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125th ASEE Annual Conference and Exposition

作者： Liu, Sin-Ning Cindy Lang, Cynthia K. Sandoval, Carolyn L. Bergman, Mindy Froyd, Jeffrey E. Industrial/Organizational Psychology Texas A and M University United States School Psychology PhD Program Texas A and M University United States Center for Teaching Excellence Texas A and M University United States Department of Psychology Texas A and M University United States Department of Engineering Education College of Engineering Ohio State University College Station United States

"Improving Student Experiences to Increase Student Engagement" (ISE-2) was awarded to Texas A&M University by the National Science Foundation, through EEC-engineering Diversity Activities. ISE-2 is a faculty development program focused on reducing implicit bias and increasing active learning, with the goals of (a) increasing student engagement, success, and retention, and (b) ultimately seeing greater increases for underrepresented minority (URM), women, and first-generation students. Ten faculty teaching first- and second-year engineering courses participated in the first cohort of ISE-2 in Summer 2017, which consisted of three workshops and six informal "coffee conversations". At the conclusion of the workshops, each faculty was tasked with completing a teaching plan for the Fall 2017 semester, to incorporate the strategies and knowledge from ISE-2 into the courses they plan to teach. Focus groups with the ISE-2 faculty were conducted in Fall 2017 to obtain feedback about the faculty development program. Classroom observations were conducted using environmental scans and the Classroom Observation Protocol for Undergraduate STEM (COPUS)1 to assess the classroom climate of faculty in the experimental (ISE-2) and control groups. Student surveys were also administered to students who were taught by ISE-2 faculty and control group faculty to assess student engagement and classroom climate. While the project is still ongoing, feedback from faculty regarding ISE-2 have been positive. © American Society for engineering Education, 2018.

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Tract Integrity Predicts Neurological Outcomes in Neonatal Hypoxic-Ischemic Encephalopathy

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Pediatrics & Neonatology 2025年

作者： Pei-Ling Tsai Yu-Chun Lo Yi-Shan Tsai Yea-Shwu Hwang Ting-Chun Lin Yao-Wen Liang Chen-En Huang Fu-Chun Hsu Yi-Fang Tu You-Yin Chen Institute of Allied Health Sciences College of Medicine National Cheng Kung University Tainan Taiwan PhD Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Medical Imaging National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan Taiwan Department of Occupational Therapy College of Medicine National Cheng Kung University Tainan Taiwan Department of Biomedical Engineering National Yang Ming Chiao Tung University Taipei Taiwan College of Medicine National Yang Ming Chiao Tung University Taipei Taiwan Department of Pediatrics National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan Taiwan Institute of Clinical Medicine College of Medicine National Cheng Kung University Tainan Taiwan Medical Device Innovation and Translation Center National Yang Ming Chiao Tung University Taipei Taiwan

Objective Early prognostication in infants with neonatal hypoxic-ischemic encephalopathy (HIE) is crucial for follow-up management. Alternations of microstructural integrity of neural fiber tracts in large-scale neural networks might predict neurological outcomes. Methods All consecutively-admitted patients with neonatal HIE from 2016 to 2020 were enrolled. Diffusion tensor imaging (DTI) tractography was performed at 4–7 days of age. Neurodevelopmental outcomes at 24 months of age were assessed with Bayley Scales of Infant Development, 3rd edition. Results A total of 62 HIE infants were enrolled, and 53 of these underwent DTI. Fractional anisotropy (FA) and mean diffusivity (MD) were measured to indicate the microstructural integrity of tracts, including the arcuate fasciculus, uncinate fasciculus, inferior fronto-occipital fasciculus, corticospinal tract (CST), and optic radiations (OR). Lower FA values of target tracts were associated with lower developmental scores at 24 months of age, particularly in the CST and OR (all P ≤ 0.003). The prognostic accuracy of FA values in CST surpassed that in the region of thalamus/basal ganglia (area under curves 0.839, 95% CI: 0.728–0.950 vs. 0.755, 95% CI: 0.583–0.928). Furthermore, the correlation between FA values in target tracts and developmental scores was most significant in infants with HIE stage III and this was not affected by therapeutic hypothermia. Conclusion Tract integrity in the CST and OR detected by DTI provides valuable insights for early prognostication in infants with HIE, regardless of therapeutic hypothermia.

关键词： neonatal hypoxic-ischemic encephalopathy diffusion tensor imaging tractography corticospinal tract optic radiations neurodevelopmental outcome

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Effects of temperature, proportion and organic loading rate on the performance of anaerobic digestion of food waste

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Biotechnology Reports 2020年 27卷 e00503页

作者： Blasius, Jandir Pereira Contrera, Ronan Cleber Maintinguer, Sandra Imaculada Alves de Castro, Marcus Cesar Avezum Graduate Program in Geosciences and Environment Institute of Geosciences and Exact Sciences São Paulo State University Júio de Mesquita Filho (UNESP) Av. 24-A Bela Vista Rio Claro 13506-900 SP CEP Brazil Hydraulic and Environmental Engineering Department (PhD) Escola Politécnica/ School of Engineering (EP) Universidade de São Paulo (USP) Av. Prof. Almeida Prado 83 trav. 2 Cidade Universitária São Paulo 05508-900 SP CEP Brazil Bioenergy Department Bioenergy Research Institute - Central Laboratory (IPBEN) - São Paulo State University: Júlio de Mesquita Filho (UNESP) (PhD) R. 10 2527 - Estádio Rio Claro 13500-230 SP Brazil University of Araraquara R. Voluntarios da Patria 1309 Araraquara 14801-320 SP Brazil

In Brazil, a significant amount of organic waste is produced in households and restaurants. This study thus aimed to determine the ideal conditions for generating methane from the treatment of household waste by anaerobic digestion, under mesophilic (37 °C) and thermophilic (55 °C) conditions, to determine the maximum organic loading rate (OLR) in the reactors, and to evaluate kinetic parameters by statistical models: Modified Gompertz, First-Order, Logistic and Transference functions. The experiments were conducted in anaerobic batch reactors. Different proportions of pre-prepared waste (PPW)/leftover waste (LW) were used: 100/0, 75/25, 50/50, 25/75, and 0/100 and different ORL: 0.15;0.30;0.45;0.60;and 0.90 g TVS (Total Volatile Solids).L⁻¹.d⁻¹. For both conditions, the optimal proportions of PPW/LW were 100/0 and 75/25 %. Under mesophilic condition, the best results were observed (869 mL of CH₄.g TVS⁻¹). The maximum organic load was 0.30 g TVS.L⁻¹.d⁻¹. The best data adjustment was performed by the Transference function. © 2020

关键词： Biochemical methane potential Kinetic models Leftover waste Organic waste treatment Pre-preparation waste

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Review of the use of mangrove forests in supporting the socio-economic life of fishing communities

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IOP Conference Series: Earth and Environmental Science 2020年第1期575卷

作者： Untari R Darma P Betaubun A A Arief PhD. Student on Agricultural System Graduate School Hasanuddin University South Sulawesi Indonesia Department of Agribusiness Faculty of Agriculture Universitas Musamus Papua Indonesia Agribusiness Study Program Faculty of Agriculture Hasanuddin University South Sulawesi Indonesia Department of civil Engineering Faculty of Engineering Universitas Musamus Papua Indonesia Socio Economic of Fisheries Study Program Faculty of Marine Science and Fisheries Hasanuddin University South Sulawesi Indonesia

Mangrove forests have an important function in human life that cannot be replaced by other functions. The existence of mangrove forests has six main functions, namely biological, ecological, physical, social, economic and chemical functions. This article discusses the description of mangrove forest management in meeting the needs of the economic and social functions of the fishing communities on the coast of Merauke Regency, Papua Province, which were reviewed descriptively using relevant literature studies. In terms of economic function, mangrove forests provide economic value for fishing communities because mangrove forests become habitat for crabs, fish and other marine biota that are captured and sold as the main source of family income. In addition, the use of mangrove forests by fishermen on the coast is used as firewood and building materials. The high utilization of mangrove forests by coastal communities that ignores ecological sustainability causes damage to mangrove forests that threatens the sustainability of ecological functions. Damage to mangrove forests in Merauke in the period 2000-2005 was recorded as wide as 2,416 ha while in the 2005-2010 period damage reached 2,233 ha of the total area of the Merauke mangrove forest which reached 216,001.95 Ha or 6.98% of the Merauke forest area. Based on this, the management of mangrove forest utilization needs to get more attention from various parties so that the ecological function of mangrove forests as a condition of sustainable development, especially for fishing communities on the coast, can be realized in Merauke Regency.

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Extending Formal Modeling for Resilient Systems Design

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Insight 2018年第3期21卷 34-41页

作者： Madni, Azad M. Sievers, Michael Madni, Ayesha Ordoukhanian, Edwin Pouya, Parisa of astronautics and executive director of the Systems Architecting and Engineering Program at the University of Southern California. Architecting and Engineering Program at the University of Southern California Research scientist at the University of Southern California's Department of Astronautical Engineering. USC's Astronautics Department PhD student in the Astronautics Department specialising in systems architecting and engineering

Resilience is a much-needed characteristic in systems that are expected to operate in uncertain environments for extended periods with a high likelihood of disruptive events. Resilience approaches today employ ad hoc methods and piece-meal solutions that are difficult to verify and test, and do not scale. Furthermore, it is difficult to assess the long-term impact of such ad hoc "resilience solutions." This paper presents a flexible contract-based approach that employs a combination of formal methods for verification and testing and flexible assertions and probabilistic modelling to handle uncertainty during mission execution. A flexible contract (FC) is a hybrid modelling construct that facilitates system verification and testing while offering the requisite flexibility to cope with non-determinism. This paper illustrates the use of FCs for multi-UAV swarm control in, partially observable, dynamic environments. However, the approach is sufficiently general for use in other domains such as self-driving vehicle and adaptive power/energy grids. © 2018 by Azad M. Madni. Published and used by INCOSE with permission.

关键词： Formal verification

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Speech Emotion Recognition using Convolutional Neural Network with Audio Word-based Embedding

Speech Emotion Recognition using Convolutional Neural Networ...

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International Symposium on Chinese Spoken Language Processing

作者： Kun-Yi Huang Chung-Hsien Wu Qian-Bei Hong Ming-Hsiang Su Yuan-Rong Zeng Department of Computer Science and Information Engineering National Cheng Kung University Taiwan PhD Program for Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Taiwan

ISBN: (纸本)9781538656280;9781538656273

A complete emotional expression typically contains a complex temporal course in a natural conversation. Related research on utterance-level, segment-level and multi-level processing lacks understanding of the underlying relation of emotional speech. In this work, a convolutional neural network (CNN) with audio word-based embedding is proposed for emotion modeling. In this study, vector quantization is first applied to convert the low level features of each speech frame into audio words using k-means algorithm. Word2vec is adopted to convert an input speech utterance into the corresponding audio word vector sequence. Finally, the audio word vector sequences of the training emotional speech data with emotion annotation are used to construct the CNN- based emotion model. The NCKU-ES database, containing seven emotion categories: happiness, boredom, anger, anxiety, sadness, surprise and disgust, was collected and five-fold cross validation was used to evaluate the performance of the proposed CNN-based method for speech emotion recognition. Experimental results show that the proposed method achieved an emotion recognition accuracy of 82.34%, improving by 8.7% compared to the Long Short Term Memory (LSTM)- based method, which faced the challenging issue of long input sequence. Comparing with raw features, the audio word-based embedding achieved an improvement of 3.4% for speech emotion recognition.

关键词： Emotion recognition Feature extraction Speech recognition Acoustics Training Databases Neural networks

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Towards decoding the coupled decision-making of metabolism and epithelial-mesenchymal transition in cancer

arXiv

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arXiv 2020年

作者： Jia, Dongya Park, Jun Hyoung Kaur, Harsimran Jung, Kwang Hwa Yang, Sukjin Tripathi, Shubham Galbraith, Madeline Deng, Youyuan Jolly, Mohit Kumar Kaipparettu, Benny Abraham Onuchic, José N. Levine, Herbert Center for Theoretical Biological Physics Rice University HoustonTX77005 United States Department of Molecular and Human Genetics Baylor College of Medicine HoustonTX77030 United States Centre for BioSystems Science and Engineering Indian Institute of Science BangaloreKarnataka560012 India PhD Program in Systems Synthetic and Physical Biology Rice University HoustonTX77005 United States Department of Physics Northeastern University BostonMA02115 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Rice University HoustonTX77005 United States Dan L. Duncan Comprehensive Cancer Center Baylor College of Medicine HoustonTX77030 United States Department of Chemistry Rice University HoustonTX77005 United States Department of Biosciences Rice University HoustonTX77005 United States Department of Bioengineering Northeastern University BostonMA02115 United States

Cancer cells have the plasticity to adjust their metabolic phenotypes for survival and metastasis. During metastasis, a developmental program known as the epithelial-mesenchymal transition (EMT) plays a critical role. There is extensive cross-talk between metabolism and EMT, but how this leads to coordinated physiological changes is still uncertain. The elusive connection between metabolism and EMT compromises the efficacy of metabolic therapies targeting metastasis. In this review, we aim for clarifying causation between metabolism and EMT based on recent experimental studies and propose integrated theoretical-experimental efforts to better understand the coupled decision-making of metabolism and EMT. © 2020, CC-BY-NC-ND.

关键词： Metabolism

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Surface tension assisted dynamic and uniform size generation of 3D spherical hydrogels (STA-DUH) 22

Surface tension assisted dynamic and uniform size generation...

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22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018

作者： Koduri, Manohar Prasad Garden, Tom Hunt, John A. Henstock, James Curran, Judith Tseng, Fan-Gang International Intercollegiate PhD Program NTHU Hsinchu Taiwan Department of Mechanical Materials and Aerospace School of Engineering University of Liverpool United Kingdom School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom Institute of Ageing and Chronic Disease William Henry Duncan Building University of Liverpool United Kingdom Engineering and System Science Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Taiwan

ISBN: (纸本)9781510897571

Technologies like additive manufacturing, microfluidics, and electrospray show a possibility of generating a variety of 3-Dimensional structures but seriously suffer in adapting and utilizing the wide variety of available biocompatible materials because of innate diverse physical and chemical properties of biomaterials. It is very important to have a technology which can be viable and dynamically adaptable for different types of materials in generating uniform structures. This work presents a novel cell-laden hydrogel generation using the surface tension phenomenon in controlling the size of the hydrogel. Copyright © (2018) by Chemical and Biological Microsystems Society. All rights reserved.

关键词： Surface tension

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Identification of gene expression signatures for psoriasis classification using machine learning techniques

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Medicine in Omics 2021年 1卷

作者： Nguyen Quoc Khanh Le Duyen Thi Do Trinh-Trung-Duong Nguyen Ngan Thi Kim Nguyen Truong Nguyen Khanh Hung Nguyen Thi Thu Trang Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei City 106 Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei City 106 Taiwan Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City 106 Taiwan Department of Computer Science and Engineering Yuan Ze University Chung-Li 32003 Taiwan School of Nutrition and Health Sciences Taipei Medical University Taipei City 110 Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan Orthopedic and Trauma Department Cho Ray Hospital Ho Chi Minh City Viet Nam International PhD Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan

Psoriasis classification requires the accurate identification of the lesional types for the early and effective diagnosis and it is worth interesting that the normal and psoriasis cell tissues exhibit different gene expression. Therefore, gene expression data is an effective source for psoriasis classification and there is a challenge regarding the selection of suitable gene signatures for its purpose. In this present study, the gene expression-based microarray data were used and 35 expression features linked with psoriasis were utilized to feed into our machine learning model. Overall, the performance of our model based on 35 mentioned-above features surpassed that of other state-of-the-art classifiers with an average accuracy of 98.3%, recall of 98.6%, and precision of 98% in 5-fold cross-validation tests. We also validate our model on two different sets of psoriasis and the performance results are significant. These results have suggested that our 35 expression signatures have been identified as key features for classifying samples between lesion and non-lesion. More specifically, the expression levels of few genes i.e., FABP5 , TGM1 , or BCAR3 are discovered as newly potential biomarkers for psoriasis classification and treatment with high confidence. This study, therefore, could shed light on developing the prediction models for psoriasis classification and treatment using gene expression profiles.

关键词： Psoriasis classification Random forest Gene expression Feature selection Machine learning FABP5 Dermatology

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Enriched Peripheral Blood-Derived Mononuclear Cells for Treating Knee Osteoarthritis

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Cell transplantation 2023年 32卷

作者： Chang-Han Chuang Chi-Chung Kuo Yueh-Feng Chiang Pei-Yuan Lee Fu-Hui Wang Chia-Ying Hsieh Ching-I Shen Yu-Hsuan Chung Kuan-Der Lee Shih-Fang Wu Hong-Lin Su Chih-Lung Lin Department of Orthopedics Show Chwan Memorial Hospital Changhua Taiwan. PhD Program in Translational Medicine National Chung Hsing University Taichung Taiwan. Rong Hsing Research Center for Translational Medicine National Chung Hsing University Taichung Taiwan. Department of Neurology Taichung Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Taichung Taiwan. School of Post-Baccalaureate Chinese Medicine Tzu Chi University Hualien Taiwan. Department of Orthopedics Taichung Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Taichung. DuoGenic StemCells Corporation Taichung Taiwan. Department of Medical Research and Cell Therapy and Regenerative Medicine Center Taichung Veterans General Hospital Taichung Taiwan. Department of Medicine and Center for Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei City Taiwan. The Joint Program of Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung Taiwan. National Health Research Institutes Taichung Taiwan. Department of Life Sciences National Chung Hsing University Taichung Taiwan. Department of Neurosurgery Asia University Hospital Taichung Taiwan. Department of Occupational Therapy Asia University Taichung Taiwan.

Osteoarthritis (OA) is a common chronic skeletal disease in the elderly. There is no effective therapy to reverse disease severity and knee OA (KOA) progression, particularly at the late stage. This study aims to examine the effect of peripheral blood-derived mononuclear cells (PBMNCs) on pain and motor function rescue in patients with Kellgren-Lawrence (KL) grade II to IV KOA. Participants received one intra-articular (IA) injection of autologous PBMNCs. The mononuclear cells were isolated from peripheral blood, enriched by a specialized medium (MoFi medium), and separated by Ficoll-Paque solution. The isolated and enriched PBMNCs could differentiate into M1 and M2 macrophages . The anti-inflammatory effect of the PBMNCs was similar to that of bone marrow mesenchymal stem cells, evaluated by complete Freund's adjuvant-induced arthritis in rodents. A single-arm and open-label pilot study showed that patients' knee pain and motor dysfunction were significantly attenuated after the cell transplantation, assessed by visual analogue scale (VAS) and Knee injury and Osteoarthritis Outcome Score (KOOS) at 6 and 12 months post-treatment. Notably, the therapeutic effect of the PBMNCs treatment can be stably maintained for 24 months, as revealed by the KOOS scores. These preclinical and pilot clinical data suggest that IA injection of MoFi-PBMNCs might serve as a novel medical technology to control the pain and the progress of KOA.

关键词： macrophages monocytes osteoarthritis peripheral blood mononuclear cells

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