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Correction to: Measurement of particulate matter 2.5 in surgical smoke and its health hazards

Surgery today 2022年第9期52卷 1348-1349页

作者： Kae Okoshi Koya Hida Koichi Kinoshita Toshitaka Morishima Yoshie Nagai Yasuko Tomizawa Kyoko Yorozuya Takehiro Nishida Hisako Matsumoto Hiroshi Yamato Department of Surgery Japan Baptist Hospital 47 Yamonomoto-cho Kitashirakawa Sakyo-ku Kyoto 606-8273 Japan. kae_md@kuhp.kyoto-u.ac.jp. Research Center for Science Technology and Social Communication in Next Generation Doshisha University Kyotanabe Japan. kae_md@kuhp.kyoto-u.ac.jp. Department of Surgery Kyoto University Hospital Kyoto Japan. Department of Surgery Japan Baptist Hospital 47 Yamonomoto-cho Kitashirakawa Sakyo-ku Kyoto 606-8273 Japan. Cancer Control Center Osaka International Cancer Institute Osaka Japan. Department of Anesthesiology Kawasaki Municipal Ida Hospital Kawasaki Japan. Department of Cardiovascular Surgery Tokyo Women's Medical University Tokyo Japan. Department of Surgery Kawasaki Municipal Hospital Kawasaki Japan. Department of Anesthesiology Masuda Red Cross Hospital Masuda Japan. Department of Respiratory Medicine and Allergology Kindai University Hospital Osakasayama Japan. Department of Health Development Institute of Industrial Ecological Sciences University of Occupational and Environmental Health Japan Kitakyushu Japan.

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research On FOPLP Package of multi-chip Power Module

Research On FOPLP Package of multi-chip Power Module

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Electronics System-Integration Technology Conference, ESTC

作者： Jing Jiang Jia ren Huo Guan qiang Song Huaiyu Ye De Bo Liu Guoqi Zhang Jun Tao Jun Wang ACADEMY for ENGINEERING&TECHNOLOGY FUDAN UNIVERSITY Shanghai China Product Research and Development Wuxi Sky Chip Interconnection Technology CO. LTD shenzhen China Shenzhen Institute Of Wide-Bandgap Semiconductors Engineering Research Center of Integrated Circuits for Next-Generation Communications Ministry of Education Southern University of Science and Technology Shenzhen China Wuxi Sky Chip Interconnection Technology CO. LTD Wuxi China Shenzhen Institute Of Wide-Bandgap Semiconductors Electronic Components Technology and Materials Delft University of Technology Delft The Netherlands

ISBN: (数字)9781728162935

ISBN: (纸本)9781728162942

Power devices are developing for the small volume, high performance and modularization. With more and more application scenarios of Brushless Direct Current Motor (BLDC), MOSFET multi-chip module (MCM) is popular with people. However, the conventional wire Bonding and Copper clip welding technology struggles to meet the requirements for the excessive heat accumulation and complex logic problems in MCM. While the above problems can be well solved by using the new Fan out panel level packing(FOPLP) technology for QFN packaging of multi-chip. The traditional welding technology is used at the bottom of the chip, and the copper porous link is used at the top of the chip with low parasitic capacitance, inductance and low R dson in electrical performance. In respect to thermal management, the θ JC on the top of the chip can be reduced, which has the effect of double-sided heat dissipation. Top Layer interconnection technology is adopted in the packaging scheme, which can have complex circuit *** paper mainly describes the technical implementation of this packaging technology, adopting the finite element software to establish a three-dimensional model of a new type of FOPLP and wire welding packaging for MCM. The thermal resistance of different packaging schemes is calculated to confirm the advantages and disadvantages of different schemes by the way of thermal simulation, the internal temperature distribution of different packaging structures and the main influencing factors of the thermal resistance of packaging compared.

关键词： Heating systems Resistance Packaging Wires Thermal resistance Resistance heating Copper

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LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping

arXiv

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arXiv 2025年

作者： Schmidinger, Jonas Vogel, Sebastian Barkov, Viacheslav Pham, Anh-Duy Gebbers, Robin Tavakoli, Hamed Correa, Jose Tavares, Tiago R. Filippi, Patrick Jones, Edward J. Lukas, Vojtech Boenecke, Eric Ruehlmann, Joerg Schroeter, Ingmar Kramer, Eckart Paetzold, Stefan Kodaira, Masakazu Wadoux, Alexandre M.J.-C. Bragazza, Luca Metzger, Konrad Huang, Jingyi Valente, Domingos S.M. Safanelli, Jose L. Bottega, Eduardo L. Dalmolin, Ricardo S.D. Farkas, Csilla Steiger, Alexander Horst, Taciara Z. Ramirez-Lopez, Leonardo Scholten, Thomas Stumpf, Felix Rosso, Pablo Costa, Marcelo M. Zandonadi, Rodrigo S. Wetterlind, Johanna Atzmueller, Martin Osnabrück University Joint Lab Artificial Intelligence and Data Science Osnabrück Germany Department of Agromechatronics Potsdam Germany Piracicaba Brazil The University of Sydney Sydney Institute of Agriculture Sydney Australia Mendel University in Brno Department of Agrosystems and Bioclimatology Brno Czech Republic Leibniz Institute of Vegetable and Ornamental Crops Next Generation Horticultural Systems Grossbeeren Germany Eberswalde University for Sustainable Development Landscape Management and Nature Conservation Eberswalde Germany Soil Science and Soil Ecology Bonn Germany Tokyo University of Agriculture and Technology Institute of Agriculture Tokyo Japan LISAH Univ. Montpellier AgroParisTech INRAE IRD L'Institut Agro Montpellier France Agroscope Field-Crop Systems and Plant Nutrition Nyon Switzerland University of Wisconsin-Madison Department of Soil Science Madison United States Federal University of Viçosa Department of Agricultural Engineering Viçosa Brazil Woodwell Climate Research Center Falmouth United States Academic Coordination Santa Maria Brazil Soil Department Santa Maria Brazil Division of Environment and Natural Resources Aas Norway University of Rostock Chair of Geodesy and Geoinformatics Rostock Germany Federal Technological University of Paraná Dois Vizinhos Brazil BÜCHI Labortechnik AG Data Science Department Flawil Switzerland Imperial College London Imperial College Business School London United Kingdom University of Tübingen Department of Geosciences Tübingen Germany University of Tübingen DFG Cluster of Excellence Machine Learning for Science’ Germany Bern University of Applied Sciences Competence Center for Soils Zollikofen Switzerland Simulation and Data Science Müncheberg Germany Federal University of Jataí Institute of Agricultural Sciences Jatai Brazil Federal University of Mato Grosso Instute of Agricultural and Environmental Scinces Sinop Brazil Department of Soil and Environment Skara

Digital soil mapping (DSM) relies on a broad pool of statistical methods, yet determining the optimal method for a given context remains challenging and contentious. Benchmarking studies on multiple datasets are needed to reveal strengths and limitations of commonly used methods. Existing DSM studies usually rely on a single dataset with restricted access, leading to incomplete and potentially misleading conclusions. To address these issues, we introduce an open-access dataset collection called Precision Liming Soil Datasets (LimeSoDa). LimeSoDa consists of 31 field- and farm-scale datasets from various countries. Each dataset has three target soil properties: (1) soil organic matter or soil organic carbon, (2) clay content and (3) pH, alongside a set of features. Features are dataset-specific and were obtained by optical spectroscopy, proximal- and remote soil sensing. All datasets were aligned to a tabular format and are ready-to-use for modeling. We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. This comparison included multiple linear regression (MLR), support vector regression (SVR), categorical boosting (CatBoost) and random forest (RF). The results showed that although no single algorithm was universally superior, certain algorithms performed better in specific contexts. MLR and SVR performed better on high-dimensional spectral datasets, likely due to better compatibility with principal components. In contrast, CatBoost and RF exhibited considerably better performances when applied to datasets with a moderate number ( © 2025, CC BY-SA.

关键词： Adversarial machine learning

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Response to the letter

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Surgery today 2022年第9期52卷 1393-1394页

作者： Kae Okoshi Koya Hida Koichi Kinoshita Toshitaka Morishima Yoshie Nagai Yasuko Tomizawa Kyoko Yorozuya Takehiro Nishida Hisako Matsumoto Hiroshi Yamato Department of Surgery Japan Baptist Hospital 47 Yamanomoto-cho Kitashirakawa Sakyo-ku Kyoto 606-8273 Japan. kae_md@kuhp.kyoto-u.ac.jp. Research Center for Science Technology and Social Communication in Next Generation Doshisha University Kyotanabe Japan. kae_md@kuhp.kyoto-u.ac.jp. Department of Surgery Graduate School of Medicine Kyoto University Kyoto Japan. kae_md@kuhp.kyoto-u.ac.jp. Department of Surgery Graduate School of Medicine Kyoto University Kyoto Japan. Department of Surgery Japan Baptist Hospital 47 Yamanomoto-cho Kitashirakawa Sakyo-ku Kyoto 606-8273 Japan. Cancer Control Center Osaka International Cancer Institute Osaka Japan. Department of Anesthesiology Kawasaki Municipal Ida Hospital Kawasaki Japan. Department of Cardiovascular Surgery Tokyo Women's Medical University Tokyo Japan. Department of Surgery Kawasaki Municipal Hospital Kawasaki Japan. Department of Anesthesiology Masuda Red Cross Hospital Masuda Japan. Department of Respiratory Medicine and Allergology Kindai University Hospital Osakasayama Japan. Department of Health Development Institute of Industrial Ecological Sciences University of Occupational and Environmental Health Kitakyushu Japan.

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Author Correction: Impaired CD4+ T cell response in older adults is associated with reduced immunogenicity and reactogenicity of mRNA COVID-19 vaccination

Nature Aging

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Nature Aging 2023年 751页

作者： Norihide Jo Yoko Hamazaki Yu Hidaka Satoshi Morita Osamu Kikuchi Manabu Muto Masaru Fukahori Takeshi Sawada Masahiko Aoki Takako E. Nakajima Masaki Yamamoto Miki Nagao Department of Life Science Frontiers Center for iPS Cell Research and Application (CiRA) Kyoto University Kyoto Japan Alliance Laboratory for Advanced Medical Research Graduate school of Medicine Kyoto University Kyoto Japan Laboratory of Immunobiology Graduate school of Medicine Kyoto University Kyoto Japan Department of Biomedical Statistics and Bioinformatics Graduate School of Medicine Kyoto University Kyoto Japan Department of Therapeutic Oncology Graduate School of Medicine Kyoto University Kyoto Japan Clinical Bio-Resource Center Kyoto University Hospital Kyoto Japan Kyoto Innovation Center for Next Generation Clinical Trials and iPS Cell Therapy (Ki-CONNECT) Kyoto University Hospital Kyoto Japan Department of Early Clinical Development Graduate school of Medicine Kyoto University Kyoto Japan Department of Clinical Laboratory Medicine Graduate School of Medicine Kyoto University Kyoto Japan

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Enhancing global agricultural monitoring system for climate-smart agriculture

Climate Smart Agriculture

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Climate Smart Agriculture 2025年第1期2卷

作者： Le Yu Zhenrong Du Xiyu Li Jinhui Zheng Qiang Zhao Hui Wu Duoji weise Yuanzhen Yang Quan Zhang Xinyue Li Xiaorui Ma Xiaomeng Huang Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing China Ministry of Education Ecological Field Station for East Asian Migratory Birds Beijing China Tsinghua University (Department of Earth System Science)- Xi'an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping Beijing China School of Information and Communication Engineering Dalian University of Technology Dalian China Geothermal Geological Brigade Tibet Autonomous Region Geological and Mineral Exploration and Development Bureau Lhasa China Key Laboratory of Environment Change and Resources Use in Beibu Gulf Ministry of Education Nanning Normal University Nanning China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal University Nanning China

Global agricultural monitoring systems face unprecedented challenges due to intensifying climate change. This paper reviews the advancements in existing global agricultural monitoring systems, highlighting deficiencies in addressing extreme weather events, data integration, and real-time analysis. To overcome these limitations, we introduce the Earth System Model-Coupled Global Agricultural Monitoring System (ESM-GAMS), an advanced framework that combines satellite and near-surface remote sensing, artificial intelligence-driven modeling, supercomputing, and crop model to enhance the accuracy and timeliness of crop monitoring and yield predictions under diverse climate scenarios. By integrating multi-source remote sensing data, ESM-GAMS mitigates delays caused by satellite revisit cycles and weather interference, enabling near real-time monitoring with results available at hourly or minute-level intervals. Additionally, the system demonstrated high accuracy in yield simulations under extreme weather, with the improved WOFOST model achieving robust R 2 values ranging from 0.55 to 0.77, indicating its reliability in predicting yields across diverse conditions. ESM-GAMS not only enables detailed daily monitoring of crop growth, but also provides early-warning capabilities for extreme weather and its impact on prediction. By optimizing resource allocation, supporting climate resilience, and enabling global data computing, ESM-GAMS represents a further step toward achieving climate-smart agriculture.

关键词： Agricultural monitoring Earth system model Remote sensing Crop model

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Exploratory study for strengthening education sectors for responding to complexities due to NATECH (Natural-Hazard Triggered Technological disasters) disasters

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IOP Conference Series: Earth and Environmental Science 2021年第1期630卷

作者： Fatma Lestari Yasuhito Jibiki Dicky Pelupessy Fumihiko Imamura Agustino Zulys Abdul Kadir Debby Paramitasari Occupational Health & Safety Department Faculty of Public Health Universitas Indonesia Next Generation Volcano Researcher Development Program Graduate School of Science Tohoku University Faculty of Psychology Universitas Indonesia International Research Institute of Disaster Science Tohoku University Chemistry Department Faculty of Mathematics and Natural Science Universitas Indonesia Disaster Risk Reduction Center Universitas Indonesia Disaster Risk Reduction Center Universitas Indonesia Disaster Risk Reduction Center Universitas Indonesia Disaster Risk Reduction Center Universitas Indonesia

The city of Cilegon in Banten Province, Indonesia is selected as a site of this study. The city locates in the western edge of Java Islands and is known as one of the most famous and significant heavy industrial zones in Indonesia. Cilegon is potentially exposed both to natural and industrial hazards so that we can consider it as a suitable place for studying NATECH (NAtural-Hazard triggered TECHnological disasters) disaster situations. The Indonesian government indicates the presence of seismic gap in the Sunda Strait and the associated tsunami risk. Large-scale facilities of chemical, petrochemical, oil and gas industries stand in coastal areas in Cilegon. The industry and its surrounding communities can be affected by combination of the natural and industrial disasters. In Cilegon, we aim at strengthening capacity of the education section in the Cilegon city government and the school principals and teachers. Our preliminary implementation and survey reveal that knowledge and understanding of teachers are very limited. We will combine existing research findings from both of industrial accidents and tsunami, and develop educational materials.

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A syndromic neurodevelopmental disorder caused by rare variants in PPFIA3 (vol 111, pg 96, 2024)

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AMERICAN JOURNAL OF HUMAN GENETICS 2024年第4期11卷 805-805页

作者： Paul, Maimuna S. Michener, Sydney L. Pan, Hongling Chan, Hiuling Pfliger, Jessica M. Rosenfeld, Jill A. Lerma, Vanesa C. Tran, Alyssa Longley, Megan A. Lewis, Richard A. Weisz-Hubshman, Monika Bekheirnia, Mir Reza Bekheirnia, Nasim Massingham, Lauren Zech, Michael Wagner, Matias Engels, Hartmut Cremer, Kirsten Mangold, Elisabeth Peters, Sophia Trautmann, Jessica Perne, Claudia Mester, Jessica L. Sacoto, Maria J. Guillen Person, Richard McDonnell, Pamela P. Cohen, Stacey R. Lusk, Laina Cohen, Ana S. A. Le Pichon, Jean-Baptiste Pastinen, Tomi Zhou, Dihong Engleman, Kendra Racine, Caroline Faivre, Laurence Moutton, Sebastien Denomme-Pichon, Anne-Sophie Koh, Hyun Yong Poduri, Annapurna Bolton, Jeffrey Knopp, Cordula Suh, Dong Sun Julia Maier, Andrea Toosi, Mehran Beiraghi Karimiani, Ehsan Ghayoor Maroofian, Reza Schaefer, Gerald Bradley Ramakumaran, Vijayalakshmi Vasudevan, Pradeep Banos-Pinero, Benito Pagnamenta, Alistair T. Prasad, Chitra Osmond, Matthew Schuhmann, Sarah Vasileiou, Georgia Russ-Hall, Sophie Scheffer, Ingrid E. Carvill, Gemma L. Mefford, Heather Bacino, Carlos A. Lee, Brendan H. Chao, Hsiao-Tuan Department of Pediatrics Section of Neurology and Developmental Neuroscience Baylor College of Medicine Houston TX USA Jan and Dan Duncan Neurological Research Institute Texas Children’s Hospital Houston TX USA Cain Pediatric Neurology Research Foundation Laboratories Jan and Dan Duncan Neurological Research Institute Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Augustana College Rock Island IL USA Summer Undergraduate Research Training (SMART) Program Baylor College of Medicine Houston TX USA Graduate Program in Electrical and Computer Engineering Rice University Houston TX USA Department of Psychology University of Houston Houston TX USA Department of Ophthalmology Baylor College of Medicine Houston TX USA Renal Genetics Clinic Baylor College of Medicine Houston TX USA Rhode Island Hospital and Hasbro Children’s Hospital Providence RI USA Institute of Neurogenomics Helmholtz Zentrum München Munich Germany Institute of Human Genetics School of Medicine Technical University Munich Germany Institute for Advanced Study Technical University of Munich Garching Germany Division of Pediatric Neurology Developmental Neurology and Social Pediatrics Dr. von Hauner Children’s Hospital Munich Germany Institute of Human Genetics School of Medicine University Hospital Bonn University of Bonn Bonn Germany GeneDx Gaithersburg MD USA Epilepsy NeuroGenetics Initiative (ENGIN) Division of Neurology Children’s Hospital of Philadelphia Philadelphia PA USA Department of Neurology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Children’s Mercy Kansas City Genomic Medicine Center The University of Missouri-Kansas City (UMKC) School of Medicine Kansas City MO USA Department of Pediatrics Children’s Mercy Kansas City Kansas City MO USA Children’s Mercy Research Institute Kansas City MO USA Children’s Mercy Hospital Kansas City MO USA University Hospital Dijon Franc

PPFIA3 encodes the protein-tyrosine phosphatase, receptor-type, F-polypeptide-interacting-protein-alpha-3 (PPFIA3), which is a member of the LAR-protein-tyrosine phosphatase-interacting-protein (liprin) family involved in synapse formation and function, synaptic vesicle transport, and presynaptic active zone assembly. The protein structure and function are evolutionarily well conserved, but human diseases related to PPFIA3 dysfunction are not yet reported in OMIM. Here, we report 20 individuals with rare PPFIA3 variants (19 heterozygous and 1 compound heterozygous) presenting with developmental delay, intellectual disability, hypotonia, dysmorphisms, microcephaly or macrocephaly, autistic features, and epilepsy with reduced penetrance. Seventeen unique PPFIA3 variants were detected in 18 families. To determine the pathogenicity of PPFIA3 variants in vivo, we generated transgenic fruit flies producing either human wild-type (WT) PPFIA3 or five missense variants using GAL4-UAS targeted gene expression systems. In the fly overexpression assays, we found that the PPFIA3 variants in the region encoding the N-terminal coiled-coil domain exhibited stronger phenotypes compared to those affecting the C-terminal region. In the loss-of-function fly assay, we show that the homozygous loss of fly Liprin-α leads to embryonic lethality. This lethality is partially rescued by the expression of human PPFIA3 WT, suggesting human PPFIA3 function is partially conserved in the fly. However, two of the tested variants failed to rescue the lethality at the larval stage and one variant failed to rescue lethality at the adult stage. Altogether, the human and fruit fly data reveal that the rare PPFIA3 variants are dominant-negative loss-of-function alleles that perturb multiple developmental processes and synapse formation.

关键词： neurodevelopmental disorder synaptic protein active zone protein Mendelian phenotypes fruit flies

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Carbon-based printed strain sensor array and wireless measuring system for application to Structural Health Monitoring 7

Carbon-based printed strain sensor array and wireless measur...

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7th Asia-Pacific Workshop on Structural Health Monitoring, APWSHM 2018

作者： Zymelka, D. Togashi, K. Kobayashi, T. National Institute of Advanced Industrial Science and Technology Tsukuba Ibaraki305-8564 Japan NMEMS Technology Research Organization Tokyo101-0026 Japan Research and Development Center Next-Generation Electronics Department Dai Nippon Printing Co. Ltd. Chiba277-0871 Japan

ISBN: (纸本)9783000603594

We demonstrate a printed strain sensor array for applications to structural health monitoring (SHM). The unit sensors in the array were made of inexpensive carbon-based materials that were screen printed on a flexible thin substrate. The sensors were designed to operate at various temperatures so that they can be used in any season of the year. Each array was equipped with a specially designed wireless measuring system that enables an automated and remote strain measurements on the analyzed bridges. The strain analysis with the developed device was based on a comparative analysis of data registered by the unit sensors and their transformation into a strain distribution. The sensor arrays were attached to a highway bridge and their functioning was verified periodically along the last two years. Moreover, we demonstrate an experiment where short-term remote measurements were performed automatically every 30 min within several days. The collected data show that the sensors can accurately detect cracks and can withstand a continuous long-term exposure to various weather conditions and strains during normal traffic on highway bridges. © APWSHM 2018. All rights reserved.

关键词： Structural health monitoring

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Grimes's Music Video "Shinigami Eyes"

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JOURNAL OF POPULAR MUSIC STUDIES 2023年第3期35卷 32-60页

作者： Vernallis, Carol Paris, Cesare Gardner, Justin Woodiwiss, Aubrey Carol Vernallis’s monograph Experiencing Music Video: Aesthetics and Cultural Context (CUP 2004) is the first to articulate a theory of how music lyrics and image can be placed in relation as well as provide detailed analyses of individual videos. Her second Unruly Media: YouTube Music Video and the New Digital Cinema (OUP 2013) takes account of a new mediascape that is driven by intensified audiovisual relations. Her third The Media Swirl (Duke 4/14/23) further considers the contemporary landscape. She is co-editor of Cybermedia: Explorations in Science Sound and Vision and Transmedia Directors (Bloomsbury) and two Oxford Handbooks on audiovisuality. She’s adjunct professor in the department of Cultural Studies and Comparative Literature at the University of Minnesota. Justin Gardner is an Associate Professor in Psychology at Stanford where he heads the Gardner lab. He and his team use a combination of functional magnetic resonance imaging computational modeling and analysis and psychophysical measurements to study how neural activity in the human cortex creates our sense of visual perception. Of particular interest is the ways our brain mechanisms give rise to our remarkable cognitive feats such as selective attention and sensory inference. Gardner is also a member of BioX an affiliate of Institute for Human-Centered Artificial Intelligence (HAI) and a member of Wu Tsai Neurosciences Institute. Cesare Parise is a Senior Lecturer in Psychology at the University of Liverpool where he heads a lab devoted to multisensory perception. His current projects include the development of a model for fly vision that can be adapted to other creatures. Parise’s background is in experimental psychology. After earning his DPhil at Oxon he worked as a research scientist for the Max Planck Institute for Biological Cybernetics and the Center for Excellence in Cognitive Interaction Technologies. In 2016 he joined Facebook Reality Labs (now Meta Reality Labs) as a Primary Investigator in perception science wh

This article draws on recent findings in neuroscience to provide a close reading of Grimes's music video "Shinigami Eyes." It includes interviews with a neuroscientist who specializes in multisensory integration, a vision scientist, a color grader, and a media scholar. While multisensory integration is a burgeoning field, accessible texts and reviews are lacking. There haven't been analyses that apply the findings from the field of multisensory integration to real media objects. Drawing on neuroscience studies, this article explores the concept of Bayesian predictions (a viewer's experience of a present event weighted against previous experiences);the ways neuroscience explains color, size and placement, and emotion work;and processes such as the inverse effectiveness (when neurons boost both lower-res and higher-res signals, with the most perceptible often for sound), super-additive multisensory effects, the attentional blink, the ventriloquist effect, congruence and incongruity, memory, distractors, sound before image and vice versa, and other features. A conversation with the color grader for "Shinigami Eyes" helps fill things in. This article emerges from a belief that modules on neuroscience and industry studies can be incorporated as components of media study courses, and that neuroscience-informed analyses can facilitate interest and engagement with close readings.

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