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The Effectiveness of Hydrothermal Alteration Mapping based on Hyperspectral Data in Tropical Region

IOP Conference Series: Earth and Environmental Science 2016年第1期42卷

作者： R R D Muhammad A Saepuloh Geothermal Technology Study Program Faculty of Mining and Petroleum Engineering Institut Teknologi Bandung Indonesia Geology Engineering Study Program Faculty of Earth Sciences and Technology Institut Teknologi Bandung Indonesia

Hyperspectral remote sensing could be used to characterize targets at earth's surface based on their spectra. This capability is useful for mapping and characterizing the distribution of host rocks, alteration assemblages, and minerals. Contrary to the multispectral sensors, the hyperspectral identifies targets with high spectral resolution. The Wayang Windu Geothermal field in West Java, Indonesia was selected as the study area due to the existence of surface manifestation and dense vegetation environment. Therefore, the effectiveness of hyperspectral remote sensing in tropical region was targeted as the study objective. The Spectral Angle Mapper (SAM) method was used to detect the occurrence of clay minerals spatially from Hyperion data. The SAM references of reflectance spectra were obtained from field observation at altered materials. To calculate the effectiveness of hyperspectral data, we used multispectral data from Landsat-8. The comparison method was conducted by comparing the SAM's rule images from Hyperion and Landsat-8, resulting that hyperspectral was more accurate than multispectral data. Hyperion SAM's rule images showed lower value compared to Landsat-8, the significant number derived from using Hyperion was about 24% better. This inferred that the hyperspectral remote sensing is preferable for mineral mapping even though vegetation covered study area.

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Geology Structure Identification based on Polarimetric SAR (PolSAR) Data and Field Based Observation at Ciwidey Geothermal Field

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IOP Conference Series: Earth and Environmental Science 2016年第1期42卷

作者： R A Pradipta A Saepuloh Suryantini Geothermal Technology Study Program Faculty of Mining and Petroleum Engineering Institut Teknologi Bandung Indonesia Geology Engineering Study Program Faculty of Earth Sciences and Technology Institut Teknologi Bandung Indonesia

Geological structure observation is difficult to be conducted at Quaternary volcanic field due to the classical problem at tropical region such as intensive erosion, dense vegetation covers, and rough terrain. The problem hampers the field observation especially for geological structures mapping. In order to overcome the problems, an active remote sensing technology based on Polarimetric Synthetic Aperture Radar (PolSAR) data was used in this study. The longer wavelength of microwave than optical region caused the SAR layer penetration higher than optics. The Ciwidey Geothermal Field, Indonesia was selected as study area because of the existence of surface manifestations with lack information about the control of geological structures to the geothermal system. Visual interpretation based on composite polarization modes was applied to identify geological structures at study area. The color composite Red-Green-Blue for HV-HH-VV polarizations provided highest texture and structural features among the other composite combination. The Linear Features Density (LFD) map was also used to interpret the fractures zones. The calculated LFD showed high anomaly about 3.6 km/km2 with two strike directions NW-SE and NE-SW. Interestingly, the surface geothermal manifestation agreed with the low anomaly of LFD. The geological structures consisted of ten faults were successfully detected and mapped. The faults type mainly are oblique-slip with strike directions NE-SW and NW-SE.

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Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification

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Nature communications 2025年第1期16卷 4852页

作者： Maria Zanti Denise G O'Mahony Michael T Parsons Leila Dorling Joe Dennis Nicholas J Boddicker Wenan Chen Chunling Hu Marc Naven Kristia Yiangou Thomas U Ahearn Christine B Ambrosone Irene L Andrulis Antonis C Antoniou Paul L Auer Caroline Baynes Clara Bodelon Natalia V Bogdanova Stig E Bojesen Manjeet K Bolla Kristen D Brantley Nicola J Camp Archie Campbell Jose E Castelao Melissa H Cessna Jenny Chang-Claude Fei Chen Georgia Chenevix-Trench Don M Conroy Kamila Czene Arcangela De Nicolo Susan M Domchek Thilo Dörk Alison M Dunning A Heather Eliassen D Gareth Evans Peter A Fasching Jonine D Figueroa Henrik Flyger Manuela Gago-Dominguez Montserrat García-Closas Gord Glendon Anna González-Neira Felix Grassmann Andreas Hadjisavvas Christopher A Haiman Ute Hamann Steven N Hart Mikael B A Hartman Weang-Kee Ho James M Hodge Reiner Hoppe Sacha J Howell Anna Jakubowska Elza K Khusnutdinova Yon-Dschun Ko Peter Kraft Vessela N Kristensen James V Lacey Jingmei Li Geok Hoon Lim Sara Lindström Artitaya Lophatananon Craig Luccarini Arto Mannermaa Maria Elena Martinez Dimitrios Mavroudis Roger L Milne Kenneth Muir Katherine L Nathanson Rocio Nuñez-Torres Nadia Obi Janet E Olson Julie R Palmer Mihalis I Panayiotidis Alpa V Patel Paul D P Pharoah Eric C Polley Muhammad U Rashid Kathryn J Ruddy Emmanouil Saloustros Elinor J Sawyer Marjanka K Schmidt Melissa C Southey Veronique Kiak-Mien Tan Soo Hwang Teo Lauren R Teras Diana Torres Amy Trentham-Dietz Thérèse Truong Celine M Vachon Qin Wang Jeffrey N Weitzel Siddhartha Yadav Song Yao Gary R Zirpoli Melissa S Cline Peter Devilee Sean V Tavtigian David E Goldgar Fergus J Couch Douglas F Easton Amanda B Spurdle Kyriaki Michailidou Biostatistics Unit The Cyprus Institute of Neurology & Genetics Nicosia Cyprus. Department of Medical Genetics Oslo University Hospital Oslo Norway. Population Health Program QIMR Berghofer Medical Research Institute Brisbane Queensland Australia. Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care University of Cambridge Cambridge UK. Department of Quantitative Health Sciences Division of Computational Biology Mayo Clinic Rochester MN USA. Department of Laboratory Medicine and Pathology Mayo Clinic Rochester MN USA. Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Department of Health and Human Services Bethesda MD USA. Department of Cancer Prevention and Control Roswell Park Comprehensive Cancer Institute Buffalo NY USA. Fred A. Litwin Center for Cancer Genetics Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Toronto Ontario Canada. Department of Molecular Genetics University of Toronto Toronto Ontario Canada. Division of Biostatistics Data Science Institute and Cancer Center Medical College of Wisconsin Milwaukee WI USA. Centre for Cancer Genetic Epidemiology Department of Oncology University of Cambridge Cambridge UK. Department of Population Science American Cancer Society Atlanta GA USA. Radiation Oncology Research Unit Hannover Medical School Hannover Germany. Copenhagen General Population Study Herlev and Gentofte Hospital Copenhagen University Hospital Herlev Denmark. Department of Clinical Biochemistry Herlev and Gentofte Hospital Copenhagen University Hospital Herlev Denmark. Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark. Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA. Department of Internal Medicine and Huntsman Cancer Institute University of Utah Salt Lake City UT USA. Centre for Genomic and Experimental Medicine Institute of Genetics & Cancer The University of Ed

Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS. As an initiative of the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Analytical Working Group we analyze germline sequencing data of BRCA1 and BRCA2 from 96,691 female breast cancer cases and 302,116 controls from three studies: the BRIDGES study of the Breast Cancer Association Consortium, the Cancer Risk Estimates Related to Susceptibility consortium, and the UK Biobank. We observe 11,207 BRCA1 and BRCA2 variants, with 6909 being coding, covering 23.4% of BRCA1 and BRCA2 VUS in ClinVar and 19.2% of ClinVar curated (likely) benign or pathogenic variants. Case-control likelihood ratio (ccLR) evidence is highly consistent with ClinVar assertions for (likely) benign or pathogenic variants; exhibiting 99.1% sensitivity and 95.3% specificity for BRCA1 and 93.3% sensitivity and 86.6% specificity for BRCA2. This approach provides case-control evidence for 787 unclassified variants; these include 579 with strong or moderate benign evidence and 10 with strong pathogenic evidence for which ccLR evidence is sufficient to alter clinical classification.

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EEG channels reduction using PCA to increase XGBoost’s accuracy for stroke detection

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AIP Conference Proceedings 2017年第1期1862卷

作者： N. Fitriah S. K. Wijaya M. I. Fanany C. Badri M. Rezal 1Biomedical Engineering Study Program Universitas Indonesia Jl. Salemba Raya No. 4 Jakarta 10430 DKI Jakarta Indonesia 2Department of Physics Faculty of Mathematics and Natural Sciences (FMIPA) Universitas Indonesia Depok 16424 Indonesia 3Faculty of Computer Science Universitas Indonesia Depok 16424 Indonesia

In Indonesia, based on the result of Basic Health Research 2013, the number of stroke patients had increased from 8.3 ‰ (2007) to 12.1 ‰ (2013). These days, some researchers are using electroencephalography (EEG) result as another option to detect the stroke disease besides CT Scan image as the gold standard. A previous study on the data of stroke and healthy patients in National Brain Center Hospital (RS PON) used Brain Symmetry Index (BSI), Delta-Alpha Ratio (DAR), and Delta-Theta-Alpha-Beta Ratio (DTABR) as the features for classification by an Extreme Learning Machine (ELM). The study got 85% accuracy with sensitivity above 86 % for acute ischemic stroke detection. Using EEG data means dealing with many data dimensions, and it can reduce the accuracy of classifier (the curse of dimensionality). Principal Component Analysis (PCA) could reduce dimensionality and computation cost without decreasing classification accuracy. XGBoost, as the scalable tree boosting classifier, can solve real-world scale problems (Higgs Boson and Allstate dataset) with using a minimal amount of resources. This paper reuses the same data from RS PON and features from previous research, preprocessed with PCA and classified with XGBoost, to increase the accuracy with fewer electrodes. The specific fewer electrodes improved the accuracy of stroke detection. Our future work will examine the other algorithm besides PCA to get higher accuracy with less number of channels.

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The implementation of constructivism approach for physics learning in vocational high school

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AIP Conference Proceedings 2016年第1期1778卷

作者： Tuwoso 1Study Program of Mechanical Engineering Education Mechanical Engineering Department Faculty of Engineering Universitas Negeri Malang Indonesia

The nowadays Physics learning at vocational high school is still focusing on teacher-centered. Therefore, the learners’ activities are only listening to a lecture from the teacher and take notes. The learning process is supposed to be students-centered, the teacher acts as a facilitator and mediator. The learning process should provide an opportunity for learners to acquire knowledge itself in accordance with the prior knowledge they already had, which is the result of interaction with the environment. Such learning process is in accordance with the constructivist view. The method in this research is quantitative research, the research design pretest-posttest control group design. The research subjects are 30 students for the experimental group and 30 students in the control group. The experimental group in this research is the group that is taught by the constructivist approach (student-centered), while the control group is taught by the teacher - centered approach. The obtained findings have significant differences in post test results of students who are treated as experimental groups and with the control group (p <0.05). The conclusion of this research is the implementation of Physics in vocational learning with constructivist approach proved to be effective and influence the improvement of learning outcome of students in the first semester for the tenth grade students of vocational high school.

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Implementation of project based learning model in mechanical machining skills package of vocational high school

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AIP Conference Proceedings 2016年第1期1778卷

作者： Dwi Agus Sudjimat 1Mechanical Engineering Education Study Program Departemen of Mechanical Engineering Faculty of Engineering Universitas Negeri Malang Indonesia

One model of learning that is most appropriate for vocational school based on standart learning process of curriculum 2013 was the use of project-based learning model. The findings of this study indicate that all of the mechanical machining teachers have implemented the project-based learning model based on their quite comprehensive understanding. Teachers perceive that project-based learning model can improve the hard skills and soft skills of the students. One weakness lies in the project is used, which is produced only by the analysis of the basic competencies of the subjects and does not use projects from industry so that most of the students’ products could not be used, what else is sold.

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Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease study 2019

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The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

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Application of tomography seismic for subsurface modeling of Kelud Mountain

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AIP Conference Proceedings 2016年第1期1730卷

作者： R. Destawan A. Bernando M. Aziz I. R. Palupi Geophysical Engineering Study Program Faculty of Mineral Technology UPN “Veteran” Yogyakarta Indonesia

Kelud is a Quaternary volcano formed by the collision between the Indo-Australian plate with the Eurasian plate, exactly in the south of Java. This volcano is included in stratovolcanoes type explosive eruption characteristics. In order observation of subsurface conditions, performed imaging tomography. The research used data recordings from the 4 point observation in 2007. The data processing started from the initial velocity modeling, ray tracing calculations using the method of bending and tomographic velocity model Vp, Vs and Vp/Vs using inversion techniques delay time. Based on the research activities carried out, were resulted velocity structure models Vp, Vs, Vp/Vs and the hypocenter distribution of volcanic earthquakes occurring in Kelud. Velocity structures of Vp and Vs with variations of negative values between -60 to 0% and the value of Vp / Vs positive indicating the presence of hot fluid Kelud from top to sea level. While the positive values of Vs velocity structure between 0 to 20%, which dominate the east and south peaks interpreted as the rest of the frozen magma from previous volcanic activity.

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3D Geothermal Modelling Using Gravity Survey on Dolok Marawa, Simalungun District, North Sumatera

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IOP Conference Series: Earth and Environmental Science 2016年第1期29卷

作者： A Rivandi R Destawan Z R Fajri W Hidayat Geophysical Engineering Study Program Faculty of Mineral Technology UPN 'Veteran' Yogyakarta Indonesia

In North Sumatera, gravity method is applied to identify the geothermal model. This method measured the earth gravitational field. This research has 160 measurement points covering 9 square kilometers. We obtained complete Bouguer anomaly values ranging 85 mGal - 130.68 mGal interpreted as a heat source of andesitic igneous rocks that are affected by the presence of Mount Bahtopu magma chamber. We interpreted the values between 40 mGal - 80 mGal as reservoir and caprock. The 3D gravity inverse modelling conducted using Gravblox, and identifying the following lithologies; Toba Pyroclastic Fall (Qjt) with density 1.92 g/cm3, Toba Pyroclastic Flow (Qjt) with density 2.00 g/cm3, Mount Bahtopu Andesite (Qlb) with density 2.4 g/cm3, and 2.6 g/cm3 which is interpreted as heat source in form of andesitic rock and Mount Bahtopu magma chamber. This heat source is estimated to be at a depth of 1.45 km to 3.78 km below the surface.

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Influence of Plastic Waste for Refuse-Derived Fuel on Downdraft Gasification

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Energy Procedia 2015年 79卷 528-535页

作者： Chatchai Kungkajit Gumpon Prateepchaikul Thaniya Kaosol Environmental Engineering Program Department of Civil Engineering Faculty of Engineering Prince of Songkla University Songkhla Thailand Department of Mechanical Engineering Faculty of Engineering Prince of Songkla University Songkhla Thailand

The potential of syngas production from used- and unused-plastic-waste Refuse-Derived Fuels (RDFs) by downdraft type fixed bed gasification technology is investigated. The purpose of this study is to investigate the syngas compositions of used- and unused-plastic-waste RDFs in the downdraft type fixed bed gasification system. It is found that used- and unused-plastic-waste RDFs can be successfully converted to generate the syngas consisting of carbon monoxide, carbon dioxide, hydrocarbon, hydrogen sulfide oxygen and water vapor. The performance of the downdraft type fixed bed gasification system is evaluated in terms of the composition of syngas and the rate of carbon monoxide production. The result can be concluded that syngas produced from the used- and unused-plastic-waste RDFs is the same. The HHV (Higher Heating Value) of the syngas from the unused-plastic-waste RDF (781 kJ/Nm 3 ) is slightly higher than that of the used one (500 kJ/Nm 3 ). It is also suggested that the gasification of used- and unused-plastic-waste RDFs is a clean alternative to fossil fuels. Moreover, the syngas can be directly used in the internal gas combustion engines.

关键词： HHV plastic waste gasification downdraft syngas RDF

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