Okay, it's time to start. Good afternoon. My name is Jun Myung Kang from Hewlett Packard Labs. And then our team is Mario Sanchez from Hewlett Packard Labs. And then we have JK Lee from Barefoot Networks. Today we're gonna talk about policy canvas where we can easily draw our own policies for open stack services. First, we're gonna show the current policy management in open stack. And then we're gonna show the motivating examples in terms of how to define policies. And then we're gonna show our policy canvas as our solution. And then we're gonna show the learning demonstration of our policy canvas on the open stack dashboard. In a countless networks or cloud environment such as the open stack, it's very critical to manage the multiple infrastructure component as a whole such as computing, storage, networking. As there are many different types of services in open stack growing, we need a well-defined policy management framework for open stack. As you know, there are multiple policy writers who want to define their own policies such as the cloud operator, network administrators or application developers. But sometimes a software-defined application itself can define their own policies. We have many multiple different types of dimensions dealing with maybe security, performance, availability and some middle boxes such as a firewall, DPI, IDS. In this talk, we're gonna tackle networking policies but we believe that our insight can be applied to the other types of policies. Okay, as you know currently we are using the security group and rules which can allow or deny some protocols or ports from source to the destinations. Maybe we can associate this group or rules to a specific VM or a specific network port. In terms of automations of cloud orchestration, we can use the HIST service with some predefined template which can guide how to define groups or rules. In terms of some application-specific policies, maybe you can use Murano service. However, this groups or rules definition is a two-level command which is a little hard to use for some older users. While this interface is fragmented, that means the multiple commands are scattered of the multiple data sources. Even though we have same policies, we have to use the multiple data sources. In terms of high-level intent-based management for OpenStack, group-based policy, GVP has been introduced. Instead of writing policies for the specific endpoint, GVP defines a group of endpoints and write policies for the communication between the EPGs, endpoint groups. However, just EPG definitions, creations, and association with the EP should be done by only via the GVP APIs. There is no way to leverage endpoint properties while policies in existing OpenStack. As you know, we have multiple policies from multiple writers, so GVP doesn't handle these multiple-writer problems. Finally, we have a very well-defined Congress service as a global policy management framework for OpenStack, has been actively integrated in the current OpenStack list. Congress basically can get some system state of the cloud from the many multiple data sources such as Nova, Neutron, Swift, and so on. And then it can verify if the cloud provides the policies. As you can see in this example, Congress is using the variant of SQL-like data log language to define the policies. And then it can provide some simple table join for the multiple policies. Actually, this data log has very good expressiveness and bust style. However, we require steep learning curve to data log and also it doesn't handle some multiple-writer problems. In order to overcome these limitations, we need to decouple some high-level intent from the underlying low-level interfaces. And also the interface should be easy to use, intuitive and high-level interfaces. And so we need some automatically deployed policies to the infrastructure and the scalability. So we are proposing the policy canvas which can draw our network policies for OpenStack services. Actually, we got an idea from the real-world examples. When we define or when we update some policies, usually we have some face-to-face meeting or some online meeting from a bunch of people from different organizations. Mostly we are using the whiteboard for discussing the some policies because it is very easy to use and user-friendly. After discussion and then deciding the policies, we can assign the task to the IT relevant people and then they can use the CLI command or management framework to using the low-level command for the dead policies. Our idea is maybe let the users easily express policies as easy as drawing diagrams on the whiteboard. And our system can take this diagram and then generate the all-relevant command or API automatically. Okay, we have multiple policies from the multiple data sources and then they can create their own policies using our policy canvas. And our policy canvas can generate all-relevant rules using the OpenStack OpenAPIs. Okay, I'm going to hand over to JK for more details about our policy canvas. Thanks, Jun. Okay, so policy canvas is built on top of two main concepts, graph abstraction and graph composition. As you know, graph can naturally express various networking policies using its node expression and then edges between them. The graph is easy to read and write by the human users, but also it's readable by the system. So you can use and leverage existing graph theories and graph algorithms to analyze, compose, and verify the policies written in graphs. So we take those multiple input policies written in, express as a graph from different policy sources and compose them into one big combined graph, the system-wide graph, conflict-free. So we are reserving the conflicts and doing this composition proactively prior to deploy those policies down to the runtime system. So it gives a chance to each policy writer to review their policy in the final form in the compose graph. And it basically prevents the unexpected system behavior from the runtime system because it will be too late to detect and then fix such a conflict in operational network. And this kind of compose graph can be used as a ground truth for policy enforcement and runtime troubleshooting. So let me talk a little bit more about the PGA, policy graph abstraction and its composition algorithm. So PGA graph model has nodes and edges and each node represents a set of, a group of endpoints sharing the same property. In this example, we have a policy P1 from application admin. It allows the communication from the marketing employees to the web servers for the HTTPS traffic. And the traffic should go through the load balancer, LB function box in the middle. So it's an accurate policy and also middle box policy. It's all expressed in one graph. And we are using the different color to express the user intent that this communication is allowed exclusively to the marketing. Then we have a similar graph from the cloud operator P2 allowing some traffic from campus to the cloud and the traffic should be monitored by the by counter BC box. And as you can notice here, the EPG nodes are defined of logical labors like a marketing web and cloud campus. They are not just random words. They are well defined logical names or labors. And they are defined from existing data sources. For example, the location information from the open stack keystone or NOVOT data services or the employee identities or the application like a web and database, this can be also extracted from the Murano and other data sources. So using those logical labors, we decoupled the policy expression from the low level specifics like IP address or MAC address so that this policy can be reused and portably on multiple different network targets. So for the competition, we compute the union of the input policies using some satiric Venn diagram analysis. So we detect the intersection between two policies P1 and P2 and see if there is any conflict. If there is a conflict, reserve the conflict by using some constraints specified in the original input policy graphs. For example, there is a conflict between P1 and P2 for the communication, the HTTP communication from non-marketing employees to the web server in the cloud we will show in the next diagram and that conflict is reserved by using the exclusive requirement from the P1 as a constraint in the composition process. After composition, we store the composed graph as a set of these two in policies. This normalization is pretty useful to make the runtime system to be able to look up the policies in a constant look up. You can make build as fast and pretty scalable runtime system. So that was the theory and this is the example that we composed from the two input policies. For that we need some relationship between labors. For example, here we leverage the information that marketing employees are in campus and web servers are deployed in the cloud so that we know that the marketing label and campus label, they need to be composed together. But there's no need to compose marketing label and cloud label because marketing employees will not be placed in the cloud anyway. And this composed graph, you can easily walk through it and verify what's going on in the final version. For example, there is no edge from non-marketing and campus to the web in cloud, correctly implementing the exclusive access requirement from P1. So this is the same policy written in English but it's not really readable by the machine. So human user needs to basically read through it, detect some overlapping relationship, conflict and somehow compose them into this kind of set of prioritized rules using GVP or group-based policy or maybe OpenFlow rule table expressions. So this kind of careful insertion of prioritization can be done in composing maybe few number of policies but it will be challenging to compose multiple maybe more than dozens of policies. And we believe that composing policies in such a prioritized rule form is too low level. The rule sets already kind of compiled version of intents and policy. So we need more higher level abstraction like this graph abstraction we have here. Then the system can automatically compose them into one big graph. So here we have a advanced version of the different policy grabbing examples. And we are using different type of colors or node shape or edge shape to clearly capture the intents of the policy writers. And we also have a label namespace or label trees defining the relationship between labels. Like I said before, in order to proactively compose such a policies written in labels, we need the relationships. And here we have three type of trees. For example, tenant tree, location tree and security status tree saying whether the virtual machine is normal status or quarantine status. So these are maintained by different sources and we extract them and maintain in the tree data structure. So for the labels with the parent-child relationships, for example the application and database labor, they have overlapping relationships. We know for sure that we need to compose the policies written for application database. But at the same time, the labels like a campus A and campus B, they have sibling relationships. They are mutually exclusive. No virtual machine will be placed in campus A or campus B at the same time. So we don't need to compose them together. Basically scoping down the composition scope and make the composition algorithm way more scalable. So to test the scalability, we took 20,000 accurate policies from global HBIT and written for more than hundreds of departments and augmented the accurate policy with service policies, compose them into one big million edge graph taking the 30 minutes. So while we're doing this composition, we realize that the existing accurate policy expressions, for example, do not clearly reveal the hidden intents of users. So when you write the whitelisting policy, you know for sure you want to allow the HTTPS traffic from source and destination, but it's not clear what do you want for the rest of it. Do you want to actually deny them or just don't care about that? If it's an application policy, you just want to allow HTTPS traffic for your web server to correctly operate, but you may not care about the other ports. It's similar to the blacklisting. So to handle this problem, we divide some four type of intern accurate edges starting from must allow, can communicate, which is kind of weak allow, block, and conditioner. These are quite useful to clearly capture the actual user intents for the whitelisting, blacklisting, or application demand. And it drastically reduces the chance of conflict between allow and deny policies from the conventional model from 50% down to something like 12%. So it greatly helps the systematic composition of such a different policies. So while the June and Mario will talk about our PGA Implementation System in OpenStack, we also have some of the Grab Compiler and Accra Intent APIs adapted by Open Daylight NIC project. So it will help us to render the policy down to the network. And there are also full papers and demos and talks if you want more information, please refer to them. Let me hand over to June. Thank you, JK. Okay, let's dive into the more interesting part and in terms of how we implemented policy canvas on the OpenStack. Like other OpenStack services, policy canvas is composed of three main parts, PGA Begn the Service and Python Client and Horizon GUI as our policy canvas GUI module. Using the policy canvas GUI, we can manage different types of policy graph and also we can create our own policies by just drawing the policy graph. Python Client can provide a CLI command and also Python binding APIs. And PGA Service can manage the PGA resources such as input, composed, deployed policy graph and label trees and function boxes. We have three types of underlying drivers, label drivers, compilation drivers and enforcement drivers. From the next slide, I'm going to show you how to use these driver modules for supporting PGA Service. Okay, I'm going to show how to create the policy graph and then how to compose multiple policy graph. As JK mentioned previously, we are using the label tree for creating the policy graph. We can get the system state from the label drivers and then you can give the label tree which is automatically created from the label drivers. And then you can use this label tree for creating our own policy by just drawing this policy graph. We can get this policy graph from multiple data sources, multiple user or multiple applications. And then we can give this multiple policy graph to the PGA Service. PGA Service can use a compilation driver for composing this multiple input policy graph by resolving the conflict as much as possible. Currently we have our own PGA graph composer and also as JK mentioned, we have another graph compiler in the Open Daylight NIC project. And compilation drivers can return this result to the composed graph and then we can show this result graph to the policy canvas. Okay, after composition and then we can maybe deploy one of the composed graph through the PGA Service. Basically this composed graph is a set of nodes and actions which means that a set of classifiers and set of actions. We can create this classifier and action through our enforcement drivers. Currently we have a neutron driver which can create a secret group or SFC or middle boxes through the neutron open APIs in terms of the actions. And then we have another congress driver for classifications. We can automatically generate the data log rules based on the EPG definitions in terms of classifier. Okay, after deploying all of our policy graph to the infrastructure. So maybe we have one new virtual machine. Congress can detect the direction new virtual machine in that it can update the congress table and then it can notify our congress drivers. Congress can driver maybe can use the congress excuse function or currently we are using our neutron driver for associating space-based secret group to the endpoint. So we don't need to create manually here. So all processes automatically map associated secret group and endpoint groups. Okay, I am going to hand over to the Mario. Mario will show the learning policy canvas demonstration. Thank you. So yeah, now we're going to actually dig into a video demo that we're going to show you of the system working. This slide is just to show you really quickly what our setup is going to be for the demo. In this case, we have our open, our policy canvas installed in the Mitaka OpenStack release using DevStack. We're going to have four different compute nodes in our setup. The different machines will be divided in a couple of different availability zones. And then we're going to use our policy canvas to create policies from the standpoint of two different stakeholders that we call host manager and zone manager. Then we're going to have different policies to deploy into the system and we're going to see how our system composes them and deploys them onto the infrastructure. Don't worry so much about the specific policies right now. That's going to be shown in the video next. So let me show hop into the video. Okay, so our demo scenario, like I said, has four different compute nodes split across two different availability zones, AC1 and AC2. In this case, two of the nodes belong to AC1, which is highlighted in green here. And the other two nodes belong to AC2, which is highlighted in blue. In this case, we're going to spin up four different virtual machines, each of which will run in a different compute node. And all of them will be connected to a single virtual private network. In this case, in our DevStack scenario, I'm going to show you next that we have only a single security group defined that will be applied to all of the VMs that are going to be created. And this default security group only has information, a single rule, that will allow us to SSH into the system, in this case. But that's the only thing we will do. So next, we're going to fast forward the video a little bit just to show the automatic creation of the VMs using the Nova CLI. And here on the right is just the horizon view of the VMs being created. So once the VMs are created, we're going to open two different terminals. The one on the top left is going to correspond to the VM1, which is instantiated in a compute node that belongs to AC1, availability zone 1. The second one will correspond to the VM3, which is a VM that belongs to availability zone 2 in this case. So next, we're going to start using our policy canvas to create the policies from the standpoint of these different two stakeholders. In the first case, we have a zone manager that only cares about connectivity between availability zones. In this case, this zone manager wants to specify a rule, a policy that allows HTTP traffic between VMs instantiated in availability zone 1 towards VM running in availability zone 2 because those are, for example, web servers. So in order for us to do this, to express it through the canvas, all we have to do is create a new policy canvas, an empty input policy canvas. We specify descriptions and the domain where it's going to be hosted in. From there, we click into the canvas. And what we're going to do is we're going to drag from the label tree in the center the different labels that actually work in this policy. In this case, we're going to be dragging from the label tree into the canvas, the label that corresponds to AC1 and AC2. Once we do that, all we have to do is create a unidirectional edge between AC1 to AC2. And all we do is allow HTTP traffic between them. Once we do that, we save the graph and we're basically done. The policy is specified. This is what the graph looks like once it's actually composed. So next, we're going to create the policies from the second stakeholder point of view. In this case, it's what we call the host manager. In our toy example, for some reason, this host manager only cares about connectivity between compute nodes. He doesn't care about connectivity between availability zones. So in this case, she wants to define a policy that allows traffic, SSH and ICMP traffic between VMs instantiated in CNC32 toward VMs created in compute node CNC3 in this case. So we're going to do that by again creating an empty input policy graph through our canvas. And what we're going to do, we go into the graph and what we're going to do is drag from the label tree, the labels that corresponds to CNC32 and CNC3 in this case. Once we do that, we create an edge between CNC32 and 3. And we're going to specify that ICMP and SSH traffic can be allowed between these two endpoints from CNC32 towards CNC3. Once we do that, we save the graph and we're done again. The policy is specified. So from here, what we have to do next is deploy the graph. To do that, first we're going to just open up a couple of different windows on the left to show you the original input policy graphs we just created so that you can keep them in mind before composition. So here in the top, we're showing the host policy graph and we're going to show the zone policy graph underneath. So from there, what we're going to do is compose a graph. We go into the policy graph canvas on the right. We select compose. And from there, we're just going to have to select the two different policies that we want to compose in this case, which are the ones we just created, which are a host policy and a zone policy. We click compose and the composition is done. In this case, this is what the compose graph looks like on the right. So from here, you can see that our PGA service automatically creates a unified conflict-free graph on the right. Had there been any conflicts in the composition of these two policies, it would have shown us a pop-up telling us that there was a problem that needs to be addressed. In this case, there were no conflicts, so the graph is created. So the last step then is, once we compose, what we have to do is deploy that into the system. The last thing we're going to do then is go into the canvas and we're going to select deploy graph and we're going to select the recently composed graph for deployment. From there, we select the graph and we click deploy. Once this happens, we're basically done. The policies have been deployed down to the infrastructure. In this case, the policy canvas will automatically create the required security groups into Neutron with the desired rules that we want and will automatically apply these security rules to the VMs that classify depending on the different EPGs that were just created using our labels. So in this case, we're just going into the security group tab where you can see that they were already created automatically with some rules that make sense according to the graphs. Then we're showing you one of the VMs and how the specific rules were applied to that particular VM. So next, what we're going to do is a quick connectivity test just for one of the policies to show you that this thing is actually working. And in this case, we're going to be testing the availability zone policy and we're going to be testing HTTP traffic between VM1 and VM3. VM1, remember, is hosted in AC1 and VM3 is hosted in AC3. So in this case, we're just tailing the log for the web server that is running on VM3. So you can see when the GET actually hits the server. And then we're just going to launch a WGET from VM1 towards VM3. And because it was already specified in the policies, it should go through. And in this case, it actually goes through. But if we do the reverse test, we try to do an HTTP GET from VM3 towards VM1 because it wasn't explicitly allowed in the input policy, it should not go through. And in this case, we are just doing that, doing a WGET from VM3 towards VM1 and it doesn't go through. We could do the same test for the other two policies but in the interest of time, we're just going to skip those. So the last thing I want to show you is how our policy canvas automatically is able to discover new VMs, assign them to a specific EPGs, depending on the characteristics of the VM and apply the actual security policies without us having to do anything. Everything is done automatically. So in this case, we're going to use HorizonView to create a new VM that belongs to AC2. We're just going to click through a couple of different static options or default options. And then we're going to hit Create. When that happens, like I said, our policy canvas will automatically identify the VM, tag it with the appropriate labels, decide which security groups apply to it and actually apply them. And in this case, we're seeing how the VM is being created. The last thing is just to show that the security groups were actually applied to it. So that's what we have for the demo here. We're going to jump back on the slides. So when we're thinking about future work or next step for our policy canvas, we're thinking about, I don't know if you noticed many of the things that we showed has to do with ACL-like policies, allow, deny in the network. In this case, we're thinking about being able to, for example, extended the canvas so that we can import policies that were not specified through the canvas itself. Example, application actually created the security rules directly on Nova. I'm sorry, on Neutron. So in this case, we should be able to load them into our policy canvas, express them in the same format, graph format and be able to use the composition algorithm that PGS provides. We're also thinking about being able, for example, to provide things like composing newly added features into Neutron. For example, QOS specifications and specific links should be fairly easily to be implemented in this graph-like abstraction. And finally, for example, being able to provide port-level connectivity that is implied in this ACL-type of rules. For example, if you're assuming that you're allowing connection, that means that their connection already exists and then you are providing they allow entry on top of it. We see a way where we can easily express port-level connectivity into the graph so that policies like this VM must be connected to this particular net what can be expressed.  Okay, so let me switch your gear a little bit here. So far, we talked about how to express policies and compose them into one big compose policy graph. Once we have it, we need to push this down to the network data planes to enforce the policies. But the data planes can have many different forms, hardware, software, etch, core. And the question is that whether this network can implement my policy correctly or not. Because different data planes have different capabilities and limitations. So it would be great to have some common clean abstraction to capture such different properties of data planes. Taking one step further, if we can actually program the policy directly down to the data plane, then we don't really need to retrofit our policy into the fixed data plane, but actually we can redefine the data plane in a way such that policy can be enforced in the best way. And finally, if you have a policy enforced down the data plane, then you want to verify it. That means that you we want to have some kind of complete network visibility. For that, there are a couple of a few industry-wide open source efforts starting from OpenFlow Data Plane Abstraction or Open Compute Project has switch abstraction interface, PSI, and P4 as a language to program the flexible data plane. For now, let me talk a little bit about P4 and its benefits in policy enforcement. So P4 is a high-level language to define the data plane. And it's a kind of C-style language that you can define how table operates in terms of match and action and you can also define the control flow between different tables. And it provides the abstract forwarding model, so it's a protocol-independent or target-independent. It's open source approach to version 2 license. And it's been adapted pretty well by the community. For example, HP's OpenSwitch network operating system replaced OpenVswitch by P4 as a default data plane emulator for development and testing. And OpenCompute.Sci was adapted P4 as an abstraction language. With P4, we can do something like this. You can pick the best protocol suited for your policy for example VXLAN or whatever incarceration protocol and remove all the others that are not really needed. Or you can define your own custom protocol for service function chaining. And you can also instrument the switches to embed switch information like a switch ID, port ID or latency experienced by the packet directly into the data packet so that you can have a complete visibility of the network and the path and many more information of the network. You can easily verify the policy in that way. So traditionally to push policy down to the data plane we use some controller APIs to populate the rules of the fixed data plane tables. But with P4 you can define your best data plane programming in P4 language and compile it through the program of the data plane whether hardware or software. The compiler can also auto generate APIs for the controller to populate the rules in the new data plane. So this could be the better way to push your policy down to the data plane. With that, let me hand over to June to conclude. In this talk we showed our policy canvas effort which is two simpler and intuitive abstractions for writing our policies just like the drawing graph. It is portable and also we can also automatically create all low-level commands from the high-level graph model and then we can deploy the infrastructures. Our current status we have a learning GUI on the open-step horizon and also we have a PGA service and all relevant APIs and also we have two neutron and congress drivers for deployment. So we have another graph compiler in Open Daylight Nick. In terms of collaborations with the open-step community we need more use cases and feedback we can express the graph form and also we would like to maybe contribute our code to the open-step community. Okay, thank you. And then we can have some clarifications. Thanks, really interesting stuff. I'm a little confused over what you call your label tree because when I think of labels I don't think of a tree at all and I'm trying to understand what kind of constraints come along with it and I know you talked about it early on but you went through it really fast. Could you maybe just spend a quick minute again on that? Sure, that's a great question. So you can start from think about the label as a common tagging or metadata mechanism used in for example Docker or any policy management system or even SC Linux, Security Linux Linux allow users to define some policies using high-level labels. So labels are just a kind of tagging or metadata that can be mapped to any endpoint. So there must be a mapping mechanism labeled down to actual endpoints. So actually the Open Daylight also has such a label mapping service which provides some kind of database or a set of coding services so that whenever the virtual machine or a network endpoint shows up in the system it may have some properties like location and owner and these can be expressed as a labels. So we are leveraging that so that we can express the policies purely in the label and later enforce down to infrastructure using such a mapping system. But label tree is another way to actually capture the relationship between labels so that we can proactively analyze the policies written in labels and compose them. So there is some inference going on actually it's an ongoing effort. For example the label tree we showed in the demo the location label tree is automatically constructed by reading the database of the NOVA and KISTAN because that's where the availability zones and then compute node informations are stored and there is a relationship between compute node and then availability zone already available in the database. So we extract this information and then model in the tree data structure. And there are some relationship between different type of labels like location and then tenant ID. They cannot be modeled as a one tree so that's why we have multiple trees. The relationship between different trees are labels belonging to different trees are modeled as a separate mapping data structure. Yep, hey thank you very good presentation. One question I had is is there plans to do policy across regions so where I could define a policy and then select instances from multiple regions? Yeah, so the algorithm and then abstraction itself does not limit and actually it's a design in a way such that we can apply the same policy across different regions and then if maybe different region have a different region manager they have their own regional policy and then you want to probably deploy the same tenant policy or application policy defined once and enforce down to different regions. Yeah, that's definitely possible. We haven't implemented that way so far because we were not able to actually model the regions in our small environment that theoretically definitely possible. So you can build like a layer of abstraction on top for multi-region. Thank you. Right, then thank you very much. If you have any other questions then just feel free to grab us in the podium. Thank you.


And from our president of the Nigerian Senate, Abubakabu Kola Sarakee has declared his intention to run for president in 2023. Sarakee threw his official Facebook page Wednesday, called on the people to join him in making the community safer and provide real opportunities for everyone. He's quoted as saying, I have a strong record of delivering an experience in making tough decisions. Let's build an Nigeria that works for everyone. Hello, hope you enjoyed the news. Please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates.


High school students that participate in the Navy Junior Reserve Officer Training Corps program typically have aspirations of joining the military. One such student is senior Quinton Fisher, the son of a retired Navy chief. He has worked long and hard to earn a full-ride scholarship to the University of South Carolina through NJRO-TC. The dedication seen in this student is a direct reflection of the support he has had from a strong family, especially his father, Edmund Fisher. It's hard for my dad to balance trying to take care of me with my life and my life as a senior going to college with the lives of my three younger siblings. But he tries his best and he does really well and he tries to help me out in all areas of my life. And that's the thing that I'm really proud of. Edmund has a reputation for being Quinton's number one fan and can always be seen cheering his son on at the different events he participates in. Now that his son is on track to become a naval officer, one question remained for the former chief petty officer. That's what I wanted him to achieve, something more that I didn't get able to achieve. So by him outranking me, I told him whenever he does become that instant, I will be in uniform no matter if I lose 30 pounds or not, but I will be in uniform to render him his first salute. And hopefully he gives me back the proper salute. So I just feel like it's a great accomplishment on him and a great push on his mom and dad. Lance Corporal Tony Nardiolo, AFN, Rota.


What's up guys, Ruxen34 back. Today we have a first edition Metal Raiders booster box. This is going to be insane. 35,000 subscriber special. I am extremely excited about this one. I should have done this a long time ago back when they were like $2,000 earlier this year, but now I had to pay $5,000, but that is totally worth it because it's going to be awesome. So the giveaway for this video, I'll be giving away nine of the 10 Super Raiders from Metal Raiders. I'm only missing Song of the Thunder. All nine of these will be given away to one of you guys. All you have to do is like the video, be subscribed and just leave a comment on the video. It doesn't matter what it is. It can be about Metal Raiders, it can be about $35,000, whatever. I don't care. It's going to be awesome. I was going to give away some Ultras, but all I had was Magic Jammer and Horn of Heaven, and with our luck of me pulling what I give away, I was not about to risk that. So I'm not giving away Magic Jammer and Horn of Heaven, but you get nine of the Super Raiders. Now let's get into this. We are opening a $5,000 booster box, and we are not weighing out the packs. We're opening all 24 packs because I want rares, I want comments, and because it's just more fun. It's just more fun when you don't weigh out the packs. Less costs effective, that's for sure. Okay, let's just do this. The Ultimate, the Legendary. Let's check out the box first. The Legendary, Pakenio Moth can be pulled in here. That is our number one goal, obviously. And then also, this is a Gate Guardian box. If you check out the IPC up there, it's a little bit hard because the crimson, the way that's a four nine, I believe. So you can pull Gate Guardian in here. That is, that would be incredible. We're about to break the seal of a $5,000 box. Here we go. We got some, okay, we gotta do that. Here we go. There it is. We just broke the seal of a $5,000 box. It also broke like a legit box. So that's good. We also have to worry a little bit about reseals. People don't really reseal Metal Raiders, but recently almost everything is getting resealed. So I think I got it from a legit seller. So I think we're fine.  So this felt pretty good. Felt pretty good. Let's make sure there's no like crazy 2020 packs in here or something. And it looks so far like we have a 100% legit Metal Raiders box. There's also one other potential crazy thing that could happen. I have heard of a box that had all hollows in it, 24 hollows. The chances of that are basically zero. But I did want to throw that out there just in case it does happen that I look like a genius. But let's go ahead and start. We're probably, the ratios are usually four supers, two ultras and one secret. I needed to announce that ahead of time because when I opened LOB, people were acting like I was supposed to pull a billion hollows or something. That was weird. I don't know. It was weird. So let's just go ahead and do this. Let's make sure we're focused in first edition Metal Raiders. I have opened like eight packs, maybe total of first edition Metal Raiders. So this is going to be pretty exciting. The second set in Yu-Gi-Oh! history right after Legend of Blue Eyes. Some really awesome cards in here. Okay, we definitely want it. Okay, we definitely look like we have a normal legit box. So here we go. For supers, I would love to pull the Gay Guardian pieces. For ultras, obviously the top seven cards would be great. Number one would be Summon Skull. I do have a Beast Skull already so I'm not trying to pull that necessarily, but I wouldn't be mad. Prevent Rat. Launcher Spider classic. Magic Jammer right off the bat. That hurts so much. Okay, let's check the centering out. Okay, here's the thing with Magic Jammer. It's always in here. But the good thing about Magic Jammer is I did have it as a kid. I thought it was really cool. This card actually looks like maybe I could get it in, which would be cool because I don't have it. So that would be good. However, it is still Magic Jammer, not the one we're looking for. But overall, out of this whole box, I would like to pull one Ultra and a Gate Guardian. That one good Ultra. So if we pull a Magic Jammer and one other Ultra that's really good and a Gate Guardian, I would consider this box definitely a win. Definitely not how we wanted to start, but that's okay. We still have a lot more cards we can pull. We definitely can pull some good rares like we definitely pulled Magician of Faith. That would be incredible. There's some good commons like Thunder Dragon. We want to pull that. Okay, this we got to be, we got to be more aggressive with these packs. We don't want to ding any corners on the way out because these cards are expensive. Ginzo number seven, our buddy Ginzo. Deep Sea Shark. Probably going to have to sleeve up all these commons as well. These are actually like really good condition. The centering is terrible on that guy. Sort of deep-seated and a Star Boy. So we are not going to get the mythical 24 hollow box that looks like Star Boy with a rare. We're going to sleeve up all our rares. Swamp Battle Guard, Tremendous Fire, and a Trent, the Int. Trent the Int. Okay. Okay. Magic Jammer. What a way to start. I feel like I opened a lot in Portuguese first edition boxes and there was almost always either a Magic Jammer, a Seven Tools, or a Horn of Heaven in the box. All right. Guilty of the D Knight. Electric Lizard. Doma of the Angel of Silence. Rainbow Flower. And a Blade Fly. Okay. Not the greatest rare, but that's okay. Let's check out the centering on it. I will probably definitely grade the rares and potentially some of the commons. Armored Zombie. Battle Steer. There is a lot of cards and metal rares too. I think there's like 143 or something. And that includes the secrets of 144 maybe. I think Thousand Dragon is number 143. Okay. The Lady Dithy. Classic. The centering is not too good on the commons it looks like, which is not too good for potential grading. Tongue. So probably not even worth grading with a centering like that. Lava Battle Guard. And a Shield and Sword. That's a cool one. The centering on the rares has been pretty decent. I think it's, yeah, pretty good on that one. Not fantastic. Castle of Dark Illusions. The second half of the commons has been pretty good. A little bit of a nick on the bottom, but that's a good one. Commonari attacks actually pretty valuable as well. I'm not going to pull out all the comments right now because they all pretty much all have a little bit of value being first edition metal raiders. Okay. All right. So we're off to a little bit of a slow start for what we're really looking for. The more infant. The unhappy maiden. The first one. The petite moth. First edition. Yes. Yes. It looks a little bit OC though, unfortunately. Dark Elf. That is a rare. We did get the Picanio moth. Yes. The epic. The legendary Picanio moth. Gigatech Wolf. Soggy, the dark clown. That's actually a pretty nice soggy. It might be, uh, credible. That would actually be a pretty decent card of grade being a pretty iconic card from the show. Getting a PSA 10 on that would be cool. Because as someone pointed out when I opened Star Deck Kaiba, there's no soggy in that. So this might be its first printing. Yeah. Neutering. The bistro butcher. The little swordsman avail. Block attack. And a witch's apprentice. Another pretty well standard rare. A little bit off on this one. Slightly off. Soul release. Larva moth. Oh, we got a ding on the, uh, the bickery box. That one's straight up dinged. That's okay though. Next pack. We're going a little slow. So if you guys are impatient, I'm sorry, but this is first edition. It was 5,000 bucks. Pretty expensive. Definitely very expensive. So we're just enjoying it. We're enjoying this Metal Raiders box. Probably won't open one of these again. So Gazelle, the king of mythical beasts. Unless I get a good deal. Musician King. Protector of the Throne. And a Harpy Lady Sisters. Okay. That's a good one. I used to have this in 10. I think I sold it. So this would be, oh wow, this card's really nice. It's not a nice chance to grade. Very cool. Harpy Lady Sisters. That's a nice card. Oh, Wing Dragon Guardian of the Fortress. That's a sweet comment. King of Yami Makai. Man, there are so many good comments in this set. Just compared to L.O.B., the comments are way better in Metal Raiders. Like they got some really awesome ones. Like all these ones from the show and stuff. Yeah. This is really good. Like Pump King, the King of Ghosts. I mean, that's just incredible. The Crass Clown. Another Pakenio Moth. Yet off-centered again. Can we get a PSA 10-1? Come on. White Magical Hat. That's a nice card. Good rare there. Our rares are looking pretty good. They might have a chance to grade those. Pakenio Moths. We're sleeping up all of those. Skull Knight is definitely like a fan favorite. People love that card. Tainan Wisdom. Harpy Lady. That's going to be a very likable one as well. Okay. Four more packs on the right side. Here we go. Here we go. Let's pull something good. The Beastro Butcher. So far we've got an Ultra and a Super. Little Swords and a Veil. Share the Pain. Block Attack. And a Masked Sorcerer. I'm loving the centering on these rares. The quality of Metal Raiders seems to be pretty good compared to a lot of other sets around it. Ring of Magnetism. There are some bad ones like Pharaoh's Servant. Once you get to that area, then Legacy of Darkness and stuff like that. Those were pretty crazy. There was some off-centering and stuff like that. We have a Dream Clown. That's a nice card. Musician King. Protector of the Throne. Ajurai Gumo. Mask of Darkness. That is a rare. Blast Juggler. Labyrinth Tank and like Labyrinth Tank. Just look at all the comments are incredible in this set. Mask of Darkness. Okay. We still have two more packs over here. One more Super on this side probably. Can we get a, I think Sui Gym would be the coolest one. They're all really cool though. Yeah. Now I can replace them up back here. I have all my empty booster boxes. I'm going to replace the Portuguese one with the English Metal Raiders. Illusionist. Faceless Mage. That's a cool one. Cyber Sorus. Robin. Oh, that scared me. When I saw that trap, that scared me a lot. Robin Zombie. That is a rare. That really scared me. Disc Magician. Rabbit Horseman and Pump King. Like look at all the Pump King and Rabbit Horsemen. Both right there are anime iconic cards. When you get to LOB, like most of the comments are not iconic at all. They're just like randomly like what are these? Okay. Pale Beast. Jellyfish. Oguchi. The Cheerful Coffin. Come on. Yes. Sui Gym. And a slight fade to it. Which is beautiful. All right. Check the back. Oh my goodness. Talk about amazing condition. Right out of the pack. You love to see that. Potential PSA 10 right there. That is awesome. Where am I putting my holos? Okay. I'm going to bring these back here. Wow. That's really good. Okay. Hunter Spider and Aki Beam. All right. So we got two really good supers I would say. Some of the best ones. What can the second half do? Can it bring us a Gate Guardian? Can it bring us a Summon Skull? Those would be, that would be the dream half. That'd be perfect. Absolutely perfect if that could happen. Come on. Doma. The Angel of Silence. The Little Swordsman of Ale. Block Attack. The Cocoon of Evolution. That's a nice short print I think. Fake Trap. All right. So they're not mapped. That could have been the Ultra Rare but it wasn't. Fake Trap. Unless we only have one Ultra Rare which I have seen. That would be catastrophic. That would be terrible. Next pack. Please get a Secret Rare. I really hope we get a Secret Rare. Chances are like one in two boxes. That's never officially released. That's why it's a secret you know. But that would be great. Protector of the Throne. The Pale Beast. Jurai Gumo. Elegant Egotists. We're getting all kinds of Harpy Lady stuff. Pretty cool rare. We haven't gotten a Magician of Faith, a Sangana, or a Witch of the Black Forest yet. Which is like ooh. And we haven't gotten a Thunder Dragon. That's a short print. So there's a lot to be pulled left hopefully in these packs. Here we go. Destroyer Golem. Mystic Lamp. Oh that destroyer. Okay that destroyer Golem got destroyed. That is not good. The top is messed up. Mystic Lamp. The Cheerful Coffin. Lady Defe. And a Little Chimeer. That is a rare. Come on rares. Give us some good ones. There are a lot of options I guess compared to most sets. Crawling Dragon. Immortal Thunder. Okay. I'm super nervous right now. Super nervous. For 35k. Can we pull something epic? From this insane booster box. All right. Blue Winged Crown. My voice is getting a little raspy here. Lava Battle Guard. Kojo Kazi. Morinfan. Princess of Surugi. That's a rare. Bottom Dweller. Ancient Brain. Share the Pain. And Swamp Battle Guard. That run. Ancient Brain. Share the Paint. Ancient Brain. Share the Paint. What is this? All right. Princess of Surugi. Okay. Come on. Be loaded. Last few packs. Gay Guardian. Gay Guardian. Gay Guardian. Come on. Here we go. Here we go. Here we go. We got a dream big. Here we go. Stem Pack. I believe that this pack will give us. Oh, it's already starting up good. They're always at the front though so they're off centered. Pecaneo Moth. Armored Lizard. Yeah. I felt something. Maybe it was the Pecaneo Moth. Vichro Butcher. Black Skull Dragon. Okay. Okay. I almost said this but in the Portuguese boxes I opened, Black Skull was always with, I couldn't remember if it was Horn of Heaven or Magic Jammer. I guess it was it was Magic Jammer. Oh, sweet. Okay. I already have this card but this card at the time recording this just sold in PSA 10 for $2,500. So that is definitely not an upsetting pull. Okay. That's really good. Hopefully this guy can grade it 10. He looks pretty good. Wow. Black Skull Dragon. We pulled this in the 30K too. So we're in the 25K in the 30K we pulled Blue Eyes and Blue Eyes. Now we pulled 30 and 35 we pulled B Skull Dragon. Okay. I'm feeling a lot better about the box now. Tremendous Fire, Trent, Punished Eagle, Armored Zombie and Flame Cerberus. Okay. Now we just need a Secret Rare and then this is the best box. It's great but not the best but it's great. It's fantastic. Here we go. B Skull Dragon. That's awesome. I'm happy about it. Unfortunately not one that I don't have. I only have one Ultra and I have that one but it's one of the best ones so I can't complain. Tongue. Baby Dragon. That's a tough one. Shadow Ghoul. We got a rare. Can we get the decent rare? Actually Shadow Ghoul is a pretty good one. I mean, it just looks awesome. Castle of Dark Illusions. Hopefully that can be a nice PSA 10 for us. All right. We're getting down the last few packs. We still need two more supers at least. Hopefully a Secret Rare. I'm a little scared. I think in the B Skull, I don't remember if I ever pulled a Gate Guardian with a B Skull out of the Portuguese packs. Maybe we can break that streak here. Deep Sea Shark. I only opened like two boxes though so one mini. Guilty at the D-Night. Twin Headed Thunder Dragon. This is actually one I've already pulled. This is funny because I have not opened much Metal Raiders and I'm pulling dupes. I opened like six packs at once. I pulled Heavy Storm and Twin Headed Thunder Dragon. So this guy looks like a PSA 10 though. I think I submitted that other one so we'll see if we get one of them to get a 10. Sagi the Dark Clown. Okay. Okay. So we have three supers, two ultras, King Gate Guardian. Show up for us in the last few packs. I'm so nervous. Oh, look at the back card. Oh no. Are these all damaged? Oh no. Okay. It's just those two. Oh my goodness. That's scary. Nebitori. Electrical Lizard. That's scary with the packs of damage. Thunder Dragon. We finally got one. Wait a second. That looks pretty good. This card's pretty expensive as a common. Looks pretty. The back centering is not good at all so maybe it'll grade. Maybe it won't. Very tough. Very tough to get that one in ice condition because it was used a lot. Reukishan Powered. A Sangan. We finally got a Sangan. I hope he wasn't dinged. Looks like he wasn't. Yeah. Yeah. Looks like it's okay down there. All right. Sangan has a rare. Nice. Now we just need Wichita Black Forest and Magician of Faith. Marvel Moth and Water of Mottics. Okay. How many packs do we have left? We have four more packs. I'm so nervous. Come on. Come on, Gate Guardian. Oh, that would be. That would be very, very crazy if we pulled it. Yeah. I didn't get a secret out of my LLV box either so that would be kind of sad. Mystic Swordsman or Horseman. Elmistic Swordsman is a while later. Illusionist. The Illusionist Faceless Mage. You might play that clip. Big Eye. The Cybersaurus. And a Muka Muka. Rare. Muka Muka. Nice. Wing Dragon Guardian of the Fortress. That's nice. And King of Yummy Makai. Okay. Next pack. Metal Raiders. Here we go. Only a few left. A few more chances. No Magician of Faith. No Sangan or no Witch of the Black Forest and no Gate Guardian so far. All right. Jellyfish. The Cheerful Coffin. Queen's Double. Lady Defe. Oh, okay. Magician of Faith. Good. Good Centering. Okay. Maybe a PSA 10 Magician of Faith. That's really good. Good Rare. Very good Rare. Okay. I'm gonna be happy about that one. No Witch but that's okay. Hopefully we don't have any more Rares if we get lucky and get a secret which I'm starting to doubt a little bit here because we haven't pulled our super yet. We probably are gonna get another super. What do we want? Probably another Gate Guardian piece like Sanga of the Thunder. Steel Scorpion. Blue Winged Crown. Lava Battle Guard. Morinfan. Garnese Aliphantus. Naturally. Of course. But that's okay. I'll take that. I will take that. I actually like this card. I think it looks really good. Garnese Aliphantus. Super Rare. All right. German Faction. We're down to one more pack. We have one more chance at Gate Guardian. Oh, do you believe in the chances, guys? I'm worried. You gotta believe. You gotta believe. Here we go. Gate Guardian. Come on. Hit the like button for luck, guys. We have one more chance. We have pulled a B Skull Dragon. Can we pull some crazy to end it? To make it absolutely insane. Here we go. Oh my goodness. I'm so scared. Share the pain. The illusion is faceless mage. Cyber Sorus. Oh my goodness. Jellyfish and a great moth.  All right. No secret rare. Oh my goodness. It hurts. It hurts. But overall, we did get some pretty good pulls. Let's see what we got out of the foil slots. All right. Overall, we got, we did get one Thunder Dragon. Only one. It's short printed. A Sengen Rare. We got a Magician of Faith. We didn't get the Witch of the Black Forest, which stinks. We got a Garnese Aliphantus classic. Had to show himself. Twin End of Thunder Dragon. Harpy Lady Sister's first edition. That's pretty good. Nice little fade to it. All these are a little faded. Suigen. That looks really nice. Super rare. Magic Jammer naturally. And the best pull of the box for sure. The Black Skull Dragon. That is definitely a great pull. If I can get a tin, this will probably be worth the box. I really enjoyed opening this. This was fun. The secret rare curse of our big boxes is now tattoo. We're two times. A little B and Metal Raiders. We did not pull a secret rare. It hurts a little bit, but I'm very happy with how it went overall because we did get probably the best Ultra, if not tied with Summit Skull in the set. So that's incredible. Even though I did already have it, I'll take two PSA 10s. Maybe I can trade it for a Summit Skull or something. That would probably be pretty awesome. Yeah. So I hope you guys enjoyed this video. Metal Raiders. Thank you again for 35,000 subscribers. That is insane. That is crazy. Maybe we'll open up some more old school boxes. We still need to open Magician's Forest Dark Crisis and Invasion of Chaos. First edition. I've opened the other eight sets from the first 11. So any of those would be crazy. If you want to support me, check out my TCG Player and eBay affiliate links below. And that's it for today. I'll see you guys later. Peace. I'm a Metal Hero. Dark Bright. Boom!


Hi I'm Commissioner Amelia Powers-Gardner and I want to thank you, the volunteers that represent us for helping us kill the repeal of right-choice voting in Utah. Thank you. This is Troy Williams, the director of Equality Utah. I want to thank all of you amazing volunteers for fighting for democracy. You are huge fans of right choice for voting. Thank you so much for all you're doing for our country and for Utah. Hi my name is Marina Lowe. I'm currently a lobbyist for the Equality Utah. I just want to say a heartfelt thanks to all of the volunteers who use their time and efforts to really make sure that right choice voting would stay in effect here in Utah. Hey everybody, represent us. This is Josh Daniels in Utah. I just want to thank you for all the work that you did as volunteers to get phone calls and text messages and email sent to legislators here in the Utah State Capitol. You have no idea the impact that you made for Utah right choice voting. Thanks to the hard work that you did, we were able to save right choice voting as an option for local cities for one more year. Hey everybody, Representative Doug Welton here.  I'm Stan Lockhart, former director of Utah right choice voting. Sometimes it seems like there's no way that you can win and it's at those times where you're willing us to keep working hard and to sacrifice in order to do everything you can, everything in your power to make it happen that miracles take place. My name is Joel Frisco. I'm a representative for Utah House of Representatives. This is 24. Citizen power is power and I appreciate you using your power as citizens to make a difference. Thank you. Collectively in Utah, over the course of the three years that cities have used right choice voting, they have saved over a million dollars in election costs, not to mention the impact on democracy with this much better form of election. So I just want to thank all of you for helping the Utah right choice voting team to defeat the bill that would have repealed right choice voting in Utah. Thank you.


Perhaps no area of the U.S. economy is less market driven than health care, and that's something that should certainly be worrying for all of us. And our guest this weekend is uniquely qualified to talk about this, Dr. Michael Akkad, who's been on the show before, is a cardiologist and internal medicine practitioner in San Francisco. And as libertarians, we tend to think about alternative treatments, but we don't think as much about alternative delivery systems for health care, and also about alternative methodologies for doctors. So two weeks ago at our Austrian Economics Research Conference, Dr. Akkad produced really a fascinating paper applying Austrian insights to medicine and how this idea of viewing the body as a machine has played a huge role in the rise of what he calls medical paternalism and one size fits all treatment. So while we tend to understand consumer sovereignty in other marketplaces, we don't understand patient sovereignty and medicine. If you're interested in how Austrian economics and in particular, praxeology might apply to the practice of medicine, stay tuned for a great lecture by Dr. Michael Akkad. Thank you very much. I'm delighted to be here. The Mises Institute has really been transforming for me professionally, and I'm very glad to be here. You know, this is a modest tentative proposal, maybe for the foundations of an Austrian School of Medicine, one of these days, who knows. The title of my talk is From Reacting Machine to Acting Person, A Praxeological Interpretation of the Patient, His Health and His Medical Care. And you know, the elephant in the room in healthcare is the following. If you ask any doctor, you know, what is health? If you ask any nurse, what is health? If you ask a medical researcher, what is health? If you ask a health policy wonk, what is health? Even if you ask a health economist what is health, you will not get a straight answer. And so I thought maybe it's conceivable that that may have something to do with the morass, the terrible situation we're in in terms of healthcare. And I'm hopeful that Austrian insights can be helpful. So let's get started. This is the outline of my talk. I will first identify two dominant modes of thinking about health in modern Western societies. And I will show that these conceptual modes are counterproductive to fostering health both economically and medically. And I will then propose a praxeological interpretation of health and sketch the possible benefits and ramifications of that interpretation. Okay. So the dominant mode of thinking about health in Western societies owes its origins to René Descartes, who at the beginning of the Scientific Revolution proposed a machine concept of the organism. The cart's proposal was a radical departure from pre-existing notions, which were rooted in the idea that the organisms have essences and natures. Instead, Descartes proposed that every material body is an assemblage of tiny particles moving mechanically according to physical laws. In the case of plants and animals, God directs the laws and the motions of these organisms. For humans, the mechanical bodies are under the control of a separate human soul acting like a ghost in the machine. In the centuries that followed Descartes' proposal, scientific discoveries began to lend credence to a machine concept of the body, however ill-defined that concept might have been. And vice versa, the machine model facilitated further scientific discoveries. Laws of classical physics and chemistry were identified. Systems were revealed to be made of basic components and these material components were increasingly well characterized and seemed to act on each other according to physical laws to produce predictable biological behaviors. And certain diseases were recognized as being due to defects in the components of the machine-like organism. By the end of the 19th century, when health care systems were beginning to emerge, the machine model was widely adopted by scientists and was bearing much fruit in medicine. Now, there's nothing wrong with models so long as they are understood to be models. But under the dual influence of ideological empiricism, which was widespread among prominent scientists, and social progressivism, which was flourishing in many Western nations at the time, and still is today, medical licensing laws incorporated and embedded the machine model into medical education, turning it into a quasi-reality. This is particularly well documented in the case of the United States, which saw an abrupt transition from a unique free market situation to a regulated health care environment in the 1910s. The transition was instigated at the behest of the Carnegie Foundation, whose leaders were enthusiastic about the progressive idea of scientific management of social affairs, and they entrusted Abraham Flexner to issue a report that was highly critical of the state of medical education for failing to systematically embrace scientific empiricism. The Flexner report explicitly promoted the machine concept of the human body, and in the aftermath of its publication, educational and licensing reforms were enacted to prevent the operation of any medical school that did not embrace the proposals advanced by the Flexner report. The idea was that if the body is like a machine, its care should only be entrusted to those who receive proper scientific training. The educational and licensing regulations of that period have dictated the modern medical school curriculum, a curriculum that has remained essentially unchanged since then. Entrance requirements mostly hinged on mastery of the physical sciences, and the curriculum begins with building block disciplines, and then moves to more complex systems. With that constructivist approach, an understanding of the body is expected to emerge from the conceptual integration of parts into systems, as one would mentally construct the workings of a machine. Again, there is nothing inherently wrong with such a structure unless our scope of understanding remains confined to it. To the extent that licensing laws and educational regulations privilege empirical knowledge over all other forms of knowledge, and to the extent that the hard sciences are considered foundational to the medical curriculum, the concept of health becomes difficult to articulate precisely within such a structure. The notion of health necessarily presupposes certain ontological considerations regarding the human person, yet the empirical sciences precisely avoid such considerations. As a result, the concept of health is generally left undefined in medical schools, while the machine model, seen as highly effective for the production of therapeutic advances, has become a de facto representation of the human body in medical circles. From that model of the human body, a certain understanding about health and disease emerges. If the body is viewed as a machine subject to disturbances, internal or external, then diseases are viewed primarily as objective dysfunctions, and health is simply the absence of disease. In fact, this is a common definition of health provided by standard medical dictionaries. But neither the machine model nor the definition of health and disease are firmly or explicitly considered valid or true. In fact, if examined, they are usually recognized as flawed or limited. Nevertheless, these are implicitly adopted operational definitions, given the empirical constraints imposed by the regulatory conditions for licensing and education. As we might expect, impelling the adoption of the machine model through educational and licensing regulations has had negative consequences. If health and disease are viewed as objective conditions to be ascertained by the physician, then the physician is put squarely in control and patients are passive since their bodies are mere machines. This of course gives rise to medical paternalism, which was particularly acute in the first half of the 20th century. It also gives rise to an invasion of medicalization, where under authority from the medical community, increasing aspects of life are placed under the purview of the healthcare system. And medical authorities may also find opportunities to identify diseases that would not be apparent or would not exist under a different framework. The view that health and disease are objective concepts also invites third parties to partake in healthcare delivery, namely regulators and insurers. Viewing healthcare is purely a technological endeavor. Regulators wish to subject it to quality and safety oversight. Reviewing diseases as defects or dysfunctions in a machine, insurers, whether public or private, are tempted to think of medical illnesses as insurable events. These errors account in large part for the endless bureaucratization and runaway cost inflation of healthcare. And the machine model is self-fulfilling. Again, since only empirical methods are considered permissible to advance claims about health and disease, these methods limit our framework of understanding to only what is measurable. When health is not being quote-on-quote delivered by the system, according to accounting measures or measures of efficiency, more interventions are called for and those interventions further mechanize care and reinforce the machine model of the human body. Now, clearly, there has been some backlash against the mechanical and reductionist concept of health in the last 50 to 60 years. The backlash began in part in response to the abuses of the eugenics movement, but also to other egregious abuses of a medical community empowered by licensing privileges and by technological means to cause great harm. And therefore, alternative definitions have been proposed. Chief among these alternative definitions is the definition of health offered by the World Health Organization in 1949, namely that health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity. Now while the WHO definition clearly acknowledges the subjective dimension of health, it has serious limitations. To begin with, by stipulating complete well-being, the WHO definition makes it hard to conceive of anyone as being healthy. It does not circumscribe the scope of medical care, but in fact makes it limitless. The definition also introduces the unclear notion of social well-being with which medical care is easily turned into a public health or even a political activity. And by defining health as well-being, the WHO definition and others like it appeal to an empiricist concept, namely the idea of the self as a bundle of experience as philosopher David Hume would have put it. In this view, only the feelings and experiences of the person ultimately matter. As a summary, we can remark that both concepts of health, the one that derives from the machine model and the one offered by the WHO, primarily consider the human being as reacting to changing conditions, rather than as a person acting on the world to achieve chosen ends. I would therefore like to entertain an interpretation of health rooted in the view that human beings are persons acting purposely, persons who select means to achieve chosen ends, which is the framework of praxeology. Under a praxeological framework, I would distinguish external means such as land, labor and capital, which are generally the concern of economic theory, from internal means such as the physical and mental conditions of the person that allow him or her to pursue chosen ends. Health then may be defined as the state that is present when a person's physical and mental conditions allow the pursuit of his or her chosen ends. Disease then is the absence of health. Now of course, the first thing to do is to ensure that the definition of health that I propose corresponds to our common sense understanding of the term and is not simply an intellectual abstraction. This is work that needs to be done carefully, but today I simply wish to remark that conditions we normally conceive as diseases, for example, heart attacks, major trauma, pneumonia, cancer, but even simpler things like the common cold generally do interfere with a person's pursuit of chosen ends and therefore seem to cohere with our definition of health and disease. An important consequence of a praxeological interpretation of health is that it locates the determination of medical necessity within the patient rather than in the physician or the public health official. Since only the patient knows what his or her chosen ends are, the definition can therefore safeguard against unwanted third party intrusions in health care. Moreover, our interpretation can actually solve what I call the paradox of the healthy blind man. Under the machine concept of health and disease, a blind person could never claim to be healthy, since a part of the body is obviously an objectively defective. Yet undoubtedly, many blind persons and many other persons with serious disabilities actually consider themselves to be perfectly well and healthy if asked about health in the context of a routine conversation. I believe that they do so because despite their disability or infirmity, they are able to pursue their own chosen ends without own due difficulty. In fact, a praxeological conception of health would promote self-regulation in the use of medical services. Rational beings naturally adjust their chosen ends according to the means that are realistically available to them, and that includes the internal means, namely ones physical and mental conditions. Therefore, a person's sense of health may be maintained despite the presence of some objective dysfunction. And this may be particularly pertinent in the case of the elderly who may naturally curtail their chosen ends as they age, and claims for medical services would not necessarily rise in proportion to physical decline. Now, one objection to my definition is that it may encourage unreasonable or irrational subjective determinations of health and disease. Imagine that I choose, as one of my ends, to become a linebacker for the Dallas Cowboys. Should my inability to gain sufficient muscle mass be considered a disease? According to my definition, it could, but I will address this difficulty in the next slide. Now, we should note that the nature of the patient-physician relationship changes in a praxeological framework. In this framework, we are no longer dealing with a subject-expert relationship, but with what I would call an owner-steward relationship. The patient is the rightful owner of his body, but in the course of medical care, he or she delegates control of the body to the physician. The physician is entrusted to work on the body with the understanding that the goal is to help achieve a condition where the patient can pursue his or her chosen ends to whatever degree possible. The transfer of control is particularly evident and incomplete in the case of surgery, but it also occurs in lesser degrees in routine medical care when a patient agrees to ingest a medication or to submit to the advice of the physician, since that medication or that advice invariably aim at changing the patient's internal means of action, namely his or her physical and mental conditions. Patients may choose to seat control of their body for a variety of reasons. They may be unable to maintain or restore their health on their own due to the illness, or they may be unwilling to shoulder the uncertainty related to health decisions. There may be other reasons as well. I would propose that medical care per se occurs only after control over the body has been transferred by the patient to the physician, and the patient submits either implicitly or explicitly to the actions of the doctor. In fact, this distinction would recover the original etymology of the word patient, which is opposed to agent. And the main decision confronting the would be patient is in the selection of the physician's steward. In that regard, licensing laws could be viewed as impinging on property rights, the rights to legitimately transfer care of one's property, one's body, to another person. Of course, the physician's steward is not obligated to treat the person, but is free to accept or refuse the consignment of the body. And that prerogative of the physician will, to some degree, safeguard against the problem of the unhealthy NFL hopeful or the problem of unreasonable or irrational health concerns on the part of individuals. In fact, this is an advantage over the empiricist model of health, since those models cannot easily deal with irrationality or unreasonable demands. And in this last slide, I would like to discuss additional concept borrows from economic theory. One concept is that a physician trained in the Austrian School of Medicine would conceive of her role as a nitrogen entrepreneur. She would see herself as being invested in the patient's internal means of action, bearing in mind the patient's chosen ends. The Austrian physician would understand that she is dealing with uncertainty and not risk as clarified by Frank Knight. Risk has to do with repeatable events and outcomes that can be quantified. In medicine, we are dealing with unrepeatable human affairs and unquantifiable uncertainty. To make medical decisions, she would use all forms of knowledge available to her, including tacit as well as scientific and technological knowledge. And she would view her medical decision the way entrepreneurs view entrepreneurial decisions as exercising judgment. This is in distinction to the way medical decisions are currently considered under the machine model, namely as calculations. As Knight proposed, entrepreneurial judgment is not articulable and therefore not contractable to third parties. The Austrian physician will not contract with a third party to provide care as if the care were an objective, measurable entity. Finally, additional considerations that the Austrian theory of medicine must address include the cases of those unable to express chosen ends, the need to elaborate a contract theory for stewardship and informed consent, and probably the need to address Mises' methodological dualism, since the connection between the physical sciences and medical care is close, and a sharp methodological separation may be counterproductive in the long term. Thank you very much.


Now, just to summarize the three key properties we covered in this video of particles, the first is spin, and the two key terms we need to keep in mind are that bosons have an integer spin quantum number, fermions have a half-integer spin quantum number. We also learned that forces and the forces that act on particular particles are very important. The two key terms you need to remember are that hadrons are acted on by strong and weak forces, whereas leptons are only acted on by the weak force. We also learned that there can be matter or ANC matter particles.


Behind me, you can see a majestic rock formation called Devil's Gate. It was formed when the Sweetwater River carved a narrow gorge through the rattlesnake mountains. Devil's Gate is among the more interesting geographical landmarks along the Oregon Trail. The gorge was impassable to wagons, and the trail passed to the south of the ridge, but this dark, gloomy canyon intrigued the immigrants. Many camped here, and almost all took the detourer to inspect the gorge and carve their names in the granite walls. How did it get its name? Well, the best explanation comes from Native American legend. For centuries, the tale was told among the Shoshone and Arapaho that a mighty tusk beast once roamed the valley.  They attacked from the outer ravines, and in the beast's death agony, its massive tusks carved a groove in the mountain range. Thus, Devil's Gate was created. Right off of State Highway 220, the Bureau of Land Management maintains Devil's Gate as a national historic landmark, with a short loop trail and signboards. So the next time you're in this area, make sure you stop off and see this unique landmark. From the University of Wyoming Extension, I'm Ashley Garles, Exploring the Nature of Wyoming.


Kelly's long diagonal down the middle for Billing who wins the head and lays it off for Dom Selanke. Tries to go around the outside of his man, still going Dom Selanke. Looks to pull it back to Phil Billing, but there's a block from Koopa. Here comes Lerma on his right foot. Oh, Jefferson into the right-hand side of the goal. And just shy of the 20-minute mark, Leeds will feel hard done by. Bournemouth will not care. Another step towards the safety line provided by Jefferson Lerma's brilliant finish. Bournemouth won Leedsnell. Runners coming from deep, in from Christie. Selanke was coming in. He's Lerma again! It's to the Jefferson Lerma! Broke to him on the six-yard line, and he hung it on the roof of the net. And can you believe it? Jefferson Lerma's on a hat-trick. Bournemouth two Leedsnell. Once again, level with the edge of the penalty area. Nonto whips a ball in deep. Banford's completely on modern net. And I'm afraid that is loose defending from the Jerry's who completely switched off and allowed Patrick Banford to give Leeds some hope with a free header into the back of the net. And with 31 minutes played, it's now Bournemouth two Leeds one. And Watara's got beyond his man here. Defender fell over. Watara right-hand side, Selanke trying to run onto it. He might still get there, Selanke! He does get there, and he does tuck it in off the left-hand post. And Bournemouth restore their two-goal advantage. And Dom Selanke has six Premier League goals for the season. And is that going to be enough to make sure that Bournemouth are absolutely playing Premier League football next season? Selanke the scorer, Bournemouth three Leeds one. There's a chance for Semenio here into the penalty. Antoine Semenio shot, and it's gone through Mélanie! And a huge moment for Antoine Semenio, who scores his first Premier League finish that gives Bournemouth four goals to one in front against Leeds. It might not be Mark Pew this time, but the words are still the same. That will do it!