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排序方式: 共有2210条查询结果,搜索用时 15 毫秒
51.
Juan Xing Pham Van Hung Stephen Symons Muhammad Shahin David Hatcher 《Sensing and Instrumentation for Food Quality and Safety》2009,3(4):211-218
Sprout damage (pre-harvest germination) in wheat results in highly deleterious effects on end-product quality. Alpha-amylase, the pre-dominant enzyme in the early stage of sprouting has the most damaging effect. This paper introduces a new method using a SWIR hyperspectral imaging system (1000–2500 nm) to predict the α-amylase activity of individual wheat kernels. Two classes of Canadian wheat, Canada Western Red Spring (CWRS) and Canada Western Amber Durum (CWAD), with samples of differing degrees of sprout damage were investigated. Individual kernels were first imaged with the hyperspectral imaging system and then the α-amylase activity of each kernel was determined analytically. Individual kernel α-amylase activity prediction was significant (R 2 0.54 and 0.73) for CWAD and CWRS, respectively using Partial Least Square regression on the hyperspectral data. A classification method is proposed to separate CWRS kernels with high α-amylase activity level from those with low α-amylase activity giving an accuracy of above 80%. This work shows that hyper/multi-spectral imaging techniques can be used for rapidly predicting the α-amylase activity of individual kernels, detecting sprouting at early stage. 相似文献
52.
Hai Pham 《Water research》2009,43(11):2936-8451
1,2-Dichloroethane (1,2-DCA) is a well-known recalcitrant groundwater contaminant. New environment-friendly approaches for the removal of 1,2-DCA that does not bring about volatilization of the compound are required. In this study, different anodophilic consortia enriched in microbial fuel cells (MFCs) operated under airtight conditions were shown to effectively degrade 1,2-DCA (up to 102 mg per liter reactor volume per day), while concomitantly generating a current. An anodophilic consortium previously enriched with acetate as the electron donor changed its composition at the rate of 48% per week and increased its richness (Rr) 3-fold, upon adapting to 1,2-DCA as the new electron donor. After being stable, during 1 month of operation, it removed up to 95% of the 1,2-DCA amount in the medium in the first 2 weeks, while converting 43 ± 4% of electrons available from the removal to electricity. A natural consortium from a 1,2-DCA contaminated site changed its composition at the rate of 9% per week and increased its Rr 2-fold, upon adapting to the MFC anode conditions with 1,2-DCA as the electron donor. After being stable, during 1 month of operation, it removed up to 85% of the 1,2-DCA amount in the medium in the first 2 weeks and the coulombic efficiency was 25 ± 4%. The operation of the MFCs under closed circuit conditions resulted in higher 1,2-DCA removal rates than the operation under open circuit conditions, indicating that bioelectrochemical activities enhanced the removal of 1,2-DCA in the MFC anode. The production of ethylene glycol, acetate and carbon dioxide indicated that the anodophilic bacteria oxidatively metabolized 1,2-DCA, probably by means of a hydrolysis-based pathway. The results show that MFCs can be potentially used as a practically convenient technology for the biological removal of 1,2-DCA. 相似文献
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Motohiko Umeyama Duc Hoang Nguyen Cat Vu Minh Xuan Roanh Le Satoshi Motani 《Water Resources Management》2014,28(12):3937-3955
Despite many previous investigations, there is no theoretically justifiable equation to determine the freshwater discharge, tidal velocity, and salinity in a complex estuary that contains several branches. In this study, the longitudinal distributions of freshwater and salinity concentration in multi-branched estuaries are investigated using a mathematical model, considering the energy balance by frictional head loss and the salt balance by diffusion and advection in a one-dimensional steady-state condition. We attempt to obtain the time-mean freshwater discharge rate quantitatively at a junction where the main flow separates into two branches. The salinity distribution along each branch is calculated by following the dispersion coefficient equation previously proposed for a single estuary. The salinity field is divided into the near-coast region and the upstream region, because in each segment the inland velocity varies according to the tidal flux. For computing the tidal velocity, we propose the Burgers equation and the Hoph-Cole transformation. The theoretical results obtained by these equations were found to be in good agreement with a set of observed data in the Red River estuary system. 相似文献
56.
Jean -Pierre Monthéard Bernard Boinon Driss Ainad-Tabet Q. T. Pham 《Polymer Bulletin》1986,16(1):59-66
Summary To study the influence of dipolar moments on the permittivity of polymers, three isomeric polymers ortho, meta and para polymethoxystyrenes have been synthesized. Physical properties and NMR studies1H and13C are described. 相似文献
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58.
Duy Binh Tran;Nguyen Khoi Nguyen Le;Minh Tue Duong;Kamo Yuna;L. A. Tuan Pham;Q. C. Thanh Nguyen;Yingmanee Tragoolpua;Thida Kaewkod;Kaeko Kamei; 《Food Science & Nutrition》2024,12(8):5722-5733
Kombucha tea is a traditional beverage originating from China and has recently gained popularity worldwide. Kombucha tea is produced by the fermentation of tea leaves and is characterized by its beneficial properties and varied chemical content produced during the fermentation process, which includes organic acids, amino acids, vitamins, minerals, and other biologically active compounds. Kombucha tea is often consumed as a health drink to combat obesity and inflammation; however, the bioactive effects of kombucha tea have not been thoroughly researched. In this study, we reveal the underlying mechanisms of the beneficial properties of kombucha tea and how they protect against obesity and inflammation by studying Drosophila models. We established an inflammatory Drosophila model by knocking down the lipid storage droplet-1 gene, a human perilipin-1 ortholog. In this model, dysfunction of lipid storage droplet-1 induces inflammation by enhancing the infiltration of hemocytes into adipose tissues, increasing reactive oxygen species production, elevating levels of proinflammatory cytokines, and promoting the differentiation of hemocytes into macrophages. These processes are regulated by the c-Jun N-terminal Kinase (JNK) pathway. Using this unique Drosophila model that mimics mammalian inflammation, we verified the beneficial effects of kombucha tea on reducing tissue inflammation. Our data confirms that kombucha tea effectively improves inflammatory conditions by suppressing the expression of cytokines and proinflammatory responses induced by lipid storage droplet-1 dysfunction. It was found that kombucha tea consumption alleviated the production of reactive oxygen species and activated the JNK signaling pathway, signifying its potential as an anti-inflammatory agent against systemic inflammatory responses connected to the JNK pathway. Kombucha tea reduced triglyceride accumulation by increasing the activity of Brummer (a lipase), thereby promoting lipolysis in third-instar larvae. Therefore, kombucha tea could be developed as a novel, functional beverage to protect against obesity and inflammation. Our study also highlights the potential use of this innovative model to evaluate the effects of bioactive compounds derived from natural products. 相似文献
59.
Ming Tian Taylor Ticer Qikun Wang Sierra Walker Anthony Pham Annie Suh Sara Busatto Irina Davidovich Rawan Al‐Kharboosh Laura Lewis‐Tuffin Baoan Ji Alfredo Quinones‐Hinojosa Yeshayahu Talmon Shane Shapiro Felix Rückert Joy Wolfram 《Small (Weinheim an der Bergstrasse, Germany)》2020,16(10)
Extracellular vesicles secreted from adipose‐derived mesenchymal stem cells (ADSCs) have therapeutic effects in inflammatory diseases. However, production of extracellular vesicles (EVs) from ADSCs is costly, inefficient, and time consuming. The anti‐inflammatory properties of adipose tissue‐derived EVs and other biogenic nanoparticles have not been explored. In this study, biogenic nanoparticles are obtained directly from lipoaspirate, an easily accessible and abundant source of biological material. Compared to ADSC‐EVs, lipoaspirate nanoparticles (Lipo‐NPs) take less time to process (hours compared to months) and cost less to produce (clinical‐grade cell culture facilities are not required). The physicochemical characteristics and anti‐inflammatory properties of Lipo‐NPs are evaluated and compared to those of patient‐matched ADSC‐EVs. Moreover, guanabenz loading in Lipo‐NPs is evaluated for enhanced anti‐inflammatory effects. Apolipoprotein E and glycerolipids are enriched in Lipo‐NPs compared to ADSC‐EVs. Additionally, the uptake of Lipo‐NPs in hepatocytes and macrophages is higher. Lipo‐NPs and ADSC‐EVs have comparable protective and anti‐inflammatory effects. Specifically, Lipo‐NPs reduce toll‐like receptor 4‐induced secretion of inflammatory cytokines in macrophages. Guanabenz‐loaded Lipo‐NPs further suppress inflammatory pathways, suggesting that this combination therapy can have promising applications for inflammatory diseases. 相似文献
60.
Breast cancer is the second most common cancer in women in the United States. With the revolution of the machine learning era, many researchers currently aim to find pathways and develop tools that may help to detect breast cancer early on in its development. We propose a novel generalized logistic dependent model with considerations of the dependence among selected biomarkers for breast cancer detection based on a set of nine biomarker predictors such as age, glucose, BMI, resistin, HOMA, MCP‐1, leptin, insulin, and adiponectin. Our research findings demonstrate that the proposed model has the potential to predict breast cancer in women just based on five biomarkers, ie, glucose, age, BMI, resistin, and MCP‐1. We also compare our model results to several other machine‐learning modeling approaches including SVM, logistic regression, random forest, and multiple regression analyses using various training data sets (60%, 70%, 80% of all data) and all the dataset. It shows that the inclusion of the dependence among those five predictors in the proposed model is worth the extra model complexity and effort for achieving a significant accuracy prediction level of breast cancer detection in women. Further work in broader validation of the conclusion of our study and exploring the ability for artificial intelligence (AI) to be able to bolster these predictions based on biomarkers are also discussed. 相似文献