|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Could wastewater analysis be a useful tool for China?——A review显示文摘Analysing wastewater samples is an innovative approach that overcomes many limitations of traditional surveys to identify and measure a range of chemicals that were consumed by or exposed to people living in a sewer catchment area. First conceptualised in 2001, much progress has been made to make wastewater analysis(WWA) a reliable and robust tool for measuring chemical consumption and/or exposure. At the moment, the most popular application of WWA, sometimes referred as sewage epidemiology, is to monitor the consumption of illicit drugs in communities around the globe, including China. The approach has been largely adopted by law enforcement agencies as a device to monitor the temporal and geographical patterns of drug consumption. In the future, the methodology can be extended to other chemicals including biomarkers of population health(e.g. environmental or oxidative stress biomarkers, lifestyle indicators or medications that are taken by different demographic groups) and pollutants that people are exposed to(e.g. polycyclic aromatic hydrocarbons,perfluorinated chemicals, and toxic pesticides). The extension of WWA to a huge range of chemicals may give rise to a field called sewage chemical-information mining(SCIM) with unexplored potentials. China has many densely populated cities with thousands of sewage treatment plants which are favourable for applying WWA/SCIM in order to help relevant authorities gather information about illicit drug consumption and population health status. However, there are some prerequisites and uncertainties of the methodology that should be addressed for SCIM to reach its full potential in China. | Jianfa Gao Jake O'Brien Foon Yin Lai Alexander L.N.van Nuijs Jun He Jochen F.Mueller Jingsha Xu Phong K.Thai | 2015 | Journal of Environmental Sciences2015，27，1： | 4 |
| 2 | The amazing potential of fungi:50 ways we can exploit fungi industrially显示文摘Fungi are an understudied,biotechnologically valuable group of organisms.Due to the immense range of habitats that fungi inhabit,and the consequent need to compete against a diverse array of other fungi,bacteria,and animals,fungi have developed numerous survival mechanisms.The unique attributes of fungi thus herald great promise for their application in biotechnology and industry.Moreover,fungi can be grown with relative ease,making production at scale viable.The search for fungal biodiversity,and the construction of a living fungi collection,both have incredible economic potential in locating organisms with novel industrial uses that will lead to novel products.This manuscript reviews fifty ways in which fungi can potentially be utilized as biotechnology.We provide notes and examples for each potential exploitation and give examples from our own work and the work of other notable researchers.We also provide a flow chart that can be used to convince funding bodies of the importance of fungi for biotechnological research and as potential products.Fungi have provided the world with penicillin,lovastatin,and other globally significant medicines,and they remain an untapped resource with enormous industrial potential. | Kevin D.Hyde Jianchu Xu Sylvie Rapior Rajesh Jeewon Saisamorn Lumyong Allen Grace T.Niego Pranami D.Abeywickrama Janith V.S.Aluthmuhandiram Rashika S.Brahamanage Siraprapa Brooks Amornrat Chaiyasen K.W.Thilini Chethana Putarak Chomnunti Clara Chepkirui Boontiya Chuankid Nimali I.de Silva Mingkwan Doilom Craig Faulds Eleni Gentekaki Venkat Gopalan Pattana Kakumyan Dulanjalee Harishchandra Hridya Hemachandran Sinang Hongsanan Anuruddha Karunarathna Samantha C.Karunarathna Sehroon Khan Jaturong Kumla Ruvishika S.Jayawardena Jian-Kui Liu Ningguo Liu Thatsanee Luangharn Allan Patrick G.Macabeo Diana S.Marasinghe Dan Meeks Peter E.Mortimer Peter Mueller Sadia Nadir Karaba N.Nataraja Sureeporn Nontachaiyapoom Meghan O’Brien Watsana Penkhrue Chayanard Phukhamsakda Uma Shaanker Ramanan Achala R.Rathnayaka Resurreccion B.Sadaba Birthe Sandargo Binu C.Samarakoon Danushka S.Tennakoon Ramamoorthy Siva Wasan Sriprom T.S.Suryanarayanan Kanaporn Sujarit Nakarin Suwannarach Thitipone Suwunwong Benjarong Thongbai Naritsada Thongklang Deping Wei S.Nuwanthika Wijesinghe Jake Winiski Jiye Yan Erandi Yasanthika Marc Stadler | 2019 | Fungal Diversity2019，，4： | 3 |
| 3 | Aggregates from mutant and wild-type alpha-synuclein proteins and NAC peptide induce apoptotic cell death in human neuroblastoma cells by formation of beta-sheet and amyloid-like filaments显示文摘 | El-Agnaf O M Jakes R Curran M D | 1998 | FEBS Letters1998，440，： | 1 |
| 4 | 显示文摘 | Ago M Jakes J EtRojas O J | 2013 | ACS Applied Materials In- terfaces2013，5，11： | 1 |
| 5 | Hemoprotozoa of freshwater turtles in queensland显示文摘 | Jakes K A O'Donoghue P Munro M | 2001 | Journal of Wildlife Dis- eases2001，37，1： | 1 |
| 6 | Thermomechanieal properties of lignin-based electrospun nanofibers and films reinforced with cellulose nanocrystals : A dynamic mechanical and nanoindentation study 显示文摘 | AGO M JAKES J E ROJAS O J | 2013 | ACS Applied Materials & Interfaces2013，5，11： | 1 |
| 7 | Prediction of impedance responses of protonic ceramic cells using artificial neural network tuned with the distribution of relaxation times显示文摘A deep-learning-based framework is proposed to predict the impedance response and underlying electrochemical behavior of the reversible protonic ceramic cell(PCC) across a wide variety of different operating conditions.Electrochemical impedance spectra(EIS) of PCCs were first acquired under a variety of opera ting conditions to provide a dataset containing 36 sets of EIS spectra for the model.An artificial neural network(ANN) was then trained to model the relationship between the cell operating condition and EIS response.Finally,ANN model-predicted EIS spectra were analyzed by the distribution of relaxation times(DRT) and compared to DRT spectra obtained from the experimental EIS data,enabling an assessment of the accumulative errors from the predicted EIS data vs the predicted DRT.We show that in certain cases,although the R^(2)of the predicted EIS curve may be> 0.98,the R^(2)of the predicted DRT may be as low as~0.3.This can lead to an inaccurate ANN prediction of the underlying time-resolved electrochemical response,although the apparent accuracy as evaluated from the EIS prediction may seem acceptable.After adjustment of the parameters of the ANN framework,the average R^(2)of the DRTs derived from the predicted EIS can be improved to 0.9667.Thus,we demonstrate that a properly tuned ANN model can be used as an effective tool to predict not only the EIS,but also the DRT of complex electrochemical systems. | Xuhao Liu Zilin Yan Junwei Wu Jake Huang Yifeng Zheng Neal PSullivan Ryan O'Hayre Zheng Zhong Zehua Pan | 2023 | Journal of Energy Chemistry2023，，3： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员