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New Slow Release Fertilizer from ENR-50/RH/Urea Composites: Effect of Sodium Chloride Concentration

Journal of Physics: Conference Series 2018年第1期1019卷

作者： Marwa N Al-Samarrai R Hamzah S T Sam N Z Noriman Omar S Dahham S Z Syed Idrus S Sudin Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Faculty of Engineering Technology (FETech) Universiti Malaysia Perlis (UniMAP) Level 1 Block S2 UniCITI Alam Campus Sungai Chucuh Padang Besar 02100 Perlis Malaysia. School of Bioprocess Engineering Universiti Malaysia Perlis (UniMAP) Kompleks Pengajian Jejawi 3 02600 Arau Perlis Malaysia. School of Human Development and Techno-communication (iKOM) Green Advanced Computing and Technology (GREAT) Research Group – CEGeoGTech Universiti Malaysia Perlis (UniMAP School of Computer and Communication Engineering (SCCE) Green Advanced Computing and Technology (GREAT) Research Group – CEGeoGTech Universiti Malaysia Perlis (UniMAP

A green and renewable slow release material (SRM) was developed using combination of urea, epoxidized natural rubber (ENR-50), NaCl and rice husk (RH). The RH was used as a support to store urea within its fibrous structure after chemical modification with 7% sodium hydroxide (NaOH). ENR-50/NaCl was used as a coating material for RH/urea beads. Two different content of salt (5% and 10% NaCl) was used to study the effect of pore formation on the composites. FTIR spectroscopy reveals that urea was successfully absorbed into RH and the recorded peaks were overlapped with the main components of RH such as cellulose, hemicellulose and lignin. UV-Vis reveals that at 10% salt loading releases urea higher than 5% salt loading. This is due to the formation of many pores in this ENR-50 composite.

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Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings

arXiv

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arXiv 2022年

作者： Bano, Sophia Casella, Alessandro Vasconcelos, Francisco Qayyum, Abdul Benzinou, Abdesslam Mazher, Moona Meriaudeau, Fabrice Lena, Chiara Cintorrino, Ilaria Anita De Paolis, Gaia Romana Biagioli, Jessica Grechishnikova, Daria Jiao, Jing Bai, Bizhe Qiao, Yanyan Bhattarai, Binod Gaire, Rebati Raman Subedi, Ronast Vazquez, Eduard Plotka, Szymon Lisowska, Aneta Sitek, Arkadiusz Attilakos, George Wimalasundera, Ruwan David, Anna L. Paladini, Dario Deprest, Jan De Momi, Elena Mattos, Leonardo S. Moccia, Sara Stoyanov, Danail Department of Computer Science University College London United Kingdom Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Italy The BioRobotics Institute Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna Italy Fetal Medicine Unit Elizabeth Garrett Anderson Wing University College London Hospital United Kingdom EGA Institute for Women's Health Faculty of Population Health Sciences University College London United Kingdom Department of Development and Regeneration University Hospital Leuven Belgium Department of Fetal and Perinatal Medicine Istituto Giannina Gaslini Italy ENIB UMR CNRS 6285 LabSTICC 29238 France Department of Computer Engineering and Mathematics University Rovira i Virgili Spain ImViA Laboratory University of Bourgogne Franche-Comté France Physics Department Lomonosov Moscow State University Russia Fudan University China Medical Computer Vision and Robotics Group Department of Mathematical and Computational Sciences University of Toronto Canada Co. Ltd China NepAL Applied Mathematics and Informatics Institute for Research Nepal Redev Technology United Kingdom Sano Center for Computational Medicine Poland Quantitative Healthcare Analysis Group Informatics Institute University of Amsterdam Amsterdam Netherlands Center for Advanced Medical Computing and Simulation Massachusetts General Hospital Harvard Medical School BostonMA United States

Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomoses to restore a physiological blood exchange among twins. The procedure is particularly challenging, from the surgeon's side, due to the limited field of view, poor manoeuvrability of the fetoscope, poor visibility due to amniotic fluid turbidity, and variability in illumination. These challenges may lead to increased surgery time and incomplete ablation of pathological anastomoses, resulting in persistent TTTS. Computer-assisted intervention (CAI) can provide TTTS surgeons with decision support and context awareness by identifying key structures in the scene and expanding the fetoscopic field of view through video mosaicking. Research in this domain has been hampered by the lack of high-quality data to design, develop and test CAI algorithms. Through the Fetoscopic Placental Vessel Segmentation and Registration (FetReg2021) challenge, which was organized as part of the MICCAI2021 Endoscopic Vision (EndoVis) challenge, we released the first large-scale multi-center TTTS dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms with a focus on creating drift-free mosaics from long duration fetoscopy videos. For this challenge, we released a dataset of 2060 images, pixel-annotated for vessels, tool, fetus and background classes, from 18 in-vivo TTTS fetoscopy procedures and 18 short video clips of an average length of 411 frames for developing placental scene segmentation and frame registration for mosaicking techniques. Seven teams participated in this challenge and their model performance was assessed on an unseen test dataset of 658 pixel-annotated images from 6 fetoscopic procedures and 6 short clips. The challenge provided an opportunity for creating generalized solutions for fetoscopic scene understanding and mosaicking. In this paper,

关键词： Pixels

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Efficient targeted gene disruption in Xenopus embryos using engineered transcription activator-like effector nucleases (TALENs)

Efficient targeted gene disruption in Xenopus embryos using ...

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2012全国发育生物学大会

作者： Yong Lei Hui Zhao Xiaogang Guo Yun Liu Yang Cao Yi Deng Xiongfeng Chen Hon Ki Christopher Cheng Igor B.Dawid Yonglong Chen Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen 518057 P.R.China Key Laboratory of Regenerative Biology Guangzhou Institutes of Biomedicine and HealthChinese Academy of Sciences Guangzhou 510530 P.R.China Department of Biology South University of Science and Technology of China Shenzhen 518055 P.R.China Advanced Biomedical Computing Center National Cancer Institute National Institutes of Health Frederick MD 21702 USA Program in Genomics of Differentiation The Eunice Kennedy Shriver National Institute of Child Health and Human Development National Institutes of Health Bethesda MD 20892 USA School of Biomedical Sciences Faculty of Medicine The Chinese University of Hong Kong Shatin New TerritoriesHong Kong P.R.China School of Biomedical Sciences Faculty of Medicine The Chinese University of Hong Kong Shatin New TerritoriesHong Kong P.R.China

Transcription activator-like effector nucleases (TALENs) are a novel approach for directed gene disruption and have been proved to be effective in various animal *** we report that TALENs can induce somatic mutations in Xenopus embryos with reliably high efficiency and that such mutations are heritable through germline *** modified the Golden Gate method for TALEN assembly to make the product suitable for RNA transcription and microinjection into Xenopus embryos.

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An integrated cyberGIS and machine learning framework for fine-scale prediction of Urban Heat Island using satellite remote sensing and urban sensor network data

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Urban informatics 2022年第1期1卷 6页

作者： Fangzheng Lyu Shaohua Wang Su Yeon Han Charlie Catlett Shaowen Wang cyberGIS Center for Advanced Digital and Spatial Studies University of Illinois at Urbana-Champaign Urbana IL USA. Department of Geography and Geographic Information Science University of Illinois at Urbana-Champaign Urbana IL USA. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. Computing Environment and Life Sciences Argonne National Laboratory Chicago IL USA.

Due to climate change and rapid urbanization, Urban Heat Island (UHI), featuring significantly higher temperature in metropolitan areas than surrounding areas, has caused negative impacts on urban communities. Temporal granularity is often limited in UHI studies based on satellite remote sensing data that typically has multi-day frequency coverage of a particular urban area. This low temporal frequency has restricted the development of models for predicting UHI. To resolve this limitation, this study has developed a cyber-based geographic information science and systems (cyberGIS) framework encompassing multiple machine learning models for predicting UHI with high-frequency urban sensor network data combined with remote sensing data focused on Chicago, Illinois, from 2018 to 2020. Enabled by rapid advances in urban sensor network technologies and high-performance computing, this framework is designed to predict UHI in Chicago with fine spatiotemporal granularity based on environmental data collected with the Array of Things (AoT) urban sensor network and Landsat-8 remote sensing imagery. Our computational experiments revealed that a random forest regression (RFR) model outperforms other models with the prediction accuracy of 0.45 degree Celsius in 2020 and 0.8 degree Celsius in 2018 and 2019 with mean absolute error as the evaluation metric. Humidity, distance to geographic center, and PM concentration are identified as important factors contributing to the model performance. Furthermore, we estimate UHI in Chicago with 10-min temporal frequency and 1-km spatial resolution on the hottest day in 2018. It is demonstrated that the RFR model can accurately predict UHI at fine spatiotemporal scales with high-frequency urban sensor network data integrated with satellite remote sensing data.

关键词： Machine learning Remote sensing Urban Heat Island Urban sensor network cyberGIS

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Erratum to “Implications of Implementing Promulgated and Prospective Emission Regulations on Air Quality and Health in India during 2030”

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Aerosol and Air Quality Research 2023年第5期23卷 1-1页

作者： Debnath, Sreyashi Karumuri, Rama Krishna Govardhan, Gaurav Jat, Rajmal Saini, Himadri Vispute, Akash Kulkarni, Santosh H. Jena, Chinmay Kumar, Rajesh Chate, D. M. Ghude, Sachin D. Indian Institute of Tropical Meteorology (IITM) Ministry of Earth Sciences Pune India Department of Atmospheric and Space Sciences Savitribai Phule Pune University Pune India King Abdullah University of Science and Technology Thuwal Saudi Arabia National Center for Medium Range Weather Forecasting Ministry of Earth Sciences Noida India University of New South Wales (UNSW) Sydney Australia Centre for Development of Advanced Computing (C-DAC) Pune India India Meteorological Department New Delhi India National Center for Atmospheric Research Boulder USA

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Perspectives for self-driving labs in synthetic biology

arXiv

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arXiv 2022年

作者： Martin, Hector Garcia Radivojevic, Tijana Zucker, Jeremy Bouchard, Kristofer Sustarich, Jess Peisert, Sean Arnold, Dan Hillson, Nathan Babnigg, Gyorgy Marti, Jose Manuel Mungall, Christopher J. Beckham, Gregg T. Waldburger, Lucas Carothers, James Sundaram, ShivShankar Agarwal, Deb Simmons, Blake A. Backman, Tyler Banerjee, Deepanwita Tanjore, Deepti Ramakrishnan, Lavanya Singh, Anup Lawrence Berkeley National Laboratory Biological Systems and Engineering Division BerkeleyCA United States Department of Energy Agile BioFoundry EmeryvilleCA United States Joint BioEnergy Institute EmeryvilleCA United States BCAM Basque Center for Applied Mathematics Bilbao Spain Lawrence Berkeley National Laboratory Scientific Data Division BerkeleyCA United States Helen Wills Neuroscience Institute Redwood Center for Theoretical Neuroscience BerkeleyCA United States Lawrence Berkeley National Laboratory Energy Storage and Distributed Resources Division BerkeleyCA United States University of California Davis Department of Computer Science DavisCA United States Global Security Computing Applications Division Lawrence Livermore National Laboratory LivermoreCA United States Engineering Directorate Lawrence Livermore National Laboratory LivermoreCA United States Center for Bioengineering Lawrence Livermore National Laboratory LivermoreCA United States Department of Chemical Engineering Molecular Engineering & Sciences Institute Center for Synthetic Biology University of Washington SeattleWA United States Biosciences Division Argonne National Laboratory ArgonneIL United States Advanced Biofuels and Bioproducts Process Development Unit Lawrence Berkeley National Laboratory BerkeleyCA United States Biomaterials and Biomanufacturing Division Sandia National Laboratories LivermoreCA United States Earth and Biological Sciences Division Pacific Northwest National Laboratories RichlandWA United States Resources and Enabling Sciences Center National Renewable Energy Laboratory GoldenCO80401 United States Department of Bioengineering University of California BerkeleyCA United States

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. While there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single target for affecting the incredibly wide repertoire of biological cell behavior. However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology. © 2022, CC BY.

关键词： Synthetic biology

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Effects of Sodium Hydroxide Treatment on LLDPE/DS Composites: Tensile Properties and Morphology

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Journal of Physics: Conference Series 2018年第1期1019卷

作者： Abduati Alnaid N Z Noriman Omar S Dahham R Hamzah S Sudin S Z Syed Idrus Z Shayfull M Mohammed Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Faculty of Engineering Technology (FETech) Universiti Malaysia Perlis (UniMAP) Level 1 Block S2 UniCITI Alam Campus Sungai Chucuh Padang Besar 02100 Perlis Malaysia. School of Computer and Communication Engineering (SCCE) Green Advanced Computing and Technology (GREAT) Research Group – CEGeoGTech Universiti Malaysia Perlis (UniMAP School of Human Development and Techno-communication (iKOM) Green Advanced Computing and Technology (GREAT) Research Group – CEGeoGTech Universiti Malaysia Perlis (UniMAP School of Manufacturing Engineering Universiti Malaysia Perlis Arau 02600 Malaysia Green Design and Manufacture Research Group Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Universiti Malaysia Perlis Kangar 0100 Malaysia Center of Excellence Geopolymer and Green Technology (CEGeoGTech) School of Materials Engineering Universiti Malaysia Perlis (UniMAP) Kompleks Pengajian Jejawi 2 02600 Arau Malaysia

In this research, the effect of different sodium hydroxide (NaOH) concentration (3, 6 and 9 wt.%) on the tensile properties of linear low density polyethylene / date seeds (LLDPE/DS) composites were investigated. The size of DS particles was measured at (125 - 250 μm) and the ratio of LLDPE over DS was fixed at 90/10 wt.%. The samples were prepared using extrusion process (screw speed at 60 rpm and barrel and die temperature at 160°C and 165°C respectively) followed by injection moulding process (from feed to exit die zone temperature at 160, 165, 170 and 175°C respectively). Results suggest that the addition of NaOH particularly 3 wt% has improved the tensile strength. Additionally, the elongation at break has improved as well. However, the high concentration of NaOH, particularly 9 wt.% effects negatively on these properties. In contrast, the Modulus shows different trend, which increased as NaOH concentration increased in the composites. The SEM section shows the improvement on DS surface as low NaOH concentration used (3 wt.%) and deterioration on the DS surface as high NaOH concentration used (9 wt.%).

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Measuring System Success In New Context By Adapting DM 2003 Framework With The External Factor Management Support

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Journal of Physics: Conference Series 2018年第1期1019卷

作者： Ibrahim Eskandar Ibrahim Fadhel Syed Zulkarnain bin Syed Idrus Amani Ali Elmetwaly Ali Ibrahim Mazni Omar Fawzia Baheshwan Malek Khalaf Albzeirat Suhaib Khalaf Albzeirat Department of Computer and Information Systems in National Institute of Administrative Science (NIAS) Mukalla Al-Shihr Yemen School of Human Development and Techno-communication University Malaysia Perlis Perlis Malaysia Green Advanced Computing and Technology (GREAT) Research Group - CEGeoGTech University Malaysia Perlis Perlis Malaysia College of Science and Arts School of Computing Universiti Utara Malaysia Kedah Malaysia Department of Information Systems Hadhramout University Mukalla Yemen School of Manufacturing Engineering University Malaysia Perlis Kampus Alam Pauh Putra 02600 Arau Perlis Malaysia Queen Rania Center for Educational Technology and Information Hashemite Kingdom of Jordan

Rate of failure of software's and information systems are high among the world and there is a dire need for engineering a systems quality framework works a success measure tool in the context of the study domain. Success measure of systems and developing a framework helps in solving the problem of higher rate of systems failure. Success measure is also, an important part of systems development to improve systems performance. However, studies showed a lack of research done on systems success in world universities Arab region universities and Yemeni universities and limited adequate frameworks. Systems especially the web-based faces high rate of failure in world and Arab region, it was observed that many funded system projects failed, it was also, noted that in Yemen systems were completed and implemented without evaluation and success measuring. The Yemen higher education management information system (YHEMIS), is a large-scale application developed and implemented without evaluation. Hence, this research measures the YHEMIS application by investigating into the factors that influence user satisfaction and system use which will further show the benefit of the system. The research findings showed that information quality, system quality and management support influenced the use and users' satisfaction and played a vital role in the success of YHEMIS. The findings showed that students' satisfaction have the strongest effect on the perceived net benefits YHEMIS brought for the students. This study provides the first empirical data on the evaluation of web-based systems success conducted on YHEMIS in Yemen. Based on the results, stakeholders can get the feedback to improve the systems and provide input to develop other software projects. The research findings can provide the support to the management of Hadhramout University to other online system projects. Hence, YHEMIS can be said to be successful and users (students) satisfaction can be considered as the indicator of

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Studies of ENR-25/TiO2 Composites for Electronic Materials Packaging Applications

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Journal of Physics: Conference Series 2018年第1期1019卷

作者： Omar S Dahham N Z Noriman R Hamzah T Adam Z Shayfull S Sudin S Z Syed Idrus Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Faculty of Engineering Technology (FETech) Universiti Malaysia Perlis (UniMAP) Level 1 Block S2 UniCITI Alam Campus Sungai Chucuh Padang Besar 02100 Perlis Malaysia. Institute of Nano Electronic Engineering (INEE) Universiti Malaysia Perlis (UniMAP) 01000 Kangar Perlis Malaysia School of Manufacturing Engineering Universiti Malaysia Perlis Arau 02600 Malaysia Green Design and Manufacture Research Group Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Universiti Malaysia Perlis Kangar 0100 Malaysia School of Computer and Communication Engineering (SCCE) Green Advanced Computing and Technology (GREAT) Research Group – CEGeoGTech Universiti Malaysia Perlis (UniMAP School of Human Development and Techno-communication (iKOM) Green Advanced Computing and Technology (GREAT) Research Group – CEGeoGTech Universiti Malaysia Perlis (UniMAP

In this study, the synthesis and characterization of epoxidized natural rubber / Titanium dioxide (ENR-25/TiO2) composites in two different solvent (Toluene and Chloroform) via sonication technique was conducted using Fourier transform infrared spectroscopy (FTIR) and Field Emission Scanning Electron Microscopy (FESEM). Spectroscopy results showed new peak at 1662 cm-1 for both ENR-25/Titania composite films, which is related to weak C-O stretching vibration. Moreover, The peak at 3390.4 cm-1 and 3384.3 cm-1 of the composites are produced by Ti-OH stretching vibration shifts. The composite with toluene solvent showed poor dispersion of TiO2, which can be seen by the agglomeration embedded in the matrix. The composite with chloroform showed same trend of composite with toluene. The poor TiO2 dispersion in the composite can be observed by the surface as bright layers. These layers appeared because the TiO2 particles covered the surface of purified ENR-25 matrix.

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