List of Supported Video Sites Video Source URL Support Embed Code Support Extract Title Support Extract Author Support YouTube Yes Yes Yes Yes Vimeo Yes Yes Yes Yes Dailymotion Yes Yes Yes No Discovery No Yes Yes No Howcast Yes Yes Yes No Influxis No Yes No No Khan Academy No Yes Yes Yes MIT Yes Yes Yes No National Geographic ® Yes Yes Yes No SchoolTube ScienceStag e ScreenCast TeacherTube ® TED Yes Yes Yes*** No No Yes Yes No No Yes No No Yes Yes No No Yes Yes Yes No Adobe TV No Yes No No
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Externalities Externalities or spillover occur when some of the benefits or costs of production are not fully reflected in market demand or supply schedules. Some of the benefits or costs of a good may spill over to a third party. It is also called third party effect. Internalizing the external cost/ benefit will lower the impact of externalities. The optimal output level is MSB = MSC. Positive externalities refer to spillover benefits. It occurs when direct consumption by some individuals impact third parties positively. Public health vaccinations and education are two examples. Because some of the benefits accrue to others, [MSB (Marginal Social Benefit) > MPC (Marginal Private Benefit)], individuals will demand too little for themselves, and resources will be underallocated by the market. Correcting for spillover benefits requires that the government somehow increase demand to increase benefits to socially desirable amounts. 1. Government can increase demand by providing subsidies like food stamps and education grants to subsidize consumers. 2. Government can finance production of goods or services such as public education or public health. 3. Government can increase supply by subsidizing production, such as higher education, immunization programs or public hospitals. Negative externalities impact the third party negatively. An example is pollution, which allows the polluter to enjoy lower production costs because the firm is passing along the cost of pollution damage or clean up to society. Because the firm does not bear the entire cost, [MSC (Marginal Social Cost) > MPC (Marginal Private Cost)], it will overallocate resources to production. Correcting for negative externalities requires that government get producers to internalize these costs. 1. Legislation can limit or prohibit pollution, which means the producers must bear costs of antipollution efforts. 2. Specific taxes on the amounts of pollution can be assessed, which causes the firm to cut back on pollution as well as provide funds for government cleanup.
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Rationale for government provision Do the positive externalities from education justify government intervention? Yes A subsidy that equates the MSB with the marginal cost can correct the market failure However, the existence of the externality does not necessitate public provision of education
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Public Goods Private goods are produced through the market because they are divisible and come in units small enough to be afforded by individual buyers. Private goods are subject to the exclusion principle, the idea that those unable and unwilling to pay are excluded from the benefits of the product. Public goods would not be produced through the market, because they are indivisible and are not subject to the exclusion principle. National defense is a public good that is there for all of the U.S. people. Government paid for that through tax revenue. Those who receive benefits without paying are part of the so-called free-rider problem. Private producers would not be able to find enough paying buyers for public goods because of the free-rider problem. Therefore, public goods are not produced voluntarily through the market but must be provided by the public sector and financed by compulsory taxes. Quasi-public goods are those that have large positive externalities, so government will sponsor their provision. Otherwise, they would be underproduced. Medical care, education, and public housing are examples. Public and quasi-public goods are purchased through government, by group, or collective, choice. In a representative democracy that means voting for the candidate whose priorities for spending most closely match your own. According to the survey result, Americans rate education as their number one priority during the last presidential campaign in 2000. Therefore, candidates tried to emphasize their education policies to get more votes. Resources are reallocated from private to public use by levying taxes on households and businesses, thus reducing their purchasing power and using the proceeds to purchase public and quasi-public goods. This can bring about a significant change in the composition of the economy’s total output. Benefit – cost analysis is a technique in decision making process of the public sector. The concept involves comparing the marginal benefit (MB) of extra public goods with the marginal cost (MC) of providing the additional public goods. The rule to follow is that marginal benefit should equal or exceed the marginal cost. If the marginal cost exceeds the marginal benefit, that project should not be selected. When several projects whose MB exceeds or equal to MC are available, the project with the highest total benefit will be selected.
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Exempt Human Subjects Research Decision Trees Educational Exemption (#1) Survey, Interview or Observation of Public Behavior (#2) Benign Behavioral Intervention (#3) Yes Children Established education setting No Comprehensive IRB review Surveys, interviews, tests, or observations No Children Yes No Comprehensive IRB review Yes Educational tests or observation w/o interaction No Yes Comprehensive IRB review No PHI Yes FERPA or PHI No Self-determined Yes No Yes No IRB Determined Self-determined IRB Determined No Comprehensive IRB review Yes Yes Deception Disclosed IRB Determined or IRB Limited Review if identifiable, sensitive data Yes Only PHI No Comprehensive IRB review No Identifiable data Yes Sensitive Data Yes IRB Determined IRB Determined Self-determined IRB Determined No Recorded w/o identifiers No Self-determined Yes IRB Determined Government collected data Yes IRB Determined No Sensitive Data PHI Yes No Yes IRB Limited Review Yes Publicly available No No Yes IRB Determined No PHI PHI Yes Not Regulated No Has deception No Identifiable data No Yes Comprehensive IRB review Yes Adverse impacts on students or teachers No Yes No Normal education practices Secondary Use, No Consent or Broad Consent (#4, 7 & 8) Identifiable data No Benign behavioral interventions Yes Yes Comprehensive IRB review Last Updated: 09/27/17 IRB Determined IRB Limited Review Self-determined Identifiable research data or nonresearch data Yes No Comprehensive IRB review Has broad consent Yes IRB Limited Review
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Other Support vs Biosketches NIH Form Project # Dates Person Months Source Annual DC Title Major Goals JIT Other Support YES YES YES YES YES YES YES RPPR Other Support YES YES YES YES YES YES YES Biosketch YES YES NO YES NO YES YES Pending Complet ed Inactive When submitte d NIH Form Roles Overlap Active JIT Other Support NO YES YES YES NO NO JIT RPPR Other Support NO YES YES NO NO YES PROGRE SS REPORT Biosketch YES NO YES NO YES NO PROPOS AL 21 Other Support Training 03/22/2019
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Bluetooth Bluetooth Feature Evolution Specifcatons 1.1 1.2 2.0 + EDR 2.1 + EDR 3.0 + HS 4.0 Voice Dialing Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Fast Transmission Speeds Yes Yes Yes Yes Lower Power Consumption Bluetooth Low Energy Yes Yes Yes Yes Call Mute Last-Number Redial Yes
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Measurement Tech/Apps Matrix Network Measurement Apps, Tech, Who Matrix 23-Sep-99 Tech\App pchar netperf/ttcp netlogger netflow virtue/pablo/etc gloperf/NWS LDAP SQL database UDP traffic gen Application Team Type admin admin application admin/app application application application application admin UC to Labs yes yes later later NU to ANL IM+ yes yes especially yes later yes especially later especially CAVERNsoft Accessbot yes yes yes ? yes yes yes yes later later yes yes yes yes yes later yes especially Cactus yes yes yes yes later yes yes later yes Mambretti Jason, Andy Jason, Alan Shalf Chuck Sellers Chen Steve Tuecke JJ, Tom Coffin Seidel (FTP mainly) Ian Dan Sandin Linda Ian, Linda Techspert Linda, Alan Ian, Volker Ian, Ruth Mike, Randy Ruth Ian Ian Ian Alan University of Illinois at Chicago
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Attribute Selection U U1 U2 U3 U4 U5 U6 U U1 U2 U3 U4 U5 U6 Muscle-pain Yes Yes Yes Yes No Yes Headache Yes Yes Yes No No No Temp. Normal High Very-high Normal High Very-high Flu No Yes Yes No No Yes Muscle-pain Yes Yes Yes Yes No Yes Temp. Normal High Very-high Normal High Very-high U U1 U2 U3 U4 U5 U6 Flu No Yes Yes No No Yes Headache Yes Yes Yes No No No Temp. Normal High Very-high Normal High Very-high Flu No Yes Yes No No Yes
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Preliminary experiments with sample crawlers Program Allowed Robots.t Resource xt (class) Check -ed? .pdf .doc Banned Resource   (noclass) .html .pdf .doc .html Import.io No No Yes Yes No Yes Yes 80Legs Yes No No Yes No No No Scrapy  No Yes Yes Yes Yes Yes Yes Selenium No No No No No No No ScrapeBox No No Yes Yes No Yes Yes iRobotSoft No No No Yes No No Yes Anenome No No Yes Yes No Yes Yes Selenium was the best, but it does not scale well. The others were not very respectful of robots.txt.
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24 Functions are not Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods are are are are are are are are are are are are are are are are are are are are are are are are not not not not not not not not not not not not not not not not not not not not not not not not Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods are are are are are are are are are are are are are are are are are are are are are are are are not not not not not not not not not not not not not not not not not not not not not not not not Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods F are are are are are are are are are are are are are are are are are are are are are are are are not not not not not not not not not not not not not not not not not not not not not not not not Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods Methods are are are are are are are are are are are are are are are are are are are are are are are are not not not not not not not not not not not not not not not not not not not not not not not not Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions Functions
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Decision System & Reducts (Rough Sets) Reduct1 = {Muscle-pain,Temp.} U U Headache U1 U2 U3 U4 U5 U6 Yes Yes Yes No No No Muscle pain Yes Yes Yes Yes No Yes Temp. Flu Normal High Very-high Normal High Very-high No Yes Yes No No Yes We are looking for rules describing Flu in terms of Headache, Muscle Pain, Temp. Muscle pain U 1,U4 Yes Yes U2 U3,U6 Yes No U5 Temp. Flu Normal High Very-high High No Yes Yes No Reduct2 = {Headache, Temp.} U Headache Temp. Flu U1 U2 U3 U4 U5 U6 Yes Yes Yes No No No Norlmal High Very-high Normal High Very-high No Yes Yes No No Yes
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An Example of Reducts & Core Reduct1 = {Muscle-pain,Temp.} U U Headache U1 U2 U3 U4 U5 U6 Yes Yes Yes No No No Muscle pain Yes Yes Yes Yes No Yes Temp. Flu Normal High Very-high Normal High Very-high No Yes Yes No No Yes CORE = {Headache,Temp}    {MusclePain, Temp} = {Temp} Muscle pain U 1,U4 Yes Yes U2 U3,U6 Yes No U5 Temp. Flu Normal High Very-high High No Yes Yes No Reduct2 = {Headache, Temp.} U Headache Temp. Flu U1 U2 U3 U4 U5 U6 Yes Yes Yes No No No Norlmal High Very-high Normal High Very-high No Yes Yes No No Yes
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Review Options Matrix trained leader agenda established reviewers prepare in advance producer presents product “reader” presents product recorder takes notes checklists used to find errors errors categorized as found issues list created team must * sign-off on result IPR* no maybe maybe maybe no maybe no no no no WT yes yes yes yes no yes no no yes yes IN yes yes yes no yes yes yes yes yes yes RRR yes yes yes no no yes no no yes maybe IPR—informal peer review WT—Walkthrough IN—Inspection RRR—round robin review (no face to face meeting)
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