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ApiNATOMY User Guide
Physiology deals with the body in terms of anatomical compartments that delineate portions of interest. The compartments can be defined at various anatomical scales, from organs to cells. Clinical and bioengineering experts are interested to see records of physical measurements associated with certain anatomical compartments.
ApiNATOMY is a methodology to coherently manage knowledge about the scale, parthood and connectivity of anatomical compartments as well as to represent and analyse process mechanisms and associated measurements. It consists of
a knowledge model about biophysical entities, and
a method to build knowledge representations of physiology processes in terms of biophysical entities and physical operations over these entities.
The following Youtube video explains the ideas underlying the ApiNATOMY methodology:
The current project delivers a graphical tool, called ApiNATOMY lyph viewer, that automatically creates a biologically meaningful visualizations of ApiNATOMY models as part of the NIH-SPARC MAP-CORE toolset.
In this manual, we overview the aforementioned software application. Installation instructions and control settings are explained in the usage guide. An important aspect of the project, the input format for specifying ApiNATOMY data models, is explained in the data model guide. Examples of the physiology models designed by a domain expert and converted to our input format are shown in the example section.
Note that despite our best effort to keep this document up-to-date, it may differ from the actual implementation of the lyph viewer. The underlying modelling concepts evolve to suit the needs of the growing group of adopters of the ApiNATOMY methodology within the biomedical community.
The ApiNATOMY lyph viewer shows 3d schematics of physiology models. The lyph viewer is a graphical component that consists of
a canvas that features a dynamic graph rendered using a 3D force-directed layout algorithm;
a control panel that allows users to change parameters of the viewer and select parts of the model to display.
The use of the ApiNATOMY lyph viewer component is illustrated via the test application that allows the user to load an ApiNATOMY data model from the local file system. In addition to the aforementioned component, the demo application includes:
a header and a footer with relevant project information;
a toolbar that allows the user to import, edit, preview and export the data model, as well as to switch the application view modes;
an integrated JSON editor to overview, analyze and modify the chosen data model;
a dedicated form-based resource editor for assisted editing of model resources;
an svg-based viewer that helps users to overview the structural relationships among model resources, including derived (auto-generated) resources.
The lyph viewer accepts as input a JSON-based object that defines ApiNATOMY resources, see model section for more detail. The model can be edited using external tools or with the help of a build-in JSON editor and custom resource editor within the demo app.
The image below shows an integrated ACE-based JSON editor. The editor uses the ApiNATOMY JSON Schema for interactive validation - the lines that violate the schema model are marked with error or warning signs.
Alternatively, the input model can be edited with the help of the form-based editor as shown in the image below. The fields in the form are also based on the ApiNATOMY JSON schema and are preconfigured to assist the modeller with the choice of correct options, i.e., multi-selection fields that expect references to lyphs, show all suitable lyphs in the model.
Users that prefer working with a table-style data, can define an ApiNATOMY model using Excel spreadsheets. The lyph viewer app can open .xlsx files and convert their content to a corresponding JSON-based model. The recognized Excel format should specify ApiNATOMY resources in separate pages named after the Graph's fields, namely, lyphs, materials, links, nodes, coalescences, and groups. Each of the pages can contain columns named as the corresponding resource class properties, i.e., id, name, external, conveyingLyph, etc. for the class Lyph in the page lyphs. In the Excel lyph specification, one can assign content to a lyph border using columns inner, radial1, outer, and radial2; the content of these columns is then mapped to the property border.borders in the JSON specification which defines an array of 4 lyph borders.
A modified model must be saved using the dedicated button on the left hand menu panel. After that it is processed as described in the Model assembly section below and an in-memory expanded model with auto-generated resources is created. This model is then visualized in the main canvas. One can also serialize this model using the menu items from the right-hand panel - the model can be either stored in a file as it is, or one can opt to serialize it in a form of a dictionary where the top object lists all resources with their unique identifiers as keys.
Sample ApiNATOMY models, including test models used in this documentation, can be found in the project's repository at GitHub.
The users define key resources, their relationships, and layout constraints in the ApiNATOMY JSON format. Naturally, these models may be incomplete or incorrect (i.e., contain typos, undefined references, or unexpected values). We tried to make the format as flexible as possible, many errors will be tolerated and some will be auto-corrected. The tool logs errors (in red), warnings (in yellow) and important actions on the model post-processing (in black) into your browser console, you can typically open it with shortcuts: on Windows and Linux: Ctrl + Shift + J, on Mac: Cmd + Option + J.
Below we describe key stages in user model post-processing in order to prepare it for visualization. Model authors aware of the post-processing procedures are more likely to understand the causes of wrong layouts and adjust their models accordingly:
Many resources that domain experts need for modelling are abstract assemblies of physiology subsystems (materials, cells, neuron pathways). It is convenient to specify such resources once and place them to the context they are used in as many times as needed. On the other hand, the ApiNATOMY model viewer creates a visual artifact for each unique visual resource (lyph, node, link) in the model. Hence, the first step is to replace the abstract templates with resource instances that inherit the majority of their characteristics from the templates. The tool identifies references to materials and lyph templates in all the fields that are expected to contain lyphs as building parts, automatically creates lyph instances with necessary characteristics and replaces abstract references with instance references. All derived or cloned resources within this step can be overviewed with the help of the relationship graph.
If tree objects are present in the model, we generate tree-like graph structures and include all created resources (nodes, links, lyphs, etc.) to the main graph (or a parent group containing the tree for nested models). The procedure replicates the tree lyph template to all generated edges (links) and assigns their topology to define overall boundaries of the tree-like conduits. At the end of this stage, the lyph template is linked to the newly created blank lyphs via its subtypes property. Check our example section for a run-through scenario with tree definitions.
At the next step, we process lyph templates: all subtypes of a lyph template inherit its layers, color, size-related properties, namely, scale, height, width, length, and thickness (unless they are overridden for the lyphs individually), external annotations, constituent materials, and auxiliary fields such as comments and create3d.
After auto-creating resources originating from tree and lyph templates, the model's graph structure is almost ready to be visualized. Hence, we create ApiNATOMY model objects and replace string identifiers with corresponding object references. Lyph and region borders are auto-created and merged with user-defined border content. Missing links and nodes for internal lyphs are also auto-created. By default, they are invisible. However, their presence is required for lyph positioning and sizing, they can also be accessed and customized via the JSONPath assign expressions. We also perform group inclusion analyses at this stage and include nested group resources into parent groups.
As the result of the previous step, the main graph has a complete map of all model resources regardless of where they were defined, i.e., all references can be resolved. If the tool detected IDs without corresponding resource definitions, we will auto-generate such objects setting their ID and class properties, all other parameters will be set to default values as defined in the ApiNATOMY JSON Schema.
To be able to fully connect related resources, we synchronize symmetric properties. In a model, a user may specify, for example, that A has a layer B and that C is a layer in A, hence A actually has two layers, B and C. At this stage, we analyze and integrate related definitions into a complete and consistent model.
After that we process model customization via the JSONPath queries in assign and interpolate properties. This is done in two steps: .. 1. we create dynamic relationships by assigning relationship fields, i.e., layers=["B"]. The tool will replace IDs in these fields with object references (thus, only IDs of known objects should be used in assign expressions, unresolved IDs will be ignored). .. 2. we complete model customization by assigning qualitative properties to resources selected by JSONPath queries for every resource in the model with assign and interpolate properties.
The relationship graph is an auxiliary tool that allows users to trace the resource derivation process described above and visually inspect the relationships among the key resources in the model. In this viw, all resources are represented by graph nodes (visualized using colored shapes according to the type of the resource) while their relationships correspond to the graph links (visualized using colored lines where each color stands for a certain type of the relationship).
The nodes in the relationship graph are organized using the so called group-in-a-box layout, which clusters nodes based on their class and creates centers of attraction for each cluster. The area occupied by a cluster depends on its size. Be default we use a setting for the group-in-a-box algorithm that allocates cluster areas based on the treemap pattern.
The group-in-a-box algorithm creates a good initial graph layout. It is used in a combination with the sticky force-directed technique when the program reassigns the nodes coordinates when the user drags them to a different location. Hence, users are free to rearrange the nodes in a way that makes understanding the model or tracing certain derivation chains easier.
An any moment, the positions of the nodes in the graph can be saved and reloaded using the dedicated buttons from the right-hand panel. The file created at this process contains only node identifiers with the corresponding coordinates. To avoid compatibility issues when a user tries to load a relationship graph coordinates after modifying an ApiNATOMY model, we do not store other information such as node and link classes/types. Nodes which do not have saved coordinates in a certain file simply remain in their initial locations. Note that switching the view modes between the relationship graph and the main ApiNATOMY visualization resets the relationship graph node positions.
Install Node.js.
Clone (or download and unzip) the project to your file system: git clone https://github.com/open-physiology/open-physiology-viewer.git
Go into the project directory: cd ./open-physiology-viewer
Install build dependencies: npm install
Run the build script: npm run build
The compiled code is in the open-physiology/dist/ folder. After that you should be able to open a demo app test-app/index.html in your browser.
A lyph viewer is available as a stand-alone module that can be used in other applications as a graphical widget. For integrating the viewer with other applications, include open-physiology-viewer.js to your build and import:
WebGLSceneModule - the module that provides the Angular component WebGLSceneComponent. The component currently accepts 3 parameters:
graphData - an ApiNATOMY model in the deserialized JSON format (as returned by the DataService).
highlighted - a reference to a visual resource (e.g., node, link, lyph, region) to highlight.
selected - a reference to a visual resource to be selected.
Knowledge representation in ApiNATOMY has its basis in the constraints of forming tissue domain architecture. In particular, physiological system experts identify compartmental models of primary functional tissue units, so-called pFTUs. A pFTU is a cuff wrapped around a central (endothelial, epithelial or neural) canal, such that no two points within this domain are beyond average diffusion distance for small molecules. Two types of transfer processes occur over pFTUs: advective solid flow along the lumen of the vessel (mass fluid transport, e.g., urine along the ureter), and diffusive solute flow between the lumen of the vessel and the rest of the tissue cuff (e.g., calcium ions through a membrane channel). A pFTU therefore represents a point of transition between long and short range molecular interactions.
Technically, an ApiNATOMY model is a JSON object that contains sets of entities which are either nodes, links, lyphs, materials, coalescences, channels, trees, or groups which contain subsets of these entities. Properties of these objects reflect the meaning and parameters of the associated physiological elements (connections, processes or tissue composition) as well as provide positioning constraints that help us to assemble them into structurally correct models of physiology.
In this manual, we explain, using small examples, how ApiNATOMY data model definitions render into graphical elements displayed by the ApiNATOMY lyph viewer.
All ApiNATOMY modelling elements have a common ancestor, an abstract resource that defines common properties present in all objects of the model.
All entities come with basic properties such as id and name to identify the physiological element. The identifiers of all entities must be unique, the tool will issue a warning if this is not the case.
Each object has a read-only property class (the user does not need to specify it, it is assigned automatically) that returns its class from the ApiNATOMY data model, such as Node, Link, Lyph, Region, Border, Material, External, Group, Tree, Channel, Coalescence, or Graph. The property external may be used to keep a reference to an external data source that defines or describes the entity, i.e., the Foundational Model of Anatomy (FMA) ontology.
The property infoFields lists properties that are shown in the information panel of the viewer. These properties are typically set by default for all entities of certain type, but may also be overridden for individual objects. For example, the following value of the infoFields property of a lyph object
"infoFields": [ "id", "name", "topology", "conveyedBy", "layers" ]
will instruct the viewer to show the lyph's id, name, topology, the signature of the link conveying the lyph, and the lyph's layers.
The models of physiology systems may contain thousands or even millions of entities. While the majority of the information will come from existing data sources (publicly maintained data sets, ontologies, clinical trials, experiments, etc.), and converted to the expected format with the help of some data manipulation scripts, many properties in our model are specific for the lyph viewer. The derived input model has to be augmented with properties that help the viewer to produce a meaningful and clean graph layout. It is likely that it will take at least several attempts for the modeller to figure out the proper constraints for the intuitive visualization of a certain model. For example, one may want to draw links that represent all blood vessels as straight thick red lines or show neural connections as curved thin blue paths.
To simplify the parameter setting process, we provide means to assign valid properties to subsets of entities in the model. Each object may contain a property assign with two fields: path which contains a JSONPath expression, and value object, that contains a JSON object to merge with each and every item in the set defined by the query in the path. For example, the following code assigns color and scale properties to all lyphs in the Neural system group:
"id"    : "group1",
"name"  : "Neural system",
"assign": {
"path"    : "$.lyphs[*]",
"value"  : {
"color": "#aaa",
"scale": { "width": 200, "height": 100 }
In addition to the assignment of properties, either individually or as part of a dynamic group, we allow users to apply color interpolating schemes and gradual distance offsets. This is done with the help of the object's property interpolate. If the JSONPath query returns a one dimensional array, the schema is applied to its elements. If the query produces a higher-dimensional array, the schema is iteratively applied to all one-dimensional splices of the array. For example, the following fragment colors three layers of every lyph in the Neural system group of lyphs using the shades of blue, starting from the opposite side of the color array with 25% offset to avoid very light and very dark shades:
"interpolate": {
"path"   : "$.lyphs[*].layers",
"color"  : {
"scheme"  : "interpolateBlues",
"offset"  : 0.25,
"length"  : 3,
"reversed": true
For the details on supported color schemes, and specification format for interpolating colors and distance offsets, see the ApiNATOMY JSON Schema documentation.
Visual resource is a subclass of Resource that lists properties common for resources with visual artifacts, such as shape and its border (lyph or region), material, node, and link.
The most basic visual artifact property is color - the color of the resource helps to interpret the model, identify resources that originate from the common template, etc. Additionally, each visual resource can have auxiliary boolean parameters hidden, inactive, and skipLabels that influence on its visibility, possibility to highlight the corresponding visual object and the visibility of its text label(s) in the lyph viewer, respectively.
The ApiNATOMY model essentially defines a graph where the positions of nodes are computed by the force-directed layout. Nodes connect links which convey lyphs, the main modelling concept in the ApiNATOMY framework.
Nodes are represented by spheres. The radius of the sphere is computed based on the value of the node's val property (the exact value depends also on the scaling factor, there is no well-defined physical characteristic associated with the numeric value of this property).
Properties charge and collide allow users to tune the forces applied to a specific node.
A modeller can control the positions of the nodes by assigning the desired location via the layout property. For example, the image below illustrates the graph for the 5 core nodes:
"nodes": [
"id"    : "a",
"name"  : "a",
"color" : "#808080",
"val"   : 10,
"fixed" : true,
"layout": { "x" : 0, "y" : 0, "z" : 0 }
"id"    : "c",
"name"  : "c",
"color" : "#D2691E",
"layout": { "x" : 100, "y" : 0, "z" : 0 }
"id"    : "n",
"name"  : "n",
"layout": { "x" : -100, "y" : 0, "z" : 0 }
"id"    : "L",
"name"  : "L",
"color" : "#ff0000",
"layout": { "x" : 0, "y" : -75, "z" : 0 }
"id"    : "R",
"name"  : "R",
"color" : "#7B68EE",
"layout": { "x" : 0, "y" : 75, "z" : 0 }
In the above example, four nodes are positioned along x and y axes. The value of each coordinate is expected to be between -100 and 100, these numbers refer to the percentage of the lengths from the center of coordinates. The actual coordinates are then computed depending on the internal scaling factor.
The node a is placed to the center of coordinates. It is marked as fixed. Positions of fixed nodes are set to coincide with the desired positions in the layout property. For other types of nodes, the layout only defines the position the node is attracted to while its actual position (x, y, z) may be influenced by various factors, i.e., global forces in the graph, rigidity of the links, positions of other nodes, etc. Note that assigning (x, y, z) coordinates for the node in the model is ineffective as these properties are overridden by our graph layout algorithm and the initial settings will simply be ignored. The tool issues the corresponding warning if an unexpected property is present in the model.
It is important to retain in the model the containment and spacial adjacency relationships among entities. Several properties of a node object are used to constraint the positions of the node on a link, within a lyph or on its surface. It is also possible to define the desired position of a node in the graphical layout based on the positions of other nodes.
To place a node on a link, we assign the link's ID to the node's property hostedBy. The related optional property offset can be used to indicate the offset in percentage from the start of the link. Thus, the definition below
"id"       : "nLR00",
"hostedBy" : "LR",
"offset"   : 0.25
instructs the viewer to position the node nLR00 at the quarter of the length of the link LR.
An alternative way to get the same result, is to include the node's ID to the hostedNodes property of the link.
To place a node on a lyph, assign the lyph's ID to the node's internalIn property. This will force the node to attract to the lyph's center. An alternative way to get the same result is to include the node's ID to the internalNodes property of the lyph.
To place a node to the center of coordinates of a set of other nodes, list their ID's in the controlNodes array.
Links connect graph nodes and perform a number of functions in the ApiNATOMY framework, most notably, they model process flow and serve as rotational axes to position and scale conveying lyphs.
By default, all links are drawn as straight lines, this corresponds to the "geometry":"link" setting. To apply another visualization method, we set the link's geometry to one of the supported values enumerated in the ApiNATOMY JSON Scheme. For example, "geometry":"semicircle" produces a spline that resembles a semicircle:
"links": [
"id"        : "RL",
"name"      : "Pulmonary",
"source"    : "R",
"target"    : "L",
"length"    : 75,
"geometry"  : "semicircle",
"stroke"    : "thick"
"id"        : "LR",
"name"      : "Systemic",
"source"    : "L",
"target"    : "R",
"id"     : "cn",
"source" : "c",
"target" : "n",
"length" : 100,
"stroke" : "dashed"
Among other link geometries supported by the lyph viewer are
spline to draw link connectors that smoothly join preceding and following links
rectangle to draw splines that resemble a semi-square connector with rounded corners
path to draw graph edges bundled together by the d3.js edge bundling method.
There are also two auxiliary link types:
invisible links are never displayed themselves but serve as axes for the lyphs they convey. The invisible links can either be defined explicitly in the model or auto-generated if a lyph that is an internalLyph of some other lyph is not conveyed by any user-defined link in the model;
force links have no corresponding visual objects and only serve the purpose of binding together selected nodes.
The property stroke set to dashed yields a dashed line while its property thick set to true indicates that the link should be drawn as a thick line. This option was introduced to overcome a well-known WebGL issue with drawing thick lines. It instructs the lyph viewer to use a custom vertex shader. The optional property lineWidth can be used to specify how thick such links should be (the default value is 0.003).
The property length defines the desired distance between the link ends in terms of the percentage from the maximal allowed length (which is equal to the main axis length in the lyph viewer). The link force from the d3-force-3d module pushes the link's source and target nodes together or apart according to the desired distance. More details about these parameters can be found in the documentation of the module.
A link of any type can be set to be collapsible. A collapsible link exists only if its ends are constrained by the visible entities in the view, i.e., the link's source and target nodes must be inside of visible lyphs, on separate lyph borders or are hosted by other visible links. If this is not the case, the source and target nodes of the collapsible link are attracted to each other until they collide to look like a single node.
Collapsible links are auto-generated for the models where one node is constrained by two or more different resources (i.e., lyph borders) meaning that it should be placed to several different locations. This functionality allows modellers to include the same semantic entity to various subsystems in the model, even if these subsystems are split by some space for readability. The auto-generated collapsible links are dashed to emphasize that the link is an auxiliary line that helps to locate duplicates of the same node.
The screenshots below show the link chain representing the anterolateral apinothalamic tract in isolation and in combination with the neural system group. Observe that in the latter case the tract's nodes are bound to the neural system lyph borders with thin dashed transitions among pairs of replicated node instances.
Each link object must refer to its source and target nodes; these nodes will be able to access the link resource via the related sourceOf and targetOf properties.
Although we do not draw arrows by default, all links in the ApiNATOMY graph are directed links. To show the arrows, set the link's flag directed. It is possible to change the direction of the link without overriding the source and target properties. If the boolean property reversed is set to true, its direction vector starts in the target node and ends in the source node, this is useful if we want to turn the lyph it conveys by 180 degrees in the 2d view.
A link may have a conveying lyph which is set via its property conveyingLyph. The lyph conveyed by the link is placed to its center and uses the link as its rotational axis. The size of the lyph in the lyph viewer depends on the link's length, a more detailed of the size computation is given in the Lyph section. Hence, one can define the same relationship from the other entity's perspective: by assigning the link's ID to the lyph's property conveydBy.
The property hostedNodes contains a set of nodes that are positioned on the link. This set should never include the link's source and target nodes.
The field fasciculatesIn represents a specialized relationship that may point to a lyph that bundles the link (e.g., representing a neural connection).
A shape is an abstract concept that defines properties and relationships shared by ApINATOMY resources that model physiology entities, namely, lyphs and regions. An important part of the shape abstraction is its border.
The property internalNodes may contain a set of nodes that have to be positioned on a shape. Such nodes will be projected to the shape's surface and attract to its center. Note that the viewer will not be able to render the graph if the positioning constraints are not satisfiable, i.e., if one tries to put the source or target node of the lyph's axis inside of the lyph, the force-directed layout method will not converge.
The property internalLyphs is used to define the inner content of a shape, i.e., neurons within the neural system parts. The related property, internalIn, will indicate to which shape (lyph or region) the given lyph belongs. Internal lyphs should have an axis of rotation to be hold in place. In practice, there may be elements with uncertain or unspecified position within a larger element, i.e., blood cells within blood fluid. Until the method of positioning of inner content within a lyph is clarified by the physiology experts, we auto-generate links and position them on a grid within the container shape.
It is possible to model a lyph within another lyph via explicit relationships, i.e., among its axis ends and lyph borders.
To sketch an entire process or a subsystem within a larger scale lyph, i.e., blood flow in kidney lobus, one may use the hostedLyphs property. Hosted lyphs get projected on the container lyph plane and get pushed to stay within its borders.
"id"         : "5",
"name"       : "Kidney Lobus",
"topology"   : "BAG",
"hostedLyphs": [ "60", "105", "63", "78", "24", "27", "30", "33" ]
Lyphs in the ApiNATOMY lyph viewer are shown as 2d rectangles either with straight or rounded corners. A lyph defines the layered tissue material that constitutes a body conduit vessel (a duct, canal, or other tube that contains or conveys a body fluid) when it is rotated around its axis.
The shape of the lyph is defined by its topology. The topology value TUBE represents a conduit with two open ends. The values of BAG and BAG2 represent a conduit with one closed end. Finally, the topology value CYST represents a conduit with both ends closed (a capsule). The images below show 2d and 3d representation of three types of lyphs: TUBE, CYST, and BAG, each with 3 layers.
In addition to the nodes and links created in the previous sections and a new link k_l with source node k and target node l, the code below produces a bag with two layers conveyed by the k_l link:
"lyphs": [
"external"   : "FMA:17881",
"layers"     : [ "7", "6"],
"scale"      : { "width": 50, "height": 50 },
"conveyedBy" : "k_l"
"id"       : "6",
"name"     : "Cortex of Kidney Lobus",
"topology" : "BAG"
"name"     : "Medulla of Kidney Lobus",
The center of the axial border of the lyph (see Lyph border) always coincides with the center of its axis. The lyph's dimensions depend on its axis and can be controlled via the scale parameter. In this example, the lyph's length and height are half the length of the link's length (50%). If you do not want a lyph size to depend on the length of its axis, assign explicit values to the properties width and height. Lyph's properties thickness and length refer to the anatomical dimensions of the related conduits. At the moment, these parameters do not affect the size of the graphical objects representing lyphs.
The lyph above consists of 2 layers. A layer is a lyph that rotates around its container lyph. The lyph's layers are specified in the property layers which contains an array of layers. Each layer object is also aware in what lyph it works as a layer via its field layerIn. Similarly to other bi-directional relationships, it is sufficient to specify only one part of it in the model, the related property is inferred automatically. By default, all layers get the equal area within the main lyph. Since all layers have the same height as the hosting lyph, the area they occupy depend on the width designated to each layer. The percentage of the width of the main lyph's width a layer occupies can be controlled via the layerWidth parameter. For instance, the code below, set the outer layers of all lyphs in the neural system group (see the example in the Entity section) to occupy 75% of their total width.
"id"    : "largeOuterLayers",
"name"  : "Enlarged outer layers of neural system lyphs",
"lyphs" : ["155", "150", "145", "140", "135", "160"],
"assign": [
"path" : "$.lyphs[*]",
"layerWidth": 75
A list of materials used in a lyph is available via its field materials, i.e.,:
"id"       : "112",
"name"     : "Lumen of Pelvis",
"topology" : "TUBE",
"materials": [ "9", "13" ]
Often a model requires many lyphs with the same layer structure. To simplify the creation of sets of such lyphs, we introduced a notion of the lyph template. A lyph with property isTemplate set to true, serves as a prototype for all lyphs in its property subtypes: such lyphs inherit their layers from the their supertype. In the example below, six lyphs are defined as subtypes of a generic cardiac lyph which works as a template to define their layer structure.
"id"        : "994",
"name"      : "Cardiac Lyphs Prototype",
"layers"    : [ "999", "998", "997" ],
"isTemplate": true,
"subtypes"  : [ "1000", "1001", "1022", "1023", "1010", "1011" ]
"id"   : "1000",
"name" : "Right Ventricle"
"name" : "Left Ventricle"
Note that inheriting layer structure from the lyph template differs from assigning layers explicitly to all subtype lyphs, either individually or via the group's assign property. A lyph with the same ID cannot be used as a layer in two different lyphs, that would imply that the same graphical object should appear in two different positions, and its dimensions and other context-dependent properties may vary as well. The code above instead implies that we replicate each of three template layers six times, i.e., 18 new lyphs are auto-generated and added to the model for the specification above.
It is possible to customize some of the subtype - layer pairs with the help of the context-dependent queries. For example, the code below
"path" : "$.[?(@.id=='1000')].layers[(@.length-1)]",
"value": { "internalLyphs": [ "995" ] }
assigns internalLyphs to two outer most layers of lyphs 1000 and 1010 while other auto-generated layers remain unchanged. These internal lyphs can be seen as yellow cysts on the image above.
The pair of properties subtypes and supertype can be used to specify a generalization relationship among lyphs without replicating their layer structure or any other properties. To trigger the derivation of layer structure, it is essential to set the isTemplate property to true.
In addition to the link's reversed property that can be used to rotate the lyph it conveyed by 180 degrees, one can set the lyph's own property angle to rotate the given lyph around its axis to the given angle (measured in degrees). Finally, a boolean property create3d indicates whether the editor should generate a 3d view for the given lyph. The view gives the most accurate representation of a lyph but does not allow one to see its inner content.
The field bundles points to the links that have to pass through the lyph.
Regions are flat shapes that help to provide context to the model, e.d., by placing certain process graphs into a region named "Lungs", one can indicate that this process is happening in the lungs.
Region internal content is similar to the content of a lyph. Regions are static and their positions are given in 2D coordinates. The border of the region can include any number of straight segments (links), unlike lyphs which always have 4 sides.
"regions": [
"id"     : "cs",
"name"   : "Cardiac system",
"points" : [{"x": -75, "y": 20}, {"x": -75, "y": 75},{"x": -25, "y": 75},{"x": -25, "y": 20}],
"color"  : "#fbb03f"
"id"     : "cns",
"name"   : "Central Nervous System",
"points" : [{"x": -65, "y": -50}, {"x": -65, "y": -15}, {"x": 65, "y": -15}, {"x": 65, "y": -50}],
"color"  : "#f4ed2f"
In the future, we plan to add an option to create regions based on paths in SVG files.
A flat shape such as lyph or region has a border. The border is an object that extends the class Visual Resource and inherits all properties from the class hierarchy: it can have its own ID, a name, a reference to an external source, etc. The owner shape can refer to its border via its border field.
Practically, borders do not make much sense without their hosting entities. Hence, we auto-generate borders for all lyphs and regions in the model and merge inline objects defining border content within the hosting entity with the generated object. The modeller should only specify entities hosted by the border if the model implies the semantic relationships among the corresponding concepts.
The lyph's border is closely related to its topology. The topology defines the types of its radial borders: false represents a border with open flow while true corresponds to closed borders. On each lyph border, i.e., the entire lyph perimeter, we distinguish 4 border segments: lyph's inner longitudinal (axial) border, first radial border, outer longitudinal border, and second radial border, roughly corresponding to the 4 sides of the lyph's rectangle. The axial border is always aligned with the lyph's axis (the link that conveys this lyph). All border segments can be accessed via the lyph border property borders which is always an array of 4 objects. Individual border objects may either remain empty or contain a reference to a Link resource that manages the content of the border. The link resource representing one of the border sides refers to its hosting border via the onBorder field.
It is possible to place nodes and other lyphs on any of the border segments. The hostedNodes property in the fragment below forces 3 nodes with the given identifiers to stick to the 2nd radial border of the Kidney Lobus lyph (see the screenshot illustrating the hostedLyphs property):
"id"      : "5",
"name"    : "Kidney Lobus",
"topology": "BAG",
"border"  : {
"borders": [ {}, {}, {}, { "hostedNodes": [ "nPS013", "nLR05", "nLR15" ] } ]
Similarly, in the next snippet, the model indicates that the 4th (2nd radial) border must convey the lyph with id = "5".
"name"    : "Renal Parenchyma",
"borders": [ {}, {}, {}, { "conveyingLyph": "5" } ]
Here one may observe that the conveyed lyph is using the container lyph's border as its axis. To avoid a whole new level of complication in the modelling schema by supporting lyphs that rotate around border objects, we auto-generate implicit and invisible straight links that coincide with 4 sides of the lyph border.
The ApiNATOMY model can contain definitions of materials, e.g.:
"materials": [
"id"  : "9",
"name": "Biological Fluid"
"id"  : "13",
"name": "Urinary Fluid"
At the moment, we do not include material objects into the graph schematics. Materials of a lyph can be displayed on the information panel if the infoFields property of the lyph is configured to show them.
A coalescence creates a fusion situation where two or more lyphs are treated as being a single entity.
There are two types of coalescence, both describing material fusion. In both cases, coalescence can only occur between lyphs that have exactly the same material composition:
Connecting coalescence represents a 'sideways' connection between two or more lyphs such that their outermost layer is shared between them. The visualisation of such a situation requires that only a "single" depiction of these layers is shown. Technically, we still use two visual objects which, however, are aligned in such a way that they appear as a single object (provided that they are of the same size).
Embedding coalescence represents dropping of a contained lyph into a container lyph such that the outer layer of the contained lyph fuses with the container lyph. The visualisation of such a situation requires that only the container lyph is shown.
The Coalescence class, apart from the generic resource properties id, name, etc., defines fields topology and lyphs which the model author should use to specify the type of the coalescence, CONNECTING or EMBEDDING (default value is CONNECTING) and the coalescing lyphs, respectively. The field lyphs expects an array of coalescing lyphs. Although semantically the order of the lyphs in the connecting coalescence are not important, in the viewer, the first lyph is treated as a "master" - while connecting the graphical depictions of coalescing lyphs, all subsequent lyphs are pushed by the force-directed layout to approach the "master" lyph and realign their outermost layers to match the outermost layer of the first lyph. In the case of the embedded coalescence, the first lyph is expected to be the housing lyph.
If a coalescence resource is defined on abstract lyphs (lyph templates), it is considered abstract and works as a template to generate coalescences among lyphs that inherit the abstract lyphs.
The images below show the visualization of connecting coalescence: two coalescing lyphs, Visceral Bowman's capsule and Glomerulus, share a common outer layer, Basement membrane:
In the case of embedding coalescence, the outer layer of the embedded lyph blends with the layer of the housing lyph, we make it invisible:
A group is a subset of entities from the ApiNATOMY model (which can also be seen as a group) that have a common semantic meaning and/or a distinct set of visual characteristics. A group can include nodes, links, lyphs, materials, and other groups (subgroups) via the properties with the corresponding names.
In the example below, we define a group of blood vessels by joining two subgroups, arterial and venous vessels.
"groups": [
"id"    : "omega",
"name"  : "Blood vessels",
"groups": ["arterial", "venous"]
"id"    : "arterial",
"name"  : "Arterial",
"nodes" : [ "nLR00", "nLR01", "nLR02", "nLR03", "nLR04", "nLR05" ],
"links" : [ "LR00", "LR01", "LR02", "LR03", "LR04" ]
"id"    : "venous",
"name"  : "Venous",
"nodes" : [ "nLR10", "nLR11", "nLR12", "nLR13", "nLR14", "nLR15", "nLR16" ],
"links" : [ "LR10", "LR11", "LR12", "LR13", "LR14", "LR15" ]
In the current version of the viewer, checkbox controls are added to the Control Panel for all top level groups so that users can see each of them in isolation or analyze the interaction among selected combinations of entities without overloading the view with unnecessary information. Since at the moment there is no functionality associated with various levels of group nesting, the content of nested groups is unfolded and copied to the top level groups. Note that if someone wants to hide or show a subgraph, it is not necessary to list lyphs conveyed by the graph links, the lyphs are considered part of the link definition for that purpose. However, if one wants to be able to toggle a certain set of lyphs but not their axes, the lyphs should be included to some group explicitly.
Graph is the top-level group that in addition to all the group parameters contains a config object. The field is not part of the semantic physiology model but it can be used to define user preferences regarding the visualization of a certain model. For example, a field filter within this object is currently used to exclude resources with given identifiers from appearing in the relationship graph.
"filter": ["6", "11", "12", "14", "15", "16", "17", "20", "21"]
Among other properties that can be stated here are the default label fields.
Group template is a generic concept to encapsulate resource definitions that result into automatic generation of subgraphs with certain structure and/or semantic meaning. A distinct property of the resource objects of this type is a readonly group property that establishes the relationship between the template and the generated group.
Another currently supported property of this generic class is length that sets in percentage the desired length of the maximal path in the generated group. This property is used to compute the default link length and, consequently, control the size of the lyph shape conveyed by the link.
There is ongoing work on supporting visual resource styles that one will be able to refer to from groups or group templates to define the appearance of links, lyphs and nodes in the entire (auto-generated) group.
This template instructs the model generator to create a chain from an ordered list of conveying lyphs, i.e., a linear concatenation of advective edges that convey the material of the innermost layer of these conveying lyphs. This requires the lyphs in the ordered list to have their innermost layers constituted of the same material.
The listing below shows an example of chain template definition:
"id": "c1",
"conveyingLyphs": ["200", "203", "204", "205", "206", "207", "208", "209", "210", "211", "212", "213", "214", "215", "216"],
"start": "s",
"end": "t"
Apart from the list of conveyingLyphs field, the template provides start and end fields which allows users to name the start and the end nodes of the chain which may be useful if one wants to integrate the chain fragment into a larger model graph.
Branching underlies the formation of numerous body systems, including the nervous system, the respiratory system, many internal glands, and the vasculature. An omega tree is a template to create a rooted tree data structure (a graph in which any two vertices are connected by exactly one path, and one node is designated the root) that we use in ApiNATOMY to model branching systems.
The Tree resource class allows users to specify a root of the tree via an optional property root that can point into an existing node. If the root node is not specified, it is either automatically generated or assigned to coincide with the source node of a link that represents the first level of the tree.
We define the level of a tree branch as the number of edges between the target node of the link and the root. A user may specify the required number of levels in a tree via its optional property numLevels which expects a positive integer value. Given the desired number of levels, the ApiNATOMY lyph viewer can generate a group (a read-only property that refers to a Group resource and encompasses all necessary nodes and links) to represent the tree. If the property lyphTemplate points to an abstract lyph, the generated links for each tree level then convey lyphs which are subtypes of this template.
Alternatively, the tree branches can be specified, partially or fully, via the property levels which expects an array of partial or complete link definitions corresponding to the tree levels. If this array contains an empty object, the missing tree level branch is auto-generated. If instead it points to an existing link, the corresponding link then becomes the branch of the tree. If source, target, or both ends of the link resource are not specified, they are auto-generated. Otherwise, it is expected that incident links (connected tree branches) share a common node; the tool will issue a warning if this is not the case.
"trees": [
"id"          : "axonal",
"name"        : "Axonal omega tree",
"root"        : "a",
"numLevels"   : 5,
"lyphTemplate": "neuronBag"
"id"          : "UOT",
"name"        : "Urinary Omega Tree",
"root"        : "b",
"levels"      : ["lnk1", "lnk2", "lnk3", "lnk4", "lnk5", "lnk6", "lnk7", "lnk8", "lnk9", "lnk10",
"lnk11", "lnk12", "lnk13", "lnk14", "lnk15", "lnk16", "lnk17", "lnk18", "lnk19", "lnk20", "lnk21"],
"branchingFactors": [1, 1, 2, 1, 1, 1, 3, 3, 20, 8, 9, 8, 9]
Our examples section demonstrates in full detail how to define omega trees using both lyphTemplate and levels properties. A combination of both approaches may help modellers to reduce an effort while specifying multi-level trees where the majority of the branches convey the same lyphs (involve the same tissue structures) while certain levels either convey different lyphs or are characterized by unique features that need to be modelled in a special way.
The trees defined this way actually do not have any branching, they look like liner chains of enumerated links. We refer to such trees as canonical, meaning that they define the basic structure necessary to generate a branching tree that models an organ or a physiological subsystem. The branching can happen at each level of the canonical tree definition, and the number of branches per level can be specified in the branchingFactors array. The size of the array does not need to coincide with the size of the levels array - branching stops at the last level with branching factor greater than 1.
A user may define a required number of branching tree instances produced from the canonical tree specification. This is done with the help of the boolean property numInstances. The generated subgraphs representing branching tree instances are available via the read-only property instances in the expanded ApiNATOMY model. The lyphs for a tree instance are assigned create3d property, i.e., the generated tree instance can be visualized using solid 3d lyph renderings.
In the case of trees with branches that convey lyphs derived from a common lyphTemplate pattern, we can use the topology property of the lyph template to define the overall topology of the tree. Generally, lyphs originating from a lyph template inherit its topology. However, the lyphs conveyed by the tree edges work as a single conduit with topological borders at the start and the end levels (root and leaves) of the tree compliant with the borders of the lyph template. Thus, the topology of the lyphs on tree edges is defined according to the table below:
Lyph template
Radial borders
Levels 2..N-1
Level N
TUBE both open TUBE TUBE TUBE TUBE
BAG 1st closed BAG TUBE TUBE BAG
BAG2 2nd closed BAG2 BAG2 TUBE TUBE
CYST both closed CYST BAG2 TUBE BAG
A tree template can be used to reduce repetition and possibility of error by automating the creation of a tree and associated conveying lyphs to distribute/embed conveying lyphs over an ordered list of housing lyphs. If the housingLyphs list is provided in a tree template, the number of levels is set to equal the size of this list, and a tree group with no branching is generated, then each level of the generated tree is bundled with the corresponding housing lyph as follows:
The edges for the non-terminal housing lyphs span the housing lyph completely. The nodes of these edges anchor on the radial borders of the outermost layer of the housing lyph, i.e. they run parallel to the longitudinal borders. For the first and the last lyphs in the housingLyphs set, only one node anchors on the radial border, the other "hangs free" inside the housing lyph.
The housing lyph is bundled with the tree level via its property bundles. Respectively, the level link refers to the housing lyph via its property fasciculatesIn
Finally, the embedded coalescence resource is created to link the housing lyph and the lyph conveyed by the bundled link.
The fragment below shows an example of housed tree definition. More details about this model can be found in the Examples section (Bolser-Lewis map)
"id": "t1",
"name": "Neuron",
"lyphTemplate": "229",
"housingLyphs": ["202", "201", "200", "203", "204", "205", "206", "207", "208", "209", "210", "211", "212", "213", "214", "228"]
The image below shows a neuron tree aligned along the chain of housing lyphs.
Semantically, lyphs in contiguous chains of lyphs have a common border, but because the chosen ApiNATOMY visualization approach depicts lyphs as centered icons with separate borders, the alignment of the omega trees that respects the border constraints set by the rules above require the non-terminal level link ends to be placed on two separate lines. To address this problem, we rely on node clones and collapsible links (drawn as dashed lines) that connect two copies of the same node. Developers who plan to work with the ApiNATOMY models should keep this in mind when traversing the ApiNATOMY graph - two semantically adjacent graph links can be separated by an auxiliary collapsible link that does not convey any lyphs. Hence, to access a link that models the next level in the generated tree group, starting from the tree level link L1,one may need to use the following 3 step traversals:
L1.target.clones[0].sourceOf => L2
Here, L1.target gives the target node of L1, then clones[0] field gives a reference to its clone (there can be more clones of the same node as this mechanism is not limited by the canonical tree level alignment), an, finally, sourceOf field would provide the following link, L2.
For the transition in the reverse direction, the similar path can be used via the opposite cloneOf field that links the cloned node to its prototype:
L2.source.cloneOf.targetOf => L1
The Channel resource class provides fields to define a template that will instruct the model generator to create specialized assemblies (groups, subgraphs) that represent membrane channels incorporated into the given housing lyphs.
To create membrane channel components, a model author provides:
an identifier for the channel alone with optional characteristics shared by all ApiNATOMY resources, i.e., name, external annotations, etc.;
identifiers of housing lyphs. A housing lyph is a lyph of at least three layers representing some cell or organelle (e.g. Sarcoplasmic Reticulum) such that the middle layer of this lyph is a membrane;
the material payload that is conveyed by the diffusive edge;
The identifiers of the housing lyphs and materials conveyed by the diffusive edges of the channel are specified in the resource properties housingLyphs and materials, respectively. Alternatively, a lyph can refer to the channel it houses via its property channel.
Given these data, the model generator creates three tube lyphs representing the three segments of the membrane channel (MC): internal, membranous and external. Each of the MC segments consists of three layers as follows:
innermost, or the content;
middle, or the wall;
outermost, or the same stuff (material) as the lyph that contains it; The group assembly generated given such a template will include 23 resources (4 nodes, 3 links, 3 lyphs with 3 layers each, 3 coalescences, and a group resource that encompasses nodes, links and lyphs of the channel instance). If the housing lyph is a template, this number of resources is then replicated for each channel instance housed by a lyph instance that is a subtype of the template.
The three MC segments are placed (housed) respectively in:
the innermost layer of the housing lyph;
the second layer of the housing lyph, which must be constituted of material of type membrane
the third layer of the housing lyph. To fulfill this requirement, we automatically set constraints that require channel nodes to be hosted by the borders of the layers of the housing lyph.
The third layer of each MC segment undergoes an embedding coalescence with the layer of the housing lyph that contains it. Each of the three MC segments conveys a diffusive edge such that both nodes of the edge conveyed by the MC segment in the second (membranous) layer are shared by the other two diffusive edges. Diffusive edges are associated with the links that convey the membrane channels (i.e., the link's conveyingType is set to DIFFUSIVE) and the material in the channel object is copied to the conveyingMaterials property of the link.
The images below show two membrane channels, mc1: Na-Ca exchanger and mc2: SR Ca-ATPase, which are housed by the abstract lyphs (templates) with IDs 63 and 60: Myocyte and Sarcoplasmic reticulum, respectively. The first image shows abstract assemblies, the second image shows the instances of these assemblies housed by two lyph instances derived from the abstract Myocyte and Sarcoplasmic reticulum lyph templates.
As one can see, channels are defined in a minimalistic way, but may cause the model generator to automatically create a potentially large number of resources, the modeller should keep this in mind to avoid state space explosion.
The basal ganglia are a group of subcortical nuclei at the base of the forebrain and top of the midbrain. The basal ganglia are associated with a variety of functions, including control of voluntary motor movements, procedural learning, habit learning, eye movements, cognition, and emotion. Basal ganglia are strongly interconnected with the cerebral cortex, thalamus, and brainstem, as well as several other brain areas.
The ApiNATOMY model automatically reproduces the layout from the schematic representation of the basal ganglia created by the physiology experts, given relational constraints among its constituent parts. Conceptually, the model consists of:
4 context lyphs: Basal Ganglia, Putamen, Globus Pallidus external (GPe) and Globus Pallidus internal (GPi) segments;
a model of a neuron composed of 3 parts: dendrite and axon modelled as trees (we call them omega trees) and a conduit representing the axon hillock (a specialized part of the cell body, or soma, of a neuron that connects to the axon) that joins the omega trees on its sides.
Even though omega trees often look like simple chains in our schematics, the underlying data model implies that a branching tree can be generated from the canonical representation given model parameters such as branching factor or mean number of branches at each level).
Technically, the model is essentially a JSON file with 4 fields: nodes, links, lyphs, and trees. The context lyphs, Putamen, GPe and GPi, are modelled as internal lyphs of Basal Ganglia:
"id"    : "bg",
"name"  : "Basal Ganglia",
"color" : "#d1d2d4",
"internalLyphColumns": 3,
"internalLyphs": [ "putamen", "gpe", "gpi" ]
This means that they are positioned on a grid within their container lyph, and the corresponding parameter, internalLyphColumns: 3 indicates that the grid should contain 3 columns. The number of rows depends on the number of internal lyphs within the container. Other space allocation methods for internal lyphs will be supported upon demand, for example, template-based treemaps appear to be particularly useful if we need to dedicate areas of various size to internal lyphs while preserving relevant adjacency constraints.
The nodes and links to model rotational axes of internal lyphs are auto generated (they can also be defined explicitly if a user wants to override the default properties, i.e., make them visible, or specify relationships between them and other graph entities). Thus, in our model, we only define the position and the size of the main context lyph's axis, Basal Ganglia:
{ "id": "a", "layout": {"x": -100, "y": 100, "z": 0 } },
{ "id": "b", "layout": { "x": 100, "y": 100, "z": 0 } },...
"id"      : "main",
"source"  : "a",
"target"  : "b",
"length"  : 100,
"geometry": "invisible",
"conveyingLyph": "bg"
},...
The trees property is an array with 2 objects defining the dendrite 1-level tree and the axonal 5-level trees:
"id"          : "dendrite",
"name"        : "Dendrite omega tree",
"root"        : "n1",
The tree root nodes are named n1 and n2, these names are explicitly given while defining the the axis of the axon hillock, and by referring to them in the tree model, we indicate that the roots of the axonal and dendrite trees coincide with the ends of the hillock.
Similarly to the root nodes, it is possible to plug an external link, a node or a lyph into the generated tree at a certain level via the optional levels property which expects an array with (partial) link definitions (see JSON Schema definition of the tree model for more details).
In the current model, we do not refer to external entities while defining the content of the tree branches. However, all auto-generated ApiNATOMY entities are also assigned IDs that can be referenced later to connect the part of the graph obtained from the tree template with the rest of the model. The identifies for auto-generated tree parts are formed using the following patterns:
{$tree.id}_node{$index}
{$tree.id}_lnk{$index}
{$tree.id}_lyph{$index}
where $tree.id is the identifier of the tree, and $index refers to a tree level. For the node names, the $index ranges from 0 to N, where N is the number of levels. Hence, the root node corresponds to the index = 0, the end node of the tree branch at the first level - to the index = 1, and so on. For the link and lyph names, the index ranges from 1 to N. For example, the valid ID names for the basal ganglia trees:
axonal_node3 - end node of the 3d level of the 'axonal' tree
axonal_lyph5 - lyph at the 5th level of the 'axonal' tree,
dendrite_lnk1 - link at the 1st level of the 'dendrite' tree.
These names can be used to impose positional constraints on the generated entities. For example, in our model, the axonal tree node is located on the 2nd radial border of the GPi lyph, while two axonal tree level lyphs are hosted by (mapped to the surface of) the the GPi lyph.
"id"          : "gpi",
"name"        : "GPi",
"color"       : "#939598",
"height"      : 30,
"border"      : { "borders": [ {}, {}, {}, { "hostedNodes": [ "axonal_node3" ] }]},
"hostedLyphs" : [ "axonal_lyph4", "axonal_lyph5" ]
Another version of the basal ganglia shows how one can combine explicitly assigned tree levels with auto-generated ones.
The lyphTemplate field in these omega tree models refers to the lyph pattern to derive the structure of the conduits in the tree branches. Firstly, the tool expands the tree template by creating the necessary graph structure (a rooted tree with the required number of levels). Secondly, the blank lyph definitions associated with the tree graph are added to the subtypes property of the lyph template. At the next stage, the lyph viewer will process the lyph templates: the prototype lyph layers, color and size settings are copied to all template subtypes. Hence, at the tree expansion stage, the user definition of the template lyph:
"id"        : "neuronBag",
"topology"  : "BAG",
"color"     : "#ccc",
"scale": {
"width" : 80,
"height": 80
"layers": ["cytosol", "plasma", "fluid"]
is extended with the definition of subtype lyphs which will get 3 layers and will occupy each the square area with a side length computed as 80% of their axis length. Note that the hillock lyph also derives its structure from the neuronBag template, as indicated by its property supertype:
"id"       : "hillock",
"name"     : "Hillock",
"supertype": "neuronBag",
"topology" : "TUBE"
Hence, after the generation of entities to represent required tree structures and bi-directional relationship synchronization, the user definition of the neuron template in the model will be auto-completed, i.e., the lyph template will know all lyphs that replicated its layers via its subtypes property:
"subtypes": [axonal_lyph1,...,axonal_lyph5, dendrite_lyph1, hillock]
The lyphs conveyed by the tree edges are seen as a single conduit with topological borders at the start and the end levels (root and leaves) of the tree compliant with the borders of the lyph template. In our example, the lyph template is of type BAG. Hence, the conveying lyphs at the end levels, dendrite_lyph1 and axonal_lyph5, are of the type BAG while all the intermediate level lyphs, axonal_lyph1,...,axonal_lyph4, are of the type TUBE.
The topology of the hillock lyph, which also inherits the layer structure from the neuronBag lyph template, has to be explicitly defined as TUBE to override the inherited topology from the template.
The image below shows the layout created by the tool for the Basal Ganglia scenario based on the resource definition explained in this section.
There is also an option to instruct the editor to generate 3d representation of lyphs: if a lyph's attribute create3d is set to true, the user will see 3d-dimensional lyphs when the option lyphs 3d in the control panel is enabled. When generating omega trees, the viewer automatically sets create3d to true, the corresponding layout for the Basal ganglia scenario is shown in the snapshot below.
The live demo of this scenario with the possibility to edit the model file in an integrated JSON editor is available here.
This model illustrates the ApiNATOMY format for the urinary arborisation. The purpose of this example is to illustrate how one can model an omega tree with branching points and resource annotation with references to external ontologies.
The urinary tree model consists of 21 level. Levels are defined as links conveying specific lyphs, from Intravesical Urethra to Visceral Bowman's Capsule. The layer structure of these lyphs is modelled with the help of abstract templates that correspond to physiological tissues: urine (URN), transitional epithelium (TE), basement membrane (BM), muscosa (Mus), muscularis (Ms1) etc.
"id"        : "IU",
"name"      : "Intravesical urethra",
"topology"  : "TUBE",
"length"    : {"min": 2, "max": 2},
"thickness" : {"min": 3, "max": 3},
"layers"    : ["URN", "Mcs", "Ms1"],
"external"  : ["UBERON:0000057"]
"id"        : "URN",
"name"      : "Urine",
"color"     : "#f9ed32",
Whenever the specific lyphs refer to abstract lyphs as their layers, meaning that the conduit we model consists of certain tissues, the lyph viewer automatically generates lyph instances and replaces the conduit layers with the references to the generated lyphs representing tissues within the conduits, i.e., urine in the intravesical urethra. The generated lyphs will refer to the template via their supertype field and later inherit a set of template properties, namely, color, scale, height, width, length, thickness, as well as the references in the fields external and materials.
In the ApiNATOMY data model, trees are templates that replicate the given lyph template to the requited number of levels. However, it may be useful to define some or all of the tree levels by referring to already existing links. This is the case when there is no common lyph template that applies to all tree levels or when the tree is part of the bigger models and its elements are connected to other parts of the graph.
The urinary omega tree below is defined in the aforementioned manner: its levels are composed of existing links that convey various lyphs. In principle, the same subgraph could be defined as a simple group, but the tree concept allows us to specify the branching patterns and automatically generate an instance of a canonical tree. The canonical omega tree is the minimal construct that is necessary to represent the structural composition of a certain organ or a physiology system, the tree instance is an actual arborisation that adheres to the structural, dimensional and branching patterns in the canonical tree. Due to certain degrees of freedom (probabilistic branching patterns, level dimension ranges, etc.) in the canonical trees, the tree instances we generate may vary.
"trees" : [
"root"        : "uot-a",
"numLevels"   : 21,
"levels"      : ["uot-lnk1", "uot-lnk2", "uot-lnk3", "uot-lnk4", "uot-lnk5", "uot-lnk6", "uot-lnk7", "uot-lnk8", "uot-lnk9", "uot-lnk10",
"uot-lnk11", "uot-lnk12","uot-lnk13", "uot-lnk14", "uot-lnk15", "uot-lnk16", "uot-lnk17","uot-lnk18","uot-lnk19", "uot-lnk20", "uot-lnk21"
"branchingFactors": [1, 1, 2, 1, 1, 1, 3],
"comment": "Branching factors for the rest of the tree removed to avoid state explosion ... 3, 20, 8, 9, 8, 9, 1, 1, 1, 1, 1, 1, 1, 1"
The images below show the canonical omega tree for the Urinary system model in 2d and 3d.
The next image shows the snapshot of the omega tree instance with branching in levels 3 and 7. The actual model of the urinary omega tree has more branching points, but due to the number of visual elements needed to represent the entire model (appr. 90 million), the viewer cannot handle all of them in the same view. If necessary, we recommend to explore different branching points separately by setting branching factor for other levels to 1.
In this model, several subgroups of items are annotated with a single ontology term. We can represent such a many-to-one mapping by defining and annotating subgroups. hence, in the ApiMATOMY model for this system, you can find subgroups defining a nephron and a loop of Henle, with the corresponding UBERON term IDs.
"id"      : "nephron",
"name"    : "Nephron",
"nodes"   : ["uot-m", "uot-n", "uot-o","uot-p","uot-q","uot-r","uot-s","uot-t","uot-u","uot-v"],
"links"   : [ "uot-lnk13", "uot-lnk14", "uot-lnk15", "uot-lnk16", "uot-lnk17", "uot-lnk18", "uot-lnk19", "uot-lnk20", "uot-lnk21"],
"lyphs"   : ["DCT", "FPofTAL", "DST", "ATL", "DTL", "PST", "PCT", "PBC", "VBC"],
"external": ["UBERON:0001285"]
"id"      : "henle",
"name"    : "Loop of Henle",
"nodes"   : ["uot-n","uot-o","uot-p","uot-q","uot-r"],
"links"   : ["uot-lnk14", "uot-lnk15", "uot-lnk16", "uot-lnk17"],
"lyphs"   : ["FPofTAL", "DST", "ATL", "DTL"],
To instruct the viewer to stretch the tree from left to right, we add layout constraints to the tree root and leaf nodes. We also rely on the assign property and JSON path expressions to customize the appearance of the nodes and lyphs: the nodes' color is set to red while the main conveying lyphs are set to the neutral grey color.
"path" : "$.nodes[*]",
"value": { "color" : "red"}
"path"  : "$.links[*].conveyingLyph",
"value" : { "color" : "#ccc" }
Please note that this example shows a rough work-in-progress model that demonstrates the use of modeling concepts rather than preserves the physiological accuracy!
The example is based on a mock-up for the Bolser-Lewis model
The model author defined the necessary resources in the Excel format. The image below shows the snapshot of the Excel template we developed as alternative to the text-based JSON format. The model from the Excel template can be exported as an .xlsx file and opened from the ApiNATOMY model viewer. The integrated converter translates the model to the JSON-based input format.
The model shows the neuron tree passing through a chain of body compartments. As a requirement, the author wanted to generate the chain given an ordered list of conveying lyphs:
The chain template shown in the image above produces a chain of connected links that convey the lyphs from the chain's conveyingLyphs property:
The neuron tree needs to be generated to match the number of housing lyphs:
The specification above does not set numLevels or levels fields; instead the size of the housingLyphs array here is used to determine the number of generated tree levels; each tree level is then "embedded" to the corresponding housing lyph. This implies that the tree level link ends are hosted by the housing lyph or, in case of layered lyphs, its outermost layer (hostedBy relationship is set).
Moreover, an embedding coalescence is defined between the pairs of the housing lyphs and the conveying lyphs of the tree levels they house.
One can observe that the generated omega tree has collapsible "spacer" links. These links should disappear in the views that do not require the same node to appear in two different locations (i.e., on borders of adjacent lyphs which are displayed with a gap). The lyph viewer determines whether spacer link ends are constrained based on the visibility of the related resources.
Generated by ESDoc(1.1.0)


Neal Pollard Preachers have: The greatest message to communicate (Rom. 1:16). It is infinitely better and more important than that shared by broadcasters, news anchors, and sports analysts (cf. 1 Cor. 1:18). The greatest "boss" to please (Eph. 6:6-7). I have known and worked with so many great elders. I understand that they "hired" me and … Continue reading It's Great To Be A Preacher!
Neal Pollard Poor Pluto. First it's a planet and then it's not anymore. It has become the Rodney Dangerfield of our solar system. In an award-winning move that probably did not make the "sub planet" feel better, "plutoed" was selected as the Word of the Year by the American Dialect Society in Anaheim, California, a … Continue reading Do You Feel Plutoed?
How Much Will It Take To Make You Happy?
Neal Pollard Well, according to a London survey, it takes--for the average person--about 1.5 million dollars to make one happy. One NBC analyst says that by knowing you make more than the Joneses next door, you are likely to be quite happy. As usual, we give our thanks to the experts. Are they better informed … Continue reading How Much Will It Take To Make You Happy?


text:
Robert Foster
OEM Coordinator
Bogota Office of Emergency Management
69 West Broad Street
Bogota Borough Hall
e-mail: oem@bogotaonline.org
To provide a comprehensive Emergency Management System which coordinates people and resources to protect the lives, property and environment of the Borough of Bogota, using an all-hazard approach through mitigation, preparedness, response and recovery from disasters and emergencies.
The Office of Emergency Management (OEM) is responsible, by Federal and State Law, for the coordination of all the Emergency Services in the Borough of Bogota. This includes Police, Fire, Emergency Medical Services, Rescue, Public Works, Health Department and all additional agencies contributing to any large scale emergency incident or disaster.
Emergency incidents can strike anytime, anywhere and in many forms, such as a hurricane, snow storm, earthquake, flood, fire, hazardous material incident; an act of nature or an act of terrorism.
Besides working closely with the Police Chief, Fire Chief, EMS Chief and Rescue Chief, the Bogota Office of Emergency Management receives support from the Bergen County Office of Emergency Management and the New Jersey State Office of Emergency Management. The Bogota Emergency Services are dedicated to the protection of our borough residents and business community.
Membership is also held in the New Jersey State Emergency Management Association where experience and knowledge are shared by all Emergency Management personnel.
During non-business hours the OEM Coordinator and Deputy Coordinator are available for emergencies through the Bogota Police Department.
Matthew Luciano
Office of Emergency Management Team
Christopher Kelemen, Mayor
Robert Foster, Coordinator
Matthew Luciano, Deputy Coordinator
Daniel Maye, Police Chief
Robert Piterski, Police Captain
Joseph Kieiber, Volunteer Fire Chief
William Hordern, Deputy Fire Chief
Michael Krynicky, Battalion Fire Chief
Wayne Sorge, Volunteer Rescue Chief
Sam Yanovich, Health Officer
Jeanne Cook, Health Secretary
Daniele Fede, Liaison to Environmental Commission
Damian Kennedy, Superintendent of Schools
Cathy Capasso, Registered Nurse
Family Emergency Preparedness Plan
Every home and family should have an Emergency Preparedness Plan for every type of emergency or disaster. The best way to protect your family from the effects of a disaster is to have a disaster plan. Here are some tips to assist you in creating your own Family Emergency Preparedness Plan
Include two places for family members to meet if separated; two ways to evacuate your home, if required; teach children how and when to dial 911; have phone numbers available for out of area friends who can assist.
Store at lease three days of emergency supplies, such as water, food, communications equipment, clothing and bedding, sanitary needs. Know where valuable papers are stored, such as social security cards, wills, bank books, insurance policies.
If you are a pet owner, your Family Emergency Preparedness Plan should include your pets.
What is the Office of Emergency Management's Role?
Should an emergency arise that would cause the activation of the Office of Emergency Management Organization, and Department Heads Would remain in charge of their respective sections. However, requests for communications, movements, resources and needs would be coordinated through the incident command post site or at the Emergency Operations Center".
How does the OEM achieve its mission?
Mitigation – Activities that eliminate or reduce the risk of disaster (insurance, building codes, flood plain management, public education)
Preparedness – Planning, exercise, training, public information systems and warning
Response – Direction/Control, warning, evacuation, emergency service to address immediate and short term effects of an emergency/ disaster
Recovery – Short term, those operations that seek to restore critical services and meet basic needs. Long term, those actions that restore the community to its normal state. Mitigation measures such as temporary housing and food, restoring non-vital Borough services.
Preparedness
Bogota's Emergency Operations Plan is on file with Bergen County OEM as well as the New Jersey State Office of Emergency Management.
Bogota's Emergency Management Plan...
Describes use of assets for all emergency / disaster situations, evacuation procedures
Describes direction and control protocol of Police, Fire, medical, DPW services
Describes alert and Warning protocol – Radio, TV, Autodialing systems
Describes critical facilities, shelters, roads, waterways
Address all emergencies – Weather related, Hazmat, Terrorism, WMD
The Bogota Office of Emergency Management Team meets on a monthly basis. The Local Emergency Planning Committee meets quarterly.
All Municipalities in the country must have an Emergency Operations Plan, which is the responsibility of the local Emergency Management Coordinator. This plan details all types of emergencies and the responsibilities of all local Emergency Services during declared state of emergencies. This plan must be undated every four (4) years and approved by the State of New Jersey. The Bogota Emergency Operations Plan was completely revised in 2009 and was approved by the State and placed in service in June of 2009. After the disastrous events of September 11, 2001, the State requested all local OEM's to prepare and submit for approval, a Terrorism Plan for their community.
The annex details the responsibilities of all Emergency Services during a terrorism incident, sets up an Emergency Management Command Post, and details what outside services should be called.
A terrorism incident is a Law Enforcement function and therefore, the Bogota Police Department is the lead agency in any response to such an incident. OEM will coordinate all involved agencies.
Transporting Pets to an Evacuation Site
Snakes can be transported in a pillowcase, but they must be transferred to a more secure housing when the reach the evacuation site. If your snakes require frequent feedings, carry food with you.
Take a water bowl large enough for soaking as well as a heating pad.
When transporting house lizards, follow the same directions as for birds.
Hamsters, gerbils etc. . . should be transported in secure carriers suitable for maintaining the animals while sheltered.
Take bedding materials, food, bowls and water bottles.
Transport in a secure travel cage or carrier. Try to keep the carrier in a quiet area. Do not let the birds out of the cage or carrier.
In cold weather, wrap a blanket over the carrier and warm up the car before placing birds inside. During warm weather, carry a plant mister to mist the bird's feathers periodically.
Do not put water inside the carrier during transport. Provide a few slices of fresh fruits and vegetables with high water content.
Have leg bands and a photo for ID.
A Few Days After a Disaster
In the first few days after a disaster, leash your pets when they go outside. Always maintain close contact. Familiar scents and landmarks may be altered and your pet may become confused and lost.
The behavior of your pets may change after an emergency. Normally quiet and friendly pets may become aggressive or defensive. Watch animals closely. Leash dogs and place them in a fenced yard with access to shelter and water.
The Bogota Emergency Operations Center is the Borough Wide Command Post for emergency operations during any major incident, involving all Emergency Services. There are three (3) different Operation Centers, which are staffed, depending on the type of incident being managed.
Incident Type: Large Scale Incident Which Affects the Entire Borough
For these incidents, where all Borough Agencies, County and State Agencies are assisting. The Emergency Operations Center will be activated at the Bogota Emergency Operations Center at 69 W. Broad Street. The following personnel will report to the Center:
The Mayor, Emergency Management Coordinator, Police Chief, Fire Chief, Rescue Chief, Public Works representative and any out of town personnel required by the Coordinator.
Incident Type: Out of Town Incidents where Bogota Emergency Services are Requested.
For an incident where the Bogota Emergency Services were requested to assist in other locations, out of the borough, and protective services were required locally, the Emergency Operations Center will be activated and maintained by committed personnel.
Incident Type: Single Location Incidents within the Borough
For a large scale incident, which is confined to one location or one section of the borough. The Emergency Operations Center will be operated at the scene, using the Emergency Management Coordinators vehicle, which is equipped to communicate to all Borough, County and State Emergency Services. In these cases, as needed the following personnel will report to the Mobile OEM Command Center
Emergency Incident County, State and Federal Links
Office of Homeland Security
United States Department of Homeland Security - FEMA

redpajama_set_name: RedPajamaCommonCrawl


Students with hearing loss face special challenges at university and college. But, there are more resources than ever to help you succeed at school. If you are a student who has recently been identified with hearing loss, HearSay provides you with the following tips to achieve academic success.
Do You Have Single-Sided Hearing Loss?


Marcel Kittel finished off the day-long efforts of his Quick-Step Floors team in style, nailing the bunch sprint in Sacramento to win the stage and first race leader's jersey over world champion Peter Sagan (Bora-hansgrohe). Elia Viviani (Team Sky) was third.
"I'm very happy how intelligent and also strong my team worked in the end," Kittel said of his win. "Chapeau to everyone for the great lead out. It was really nice, promising also for the next week. We are all very happy to start the Tour of California like that."
"It's not a surprise that maybe the beginning of the race was not super intense," he said. "It was a really easy stage when you look at the profile. Some teams tried to go in the crosswinds after around 80km, but nothing happened; the wind was not strong enough and the direction was not good enough. So in the end it came down to a sprint."
It didn't take long for the breakaway to form on the flat roads outside of town, with BMC Racing's Floris Gerts, UnitedHealthcare's Jonny Clarke, Novo Nordisk's Charles Planet and Jelly Belly-Maxxis' Ben Wolfe escaping the bunch and building a lead of two minutes rather quickly.


text:
my-PV integrates electric water heating system into SMA PV battery system
As part of a reference project in Borken, Germany, my-PV GmbH has integrated its electric hot water preparation system into an existing PV battery system created by SMA Solar Technology AG. Installing the AC ELWA-E system resulted in a system with a hybrid storage that can increase self-consumption of self-generated electricity by up to 100 %. AC ELWA-E is the newest member of my-PV's ELWA product line and is available with immediate effect.
October 12, 2016 my-PV GmbH
Austria-based my-PV has developed the alternating current model AC ELWA-E specially for smart home systems with integrated battery storage. The heating element is infinitely variable from 0 to 3,000 watts, adjusts its output to the power surplus once a second, and thus reacts very quickly. AC ELWA-E is integrated into the facility management system via Ethernet and has a standby consumption of less than 1.5 watts.
SMA-employee Manuel März was the beta-tester for this particularly flexible energy supply for one-family homes. A grid-connected photovoltaic unit with connected battery storage has been supplying his house in Borken with power since 2014. The building is heated using an air-to-water heat pump. In spring 2016 März upgraded the system to include an AC ELWA-E developed by my-PV.
Hybrid storage maximises self-consumption
The complex system is controlled by an SMA Sunny Home Manager. The photovoltaic plant first covers the current own power requirement and then charges the battery. The rest of the solar power then heats water for the heating system via the AC ELWA-E. Now that the photovoltaic unit not only supplies the house with electricity but also with heat, the heat pump is only used to generate energy as a last resort.
"Thanks to the AC ELWA-E I was able to deactivate my heat pump completely during the summer months. That means a longer service life for such sensitive technology", is how März describes the advantages of the new system. Dr Gerhard Rimpler, CEO of my-PV GmbH, sees the advantage of AC ELWA-E over an auxiliary battery storage especially in terms of price. "The cost of AC ELWA-E as additional storage capacity is nothing compared to the present cost of batteries", he says. On top of that, an existing system can be expanded with little extra effort.
www.my-pv.com


In some states, STEM policymaking efforts have not achieved their intended results, often due to initiatives lacking one or more of the following essential elements: statewide coordination, adequate funding and evaluation. That is the latest analysis from the Education Commission of the States (ECS), which recently published a report that examines one state's success in implementing STEM policy and offers key practices for other policymakers.
In the "Promising Practices in Education" report, ECS focuses on STEM policy efforts within Utah. In 2013, the state established the Utah STEM Action Center, which fuels research and implementation of STEM education best practices throughout the state. Prior to the center, Utah school districts were purchasing supplemental math learning tools, but had no data on whether the products would yield desired outcomes. The center allowed districts to test a wide variety of products and even set specific qualifications for products, according to the report.
Evaluation – Policymakers examined long-term STEM programs to determine their impact.
Additional components that were critical to the center's success, according to the report, include communications; marketing and positioning; partnerships and liaisons; and funding.
The full report is available on the Education Commission of the States site.


text:
Igudesman & Joo bring blend of music, comedy to Englert
Zach Berg
zberg@press-citizen.com
The world of classical music is a little too stale for the musical comedy duo Igudesman & Joo.
Composed of Russian violinist Aleksey Igudesman and British-Korean pianist Hyung-ji Joo, the classically-trained duo has made a name for themselves by treating the likes of Wolfgang Amadeus Mozart.
With over 35 million views on YouTube, hundreds of concerts across the globe – from Belgrade, Serbia to Pittsburgh, Penn. – and performances alongside world renowned classical musicians, and even James Bond, aka Sir Roger Moore, the duo of Igudesman & Joo has fused the worlds of comedy and music into one.
Whether it be Joo karate-chopping his piano keys in a way that Beethoven can still be heard, or Igudesman singing a Mozart-themed version of Gloria Gaynor's disco anthem "I Will Survive," the two are bringing their one-of-a-kind blend of comedy and music to The Englert Theatre at 8 p.m. Saturday.
"The way classical music is present very often is too stuffy," Igudesman said during a phone interview last week.
"There's a lot of comedy in the music. Haydn had the random breaks and pauses in his music. Beethoven was deeply sardonic. Even Schubert wrote comedies," Igudesman said.
Joseph Haydn, the famed Austrian composer who taught Beethoven, was once employed by a king who would often fall asleep during performances of his music. In response, Haydn wrote a soft piece that had sudden and violently loud notes that would startle the king awake. That's the kind of comedy Igudesman & Joo brings to classical comedy.
"Every Shakespeare tragedy has the comic parts in it, so why not classical," Igudesman asked.
The style of comedy the two musicians share is deeply indebted to the iconic British comedy troupe Monty Python, Igudesman said. While Monty Python members weren't classically trained like Igudesman, the troupe's dedication to music was obvious with tunes like "The Lumberjack Song" and "Always Look on the Bright Side of Life."
The duo does also have more modern influences when it comes to the art of mixing humor and music: Matt Parker and Trey Stone, the creators of "South Park." Though the cartoon is infamous for its foul-mouthed fourth graders, Igudesman says the show "has a lot of music produced and written at a very high level."
The comedy duo know a thing or two about music that's written and performed at a high level. The two met at the Yehudi Menuhin School in England when they were both 12 years old. Attending a school named after, and founded by, a man roundly considered one of the great violinists of the 20th century may add some pressure to students, but Joo and Igudesman did not crack, they just became a little nutty.
"We bonded over fish and chips," Igudesman recalled. "But we also bonded over how we viewed music, with that nod to humor."
The two would go one to establish themselves as well respected artists in the music world. Joo has performed as a solo pianist for conductors and orchestras across the globe and even recorded piano pieces for Billy Joel's 2001 album "Fantasies and Delusions."
Igudesman has also recorded music and performed as a solo artist around the world. He has also written multiple books of sheet music ranging from songs written about cats to songs about pigs. He's even a regular in the orchestras famed movie composer Hans Zimmer uses to record the scores of movies – Igudesman was featured in the Academy Award nominated score for the 2009 "Sherlock Holmes" film.
But it's the comedic stylings of Igudesman & Joo that has brought them the most notoriety, Igudesman said. Starting in 2004, the two started touring a show called "A Little Nightmare Music," a show that had as much piano and violin music as it did staged bickering and arguments between the two performers.
As the years passed, and websites like YouTube became more popular, Igudesman said that a curious thing started to happen. "People who had never listened to classical music before were coming to our shows. People were bringing kids."
By 2007, videos of their performances were racking up millions of views on YouTube, which is something he never expected to happen.
"That was never the primary reason we did these performances. It was just a wonderful byproduct," Igudesman said. "The premise is always an artistic one: music being performed at a high level in an entertaining way."
"The fact that this would bring kids and people who don't like music can get a laugh is just fascinating for us. We enjoy it all immensely."
And now the two are back on the road with their new comedic musical hybrid, "And Now Mozart," which blends classical music with cowboy hats, police uniforms, and all other manners of comedy.
But no matter how many laughs the two of them get, Igudesman assured audiences their music will never been anything less than the best they can perform.
"(Joo's) dedication to improving and never letting go of the idea that we can do this better ensures that we'll never play a single note just for the sake it," Igudesman said.
What: Igudesman and Joo presents "And Now Mozart," a comedic blend of classical violin, piano by two classically trained musicians who also happen to be big fans of "South Park."
Where: The Englert Theatre, 221 E. Washington St., Iowa City.
When: 8p.m. Saturday.
Tickets: $35. DVD copies of previous Igudesman and Joo shows will also be on sale at the event.
Reach Zach Berg at 319-887-5412, zberg@press-citizen.com, or follow him on Twitter at @ZacharyBerg.