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Hiroyuki Yasui, Yasunori Matsuzaki, Ayumu Konno,
Published: 10 May 2021
Neuroscience, Volume 462, pp 328-336; doi:10.1016/j.neuroscience.2020.04.004

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, Jun Kunimatsu, Tomoki W. Suzuki, Masashi Kameda, Shogo Ohmae, Akiko Uematsu, Ryuji Takeya
Published: 10 May 2021
Neuroscience, Volume 462, pp 220-234; doi:10.1016/j.neuroscience.2020.04.039

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Li-Da Su, Fang-Xiao Xu, Xin-Tai Wang, Xin-Yu Cai,
Published: 10 May 2021
Neuroscience, Volume 462, pp 320-327; doi:10.1016/j.neuroscience.2020.05.028

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Heeyoun Park, Yukio Yamamoto,
Published: 10 May 2021
Neuroscience, Volume 462, pp 44-55; doi:10.1016/j.neuroscience.2020.05.036

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Meike E. van der Heijden,
Published: 10 May 2021
Neuroscience, Volume 462, pp 4-21; doi:10.1016/j.neuroscience.2020.06.010

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Published: 10 May 2021
Neuroscience, Volume 462, pp 191-204; doi:10.1016/j.neuroscience.2020.07.021

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Published: 10 May 2021
Neuroscience, Volume 462, pp 175-190; doi:10.1016/j.neuroscience.2020.08.026

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Rui Jiang, Shengnan Qian, , Ying Qin, Yujuan Wu, Jianxin Zou, Xiaoqin Zeng
Journal of Materials Science & Technology, Volume 72, pp 104-113; doi:10.1016/j.jmst.2020.08.041

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Jinya Soga, Masayuki Matsuyama, Hiroaki Miura, Stephen Highstein, Robert Baker,
Published: 10 May 2021
Neuroscience, Volume 462, pp 205-219; doi:10.1016/j.neuroscience.2020.09.016

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Liyuan Han, , , Xuemin Yin, Jiajia Sun, Hejun Li, Fengpei Zhang, Xinran Ren, Xi Wang
Journal of Materials Science & Technology, Volume 72, pp 154-161; doi:10.1016/j.jmst.2020.07.020

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Wen Zhang, , Chenguang Xu, Wenyu Lu, , Jiahu Ouyang, Yu Zhou
Journal of Materials Science & Technology, Volume 72, pp 23-28; doi:10.1016/j.jmst.2020.07.019

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, Anqiao Zhang, Jinmian Yue, Xudong Zhang, Yuanli Xu
Journal of Materials Science & Technology, Volume 72, pp 197-201; doi:10.1016/j.jmst.2020.07.042

Xudong Liu, , Ling Ding, Xiaoxiao Zhao, Panbo Liu, Tiehu Li
Journal of Materials Science & Technology, Volume 72, pp 93-103; doi:10.1016/j.jmst.2020.09.012

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Hao Liu, , Guifeng Fan, Yucong Ma, Hua Hao, Wen Zhang
Journal of Materials Science & Technology, Volume 72, pp 202-216; doi:10.1016/j.jmst.2020.08.064

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Peiru Yang, , Qianying Guo,
Journal of Materials Science & Technology, Volume 72, pp 162-171; doi:10.1016/j.jmst.2020.09.024

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Jinsook Kim,
Published: 10 May 2021
Neuroscience, Volume 462, pp 22-35; doi:10.1016/j.neuroscience.2020.10.008

Abstract:
Molecular layer interneurons (MLIs) play an important role in cerebellar information processing by controlling Purkinje cell (PC) activity via inhibitory synaptic transmission. A local MLI network, constructed from both chemical and electrical synapses, is organized into spatially structured clusters that amplify feedforward and lateral inhibition to shape the temporal and spatial patterns of PC activity. Several recent in vivo studies indicate that such MLI circuits contribute not only to sensorimotor information processing, but also to precise motor coordination and cognitive processes. Here, we review current understanding of the organization of MLI circuits and their roles in the function of the mammalian cerebellum.
, Deepa K. Ingawale
Published: 10 May 2021
Journal of Ethnopharmacology, Volume 271; doi:10.1016/j.jep.2020.113709

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Lei Chen, , Yujie Feng, Xiaoyu Xu, Xiaobo Luo, Zhaojie Zhang
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144335

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Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144262

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, Kathryn Proctor, Erika Castrignanò,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144360

Abstract:
This is the first study of broad range of chemical classes CECs conducted in the upper Wisla river catchment including the biggest WWTPs in this region and surface waters. The list of compounds is extensive and the paper provides, for the first time, better understanding of environmental burden from PCPCs in Poland. Cumulative contribution of hypertension pharmaceuticals, nonsteroidal anti-inflammatory drugs (NSAIDs) and lifestyle chemicals was 89% and 95% in wastewater influent, and 75% in wastewater effluent at both WWTPs. Significant removal efficiencies, exceeding 90%, were found for parabens, UV filters, NSAIDs, steroid estrogens, plasticizers, antibacterials/antibiotics, stimulants and metabolites and lifestyle chemicals. The comparison of the average mass loads of CECs between the influent and effluent, has shown that 27% and 29% of all detected CECs were removed by less than 50%. An increase of concentrations of CECs in the effluent was observed for 18% and 20% of all detected CECs in Kujawy and Plaszow WWTPs, respectively. Negative mass balances of fexofenadine, venlafaxine, o-desmethyltramadol, ketamine and temazepam were noted within WWTPs, which are a result of dissolution of persistent contaminants accumulated in aggregates and/or back-transformation or de-conjugation of metabolites into parent compounds. 44 CECs were detected in surface waters located upstream and downstream of the WWTPs. The concentrations of compounds were largely dependent on the dilution factor of WWTP discharge. The risk quotation (RQ) values for compounds present in surface waters were calculated in relation to their potential for bioaccumulation. Among compounds with high potential for bioaccumulation, with log KOW ≥ 4.5, diclofenac, atorvastatin and triclosan were found to be of high risk. Many CECs with high, moderate or even low environmental impact have shown high potential for bioaccumulation and should be considered as priority at the same risk level. Moreover, possible synergistic action is still of concern.
Lingmei Sun, Kai Liao,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144362

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Xiaoqing Jia, Liangbo Xie, Zhuang Li, , Runmian Ming, Qingyue Zhang, Xueyue Mi,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144368

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, Ahmed Abdeen, Maroua Jalouli, Afaf Abdelkader, Ameer Megahed, Abdullah Alkahtane, Rafa Almeer, Norah M. Alhoshani, Norah S. Al-Johani, Saad Alkahtani, et al.
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144781

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, Christina Kassara, Zoi Vrontisi, Aristides Moustakas
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144471

Abstract:
Wind energy is the leading renewable technology towards achieving climate goals, yet biodiversity trade-offs via land take are emerging. Thus, we are facing the paradox of impacting on biodiversity to combat climate change. We suggest a novel method of spatial planning that enhances windfarm sustainability: investments are prioritized in the most fragmented zones that lie outside the Natura 2000 network of protected areas. We showcase it in Greece, a biodiversity hotspot with a strong climate policy and land conflict between conservation and wind energy schemes. The analysis indicates that the suggested investment zone supports wind harnessing 1.5 times higher than the 2030 national goal, having only marginally lower (4%) wind speed. It performs well for the conservation of the annexed habitats and species of the two Nature Directives and it greatly overlaps with the Important Bird Areas (93%) and the roadless areas (80%) of Greece. It also greatly overlaps (82%–91%) with the exclusion zones suggested according to three sensitivity maps for bird conservation. Since land use change triggers biodiversity decline, we underline the necessity of such approaches for meeting both climate and biodiversity goals and call for a greater environmental policy convergence towards biodiversity conservation and no net land take.
Avinash Alagumalai, , Frank Hollmann,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144856

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Xiang Tang, Man Zhou, , Guangming Zeng, Rui Gong, Qiuxiang Xu, Biao Song, Zhaohui Yang, Yang Yang, Chengyun Zhou, et al.
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144470

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Chester G. Scotch, , James Constantz
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144367

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, M. Martínez-Martorell, S. Huete-Hernández, V.B. Aguilar-Pozo, J. Dosta, J.M. Chimenos
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144284

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, Stephan Hilgert, Johannes Alexander, Júlio César Rodrigues de Azevedo, Tobias Morck, Stephan Fuchs, Thomas Schwartz
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144526

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, Yi Zheng, Xiaoxiao Wen, Sabrina S. Smith, Javlon Nizomov, Jennifer Fishe, William R. Hogan, Elizabeth A. Shenkman, Jiang Bian
Science of The Total Environment, Volume 768, pp 144832-144832; doi:10.1016/j.scitotenv.2020.144832

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Jie Gao, Tianliang Zheng, , Hongchen Jiang
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144709

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Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144530

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Yeqi Du, Deshuang Yu, Xiaoxia Wang, Jianyuan Zhen, Chunxue Bi, Xiuzhen Gong,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144446

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, Paula Peixoto Assemany, Angélica Cássia De Oliveira Carneiro, Jéssica Ferreira, Maurino Magno De Jesus Júnior, Fábio De Ávila Rodrigues, Maria Lúcia Calijuri
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144480

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Chuanhua Li, Yutao Wang, , Hongjuan Cao, Wangping Li, Tonghua Wu
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144525

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Manupati Hemalatha, Uday Kiran, Santosh Kumar Kuncha, Harishankar Kopperi, C.G. Gokulan, ,
Science of The Total Environment, Volume 768, pp 144704-144704; doi:10.1016/j.scitotenv.2020.144704

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Prasanna Kumarathilaka, , Saman Seneweera, Yong Sik Ok
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144531

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Huaicheng Zhang, Shudi Zhao, , Kaiqin Bian, Shanqi Shen, Meng Tao, Peng Shi
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144450

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Richard J. Boothroyd, Richard D. Williams, Trevor B. Hoey, Pamela L.M. Tolentino, Xiao Yang
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144460

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, Saskia Knillmann, Oliver Kaske, Liseth C. Atencio, Lisa Bittner, Julia E. Albrecht, Astrid Götz, Ann-Katrin Fahl, Liza-Marie Beckers, Martin Krauss, et al.
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144456

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, Qianfang Meng, Xin Li, Yujie Yuan, Yuhui Peng, Xiaodong Li, Shuai Li, Ziqian Zhu, Ming Yan
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144534

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Yan Li, Luuk K. Koopal, , Alin Shen,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144858

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Yanhua Zheng, , Shuzhang Feng, Zhe Cai, Yang Shen, Chuanyou Ying, Xiaoyuan Wang, Qian Liu
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144520

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Xuefeng Xie, , Ming Zhu, Michael Meadows, Licai Sun, Tao Wu, Xinguo Bu, Yan Xu
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2021.144996

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Dan-Qi Wang, Chen-Hao Zhou, Ming Nie, Ji-Dong Gu,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2021.144993

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, Paolo Ciampi, Timea Katona, Matteo Censini, , Gian Piero Deidda, Giorgio Cassiani
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2021.144997

Abstract:
The characterization of contaminated sites is a serious issue that requires a number of techniques to be deployed in the field to reconstruct the geometry, hydraulic properties and state of contamination of the shallow subsurface, often at the hundreds of meter scale with metric resolution. Among the techniques that have been proposed to complement direct investigations (composed of drilling, sampling, and laboratory characterization) are geophysical methods, which can provide extensive spatial coverage both laterally and at depth with the required resolution. However, geophysical methods only measure physical properties that are indirectly related to contamination, and their correlation may be difficult to ascertain without direct ground truth. In this study, we present a successful example where the results of complex conductivity measurements conducted in an imaging framework are compared with direct evidence of subsoil contamination at a jet fuel impacted site. Thus, proving that a combination of direct and indirect investigations can be successfully used to image a site in its complex (potentially 3D) structure in order to build a reliable conceptual model of the site.
Jiafen Liao, Jiahang Li, Ziming Han, Guangze Lyu, A. Mark Ibekwe,
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2020.144458

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, Maria M. Uzelac, Sanja J. Armaković, Uroš Gašić, Dragana D. Četojević-Simin, Stevan Armaković
Science of The Total Environment, Volume 768; doi:10.1016/j.scitotenv.2021.144991

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