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Analysis of Genetic Association Studies
 
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Teri Manolio, M.D., Ph.D. Director, Office of Population Genomics, NHGRI. Genetics for Epidemiologists: Applications of Human Genomics to Population Sciences, was a short course for investigators and trainees in the field of epidemiology and related population-based sciences. It was conducted by the National Human Genome Research Institute (NHGRI) on May 13-14, 2008 at Northwestern University in Chicago. The goal of Genetics for Epidemiologists (GFE) was to familiarize epidemiologists and population-based researchers with recent developments in the theory and methods of human genetics that might be applied to the study of the distribution, natural history and etiology of diseases in populations. The course consisted of eight one-hour lectures and focused on the interface between genetics and epidemiology. Emphasis was on the application of modern human genome analysis methodologies to studies of human populations through the design, conduct, analysis, and interpretation of studies which effectively answer the epidemiologic question of interest. GFE is co-sponsored by the Office of Population Genomics, NHGRI, and the Department of Preventive Medicine at Northwestern University's Feinberg School of Medicine. These videocasts are provided as an educational tool for epidemiologic investigators interested in learning more about applying genomics to their work. More: http://www.genome.gov/27026645
20. Principal Component Analysis (cont.)
 
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MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet In this lecture, Prof. Rigollet talked about principal component analysis: main principle, algorithm, example, and beyond practice. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 5222 MIT OpenCourseWare
Dr. Marvin Weinstein: "Quantum Insights: Finding Meaning in the World’s [...]" | Talks at Google
 
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Dr. Marvin Weinstein comes to Google to discuss Dynamic Quantum Clustering (DQC), a novel approach to data analysis using concepts from quantum mechanics. Dr. Weinstein provides an introduction to the ideas behind DQC and discuss its application towards various fields, including cancer diagnoses and identifying early Alzheimer's signals. Dr. Marvin Weinstein worked as a theoretical physicist at Stanford's SLAC National Accelerator Laboratory for 42 years. While at SLAC, he co-developed Dynamic Quantum Clustering, a novel algorithm for performing density mapping on unstructured data. He is currently the CEO of Quantum Insights, a company that consults on the application of Dynamic Quantum Clustering (DQC) to analyzing large, complex datasets. Dr. Weinstein received his PhD from Columbia University and completed his postdoc at the Institute for Advanced Study in Princeton.
Views: 5742 Talks at Google
Interpreting Heat Map Visualizations
 
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Interpreting Heat Map Visualizations: Learn how to interpret data presented in heat map visualizations; Consider heat map visualization configuration options which may not be intuitive. This video is current as of Spotfire 6.5. Some interactive features in the original video are not available in YouTube. The original is available here: http://learn.spotfire.tibco.com/mod/url/view.php?id=5350 (Click "Login as guest" to access that link if needed)
Views: 25596 TIBCO Products
The Making of “Fungible Open Data” in Biomedical Research: Governance, Epistemic Trust, Public Good
 
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This talk discusses the epistemic, societal, and ethical implications of making publicly available and reusing open data from biomedical research. Today, making scientific data open is promoted by funding agencies and lawmakers as means to speed up the research process, leverage public investments in large-scale data collections, and increase public trust in science. Especially in genomics research, scientists are increasingly encouraged, and sometimes required, to make their data openly available right after data collection and prior to publication. These policies are challenging well-established community norms, scientific collaborative practices, and epistemic processes for knowledge validation. Moreover, scientists are concerned about the possibility for third parties to exploit their data inappropriately, unethically, or in misleading ways. The main case study is the FaceBase Consortium, a consortium for data sharing operating in the craniofacial research domain. Data types include facial images, metrics for facial norms, gene expression data, and results from genome-wide association studies (GWAS). The reuse of these various “kinds” of data has applications beyond their original context of production that span from the design of mobile apps for facial recognition to the development of forensic DNA phenotypic technologies. See more at https://www.microsoft.com/en-us/research/video/making-fungible-open-data-biomedical-research-regimes-governance-epistemic-trust-public-good/
Views: 1233 Microsoft Research
Data Issues: Multiple Testing, Bias, Confounding, Missing...
 
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Dr. Lance Waller from Emory University presents a lecture titled "Data Issues: Multiple Testing, Bias, Confounding, & Missing Data." View Slides https://drive.google.com/open?id=0B4IAKVDZz_JUczRSd0NucjlhT00 Lecture Abstract Once data are scraped, wrangled, linked, merged, and analyzed, what information do they reveal and can we trust the resulting conclusions? In this presentation, we define and review data issues relating to the analysis and interpretation of observational data from the field of epidemiology and consider implications for data science, especially regarding the goal of moving from big data to knowledge. Specifically, we explore concepts of bias, confounding, effect modification, and missing/mismeasured data as applied to data science. We provide an analytic context based on sampling concepts and explore relevant literature and tools from epidemiology, biostatistics, computer science, and data science. As with many issues in data science, the full applicability of the concepts is very much a work in progress and present multiple opportunities for future development. About the Speaker Lance A. Waller, Ph.D. is Rollins Professor and Chair of the Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University. He is a member of the National Academy of Science Committee on Applied and Theoretical Statistics. His research involves the development of statistical methods for geographic data including applications in environmental justice, epidemiology, disease surveillance, spatial cluster detection, conservation biology, and disease ecology. His research appears in biostatistical, statistical, environmental health, and ecology journals and in the textbook Applied Spatial Statistics for Public Health Data (2004, Wiley). Join our weekly meetings from your computer, tablet or smartphone. Visit our website to view our schedule and join our next live webinar! http://www.bigdatau.org/data-science-seminars
Sparse and large-scale learning with heterogeneous data
 
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Google Tech Talks September 5, 2006 Gert Lanckriet is assistant professor in the Electrical and Computer Engineering Department at the University of California, San Diego. He conducts research on machine learning, applied statistics and convex optimization with applications in computational biology, finance, music and vision. ABSTRACT An important challenge for the field of machine learning is to deal with the increasing amount of data that is available for learning and to leverage the (also increasing) diversity of information sources, describing these data. Beyond classical vectorial data formats, data in the format of graphs, trees, strings and beyond have become widely available for data...
Views: 2837 GoogleTechTalks
TCGA: Pathway and Network Analysis of Somatic Mutations Across Cancer Types in TCGA - Ben Raphael
 
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November 27-28, 2012 - The Cancer Genome Atlas' 2nd Annual Scientific Symposium: Enabling Cancer Research Through TCGA More: http://www.genome.gov/27551851
Unsupervised Machine Learning
 
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Dr. Ali Shojaie from the University of Washington presents a lecture titled "Unsupervised Machine Learning." View Slides https://drive.google.com/open?id=0B4IAKVDZz_JUR0V5c0w4MzNjLWM Lecture Abstract In this lecture, Dr. Shojaie will give an overview of unsupervised learning methods commonly used in biological applications, including dimension reduction (such as PCA and MDS), clustering and graphical modeling. Particular emphasis will be given to the generalizability of results from unsupervised learning methods, especially when these methods are used as part of the analysis pipeline in conjunction with supervised learning techniques. About the Speaker Ali Shojaie is an Associate Professor of Biostatistics and Adjunct Associate Professor of Statistics at the University of Washington. Originally trained in Industrial and Systems Engineering, he obtained his PhD in Statistics from the University of Michigan, while completing Masters degrees in Applied Mathematics and Human Genetics. Prior to joining the University of Washington in 2011, he participated in the program on Complex Networks as a Visiting Scholar at the Statistical and Mathematical Sciences Institute (SAMSI). Ali’s current research lies in the intersection of machine learning for high-dimensional data, statistical network analysis and applications in biology and social sciences and he teaches multiple regular and short courses on statistical machine learning and network analysis. Join our weekly meetings from your computer, tablet or smartphone. Visit our website to view our schedule and join our next live webinar! http://www.bigdatau.org/data-science-seminars
Developmental Origins of Brain Circuit Architecture and Psychiatric Disorders (Day 1)
 
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Developmental Origins of Brain Circuit Architecture and Psychiatric Disorders (Day 1) Air date: Thursday, November 29, 2018, 8:30:00 AM Category: Conferences Runtime: 07:43:30 Description: Developmental neurobiology is a critical ingredient for understanding the structure and function of the human brain. Classical anatomists recognized that the brain’s component architecture is most accurately seen through the lens of neurodevelopment. This principle has been further applied to understand the brain’s internal connections, capacity for learning, and functional maturation. By drawing together researchers from different fields, this symposium aims to generate healthy discussion and debate on how advances in neurodevelopment have shaped and will continue to shape, our understanding of brain architecture and function, both in health and in psychiatric disorders. For more information go to https://nimhbraincircuit.com Author: National Institute of Mental Health, NIH Permanent link: https://videocast.nih.gov/launch.asp?27214
Views: 961 nihvcast
Genetic studies on Jews | Wikipedia audio article
 
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This is an audio version of the Wikipedia Article: Genetic studies on Jews Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. You can find other Wikipedia audio articles too at: https://www.youtube.com/channel/UCuKfABj2eGyjH3ntPxp4YeQ You can upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts "The only true wisdom is in knowing you know nothing." - Socrates SUMMARY ======= Genetic studies on Jews are part of the population genetics discipline and are used to better understand the chronology of migration provided by research in other fields, such as history, archaeology, linguistics, and paleontology. These studies investigate the origins of various Jewish populations today. In particular, they investigate whether there is a common genetic heritage among various Jewish populations. Studies of autosomal DNA, which look at the entire DNA mixture, show that Jewish populations have tended to form relatively closely related groups in independent communities with most in a community sharing significant ancestry. For populations of the Jewish diaspora, the genetic composition of Ashkenazi, Sephardi, and Mizrahi Jewish populations show significant amounts of shared Middle Eastern ancestry. According to Behar and colleagues (2010), this is "consistent with a historical formulation of the Jewish people as descending from ancient Hebrew and Israelites of the Levant" and "the dispersion of the people of ancient Israel throughout the Old World". Jews living in the North African, Italian, and Iberian regions show variable frequencies of admixture with the historical non-Jewish population along the maternal lines. In the case of Ashkenazi and Sephardi Jews (in particular Moroccan Jews), who are closely related, the source of non-Jewish admixture is mainly southern European. Behar and colleagues have remarked on an especially close relationship between Ashkenazi Jews and modern Italians. Some studies show that the Bene Israel and Cochin Jews of India, and the Beta Israel of Ethiopia, while more closely resembling the local populations of their native countries, have some ancient Jewish descent.
Views: 98 wikipedia tts
Nickel | Wikipedia audio article
 
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This is an audio version of the Wikipedia Article: Nickel 00:03:13 1 Properties 00:03:22 1.1 Atomic and physical properties 00:04:14 1.1.1 Electron configuration dispute 00:05:07 1.2 Isotopes 00:05:38 1.3 Occurrence 00:08:52 2 Compounds 00:10:28 2.1 Nickel(0) 00:10:52 2.2 Nickel(I) 00:11:34 2.3 Nickel(II) 00:12:19 2.4 Nickel(III) and (IV) 00:14:12 3 History 00:15:06 4 Coinage 00:17:32 4.1 Canada 00:17:48 4.2 Switzerland 00:18:27 4.3 United Kingdom 00:18:41 4.4 United States 00:18:56 4.5 Current use 00:19:44 5 World production 00:20:22 6 Extraction and purification 00:21:41 6.1 Electrorefining 00:23:00 6.2 Mond process 00:23:21 6.3 Metal value 00:24:45 7 Applications 00:26:14 8 Biological role 00:29:30 9 Toxicity 00:31:56 10 References Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. You can find other Wikipedia audio articles too at: https://www.youtube.com/channel/UCuKfABj2eGyjH3ntPxp4YeQ You can upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts "The only true wisdom is in knowing you know nothing." - Socrates SUMMARY ======= Nickel is a chemical element with symbol Ni and atomic number 28. It is a silvery-white lustrous metal with a slight golden tinge. Nickel belongs to the transition metals and is hard and ductile. Pure nickel, powdered to maximize the reactive surface area, shows a significant chemical activity, but larger pieces are slow to react with air under standard conditions because an oxide layer forms on the surface and prevents further corrosion (passivation). Even so, pure native nickel is found in Earth's crust only in tiny amounts, usually in ultramafic rocks, and in the interiors of larger nickel–iron meteorites that were not exposed to oxygen when outside Earth's atmosphere. Meteoric nickel is found in combination with iron, a reflection of the origin of those elements as major end products of supernova nucleosynthesis. An iron–nickel mixture is thought to compose Earth's inner core.Use of nickel (as a natural meteoric nickel–iron alloy) has been traced as far back as 3500 BCE. Nickel was first isolated and classified as a chemical element in 1751 by Axel Fredrik Cronstedt, who initially mistook the ore for a copper mineral, in the cobalt mines of Los, Hälsingland, Sweden. The element's name comes from a mischievous sprite of German miner mythology, Nickel (similar to Old Nick), who personified the fact that copper-nickel ores resisted refinement into copper. An economically important source of nickel is the iron ore limonite, which often contains 1–2% nickel. Nickel's other important ore minerals include pentlandite and a mixture of Ni-rich natural silicates known as garnierite. Major production sites include the Sudbury region in Canada (which is thought to be of meteoric origin), New Caledonia in the Pacific, and Norilsk in Russia. Nickel is slowly oxidized by air at room temperature and is considered corrosion-resistant. Historically, it has been used for plating iron and brass, coating chemistry equipment, and manufacturing certain alloys that retain a high silvery polish, such as German silver. About 9% of world nickel production is still used for corrosion-resistant nickel plating. Nickel-plated objects sometimes provoke nickel allergy. Nickel has been widely used in coins, though its rising price has led to some replacement with cheaper metals in recent years. Nickel is one of four elements (the others are iron, cobalt, and gadolinium) that are ferromagnetic at approximately room temperature. Alnico permanent magnets based partly on nickel are of intermediate strength between iron-based permanent magnets and rare-earth magnets. The metal is valuable in modern times chiefly in alloys; about 68% of world production is used in stainless steel. A further 10% is used for nickel-based and copper-based alloys, 7% for alloy steels, 3% in foundries, 9% in plating and 4% in other applications, including the fast-growing battery sector. As a compound, nickel has a number of niche chemical manufacturing uses, such as a catalyst for hydrogenation, cathodes for batteries, pigments and metal surface treatments. Nickel is an essential nutrient for some microorganisms and plants that have enzymes with nickel as an active site.
Views: 13 wikipedia tts
2018 Sentinel Initiative Annual Public Workshop
 
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This annual workshop serves as a forum to bring together leading experts and interested stakeholders to discuss the ongoing development of the Sentinel Initiative. The Food and Drug Administration Amendments Act of 2007 authorized the Sentinel Initiative with the charge of utilizing electronic health care data for post market risk identification and analysis of medical product safety.
Views: 1912 Duke Margolis
Healthcare Utilization, Economics and Value (Summary) - Katrina Armstrong
 
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September 28, 2015 - Integrating Genomic Sequencing into Clinical Care: CSER and Beyond More: http://www.genome.gov/27562330
Nickel | Wikipedia audio article
 
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This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Nickel 00:03:14 1 Properties 00:03:23 1.1 Atomic and physical properties 00:04:15 1.1.1 Electron configuration dispute 00:05:09 1.2 Isotopes 00:05:40 1.3 Occurrence 00:08:55 2 Compounds 00:10:31 2.1 Nickel(0) 00:10:56 2.2 Nickel(I) 00:11:38 2.3 Nickel(II) 00:12:23 2.4 Nickel(III) and (IV) 00:14:16 3 History 00:15:10 4 Coinage 00:17:37 4.1 Canada 00:17:54 4.2 Switzerland 00:18:32 4.3 United Kingdom 00:18:47 4.4 United States 00:19:02 4.5 Current use 00:19:50 5 World production 00:20:28 6 Extraction and purification 00:21:47 6.1 Electrorefining 00:23:06 6.2 Mond process 00:23:27 6.3 Metal value 00:24:52 7 Applications 00:26:21 8 Biological role 00:29:37 9 Toxicity 00:32:04 10 References Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts "There is only one good, knowledge, and one evil, ignorance." - Socrates SUMMARY ======= Nickel is a chemical element with symbol Ni and atomic number 28. It is a silvery-white lustrous metal with a slight golden tinge. Nickel belongs to the transition metals and is hard and ductile. Pure nickel, powdered to maximize the reactive surface area, shows a significant chemical activity, but larger pieces are slow to react with air under standard conditions because an oxide layer forms on the surface and prevents further corrosion (passivation). Even so, pure native nickel is found in Earth's crust only in tiny amounts, usually in ultramafic rocks, and in the interiors of larger nickel–iron meteorites that were not exposed to oxygen when outside Earth's atmosphere. Meteoric nickel is found in combination with iron, a reflection of the origin of those elements as major end products of supernova nucleosynthesis. An iron–nickel mixture is thought to compose Earth's inner core.Use of nickel (as a natural meteoric nickel–iron alloy) has been traced as far back as 3500 BCE. Nickel was first isolated and classified as a chemical element in 1751 by Axel Fredrik Cronstedt, who initially mistook the ore for a copper mineral, in the cobalt mines of Los, Hälsingland, Sweden. The element's name comes from a mischievous sprite of German miner mythology, Nickel (similar to Old Nick), who personified the fact that copper-nickel ores resisted refinement into copper. An economically important source of nickel is the iron ore limonite, which often contains 1–2% nickel. Nickel's other important ore minerals include pentlandite and a mixture of Ni-rich natural silicates known as garnierite. Major production sites include the Sudbury region in Canada (which is thought to be of meteoric origin), New Caledonia in the Pacific, and Norilsk in Russia. Nickel is slowly oxidized by air at room temperature and is considered corrosion-resistant. Historically, it has been used for plating iron and brass, coating chemistry equipment, and manufacturing certain alloys that retain a high silvery polish, such as German silver. About 9% of world nickel production is still used for corrosion-resistant nickel plating. Nickel-plated objects sometimes provoke nickel allergy. Nickel has been widely used in coins, though its rising price has led to some replacement with cheaper metals in recent years. Nickel is one of four elements (the others are iron, cobalt, and gadolinium) that are ferromagnetic at approximately room temperature. Alnico permanent magnets based partly on nickel are of intermediate strength between iron-based permanent magnets and rare-earth magnets. The metal is valuable in modern times chiefly in alloys; about 68% of world production is used in stainless steel. A further 10% is used for nickel-based and copper-based alloys, 7% for alloy steels, 3% in foundries, 9% in plating and 4% in other applications, including the fast-growing battery sector. As a compound, nickel has a number of niche chemical manufacturing uses, such as a catalyst for hydrogenation, cathodes for batteries, pigments and metal surface treatments. Nickel is an essential nutrient for some microorganisms a ...
Views: 25 wikipedia tts
Nickel | Wikipedia audio article
 
37:00
This is an audio version of the Wikipedia Article: Nickel 00:03:13 1 Properties 00:03:22 1.1 Atomic and physical properties 00:04:14 1.1.1 Electron configuration dispute 00:05:08 1.2 Isotopes 00:05:38 1.3 Occurrence 00:08:52 2 Compounds 00:10:28 2.1 Nickel(0) 00:10:53 2.2 Nickel(I) 00:11:35 2.3 Nickel(II) 00:12:20 2.4 Nickel(III) and (IV) 00:14:13 3 History 00:15:06 4 Coinage 00:17:33 4.1 Canada 00:17:49 4.2 Switzerland 00:18:28 4.3 United Kingdom 00:18:42 4.4 United States 00:18:57 4.5 Current use 00:19:45 5 World production 00:20:23 6 Extraction and purification 00:21:42 6.1 Electrorefining 00:23:01 6.2 Mond process 00:23:22 6.3 Metal value 00:24:46 7 Applications 00:26:15 8 Biological role 00:29:31 9 Toxicity 00:31:58 10 References Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. You can find other Wikipedia audio articles too at: https://www.youtube.com/channel/UCuKfABj2eGyjH3ntPxp4YeQ You can upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts "The only true wisdom is in knowing you know nothing." - Socrates SUMMARY ======= Nickel is a chemical element with symbol Ni and atomic number 28. It is a silvery-white lustrous metal with a slight golden tinge. Nickel belongs to the transition metals and is hard and ductile. Pure nickel, powdered to maximize the reactive surface area, shows a significant chemical activity, but larger pieces are slow to react with air under standard conditions because an oxide layer forms on the surface and prevents further corrosion (passivation). Even so, pure native nickel is found in Earth's crust only in tiny amounts, usually in ultramafic rocks, and in the interiors of larger nickel–iron meteorites that were not exposed to oxygen when outside Earth's atmosphere. Meteoric nickel is found in combination with iron, a reflection of the origin of those elements as major end products of supernova nucleosynthesis. An iron–nickel mixture is thought to compose Earth's inner core.Use of nickel (as a natural meteoric nickel–iron alloy) has been traced as far back as 3500 BCE. Nickel was first isolated and classified as a chemical element in 1751 by Axel Fredrik Cronstedt, who initially mistook the ore for a copper mineral, in the cobalt mines of Los, Hälsingland, Sweden. The element's name comes from a mischievous sprite of German miner mythology, Nickel (similar to Old Nick), who personified the fact that copper-nickel ores resisted refinement into copper. An economically important source of nickel is the iron ore limonite, which often contains 1–2% nickel. Nickel's other important ore minerals include pentlandite and a mixture of Ni-rich natural silicates known as garnierite. Major production sites include the Sudbury region in Canada (which is thought to be of meteoric origin), New Caledonia in the Pacific, and Norilsk in Russia. Nickel is slowly oxidized by air at room temperature and is considered corrosion-resistant. Historically, it has been used for plating iron and brass, coating chemistry equipment, and manufacturing certain alloys that retain a high silvery polish, such as German silver. About 9% of world nickel production is still used for corrosion-resistant nickel plating. Nickel-plated objects sometimes provoke nickel allergy. Nickel has been widely used in coins, though its rising price has led to some replacement with cheaper metals in recent years. Nickel is one of four elements (the others are iron, cobalt, and gadolinium) that are ferromagnetic at approximately room temperature. Alnico permanent magnets based partly on nickel are of intermediate strength between iron-based permanent magnets and rare-earth magnets. The metal is valuable in modern times chiefly in alloys; about 68% of world production is used in stainless steel. A further 10% is used for nickel-based and copper-based alloys, 7% for alloy steels, 3% in foundries, 9% in plating and 4% in other applications, including the fast-growing battery sector. As a compound, nickel has a number of niche chemical manufacturing uses, such as a catalyst for hydrogenation, cathodes for batteries, pigments and metal surface treatments. Nickel is an essential nutrient for some microorganisms and plants that have enzymes with nickel as an active site.
Views: 15 wikipedia tts
Machine intelligence | Wikipedia audio article
 
01:48:36
This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Artificial_intelligence 00:05:06 1 History 00:12:09 2 Basics 00:20:38 3 Problems 00:21:15 3.1 Reasoning, problem solving 00:22:08 3.2 Knowledge representation 00:25:56 3.3 Planning 00:27:03 3.4 Learning 00:28:41 3.5 Natural language processing 00:30:27 3.6 Perception 00:31:24 3.7 Motion and manipulation 00:32:59 3.8 Social intelligence 00:34:25 3.9 General intelligence 00:37:12 4 Approaches 00:38:00 4.1 Cybernetics and brain simulation 00:38:47 4.2 Symbolic 00:39:57 4.2.1 Cognitive simulation 00:40:41 4.2.2 Logic-based 00:41:26 4.2.3 Anti-logic or scruffy 00:42:17 4.2.4 Knowledge-based 00:43:06 4.3 Sub-symbolic 00:43:44 4.3.1 Embodied intelligence 00:44:54 4.3.2 Computational intelligence and soft computing 00:45:43 4.4 Statistical learning 00:47:42 4.5 Integrating the approaches 00:49:55 5 Tools 00:50:15 5.1 Search and optimization 00:53:14 5.2 Logic 00:55:18 5.3 Probabilistic methods for uncertain reasoning 00:57:32 5.4 Classifiers and statistical learning methods 00:59:44 5.5 Artificial neural networks 01:03:12 5.5.1 Deep feedforward neural networks 01:06:05 5.5.2 Deep recurrent neural networks 01:07:40 5.6 Evaluating progress 01:10:47 6 Applications 01:12:03 6.1 Healthcare 01:14:48 6.2 Automotive 01:17:41 6.3 Finance and economics 01:19:41 6.4 Government 01:19:50 6.5 Video games 01:20:33 6.6 Military 01:21:05 6.7 Audit 01:21:32 6.8 Advertising 01:22:14 6.9 Art 01:23:21 7 Philosophy and ethics 01:24:08 7.1 The limits of artificial general intelligence 01:27:09 7.2 Potential harm 01:27:50 7.2.1 Existential risk 01:30:40 7.2.2 Devaluation of humanity 01:31:21 7.2.3 Social justice 01:31:50 7.2.4 Decrease in demand for human labor 01:33:35 7.2.5 Autonomous weapons 01:34:02 7.3 Ethical machines 01:34:30 7.3.1 Artificial moral agents 01:35:17 7.3.2 Machine ethics 01:37:31 7.3.3 Malevolent and friendly AI 01:39:07 7.4 Machine consciousness, sentience and mind 01:39:39 7.4.1 Consciousness 01:41:02 7.4.2 Computationalism and functionalism 01:41:48 7.4.3 Strong AI hypothesis 01:42:25 7.4.4 Robot rights 01:43:02 7.5 Superintelligence 01:43:36 7.5.1 Technological singularity 01:44:54 7.5.2 Transhumanism 01:45:42 8 In fiction 01:48:21 9 See also Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.9710106818362554 Voice name: en-GB-Wavenet-D "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= In the field of computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. More specifically, Kaplan and Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler's Theorem, "AI is whatever hasn't been done yet." For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent routing in content delivery networks and military simulations. Borrowing from the management literat ...
Views: 52 wikipedia tts
Colorado: Energy and Environmental Justice
 
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This presentation will review general environmental justice concerns in Colorado, zeroing in on two significant energy production sectors and their contributions to environmental injustice and public health concerns in Colorado. These include uranium mining/milling for nuclear weapons and power production, as well as unconventional oil and gas production. Stephanie will discuss her active research agendas in each, reviewing findings of several distinct research programs. Date of seminar: February 24th, 2017 Speaker: Stephanie Malin, Assistant Professor, Department of Sociology, CSU
Views: 39 ISESS Fort Collins
Artificial intelligence | Wikipedia audio article
 
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This is an audio version of the Wikipedia Article: Artificial intelligence Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. You can find other Wikipedia audio articles too at: https://www.youtube.com/channel/UCuKfABj2eGyjH3ntPxp4YeQ You can upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts "The only true wisdom is in knowing you know nothing." - Socrates SUMMARY ======= Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler's Theorem, "AI is whatever hasn't been done yet." For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent routing in content delivery networks and military simulations. Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an "AI winter"), followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other. These sub-fields are based on technical considerations, such as particular goals (e.g. "robotics" or "machine learning"), the use of particular tools ("logic" or artificial neural networks), or deep philosophical differences. Subfields have also been based on social factors (particular institutions or the work of particular researchers).The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects. General intelligence is among the field's long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many others. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it". This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI to be a danger to humanity if it progresses unabated. Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.
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