-698.[37] Tian X. R., Shu L. F. & He Q. T., Selection of fire-resistant Tree Species for Southwestern China, Forestry Studies in China, 3(2), 2001, pp. 32-38.[38] Deng C. N., Pan X. M., Zhang H. Y. & Pan X. L., Fire-resistance of six tree species to fire probed by chlorophyll fluorescence, Journal of Food, Agriculture & Environment, 10(2), 2012, pp. 1329-1333.[39] Nguyễn Tiến Bân (Chủ biên), Danh lục các loài Thực vật Việt Nam, tập 2, Nxb. Nông nghiệp, 2003, 1203 tr.[40] Nguyễn Tiến Bân (Chủ biên), Danh lục các loài Thực vật Việt Nam, tập 3, Nxb. Nông nghiệp, 2005, 1248 tr.

Graphene-based composites have received a great deal of attention in recent year because the presence of graphene can enhance the conductivity, strength of bulk materials and help create composites with superior qualities. Moreover, the incorporation of metal oxide nanoparticles such as Fe3O4 can improve the catalytic efficiency of composite material. In this work, we have synthesized a composite material with the combination of reduced graphene oxide (rGO), and Fe3O4 modified tissue-paper (mGO-PP) via a simple hydrothermal method, which improved the removal efficiency of the of methylene blue (MB) in water. MB blue is used as the model of contaminant to evaluate the catalytic efficiency of synthesized material by using a Fenton-like reaction. The obtained materials were characterized by SEM, XRD. The removal of materials with methylene blue is investigated by UV-VIS spectroscopy, and the result shows that mGO-PP composite is the potential composite for the color removed which has the removal efficiency reaching 65% in acetate buffer pH = 3 with the optimal time is 7 h. Keywords Graphene-based composite, methylene blue, Fenton-like reaction. References [1] Ma Joshi, Rue Bansal, Reng Purwar, Colour removal from textile effluents, Indian Journal of Fibre & Textile Research, 29 (2004) 239-259 http://nopr.niscair.res.in/handle/123456789/24631.[2] Kannan Nagar, Sundaram Mariappan, Kinetics and mechanism of removal of methylene blue by adsorption on various carbons-a comparative study, Dyes and pigments, 51 (2001) 25-40 https://doi.org/10.1016/S0143-7208(01)00056-0.[3] K Rastogi, J. N Sahu, B. C Meikap, M. N Biswas, Removal of methylene blue from wastewater using fly ash as an adsorbent by hydrocyclone, Journal of hazardous materials, 158 (2008) 531-540.https://doi.org/10.1016/j.jhazmat.2008.01. 105.[4] Qin Qingdong, Ma Jun, Liu Ke, Adsorption of anionic dyes on ammonium-functionalized MCM-41, Journal of Hazardous Materials, 162 (2009) 133-139 https://doi.org/10.1016/j.jhazmat. 2008.05.016.[5] Mui Muruganandham, Rps Suri, Sh Jafari, Mao Sillanpää, Lee Gang-Juan, Jaj Wu, Muo Swaminathan, Recent developments in homogeneous advanced oxidation processes for water and wastewater treatment, International Journal of Photoenergy, 2014 (2014). http://dx. doi.org/10.1155/2014/821674.[6] Herney Ramirez, Vicente Miguel , Madeira Luis Heterogeneous photo-Fenton oxidation with pillared clay-based catalysts for wastewater treatment: a review, Applied Catalysis B: Environmental, 98 (2010) 10-26 https://doi.org/ 10.1016/j.apcatb.2010.05.004.[7] Guo Rong, Jiao Tifeng, Li Ruifei, Chen Yan, Guo Wanchun, Zhang Lexin, Zhou Jingxin, Zhang Qingrui, Peng Qiuming, Sandwiched Fe3O4/carboxylate graphene oxide nanostructures constructed by layer-by-layer assembly for highly efficient and magnetically recyclable dye removal, ACS Sustainable Chemistry & Engineering, 6 (2017) 1279-1288 https://doi.org/10.1021/acssuschemeng.7b03635.[8] Sun Chao, Yang Sheng-Tao, Gao Zhenjie, Yang Shengnan, Yilihamu Ailimire, Ma Qiang, Zhao Ru-Song, Xue Fumin, Fe3O4/TiO2/reduced graphene oxide composites as highly efficient Fenton-like catalyst for the decoloration of methylene blue, Materials Chemistry and Physics, 223 (2019) 751-757 https://doi.org/ 10.1016/j.matchemphys.2018.11.056.[9] Guo Hui, Ma Xinfeng, Wang Chubei, Zhou Jianwei, Huang Jianxin, Wang Zijin, Sulfhydryl-Functionalized Reduced Graphene Oxide and Adsorption of Methylene Blue, Environmental Engineering Science, 36 (2019) 81-89 https://doi. org/10.1089/ees.2018.0157.[10] Zhao Lianqin, Yang Sheng-Tao, Feng Shicheng, Ma Qiang, Peng Xiaoling, Wu Deyi, Preparation and application of carboxylated graphene oxide sponge in dye removal, International journal of environmental research and public health, 14 (2017) 1301 https://doi.org/10.3390/ijerph14111301.[11] Yu Dandan, Wang Hua, Yang Jie, Niu Zhiqiang, Lu Huiting, Yang Yun, Cheng Liwei, Guo Lin, Dye wastewater cleanup by graphene composite paper for tailorable supercapacitors, ACS applied materials & interfaces, 9 (2017) 21298-21306 https://doi.org/10.1021/acsami.7b05318.[12] Wang Hou, Yuan Xingzhong, Wu Yan, Huang Huajun, Peng Xin, Zeng Guangming, Zhong Hua, Liang Jie, Ren MiaoMiao, Graphene-based materials: fabrication, characterization and application for the decontamination of wastewater and wastegas and hydrogen storage/generation, Advances in Colloid and Interface Science, 195 (2013) 19-40 https://doi. org/10.1016/j.cis.2013.03.009.[13] Marcano Daniela C, Kosynkin Dmitry V, Berlin Jacob M, Sinitskii Alexander, Sun Zhengzong, Slesarev Alexander, Alemany Lawrence B, Lu Wei, Tour James M, Improved synthesis of graphene oxide, ACS nano, 4 (2010) 4806-4814 https://doi.org/10.1021/nn1006368.[14] Zhang Jiali, Yang Haijun, Shen Guangxia, Cheng Ping, Zhang Jingyan, Guo Shouwu, Reduction of graphene oxide via L-ascorbic acid, Chemical Communications, 46 (2010) 1112-1114 http://doi. org/10.1039/B917705A [15] Gong Ming, Zhou Wu, Tsai Mon-Che, Zhou Jigang, Guan Mingyun, Lin Meng-Chang, Zhang Bo, Hu Yongfeng, Wang Di-Yan, Yang Jiang, Nanoscale nickel oxide/nickel heterostructures for active hydrogen evolution electrocatalysis, Nature communications, 5 (2014) 4695 https:// doi.org/10.1038/ncomms5695.[16] Wu Zhong-Shuai, Yang Shubin, Sun Yi, Parvez Khaled, Feng Xinliang, Müllen Klaus, 3D nitrogen-doped graphene aerogel-supported Fe3O4 nanoparticles as efficient electrocatalysts for the oxygen reduction reaction, Journal of the American Chemical Society, 134 (2012) 9082-9085 https://doi.org/10.1021/ja3030565.[17] Nguyen Son Truong, Nguyen Hoa Tien, Rinaldi Ali, Nguyen Nam Van, Fan Zeng, Duong Hai Minh, Morphology control and thermal stability of binderless-graphene aerogels from graphite for energy storage applications, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 414 (2012) 352-358 https://doi.org/ 10.1016/j.colsurfa.2012.08.048.[18] Deng Yang, Englehardt James D, Treatment of landfill leachate by the Fenton process, Water research, 40 (2006) 3683-3694 https://doi.org/ 10.1016/j.watres.2006.08.009.

Three compounds were isolated from the rhizome part of Canna edulis for the first time including liquiritigenin, methyl caffeate and uracil. Their structures were elucidated by spectroscopic methods as MS and NMR. Keywords Canna edulis Ker Gawl, liquiritigenin, methyl caffeate, uracil. References [1] T. H. Vu, Q. U. Le, Edible Canna (Canna edulis Ker), A Potential Crop for Vietnam Food Industry, International Journal of Botany Studies, Vol. 4, No. 4, 2019, pp. 58–59.[2] N. Tanakar, The Utilization of Edible Canna Plants in Southeastern Asia and Southern China, Economic Botany, Vol. 58, No. 1, 2004, 112–114.[3] A. S. A. Snafi, Bioactive Components and Pharmacological Effects of Canna indica - an Overview, International Journal of Pharmacology and Toxicology, Vol. 5, No. 2, 2015, pp. 71–75.[4] X. J. Zhang, Z. W. Wang, Q. Mi, Phenolic Compounds from Canna edulis Ker Residue and Their Antioxidant Activity, LWT - Food Science Technology, Vol. 44, No. 10, 2011, pp. 2091–2096, https://doi.org/10.1016/j.lwt.2011.05.021. [5] F. Xie, S. Gong, W. Zhang, J. Wu, Z. Wang, Potential of Lignin from Canna edulis Ker Residue in The Inhibition of α-d-glucosidase: Kinetics and Interaction Mechanism Merging with Docking Simulation, International Journal of Biology and Macromolecules, Vol. 95, 2017, pp. 592–602, https://doi.org/10.1016/j.ijbiomac.2016.11.100.[6] J. Zhang, Z. W. Wang, Soluble Dietary Fiber from Canna edulis Ker By-product and Its Physicochemical Properties, Carbohydrates Polymers, Vol. 92, No. 1, 2013, pp. 289–296, http:/doi.org/10.1016/j.carbpol.2012.09.067.[7] T. M. H. Nguyen, H. L. Le, T. T. Ha, B. H. Bui, N. T. Le, V. H. Nguyen, T. V. A. Nguyen, Inhibitory Effect on Human Platelet Aggregation and Coagulation and Antioxidant Activity of Canna edulis Ker Gawl Rhizhomes and Its Secondary Metabolites, Journal of Ethnopharmacology, Vol. 263, 2020, pp. 113-136, https:/doi.org/10.1016/j.jep.2020.113136.[8] T. A. Y. Diaa, M. A. Ramada, A. A. Khalifa, Acetophenones, a Chalcone, a Chromone and Flavonoids from Pancratium Maritimum, Phytochemistry, Vol. 49, No. 8, pp. 1998, pp. 2579-2583, http:/doi.org/10.1016/S003109422(98)00429-4. [9] W. Koji, Y. Osanai, T. Imaizumi, S. Kanno, M. Takeshita, M. Ishikawa, Inhibitory Effect of The Alkyl Side Chain of Caffeic Acid Analogues on Lipopolysaccharide-induced Nitric Oxide Production in RAW264.7 Macrophages, Bioorganic Med. Chem., Vol. 16, No. 16, 2008, pp. 7795–7803, https:/doi.org/10.1016/j.bmc.2008.07.006.[10] C. Y. Wang, L. Han, K. Kang, C. L. Shao, Y. X. Wei, C. J. Zheng, H. S Guan, Secondary Metabolites From Green Algae Ulva Pertusa, Chemistry of Natural Compounds Vol. 46, No. 5, 2010, pp. 828-830.[11] C. T. Inh, N. T. H. Van, P. M. Quan, T. T. Q. Trang, T. A. Vien, N. T. Thuy, D. T. Thao, New Diterpenoid Isolated from Medicinal Plant Euphorbia tithymaloides (P.), Vietnam J. Chem., Vol. 54, 2016, pp. 274-279, https:/doi.org/10.15625/0866-7144.2016-00304 (in Vietnamese).[12] Q. Y. Li, H. Liang, B. Wang, Z. Z. Zhao, Chemical Constituents of Momordica charantia L, Yao Xue Xue Bao, Vol. 44, No. 9, 2009, pp. 1014-1018.[13] V. T. Diep, L. T. Loan, N. T. Thu, T. T. Ha, N. M. Khoi, N. H. Tuan, D. T. Ha, Triterpen, Flavonoid and Pyrimidine Compounds from The Aerial Parts of Dregea volubilis, Journal of Medicinal Materials, Vol. 24, No. 6, 2019, pp. 329-332.[14] H. M. Eid, D. Vallerand, A. Muhammad, T. Durst, P. S. Haddad, L. C. Martineau, Structural Constraints and the Importance of Lipophilicity for the Mitochondrial Uncoupling Activity of Naturally Occurring Caffeic Acid Esters with Potential for the Treatment of Insulin Resistance, Biochemical Pharmacology, Vol. 79, No. 3, 2010, pp. 444–454, https:/doi.org/10.1016/j.bcp.2009.08.026.[15] K. Takahashi, Y. Yoshioka, E. Kato, S. Katsuki, O. Iida, K. Hosokawa, J. Kawabata, Methyl Caffeate as a Glucosidase Inhibitor from Solanum Torvum fruits and the Activity of Related Compounds, Bioscience, Biotechnology and Biochemistry, Vol. 74, No. 4, 2010, pp. 741–745, https:/doi.org/10.1271/bbb.9087.[16] S. M. Fiuza, C. Gomes, L. J. Teixeira, M. T. G. D. Cruz, M. N. Cordeiro, N. Milhazes, F. Borges, M. P. Marques, Phenolic Acid Derivatives with Potential Anticancer Properties, a Structure-Activity Relationship Study Part 1: Methyl, Propyl and Octyl Esters of Caffeic and Gallic Acids, Bioorgan Med Chem, Vol. 12, No. 13, 2004, pp. 3581-3589, https:/doi.org/10.1016/j.bmc.2004.04.026.[17] S. P. Lee, G. Jun, E. Yoon, S. Park, C. Yang, Inhibitory Effect of Methyl Caffeate on Fos-Jun-DNA Complex Formation and Suppression of Cancer Cell Growth, Bulletin of Korean Chemical Society, Vol. 22, No. 10, 2001, pp. 1131-1135.

Object segmentation is an important task which is widely employed in many computer vision applications such as object detection, tracking, recognition, and retrieval. It can be seen as a two-phase process: object detection and segmentation. Object segmentation becomes more challenging in case there is no prior knowledge about the object in the scene. In such conditions, visual attention analysis via saliency mapping may offer a mean to predict the object location by using visual contrast, local or global, to identify regions that draw strong attention in the image. However, in such situations as clutter background, highly varied object surface, or shadow, regular and salient object segmentation approaches based on a single image feature such as color or brightness have shown to be insufficient for the task. This work proposes a new salient object segmentation method which uses a depth map obtained from the input image for enhancing the accuracy of saliency mapping. A deep learning-based method is employed for depth map estimation. Our experiments showed that the proposed method outperforms other state-of-the-art object segmentation algorithms in terms of recall and precision. KeywordsSaliency map, Depth map, deep learning, object segmentation References[1] Itti, C. Koch, E. Niebur, A model of saliency-based visual attention for rapid scene analysis, IEEE Transactions on pattern analysis and machine intelligence 20(11) (1998) 1254-1259.[2] Goferman, L. Zelnik-Manor, A. Tal, Context-aware saliency detection, IEEE transactions on pattern analysis and machine intelligence 34(10) (2012) 1915-1926.[3] Kanan, M.H. Tong, L. Zhang, G.W. Cottrell, Sun: Top-down saliency using natural statistics, Visual cognition 17(6-7) (2009) 979-1003.[4] Liu, Z. Yuan, J. Sun, J. Wang, N. Zheng, X. Tang, H.-Y. Shum, Learning to detect a salient object, IEEE Transactions on Pattern analysis and machine intelligence 33(2) (2011) 353-367.[5] Perazzi, P. Krähenbühl, Y. Pritch, A. Hornung, Saliency filters: Contrast based filtering for salient region detection, in: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, IEEE, 2012, pp. 733-740.[6] M. Cheng, N.J. Mitra, X. Huang, P.H. Torr, S.M. Hu, Global contrast based salient region detection, IEEE Transactions on Pattern Analysis and Machine Intelligence 37(3) (2015) 569-582.[7] Borji, L. Itti, State-of-the-art in visual attention modeling, IEEE transactions on pattern analysis and machine intelligence 35(1) (2013) 185-207.[8] Simonyan, A. Vedaldi, A. Zisserman, Deep inside convolutional networks: Visualising image classification models and saliency maps, arXiv preprint arXiv:1312.6034.[9] Li, Y. Yu, Visual saliency based on multiscale deep features, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 5455-5463.[10] Liu, J. Han, Dhsnet: Deep hierarchical saliency network for salient object detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 678-686.[11] Achanta, S. Hemami, F. Estrada, S. Susstrunk, Frequency-tuned saliency detection model, CVPR: Proc IEEE, 2009, pp. 1597-604.Fu, J. Cheng, Z. Li, H. Lu, Saliency cuts: An automatic approach to object segmentation, in: Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, IEEE, 2008, pp. 1-4Borenstein, J. Malik, Shape guided object segmentation, in: Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, Vol. 1, IEEE, 2006, pp. 969-976.Jiang, J. Wang, Z. Yuan, T. Liu, N. Zheng, S. Li, Automatic salient object segmentation based on context and shape prior., in: BMVC. 6 (2011) 9.Ciptadi, T. Hermans, J.M. Rehg, An in depth view of saliency, Georgia Institute of Technology, 2013.Desingh, K.M. Krishna, D. Rajan, C. Jawahar, Depth really matters: Improving visual salient region detection with depth., in: BMVC, 2013.Li, J. Ye, Y. Ji, H. Ling, J. Yu, Saliency detection on light field, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014, pp. 2806-2813.Koch, S. Ullman, Shifts in selective visual attention: towards the underlying neural circuitry, in: Matters of intelligence, Springer, 1987, pp. 115-141.Laina, C. Rupprecht, V. Belagiannis, F. Tombari, N. Navab, Deeper depth prediction with fully convolutional residual networks, in: 3D Vision (3DV), 2016 Fourth International Conference on, IEEE, 2016, pp. 239-248.Bruce, J. Tsotsos, Saliency based on information maximization, in: Advances in neural information processing systems, 2006, pp. 155-162.Ren, X. Gong, L. Yu, W. Zhou, M. Ying Yang, Exploiting global priors for rgb-d saliency detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015, pp. 25-32.Fang, J. Wang, M. Narwaria, P. Le Callet, W. Lin, Saliency detection for stereoscopic images., IEEE Trans. Image Processing 23(6) (2014) 2625-2636.Hou, L. Zhang, Saliency detection: A spectral residual approach, in: Computer Vision and Pattern Recognition, 2007. CVPR’07. IEEE Conference on, IEEE, 2007, pp. 1-8.Guo, Q. Ma, L. Zhang, Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform, in: Computer vision and pattern recognition, 2008. cvpr 2008. ieee conference on, IEEE, 2008, pp. 1-8.Fang, W. Lin, B.S. Lee, C.T. Lau, Z. Chen, C.W. Lin, Bottom-up saliency detection model based on human visual sensitivity and amplitude spectrum, IEEE Transactions on Multimedia 14(1) (2012) 187-198.Lang, T.V. Nguyen, H. Katti, K. Yadati, M. Kankanhalli, S. Yan, Depth matters: Influence of depth cues on visual saliency, in: Computer vision-ECCV 2012, Springer, 2012, pp. 101-115.Zhang, G. Jiang, M. Yu, K. Chen, Stereoscopic visual attention model for 3d video, in: International Conference on Multimedia Modeling, Springer, 2010, pp. 314-324.Wang, M.P. Da Silva, P. Le Callet, V. Ricordel, Computational model of stereoscopic 3d visual saliency, IEEE Transactions on Image Processing 22(6) (2013) 2151-2165.Peng, B. Li, W. Xiong, W. Hu, R. Ji, Rgbd salient object detection: A benchmark and algorithms, in: European Conference on Computer Vision (ECCV), 2014, pp. 92-109.Wu, L. Duan, L. Kong, Rgb-d salient object detection via feature fusion and multi-scale enhancement, in: CCF Chinese Conference on Computer Vision, Springer, 2015, pp. 359-368.Xue, Y. Gu, Y. Li, J. Yang, Rgb-d saliency detection via mutual guided manifold ranking, in: Image Processing (ICIP), 2015 IEEE International Conference on, IEEE, 2015, pp. 666-670.Katz, A. Adler, Depth camera based on structured light and stereo vision, uS Patent App. 12/877,595 (Mar. 8 2012).Chatterjee, G. Molina, D. Lelescu, Systems and methods for determining depth from multiple views of a scene that include aliasing using hypothesized fusion, uS Patent App. 13/623,091 (Mar. 21 2013).Matthies, T. Kanade, R. Szeliski, Kalman filter-based algorithms for estimating depth from image sequences, International Journal of Computer Vision 3(3) (1989) 209-238.Y. Schechner, N. Kiryati, Depth from defocus vs. stereo: How different really are they?, International Journal of Computer Vision 39(2) (2000) 141-162.Delage, H. Lee, A.Y. Ng, A dynamic bayesian network model for autonomous 3d reconstruction from a single indoor image, in: Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, Vol. 2, IEEE, 2006, pp. 2418-2428.Saxena, M. Sun, A.Y. Ng, Make3d: Learning 3d scene structure from a single still image, IEEE transactions on pattern analysis and machine intelligence 31(5) (2009) 824-840.Hedau, D. Hoiem, D. Forsyth, Recovering the spatial layout of cluttered rooms, in: Computer vision, 2009 IEEE 12th international conference on, IEEE, 2009, pp. 1849-1856.Liu, S. Gould, D. Koller, Single image depth estimation from predicted semantic labels, in: Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, IEEE, 2010, pp. 1253-1260.Ladicky, J. Shi, M. Pollefeys, Pulling things out of perspective, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014, pp. 89-96.K. Nathan Silberman, Derek Hoiem, R. Fergus, Indoor segmentation and support inference from rgbd images, in: ECCV, 2012.Liu, J. Yuen, A. Torralba, Sift flow: Dense correspondence across scenes and its applications, IEEE transactions on pattern analysis and machine intelligence 33(5) (2011) 978-994.Konrad, M. Wang, P. Ishwar, 2d-to-3d image conversion by learning depth from examples, in: Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on, IEEE, 2012, pp. 16-22.Liu, C. Shen, G. Lin, Deep convolutional neural fields for depth estimation from a single image, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 5162-5170.Wang, X. Shen, Z. Lin, S. Cohen, B. Price, A.L. Yuille, Towards unified depth and semantic prediction from a single image, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 2800-2809.Geiger, P. Lenz, C. Stiller, R. Urtasun, Vision meets robotics: The kitti dataset, International Journal of Robotics Research (IJRR).Achanta, S. Süsstrunk, Saliency detection using maximum symmetric surround, in: Image processing (ICIP), 2010 17th IEEE international conference on, IEEE, 2010, pp. 2653-2656.E. Rahtu, J. Kannala, M. Salo, J. Heikkilä, Segmenting salient objects from images and videos, in: Computer Vision-ECCV 2010, Springer, 2010, pp. 366-37.

Vitamin E (VitE) is a potent antioxidant and contributes as an apoptosis inhibitor by preventing apoptotic death by suppressing cell membrane scrambling with phosphatidylserine translocation and caspase activites. Fas ligand (FasL) is well known to induce cell apoptosis. Activation of phosphoinositide 3 kinase (PI3K) signalling is stimulated by VitE. The present study addressed the effects of VitE on survival of mouse dendritic cells (DCs) and signalling molecules underlying. To this end, mouse bone marrow cells were isolated and cultured to attain bone marrow-derived DCs (BMDCs). The cells were treated with FasL in the presence or absence of VitE. Western blotting and FACS analysis were performed to determine expression of signalling molecules and their involvement in DC apoptosis. As a result, FasL treatment resulted in activation of caspase 8 and an increased number of Annexin V+ cells, the effects were significantly suppressed when VitE was present in the cell culture. Importantly, the anti-apoptotic effects of VitE were abolished by using pharmacological inhibition of PI3K signaling with LY294002. Our results showed that VitE inhibited FasL-mediated DC apoptosis through PI3K signalling, the effect is expected to facilitate the survival of DCs and promote the immune response against pathogens. Keywords Caspase, Dendritic cell; Fas ligand; PI3K and vitamin E. References [1] J. Banchereau, R.M. Steinman, Dendritic cells and the control of immunity, Nature 392 (1998) 245-52.[2] E. Ingulli, A. Mondino, A. Khoruts, M.K. Jenkins, In vivo detection of dendritic cell antigen presentation to CD4(+) T cells, J Exp Med 185 (1997) 2133-41.[3] C. Yang, H.Z. Liu, Z.X. Fu, PEG-liposomal oxaliplatin induces apoptosis in human colorectal cancer cells via Fas/FasL and caspase-8, Cell Biol Int 36 (2012) 289-96.[4] Q.G. Yan, J.G. Shi, F. Zhang, Q.T. Zhao, X.W. Pang, R. Chen, P.Z. Hu, Q.L. Li, Z. Wang, G.S. Huang, Overexpression of CYP2E1 enhances sensitivity of hepG2 cells to fas-mediated cytotoxicity, Cancer Biol Ther 7 (2008) 1280-7.[5] A. Hamai, C. Richon, F. Meslin, F. Faure, A. Kauffmann, Y. Lecluse, A. Jalil, L. Larue, M.F. Avril, S. Chouaib, M. Mehrpour, Imatinib enhances human melanoma cell susceptibility to TRAIL-induced cell death: Relationship to Bcl-2 family and caspase activation, Oncogene 25 (2006) 7618-34.[6] S. Lucken-Ardjomande, J.C. Martinou, Regulation of Bcl-2 proteins and of the permeability of the outer mitochondrial membrane, C R Biol 328 (2005) 616-31.[7] M. Rescigno, V. Piguet, B. Valzasina, S. Lens, R. Zubler, L. French, V. Kindler, J. Tschopp, P. Ricciardi-Castagnoli, Fas engagement induces the maturation of dendritic cells (DCs), the release of interleukin (IL)-1beta, and the production of interferon gamma in the absence of IL-12 during DC-T cell cognate interaction: a new role for Fas ligand in inflammatory responses, J Exp Med 192 (2000) 1661-8.[8] C. Qian, L. Qian, Y. Yu, H. An, Z. Guo, Y. Han, Y. Chen, Y. Bai, Q. Wang, X. Cao, Fas signal promotes the immunosuppressive function of regulatory dendritic cells via the ERK/beta-catenin pathway, J Biol Chem 288 (2013) 27825-35.[9] L. Bo, S. Jiang, Y. Xie, H. Kan, W. Song, J. Zhao, Effect of Vitamin E and Omega-3 Fatty Acids on Protecting Ambient PM2.5-Induced Inflammatory Response and Oxidative Stress in Vascular Endothelial Cells, PLoS One 11 (2016) e0152216.[10] K.S. Ahn, G. Sethi, K. Krishnan, B.B. Aggarwal, Gamma-tocotrienol inhibits nuclear factor-kappaB signaling pathway through inhibition of receptor-interacting protein and TAK1 leading to suppression of antiapoptotic gene products and potentiation of apoptosis, J Biol Chem 282 (2007) 809-20.[11] E. Pierpaoli, V. Viola, F. Pilolli, M. Piroddi, F. Galli, M. Provinciali, Gamma- and delta-tocotrienols exert a more potent anticancer effect than alpha-tocopheryl succinate on breast cancer cell lines irrespective of HER-2/neu expression, Life Sci 86 (2010) 668-75.[12] A.A. Albahrani, R.F. Greaves, Fat-Soluble Vitamins: Clinical Indications and Current Challenges for Chromatographic Measurement, Clin Biochem Rev 37 (2016) 27-47.[13] E. Shumilina, N. Zahir, N.T. Xuan, F. Lang, Phosphoinositide 3-kinase dependent regulation of Kv channels in dendritic cells, Cell Physiol Biochem 20 (2007) 801-8.[14] X. Jin, L. Song, X. Liu, M. Chen, Z. Li, L. Cheng, H. Ren, Protective efficacy of vitamins C and E on p,p'-DDT-induced cytotoxicity via the ROS-mediated mitochondrial pathway and NF-kappaB/FasL pathway, PLoS One 9 (2014) e113257.[15] B.C. Richardson, N.D. Lalwani, K.J. Johnson, R.M. Marks, Fas ligation triggers apoptosis in macrophages but not endothelial cells, Eur J Immunol 24 (1994) 2640-5.[16] J. Tschopp, M. Irmler, M. Thome, Inhibition of fas death signals by FLIPs, Curr Opin Immunol 10 (1998) 552-8.[17] J. Chung, Y.O. Yoon, J.S. Lee, T.K. Ha, S.M. Ryu, K.H. Kim, M.H. Jeong, T.R. Yoon, H.K. Kim, Inulin induces dendritic cells apoptosis through the caspase-dependent pathway and mitochondrial dysfunction, Biol Pharm Bull 34 (2011) 495-500.[18] S. Kreuz, D. Siegmund, J.J. Rumpf, D. Samel, M. Leverkus, O. Janssen, G. Hacker, O. Dittrich-Breiholz, M. Kracht, P. Scheurich, H. Wajant, NFkappaB activation by Fas is mediated through FADD, caspase-8, and RIP and is inhibited by FLIP, J Cell Biol 166 (2004) 369-80.[19] S. Buonocore, S. Van Meirvenne, F.X. Demoor, F. Paulart, K. Thielemans, M. Goldman, V. Flamand, Dendritic cells transduced with viral interleukin 10 or Fas ligand: no evidence for induction of allotolerance in vivo, Transplantation 73 (2002) S27-30.[20] D. Ashany, A. Savir, N. Bhardwaj, K.B. Elkon, Dendritic cells are resistant to apoptosis through the Fas (CD95/APO-1) pathway, J Immunol 163 (1999) 5303-11.[21] D. Ashany, X. Song, E. Lacy, J. Nikolic-Zugic, S.M. Friedman, K.B. Elkon, Th1 CD4+ lymphocytes delete activated macrophages through the Fas/APO-1 antigen pathway, Proc Natl Acad Sci U S A 92 (1995) 11225-9.[22] S. Qi, W. Fu, C. Wang, C. Liu, C. Quan, A. Kourouma, M. Yan, T. Yu, P. Duan, K. Yang, BPA-induced apoptosis of rat Sertoli cells through Fas/FasL and JNKs/p38 MAPK pathways, Reprod Toxicol 50 (2014) 108-16.[23] L.P. Eberl, G. Egidy, F. Pinet, L. Juillerat-Jeanneret, Endothelin receptor blockade potentiates FasL-induced apoptosis in colon carcinoma cells via the protein kinase C-pathway, J Cardiovasc Pharmacol 36 (2000) S354-6.[24] N.T. Xuan, P.T. Trang, N. Van Phong, N.L. Toan, D.M. Trung, N.D. Bac, V.L. Nguyen, N.H. Hoang, N. Van Hai, Klotho sensitive regulation of dendritic cell functions by vitamin E, Biol Res 49 (2016) 45-54.[25] M. Baskiewicz-Masiuk, B. Machalinski, The role of the STAT5 proteins in the proliferation and apoptosis of the CML and AML cells, Eur J Haematol 72 (2004) 420-9.