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Date modified: Oct.3rd 2010


22 November 1996
Disease Outbreak Reported
A media statement by the Department of Health on 21 November informs that routine monitoring of all people known to have been exposed at some level of risk to the two Ebola fever patients treated in Johannesburg is continuing. No additional cases of Ebola fever have been confirmed but monitoring will continue at a meticulous level until the last contact clears the 21-day incubation period. The nurse who became infected while caring for an Ebola patient from Gabon is still in a serious but stable condition.
All contacts undergo twice-daily checks at the hospitals where they are employed. This includes taking of temperatures and checking by a health worker. A contact with raised temperature who reports a headache or feeling generally unwell will be referred for clinical examination and blood test. In some cases contacts had been admitted to the hospital at Rietfontein for a brief stay, while other contacts are monitored on an outpatient basis.
A total of 41 people have been removed from the monitoring list because the incubation period has elapsed. The number of contacts on the list fluctuates because names are sometimes added, especially as a result of new staff coming on shift to care for the hospitalized nurse.


Money Play. How should Red play 43?
pips Red=82 White=142
(CorrectAnswer= 0/0, ErrorScore= 0)
A classic ‘pay me now pay me later' problem that is easy to get wrong. Those two stripped points are more difficult to clear than you might think and problems may start immediately.
Meanwhile. White has a lot of blots strewn around. If White's third checker on his bar-point was on his 3-pt giving him a 3-pt board then 10/7, 10/6 and 6/2, 4/1 would be virtually tied.
As it is 10/7, 10/6 is a very clear winner with 6/2, 4/1 nearly a blunder. Both plays win about the same percentage of games but 10/7, 10/6 wins 6% more gammons because White has to give up his anchor to hit and because of the state of his home board. That 6% is a huge difference. Never forget to evaluate gammon possibilities in positions like this.
Meanwhile. White has a lot of blots strewn around. If White's third checker on his bar-point was on his 3-pt giving him a 3-pt board then 10/7, 10/6 and 6/2, 4/1 would be virtually tied.
As it is 10/7, 10/6 is a very clear winner with 6/2, 4/1 nearly a blunder. Both plays win about the same percentage of games but 10/7, 10/6 wins 6% more gammons because White has to give up his anchor to hit and because of the state of his home board. That 6% is a huge difference. Never forget to evaluate gammon possibilities in positions like this.
1. Cubeful 2-ply 15/11 6/4(2) Eq.: +0.084 0.556 0.131 0.004 - 0.444 0.127 0.003 2. Cubeful 2-ply 24/22 13/11 6/4(2) Eq.: -0.053 (-0.137) 0.525 0.135 0.006 - 0.475 0.158 0.005 3. Cubeful 2-ply 13/11(2) 6/4(2) Eq.: -0.068 (-0.153) 0.519 0.139 0.006 - 0.481 0.160 0.005 4. Cubeful 2-ply 13/11 8/4 6/4 Eq.: -0.117 (-0.202) 0.505 0.141 0.006 - 0.495 0.167 0.006 5. Cubeful 2-ply 24/22 15/13 6/4(2) Eq.: -0.122 (-0.206) 0.504 0.116 0.004 - 0.496 0.153 0.004


open fun saveConfig(command: ICommand<*>): Unit
Saves the command's current properties to JSON.
command - The command to save its properties to JSON.
command
See Also
CommandConfig.writeConfigs


| MPI_CANCEL(request) | |
| IN request | communication request (handle) |
int MPI_Cancel(MPI_Request *request)
MPI_Cancel(request, ierror)
TYPE(MPI_Request), INTENT(IN) :: request
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_CANCEL(REQUEST, IERROR)
INTEGER REQUEST, IERROR
A call to MPI_CANCEL marks for cancellation a pending, nonblocking communication operation (send or receive). The cancel call is local. It returns immediately, possibly before the communication is actually cancelled. It is still necessary to call MPI_REQUEST_FREE, MPI_WAIT or MPI_TEST (or any of the derived operations) with the cancelled request as argument after the call to MPI_CANCEL. If a communication is marked for cancellation, then a MPI_WAIT call for that communication is guaranteed to return, irrespective of the activities of other processes (i.e., MPI_WAIT behaves as a local function); similarly if MPI_TEST is repeatedly called in a busy wait loop for a cancelled communication, then MPI_TEST will eventually be successful.
MPI_CANCEL can be used to cancel a communication that uses a persistent request (see Section Persistent Communication Requests ), in the same way it is used for nonpersistent requests. A successful cancellation cancels the active communication, but not the request itself. After the call to MPI_CANCEL and the subsequent call to MPI_WAIT or MPI_TEST, the request becomes inactive and can be activated for a new communication.
The successful cancellation of a buffered send frees the buffer space occupied by the pending message.
Either the cancellation succeeds, or the communication succeeds, but not both. If a send is marked for cancellation, then it must be the case that either the send completes normally, in which case the message sent was received at the destination process, or that the send is successfully cancelled, in which case no part of the message was received at the destination. Then, any matching receive has to be satisfied by another send. If a receive is marked for cancellation, then it must be the case that either the receive completes normally, or that the receive is successfully cancelled, in which case no part of the receive buffer is altered. Then, any matching send has to be satisfied by another receive.
If the operation has been cancelled, then information to that effect will be returned in the status argument of the operation that completes the communication.
Rationale.
Although the IN request handle parameter should not need to be passed
by reference, the C binding has listed the argument type as MPI_Request* since
MPI-1.0. This function signature therefore cannot be changed without breaking
existing MPI applications.
( End of rationale.)
| MPI_TEST_CANCELLED(status, flag) | |
| IN status | status object (Status) |
| OUT flag | (logical) |
int MPI_Test_cancelled(const MPI_Status *status, int *flag)
MPI_Test_cancelled(status, flag, ierror)
TYPE(MPI_Status), INTENT(IN) :: status
LOGICAL, INTENT(OUT) :: flag
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_TEST_CANCELLED(STATUS, FLAG, IERROR)
LOGICAL FLAG
INTEGER STATUS(MPI_STATUS_SIZE), IERROR
Returns flag = true if the communication associated with the status object was cancelled successfully. In such a case, all other fields of status (such as count or tag) are undefined. Returns flag = false, otherwise. If a receive operation might be cancelled then one should call MPI_TEST_CANCELLED first, to check whether the operation was cancelled, before checking on the other fields of the return status.
Advice to users.
Cancel can be an expensive operation that should be used only exceptionally.
( End of advice to users.)
Advice
to implementors.
If a send operation uses an ``eager'' protocol (data is transferred to
the receiver
before a matching receive is posted), then the cancellation of this send
may require communication with the intended receiver in order to free
allocated
buffers. On some systems this may require an interrupt to the
intended receiver.
Note that, while communication may be needed to implement
MPI_CANCEL,
this is still a local operation, since its completion does not
depend on the code executed by other processes. If processing is required on
another process, this should be transparent to the application (hence the need
for an interrupt and an interrupt handler).
( End of advice to implementors.)


You might be surprised to know that the Looney Tunes have actually been around since before you were born. These are their life stories!
Joe Adamson, Film Historian/Filmmaker, is the author of Bugs Bunny: Fifty Years and Only One Grey Hare and Tex Avery: King of Cartoons.


A User Experience Developer Who Loves Exploring Possibilities
I am a Master of Health Informatics new grad at the University of Michigan (Go Blue!), focusing on UX design and consumer health technologies. Pivoting my career from business to UX design, I am not afraid of challenges and excited about learning anything to build a great product that helps people.
View ResumeA web app that detects the human face present in the image.
I use Clarifai API to detect the human faces in the image the user uploaded after they registered and save the counts of their uploaded image. I use React.js to build the front-end with Tachyons CSS, use Node.js and express.js, and cooperate with Clarifai face detection API, and use PostgreSQL to build the user login system and database that keeps track of the entries number.
— Full-stack, React, API, Node.JS
A movie database project using React and TMDB API.
I used React, CSS3, and The Movie Database API to create an interactive hulu-like website.
— React, Firebase, API
A useful web tool to help you create gradient CSS background.
I used pure HTML, CSS and Javascript to create a website that would randomly generate gradient background.
— Front-end, Javascript, CSS
The project is about building a responsive landing page with pure HTML5, CSS3 amd Flexbox.
— Front-end, Responsive Design
The project is about building a responsive landing page with pure HTML5, CSS3 amd Flexbox.
— Front-end, Responsive Design
Would you like to work with me? Awesome!
Let's Talk


Built-In Namespace _global_
| Method Attributes | Method Name and Description |
|---|---|
|
countClick(element, parent, parent_container, obj_id, obj_loc, ip)
|
|
|
filterBy(element)
|
|
|
sendData(_new_search, min_index, _flag, searchField, searchFilter, http_req, form, resp, json, status_code, data, span)
|
|
|
sortObjects(data)
|
Method Detail
countClick(element, parent, parent_container, obj_id, obj_loc, ip)
- Parameters:
- {object} element
- References the element with link for the corresponding item for each row.
- {object} parent
- The parent DOM element of the element.
- {object} parent_container
- The container which encapsulates the parent of element.
- {int} obj_id
- The product_id for that specific parent row.
- {string} obj_loc
- The URL of the current page. Used to build a link to the BE script.
- {string} ip
- The ip of the client.
filterBy(element)
- Parameters:
- {object} element
- References the DOM element (i.e. select) that initiates the script.
{int}
getDocumentHeight()
- Returns:
- {int} window_max_h
sendData(_new_search, min_index, _flag, searchField, searchFilter, http_req, form, resp, json, status_code, data, span)
- Parameters:
- {boolean} _new_search
- If true - initiates new search, if false - just adds rows to existing ones.
- {int} min_index
- The minimum index from which the search should be initiated.
- {string} _flag
- A flag to point the function to the needed action: Add (to existing rows) or New (only add new rows).
- {string} searchField
- Stores the text entered by the user in the search field.
- {string} searchFilter
- Stores the selected filter option by the user - (name or description search).
- {object} http_req
- Instance of createXMLHttpInstance to send an async request to the back-end.
- {object} form
- Instance of FormData to store all the data that is to be sent to the back-end through the 'http_req'.
- {string} resp
- The JSON formatted string returned by the back-end.
- {JSON} json
- JSON object from the data in 'resp' varialbe.
- {boolean} status_code
- The status code returned from the server. Only processed if true, everything else is considered as false (problem).
- {JSON} data
- JSON object with the actual row data from @see json.
- {object} span
- References the span DOM element where all the returned rows will loaded to the front-end.
- See:
- parseJson to parse the returned JSON formatted string.
- sortObjects to sort returned rows in ascending order by product_id.
- setCategories to load the returned categories in the dropdown used for fitlering the rows by category.
{array}
sortObjects(data)
- Parameters:
- {array} data
- json object with the returned rows by the back-end
- Returns:
- {array}


Current temperature is:
Power saving mode is on
Current weather in London is:
Current temperature in London is:
degrees


NMU student missing
by Algoa FMDetectives from Bethelsdorp in Port Elizabeth are looking for a 23-year-old Nelson Mandela University student who went missing on Wednesday.
Spokesperson Colonel Priscilla Naidu says Keanan Bouwer left his house in Heath Park on the 27th at about 11 am to go to University and later in the afternoon messaged his mother to inform her that he was going to the cricket at St Georges Park.
She says that was the last time anybody had contact with him.
At 9 am on Friday morning police found Bouwer's car abandoned near Settlers Park in Walmer.
Naidu says it is alleged that the car was parked there on Wednesday evening.
She says the car was locked but does appear to have been tampered with.

Any person with information on his possible whereabouts is asked to contact Detective Captain Kobus Williams at SAPS Bethesldorp on<PHONE_NUMBER>


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Differentially abundant taxa between Parkinson’s disease patients (PD) and healthy controls (HC)
Overview of the most frequently reported differentially abundant fecal microbiota between PD and HC, found in at least four independent populations. Reported taxa are mentioned in bold, with higher taxonomic levels (phylum and/or family) provided when applicable. Total number of citations and the number of citations indicating an increased or decreased relative abundance in PD are mentioned respectively. Number of publications reporting a statistically significant difference in relative abundance ( P < 0.05) are mentioned between parentheses. 1Depending on the taxonomic nomenclature, Akkermansia can also be classified as a genus of the family Akkermansiaceae.


In algorithm analysis, the process of deriving asymptotic bounds for one problem from the asymptotic bounds of another. In particular, if problem A can be used to solve problem B, and problem A is proved to be in \(O(f(n))\), then problem B must also be in \(O(f(n))\). Reductions are often used to show that certain problems are at least as expensive as sorting, or that certain problems are NP-Complete.
- reference
A value that enables a program to directly access some particular data item. An example might be a byte position within a file where the record is stored, or a pointer to a record in memory. (Note that Java makes a distinction between a reference and the concept of a pointer, since it does not define a reference to necessarily be a byte position in memory.)
- reference count algorithm
An algorithm for garbage collection. Whenever a reference is made from a variable to some memory location, a counter associated with that memory location is incremented. Whenever the reference is changed or deleted, the reference count is decremented. If this count goes to zero, then the memory is considered free for reuse. This approach can fail if there is a cycle in the chain of references.
- reference parameter
A parameter that has been passed by reference. Such a parameter can be modified inside the function or method.
- reflexive
In set notation, binary relation \(R\) on set \(S\) is reflexive if \(aRa\) for all \(a \in \mathbf{S}\).
- Region Quadtree
A spatial data structure for storing 2D pixel data. The idea is that the root of the tree represents the entire image, and it is recursively divided into four equal subquadrants if not all pixels associated with the current node have the same value. This is structurally equivalent to a PR quadtree, only the decomposition rule is changed.
- regular expression
A way to specify a set of strings that define a language using the operators of union, contatenation, and star-closure. A regular expression defines some regular language.
- regular grammar
And grammar that is either right-regular or left-regular. Every regular grammar describes a regular language.
- regular language
A language \(L\) is a regular language if and only if there exists a Deterministic Finite Automata \(M\) such that \(L = L(M)\).
- relation
In set notation, a relation \(R\) over set \(\mathbf{S}\) is a set of ordered pairs from \(\mathbf{S}\).
- replacement selection
A variant of heapsort most often used as one phase of an external sort. Given a collection of records stored in an array, and a stream of additional records too large to fit into working memory, replacement selection will unload the heap by sending records to an output stream, and seek to bring new records into the heap from the input stream in preference to shrinking the heap size whenever possible.
- reserved block
In a memory manager, this refers to space in the memory pool that has been allocated to store data received from the client. This is in contrast to the free blocks that represent space in the memory pool that is not allocated to storing client data.
- resource constraints
Examples of resource constraints include the total space available to store the data (possibly divided into separate main memory and disk space constraints) and the time allowed to perform each subtask.
- root
In a tree, the topmost node of the tree. All other nodes in the tree are descendants of the root.
- rotation
In the AVL Tree and Splay Tree, a rotation is a local operation performed on a node, its children, and its grandchildren that can result in reordering their relationship. The goal of performing a rotation is to make the tree more balanced.
- rotational delay
When processing a disk access, the time that it takes for the first byte of the desired data to move to under the I/O head. On average, this will take one half of a disk rotation, and so constitutes a substantial portion of the time required for the disk access.
- rotational latency
A synonym for rotational delay.
- run
A series of sorted records. Most often this refers to a (sorted) subset of records that are being sorted by means of an external sort.
- run file
A temporary file that is created during the operation of an external sort, the run file contains a collection of runs. A common structure for an external sort is to first create a series of runs (stored in a run file), followed by merging the runs together.
- run-time polymorphism
A form of polymorphism known as Overriding. Overridden methods are those which implement a new method with the same signature as a method inherited from its base class. Compare to compile-time polymorphism.
- runtime environment
The environment in which a program (of a particular programming language) executes. The runtime environment handles such activities as managing the runtime stack, the free store, and the garbage collector, and it conducts the execution of the program.
- runtime stack
The place where an activation record is stored when a subroutine is called during a program’s runtime.
- scanner
The part of a compiler that is responsible for doing lexical analysis.
- scope
The parts of a program that can see and access a variable.
- search key
A field or part of a record that is used to represent the record when searching. For example, in a database of customer records, we might want to search by name. In this case the name field is used as the search key.
- search lower bound
The problem of searching in an array has provable lower bounds for specific variations of the problem. For an unsorted array, it is \(\Omega(n)\) comparisons in the worst case, typically proved using an adversary argument. For a sorted array, it is \(\Omega(\log n)\) in the worst case, typically proved using an argument similar to the sorting lower bound proof. However, it is possible to search a sorted array in the average case in \(O(\log \log n)\) time.
- search problem
Given a particular key value \(K\), the search problem is to locate a record \((k_j, I_j)\) in some collection of records L such that \(k_j = K\) (if one exists). Searching is a systematic method for locating the record (or records) with key value \(k_j = K\).
- search tree
A tree data structure that makes search by key value more efficient. A type of container, it is common to implement an index using a search tree. A good search tree implementation will guarentee that insertion, deletion, and search operations are all \(\Theta(\log n)\).
- search trie
Any search tree that is a trie.
- searching
Given a search key \(K\) and some collection of records L, searching is a systematic method for locating the record (or records) in L with key value \(k_j = K\).
- secondary clustering
In hashing, the tendency in certain collision resolution methods to create clustering in sections of the hash table. In primary clustering, this is caused by a cluster of keys that don’t necessarily hash to the same slot but which following significant portions of the same probe sequence during collision resolution. Secondary clustering results from the keys hashing to the same slot of the table (and so a collision resolution method that is not affected by the key value must use the same probe sequence for all such keys). This problem can be resolved by double hashing since its probe sequence is determined in part by a second hash function.
- secondary index
Synonym for secondary key index.
- secondary key
A key field in a record such as salary, where a particular key value might be duplicated in multiple records. A secondary key is more likely to be used by a user as a search key than is the record’s primary key.
- secondary key index
Associates a secondary key value with the primary key of each record having that secondary key value.
- secondary storage
Refers to slower but cheaper means of storing data. Typical examples include a disk drive, a USB memory stick, or a solid state drive.
- sector
A unit of space on a disk drive that is the amount of data that will be read or written at one time by the disk drive hardware. This is typically 512 bytes.
- sector header
On a disk drive, a piece of information at the start of a sector that allows the I/O head to recognize the identity (or equivalently, the address) of the current sector.
- seed
In random number theory, the starting value for a random number series. Typically used with any linear congruential method.
- seek
On a disk drive, the act of moving the I/O head from one track to another. This is usually considered the most expensive step during a disk access.
- selection sort
While this sort requires \(\Theta(n^2)\) time in the best, average, and worst cases, it requires only \(\Theta(n)\) swap operations. Thus, it does relatively well in applications where swaps are expensive. It can be viewed as an optimization on bubble sort, where a swap is deferred until the end of each iteration.
- self-organizing list
A list that, over a series of search operations, will make use of some heuristic to re-order its elements in an effort to improve search times. Generally speaking, search is done sequentially from the beginning, but the self-organizing heuristic will attempt to put the records that are most likely to be searched for at or near the front of the list. While typically not as efficient as binary search on a sorted list, self-organizing lists do not require that the list be sorted (and so do not pay the cost of doing the sorting operation).
- self-organizing list heuristic
A heuristic to use for the purpose of maintaining a self-organizing list. Commonly used heuristics include move-to-front and transpose.
- separate chaining
In hashing, a synonym for open hashing
- sequence
In set notation, a collection of elements with an order, and which may contain duplicate-valued elements. A sequence is also sometimes called a tuple or a vector.
- sequential access
In file processing terminology, the requirement that all records in a file are accessed in sequential order. Alternatively, a storage device that can only access data sequentially, such as a tape drive.
- sequential fit
In a memory manager, the process of searching the memory pool for a free block large enough to service a memory request, possibly reserving the remaining space as a free block. Examples are first fit, circular first fit, best fit, and worst fit.
- sequential search
The simplest search algorithm: In an array, simply look at the array elements in the order that they appear.
- sequential tree representation
A representation that stores a series of node values with the minimum information needed to reconstruct the tree structure. This is a technique for serializing a tree.
- serialization
The process of taking a data structure in memory and representing it as a sequence of bytes. This is sometimes done in order to transmit the data structure across a network or store the data structure in a stream, such as on disk. Deserialization reconstructs the original data structure from the serialized representation.
- set
- set former
A way to define the membership of a set, by using a text description. Example: \(\{x\ |\ x\ \mbox{is a positive integer}\}\).
- set product
Written \(\mathbf{Q} \times \mathbf{P}\), the set product is a set of ordered pairs such that ordered pair \((a, b)\) is in the product whenever \(a \in \mathbf{P}\) and \(b \in \mathbf{Q}\). For example, when \(\mathbf{P} = \{2, 3, 5\}\) and \(\mathbf{Q} = \{5, 10\}\), \(\mathbf{Q} \times \mathbf{P} = \{(2, 5),\ (2, 10),\ (3, 5),\ (3, 10),\ (5, 5),\ (5, 10)\}\).
- shallow copy
Copying the reference or pointer value without copying the actual content.
- Shellsort
A sort that relies on the best-case cost of insertion sort to improve over \(\Theta(n^2)\) worst case cost.
- shifting method
A technique for finding a closed-form solution to a summation or recurrence relation.
- shortest path
Given a graph with distances or weights on the edges, the shortest path between two nodes is the path with least total distance or weight. Examples of the shortest paths problems are the single-source shortest paths problem and the all-pairs shortest paths problem.
- sibling
In a tree, a sibling of node \(A\) is any other node with the same parent as \(A\).
- signature
In a programming language, the signature for a function is its return type and its list of parameters and their types.
- signature file
In document processing, a signature file is a type of bitmap used to indicate which documents in a collection contain a given keyword, such that there is a bitmap for each keyword.
- simple cycle
In graph terminology, a cycle is simple if its corresponding path is simple, except that the first and last vertices of the cycle are the same.
- simple path
In graph terminology, a path is simple if all vertices on the path are distinct.
- simple type
A data type whose values contain no subparts. An example is the integers.
- simulating recursion
If a programming language does not support recursion, or if you want to implement the effects of recursion more efficiently, you can use a stack to maintain the collection of subproblems that would be waiting for completion during the recursive process. Using a loop, whenever a recursive call would have been made, simply add the necessary program state to the stack. When a return would have been made from the recursive call, pop the previous program state off of the stack.
- single rotation
A type of rebalancing operation used by the Splay Tree and AVL Tree.
- single-source shortest paths problem
Given a graph with weights or distances on the edges, and a designated start vertex \(s\), find the shortest path from \(s\) to every other vertex in the graph. One algorithm to solve this problem is Dijkstra’s algorithm.
- singly linked list
A linked list implementation variant where each list node contains access an pointer only to the next element in the list.
- skip list
A form of linked list that adds additional links to improve the cost of fundamental operations like insert, delete, and search. It is a probabilistic data structure since it adds the additional links using a probabilistic algorithm. It can implement a dictionary more efficiently than a BST, and is roughly as difficult to implement.
- slot
In hashing, a position in a hash table.
- snowplow argument
An analogy used to give intuition for why replacement selection will generate runs that are on average twice the size of working memory. Records coming from the input stream have key values that might be of any size, whose size is related to the position of a falling snowflake. The replacement selection process is analogous to a snowplow that moves around a circular track picking up snow. In steady state, given a certain amount of snow equivalent to working memory size \(M\), an amount of snow (incoming records from the input stream) is expected to fall ahead of the plow as the size of the working memory during one cycle of the plow (analogously, one run of the replacement selection algorithm). Thus, the snowplow is expected in one pass (one run of replacement selection) to pick up \(2M\) snow.
- software engineering
The study and application of engineering to the design, development, and maintenance of software.
- software reuse
In software engineering, the concept of reusing a piece of software. In particular, using an existing piece of software (such as a function or library) when creating new software.
- solution space
The possible solutions to a problem. This typically refers to an optimization problem, where some solutions are more desireable than others.
- solution tree
An ordering imposed on the set of solutions within a solution space in the form of a tree, typically derived from the order that some algorithm would visit the solutions.
- sorted list
A list where the records stored in the list are arranged so that their key values are in ascending order. If the list uses an array-based list implementation, then it can use binary search for a cost of \(\Theta(\log n)\). But both insertion and deletion will be require \(\Theta(n)\) time.
- sorting lower bound
The lower bound for the problem of sorting is \(\Omega(n \log n)\). This is traditionally proved using a decision tree model for sorting algorithms, and recognizing that the minimum depth of the decision tree for any sorting algorithm is \(\Omega(n \log n)\) since there are \(n!\) permutations of the \(n\) input records to distinguish between during the sorting process.
- sorting problem
Given a set of records \(r_1\), \(r_2\), …, \(r_n\) with key values \(k_1\), \(k_2\), …, \(k_n\), the sorting problem is to arrange the records into any order \(s\) such that records \(r_{s_1}\), \(r_{s_2}\), …, \(r_{s_n}\) have keys obeying the property \(k_{s_1} \leq k_{s_2} \leq ... \leq k_{s_n}\). In other words, the sorting problem is to arrange a set of records so that the values of their key fields are in non-decreasing order.
- space/time tradeoff
Many programs can be designed to either speed processing at the cost of additional storage, or reduce storage at the cost of additional processing time.
- sparse graph
A graph where the actual number of edges is much less than the possible number of edges. Generally, this is interpreted to mean that the degree for any vertex in the graph is relatively low.
- sparse matrix
A matrix whose values are mostly zero. There are a number of data structures that have been developed to store sparse matrices, with the goal of reducing the amount of space required to represent it as compared to simply using a regular matrix representation that stores a value for every matrix position.
- spatial
Referring to a position in space.
- spatial application
An application what has spatial aspects. In particular, an application that stores records that need to be searched by location.
- spatial attribute
An attribute of a record that has a position in space, such as the coordinate. This is typically in two or more dimensions.
- spatial data
Any object or record that has a position (in space).
- spatial data structure
A data structure designed to support efficient processing when a spatial attribute is used as the key. In particular, a data structure that supports efficient search by location, or finds all records within a given region in two or more dimensions. Examples of spatial data structures to store point data include the bintree, the PR quadtree and the kd tree.
- spindle
The center of a disk drive that holds the platters in place.
- Splay Tree
A variant implementation for the BST, which differs from the standard BST in that it uses modified insert and remove methods in order to keep the tree balanced. Similar to an AVL Tree in that it uses the concept of rotations in the insert and remove operations. While a Splay Tree does not guarentee that the tree is balanced, it does guarentee that a series of \(n\) operations on the tree will have a total cost of \(\Theta(n \log n)\) cost, meaning that any given operation can be viewed as having amortized cost of \(\Theta(\log n)\).
- splaying
The act of performing an rebalancing operation on a Splay Tree.
- stable
A sorting algorithm is said to be stable if it does not change the relative ordering of records with identical key values.
- stack
A list-like structure in which elements may be inserted or removed from only one end.
- stack frame
Frame of data that pushed into and poped from call stack
- stack variable
Another name for a local variable.
- stale pointer
Within the context of a buffer pool or memory manager, this means a reference to a buffer or memory location that is no longer valid. For example, a program might make a memory request to a buffer pool, and be given a reference to the buffer holding the requested data. Over time, due to inactivity, the contents of this buffer might be flushed. If the program holding the buffer reference then tries to access the contents of that buffer again, then the data contents will have changed. The possibility for this to occur depends on the design of the interface to the buffer pool system. Some designs make this impossible to occur. Other designs make it possible in an attempt to deliver greater performance.
- start state
In a finite automata, the designated state in which the machine will always begin a computation.
- start symbol
In a grammar, the designated non-terminal that is the intial point for deriving a string in the langauge.
- state
The condition that something is in at some point in time. In computing, this typically means the collective values of any existing variables at some point in time. In an automata, a state is an abstract condition, possibly with associated information, that is primarily defined in terms of the conditions that the automata may transition from its present state to another state.
- State Machine
Synonym for finite automata.
- static
Something that is not changing (in contrast to dynamic). In computer programming, static normally refers to something that happens at compile time. For example, static analysis is analysis of the program’s text or structure, as opposed to its run-time behavior. Static binding or static memory allocation occurs at compile time.
- static scoping
A synonym for lexical scoping.
- Strassen’s algorithm
A recursive algorithm for matrix multiplication. When multiplying two \(n \times n\) matrices, this algorithm runs faster than the \(\Theta(n^3)\) time required by the standard matrix multiplication algorithm. Specifically, Strassen’s algorithm requires time \(Theta(n^{\log_2 7})\) time. This is achieved by refactoring the sub-matrix multiplication and addition operations so as to need only 7 sub-matrix multiplications instead of 8, at a cost of additional sub-matrix addition operations. Thus, while the asymptotic cost is lower, the constant factor in the growth rate equation is higher. This makes Strassen’s algorithm inefficient in practice unless the arrays being multiplied are rather large. Variations on Strassen’s algorithm exist that reduce the number of sub-matrix multiplications even futher at a cost of even more sub-matrix additions.
- strategy
An approach to accomplish a task, often encapsulated as an algorithm. Also the name for a design pattern that separates the algorithm for performing a task from the control for applying that task to each member of a collection. A good example is a generic sorting function that takes a collection of records (such as an array) and a “strategy” in the form of an algorithm that knows how to extract the key from a record in the array. Only subtly different from the visitor design pattern, where the difference is primarily one of intent rather than syntax. The strategy design pattern is focused on encapsulating an activity that is part of a larger process, so that different ways of performing that activity can be substituted. The visitor design pattern is focused on encapsulating an activity that will be performed on all members of a collection so that completely different activities can be substituted within a generic method that accesses all of the collection members.
- stream
The process of delivering content in a serialized form.
- strict partial order
In set notation, a relation that is irreflexive, antisymmetric, and transitive.
- strong induction
An alternative formulation for the induction step in a proof by induction. The induction step for strong induction is: If Thrm holds for all \(k, c \leq k < n\), then Thrm holds for \(n\).
- subclass
In object-oriented programming, any class within a class hierarchy that inherits from some other class.
- subgraph
A subgraph \(\mathbf{S}\) is formed from graph \(\mathbf{G}\) by selecting a subset \(\mathbf{V}_s\) of \(\mathbf{G}\)’s vertices and a subset \(\mathbf{E}_s\) of \(\mathbf{G}\)’s edges such that for every edge \(e \in \mathbf{E}_s\), both vertices of \(e\) are in \(\mathbf{V}_s\).
- subset
In set theory, a set \(A\) is a subset of a set \(B\), or equivalently \(B\) is a superset of \(A\), if all elements of \(A\) are also elements of \(B\).
- subtract-and-guess
A technique for finding a closed-form solution to a summation or recurrence relation.
- subtree
A subtree is a subset of the nodes of a binary tree that includes some node \(R\) of the tree as the subtree root along with all the descendants of \(R\).
- successful search
When searching for a key value in a collection of records, we might find it. If so, we call this a successful search. The alternative is an unsuccessful search.
- summation
The sum of costs for some function applied to a range of parameter values. Often written using Sigma notation. For example, the sum of the integers from 1 to \(n\) can be written as \(\sum_{i=1}^{n} i\).
- superset
In set theory, a set \(A\) is a subset of a set \(B\), or equivalently \(B\) is a superset of \(A\), if all elements of \(A\) are also elements of \(B\).
- symbol table
As part of a compiler, the symbol table stores all of the identifiers in the program, along with any necessary information needed about the identifier to allow the compiler to do its job.
- symmetric
In set notation, relation \(R\) is symmetric if whenever \(aRb\), then \(bRa\), for all \(a, b \in \mathbf{S}\).
- symmetric matrix
A square matrix that is equal to its transpose. Equivalently, for a \(n \times n\) matrix \(A\), for all \(i,j < n\), \(A[i, j] = A[j, i]\).
- syntax analysis
A phase of compilation that accepts tokens, checks if program is syntactically correct, and then generates a parse tree.
- tail
The end of a list.
- terminal
A specific character or string that appears in a production rule. In contrast to a non-terminal, which represents an abstract state in the production. Similar to a literal, but this is the term more typically used in the context of a compiler.
- Theta notation
In algorithm analysis, \(\Theta\) notation is used to indicate that the upper bound and lower bound for an algorithm or problem match.
- token
The basic logical units of a program, as deterimined by lexical analysis. These are things like arithmetic operators, language keywords, variable or function names, or numbers.
- tombstone
In hashing, a tombstone is used to mark a slot in the hash table where a record has been deleted. Its purpose is to allow the collision resolution process to probe through that slot (so that records further down the probe sequence are not unreachable after deleting the record), while also allowing the slot to be reused by a future insert operation.
- topological sort
The process of laying out the vertices of a DAG in a linear order such that no vertex \(A\) in the order is preceded by a vertex that can be reached by a (directed) path from \(A\). Usually the (directed) edges in the graph define a prerequisite system, and the goal of the topological sort is to list the vertices in an order such that no prerequisites are violated.
- total order
A binary relation on a set where every pair of distinct elements in the set are comparable (that is, one can determine which of the pair is greater than the other).
- total path length
- Towers of Hanoi problem
A standard example of a recursive algorithm. The problem starts with a stack of disks (each with unique size) stacked decreasing order on the left pole, and two additional poles. The problem is to move the disks to the right pole, with the constraints that only one disk can be moved at a time and a disk may never be on top of a smaller disk. For \(n\) disks, this problem requires \(\Theta(2^n)\) moves. The standard solution is to move \(n-1\) disks to the middle pole, move the bottom disk to the right pole, and then move the \(n-1\) disks on the middle pole to the right pole.
- track
On a disk drive, a concentric circle representing all of the sectors that can be viewed by the I/O head as the disk rotates. The significance is that, for a given placement of the I/O head, the sectors on the track can be read without performing a (relatively expensive) seek operation.
- track-to-track seek time
Expected (average) time to perform a seek operation from a random track to an adjacent track. Thus, this can be viewed as the minimum possible seek time for the disk drive. This is one of two metrics commonly provided by disk drive vendors for disk drive performance, with the other being average seek time.
- trailer node
Commonly used in implementations for a linked list or related structure, this node follows the last element of the list. Its purpose is to simplify the code implementation by reducing the number of special cases that must be programmed for.
- transducer
A machine that takes an input and creates an output. A Turing Machine is an example of a transducer.
- transitive
In set notation, relation \(R\) is transitive if whenever \(aRb\) and \(bRc\), then \(aRc\), for all \(a, b, c \in \mathbf{S}\).
- transpose
In the context of linear algebra, the transpose of a matrix \(A\) is another matrix \(A^T\) created by writing the rows of \(A\) as the columns of \(A^T\). In the context of a self-organizing list, transpose is a heuristic used to maintain the list. Under this heuristic, whenever a record is accessed it is moved one position closer to the front of the list.
- trap state
In a FSA, any state that has all transitions cycle back to itself. Such a state might be final.
- traversal
Any process for visiting all of the objects in a collection (such as a tree or graph) in some order.
- tree
A tree \(\mathbf{T}\) is a finite set of one or more nodes such that there is one designated node \(R\), called the root of \(\mathbf{T}\). If the set \((\mathbf{T} -\{R\})\) is not empty, these nodes are partitioned into \(n > 0\) disjoint sets \(\mathbf{T}_0\), \(\mathbf{T}_1\), …, \(\mathbf{T}_{n-1}\), each of which is a tree, and whose roots \(R_1, R_2, ..., R_n\), respectively, are children of \(R\).
- tree traversal
A traversal performed on a tree. Traditional tree traversals include preorder and postorder traversals for both binary and general trees, and inorder traversal that is most appropriate for a BST.
- trie
A form of search tree where an internal node represents a split in the key space at a predetermined location, rather than split based on the actual key values seen. For example, a simple binary search trie for key values in the range 0 to 1023 would store all records with key values less than 512 on the left side of the tree, and all records with key values equal to or greater than 512 on the right side of the tree. A trie is always a full tree. Folklore has it that the term comes from “retrieval”, and should be pronounced as “try” (in contrast to “tree”, to distinguish the differences in the space decomposition method of a search tree versus a search trie). The term “trie” is also sometimes used as a synonym for the alphabet trie.
- truth table
In symbolic logic, a table that contains as rows all possible combinations of the boolean variables, with a column that shows the outcome (true or false) for the expression when given that row’s truth assignment for the boolean variables.
- tuple
In set notation, another term for a sequence.
- Turing machine
A type of finite automata that, while simple to define completely, is capable of performing any computation that can be performed by any known computer.
- Turing-acceptable
A language is \(Turing-acceptable\) if there is some Turing machine that accepts it. That is, the machine will halt in an accepting configuration if the string is in the language, and go into a hanging configuration if the string is not in the language.
- Turing-computable function
Any function for which there exists a Turing machine that can perform the necessary work to compute the function.
- Turing-decidable
A language is Turing-decideable if there exists a Turing machine that can clearly indicate for every string whether that string is in the language or not. Every Turing-decidable language is also Turing-acceptable, because the Turing machine that can decide if the string is in the language can be modified to go into a hanging configuration if the string is not in the language.
- two-coloring
An assignment from two colors to regions in an image such that no two regions sharing a side have the same color.
- type
A collection of values.
- unary notation
A way to represent natural numbers, where the value of zero is represented by the empty string, and the value \(n\) is represented by a series of \(n\) marks.
- uncountably infinite
- uncountable
An infinite set is uncountably infinite if there does not exist any mapping from it to the set of integers. This is often proved using a diagonalization argument. The real numbers is an example of an uncountably infinite set.
- underflow
The condition where the amount of data stored in an entity has dropped below some minimum threshold. For example, a node in a B-tree is required to be at least half full. If a record deletion causes the node to be less than half full, then it is in a condition of underflow, and something has to be done to correct this.
- undirected edge
An edge that connects two vertices with no direction between them. Many graph representations will represent such an edge with two directed edges.
- undirected graph
- uninitialized
Uninitialized variable means it has no initial value.
- UNION
One half of the UNION/FIND algorithm for managing disjoint sets. It is the process of merging two trees that are represented using the parent pointer representation by making the root for one of the trees set its parent pointer to the root of the other tree.
- UNION/FIND
A process for mainining a collection of disjoint sets. The FIND operation determines which disjoint set a given object resides in, and the UNION operation combines two disjoint sets when it is determined that they are members of the same equivalence class under some equivalence relation.
- unit production
A unit production is a production in a grammar of the form \(A \rightarrow B\), where \(A, B \in\) the set of non-terminals for the grammar. Any grammar with unit productions can be rewritten to remove them.
- unsolveable problem
A problem that can proved impossible to solve on a computer. The classic example is the halting problem.
- unsorted list
A list where the records stored in the list can appear in any order (as opposed to a sorted list). An unsorted list can support efficient (\(\Theta(1)\)) insertion time (since you can put the record anywhere convenient), but requires \(\Theta(n)\) time for both search and and deletion.
- unsuccessful search
When searching for a key value in a collection of records, we might not find it. If so, we call this an unsuccessful search. Usually we require that this means that no record in the collection actually has that key value (though a probabilistic algorithm for search might not require this to be true). The alternative to an unsuccessful search is a successful search.
- unvisited
In graph algorithms, this refers to a node that has not been processed at the current point in the algorithm. This information is typically maintained by using a mark array.
- upper bound
In algorithm analysis, a growth rate that is always greater than or equal to the growth rate of the algorithm in question. In practice, this is the slowest-growing function that we know grows at least as fast as all but a constant number of inputs. It could be a gross over-estimate of the truth. Since the upper bound for the algorithm can be very different for different situations (such as the best case or worst case), we typically have to specify which situation we are referring to.
- value parameter
A parameter that has been passed by value. Changing such a parameter inside the function or method will not affect the value of the calling parameter.
- variable-length coding
Given a collection of objects, a variable-length coding scheme assigns a code to each object in the collection using codes that can be of different lengths. Typically this is done in a way such that the objects that are most likely to be used have the shortest codes, with the goal of minimizing the total space needed to represent a sequence of objects, such as when representing the characters in a document. Huffman coding is an example of a variable-length coding scheme. This is in contrast to fixed-length coding.
- vector
In set notation, another term for a sequence. As a data structure, the term vector usually used as a snyonym for a dynamic array.
- vertex
- virtual memory
A memory management technique for making relatively fast but small memory appear larger to the program. The large “virtual” data space is actually stored on a relatively slow but large backing storage device, and portions of the data are copied into the smaller, faster memory as needed by use of a buffer pool. A common example is to use RAM to manage access to a large virtual space that is actually stored on a disk drive. The programmer can implement a program as though the entire data content were stored in RAM, even if that is larger than the physical RAM available making it easier to implement.
- visit
During the process of a traversal on a graph or tree the action that takes place on each node.
- visited
In graph algorithms, this refers to a node that has previously been processed at the current point in the algorithm. This information is typically maintained by using a mark array.
- visitor
A design pattern where a traversal process is given a function (known as the visitor) that is applied to every object in the collection being traversed. For example, a generic tree or graph traversal might be designed such that it takes a function parameter, where that function is applied to each node.
- volatile
In the context of computer memory, this refers to a memory that loses all stored information when the power is turned off.
- weight
A cost or distance most often associated with an edge in a graph.
- weighted graph
- weighted path length
Given a tree, and given a weight for each leaf in the tree, the weighted path length for a leaf is its weight times its depth.
- weighted union rule
When merging two disjoint sets using the UNION/FIND algorithm, the weighted union rule is used to determine which subtree’s root points to the other. The root of the subtree with fewer nodes will be set to point to the root of the subtree with more nodes. In this way, the average depth of nodes in the resulting tree will be less than if the assignment had been made in the other direction.
- working memory
The portion of main memory available to an algorithm for its use. Typically refers to main memory made available to an algorithm that is operating on large amounts of data stored in peripheral storage, the working memory represents space that can hold some subset of the total data being processed.
- worst case
In algorithm analysis, the problem instance from among all problem instances for a given input size \(n\) that has the greatest cost. Note that the worst case is not when \(n\) is big, since we are referring to the wrost from a class of inputs (i.e, we want the worst of those inputs of size \(n\)).
- worst fit
In a memory manager, worst fit is a heuristic for deciding which free block to use when allocating memory from a memory pool. Worst fit will always allocate from the largest free block. The rationale is that this will be the method least likely to cause external fragmentation in the form of small, unuseable memory blocks. The disadvantage is that it tends to eliminate the availability of large freeblocks needed for unusually large requests.
- zigzig
A type of rebalancing operation used by splay trees.
- Zipf distribution
A data distribution that follows Zipf’s law, an emprical observation that many types of data studied in the physical and social sciences follow a power law probability distribution. That is, the frequency of any record in the data collection is inversely proportional to its rank when the collection is sorted by frequency. Thus, the most frequently appearing record has a frequency much higher than the next most frequently appearing record, which in turn has a frequency much higher than the third (but with ratio slightly lower than that for the first two records) and so on. The 80/20 rule is a casual characterization of a Zipf distribution. Adherence to a Zipf distribution is important to the successful operation of a cache or self-organizing list.
- zone
In memory management, the concept that different parts of the memory pool are handled in different ways. For example, some of the memory might be handled by a simple freelist, while other portions of the memory pool might be handled by a sequential fit memory manager. On a disk drive the concept of a zone relates to the fact that there are limits to the maximum data density, combined with the fact that the need for the same angular distance to be used for a sector in each track means that tracks further from the center of the disk will become progressively less dense. A zone in this case is a series of adjacent tracks whose data density is set by the maximum density of the innermost track of that zone. The next zone can then reset the data density for its innermost track, thereby gaining more total storage space while preserving angular distance for each sector.


public class AccessibilityNodeProviderCompat
extends java.lang.Object
android.view.accessibility.AccessibilityNodeProvider
introduced after API level 4 in a backwards compatible fashion.| Constructor and Description |
|---|
AccessibilityNodeProviderCompat()
Creates a new instance.
|
AccessibilityNodeProviderCompat(java.lang.Object provider)
Creates a new instance wrapping an
android.view.accessibility.AccessibilityNodeProvider . |
| Modifier and Type | Method and Description |
|---|---|
AccessibilityNodeInfoCompat |
createAccessibilityNodeInfo(int virtualViewId)
Returns an
AccessibilityNodeInfoCompat representing a virtual view,
i.e. a descendant of the host View, with the given virtualViewId
or the host View itself if virtualViewId equals to View#NO_ID . |
java.util.List<AccessibilityNodeInfoCompat> |
findAccessibilityNodeInfosByText(java.lang.String text,
int virtualViewId)
Finds
AccessibilityNodeInfoCompat s by text. |
AccessibilityNodeInfoCompat |
findFocus(int focus)
Find the virtual view, i.e. a descendant of the host View, that has the
specified focus type.
|
java.lang.Object |
getProvider() |
boolean |
performAction(int virtualViewId,
int action,
Bundle arguments)
Performs an accessibility action on a virtual view, i.e. a descendant of the
host View, with the given
virtualViewId or the host View itself
if virtualViewId equals to View#NO_ID . |
public AccessibilityNodeProviderCompat()
public AccessibilityNodeProviderCompat(java.lang.Object provider)
android.view.accessibility.AccessibilityNodeProvider
.provider
- The provider.public java.lang.Object getProvider()
android.view.accessibility.AccessibilityNodeProvider
.public AccessibilityNodeInfoCompat createAccessibilityNodeInfo(int virtualViewId)
AccessibilityNodeInfoCompat
representing a virtual view,
i.e. a descendant of the host View, with the given virtualViewId
or the host View itself if virtualViewId
equals to View#NO_ID
.
A virtual descendant is an imaginary View that is reported as a part of the view hierarchy for accessibility purposes. This enables custom views that draw complex content to report them selves as a tree of virtual views, thus conveying their logical structure.
The implementer is responsible for obtaining an accessibility node info from the pool of reusable instances and setting the desired properties of the node info before returning it.
virtualViewId
- A client defined virtual view id.AccessibilityNodeInfoCompat
for a virtual descendant
or the host View.AccessibilityNodeInfoCompat
public boolean performAction(int virtualViewId, int action, Bundle arguments)
virtualViewId
or the host View itself
if virtualViewId
equals to View#NO_ID
.virtualViewId
- A client defined virtual view id.action
- The action to perform.arguments
- Optional arguments.createAccessibilityNodeInfo(int)
,
AccessibilityNodeInfoCompat
public java.util.List<AccessibilityNodeInfoCompat> findAccessibilityNodeInfosByText(java.lang.String text, int virtualViewId)
AccessibilityNodeInfoCompat
s by text. The match is case insensitive
containment. The search is relative to the virtual view, i.e. a descendant of the
host View, with the given virtualViewId
or the host View itself
virtualViewId
equals to View#NO_ID
.virtualViewId
- A client defined virtual view id which defined
the root of the tree in which to perform the search.text
- The searched text.createAccessibilityNodeInfo(int)
,
AccessibilityNodeInfoCompat
public AccessibilityNodeInfoCompat findFocus(int focus)
focus
- The focus to find. One of
AccessibilityNodeInfoCompat.FOCUS_INPUT
or
AccessibilityNodeInfoCompat.FOCUS_ACCESSIBILITY
.AccessibilityNodeInfoCompat.FOCUS_INPUT
,
AccessibilityNodeInfoCompat.FOCUS_ACCESSIBILITY


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Version 4.23¶
Release date: 2020-06-25
This release contains a number of bug fixes and new features since the release of pgAdmin4 4.22.
New features¶
Issue #5468 - Added option to ignore the whitespaces while comparing objects in schema diff.
Issue #5500 - Added server group name while selecting servers in schema diff.
Issue #5516 - Added support of Row Security Policies.
Issue #5576 - Improve error messaging if the storage and log directories cannot be created.
Housekeeping¶
Issue #5325 - Improve code coverage and API test cases for Collations.
Issue #5574 - Cleanup Windows build scripts and ensure Windows x64 builds will work.
Issue #5581 - Documentation of Row Level Security Policies.
Bug fixes¶
Issue #3591 - Ensure that the query tool should display the proper error message while terminating the active session.
Issue #3669 - Ensure that proper error should be displayed for the deleted node.
Issue #3787 - Disabled the Stop process button after clicking it and added a message ‘Terminating the process…’ to notify the user.
Issue #4226 - Fixed an issue where select all checkbox only selects the first 50 tables.
Issue #5416 - Ensure that the query tool panel gets closed when clicking on the ‘Don’t Save’ button.
Issue #5465 - Fixed an issue where the Edge browser version is showing wrong and warning message gets displayed.
Issue #5492 - Fixed an issue where the search object is unable to locate inherited tables and constraint filters are not working.
Issue #5507 - Fixed connection and version number detection issue when the database server is upgraded.
Issue #5521 - Fixed an issue when dumping servers from a desktop pgAdmin app by providing an option ‘–sqlite-path’.
Issue #5539 - Fixed typo in exception keyword.
Issue #5584 - Fixed an issue where two identical tables showing different by schema diff tool.
Issue #5592 - Ensure that pgadmin should be able to connect to the server which has password more than 1000 characters.


|
SingularityThat singular sensation you're feeling is the very fabric of spacetime disintegrating around your ears.If you ask an astrophysicist what a singularity is, he'll likely say it's a point in space where matter has become infinitely dense and the resulting gravitational field has dramatically warped space and time. If you ask a mathematician what a singularity is, he'll tell you it's an uncomputable point for which you can compute all the surrounding points. It's the hole in the piece of graph paper. These two definitions mean pretty much the same thing, but neither conveys how a singularity epitomizes the mind-bending funhouse atmosphere of the collective oxymoron we laughably refer to as "reality." The physical idea of a singularity is intimately tied to the mathematical concept. An uncomputable point in space invariably represents the most extreme conditions known to science. Singularities are arguably the best available evidence that the universe is made out of math, because it appears that reality breaks down at the same place that math breaks down. Around the start of the 20th century, people began to realize that the universe was a lot weirder than previously thought. Physicists began to speculate about what would happen when a dying star collapsed, and in 1939, J. Robert Oppenheimer and Hartland Snyder put forward a model of the star collapsing to a "single point" -- compacting to infinitesmal size and reaching a measurement of density which is mathematically infinite, at which point the equations to describe the interior of the object break down, creating a singularity. Physicist John Wheeler first used the phrase "black hole" to describe this phenomenon, which warps the very fabric of space and time into strange shapes.  Even space collapses, and the spacetime distortion creates an "event horizon" -- the point of no return. Science fiction writers and physicists have speculated that black holes might be a gateway to other universes, parallel worlds, higher dimensions or some commbination of all three. In sci-fi, this theory offers the possibility of cheerful jaunts in which daring adventurers somehow fly their spaceships through the event horizon and pop out on the other side, ready to explore strange new worlds. While some physicists do believe black holes transport matter into another universe, traveling through a black hole is not unlike travelling through a wood chipper. All your parts end up on the other side, but not in their original configuration.  Under this theory, the black hole purees all the matter that falls into it and shoots it out in a jet somewhere else in this universe or an entirely different one. Anything that falls into the event horizon is gone forever, pulverized into a subatomic paste and trapped in a web of frozen time. There are no fancy shields or clever tricks that could possibly ease the way. There is no loophole for adventure, unless you consider entering the afterlife an adventure. By definition, a black hole disassembles anything caught in its web and reduces it to component parts so small they cannot be observed by even the most exacting microscope. Because of the event horizon, black holes cannot be directly observed and no information can emerge from inside.  Typical effects include a giant spiralling swirl of matter falling into the singularity. As the matter is pulverized (but before it falls into the event horizon), it emits X-rays, highly energetic radiation that moves fast enough to escape the black hole's gravity. By studying these X-rays, scientists have been able use radio telescopes to spot several likely black holes, including a super-massive one in the center of the Milky Way galaxy, which is devouring stars at a phenomenal rate. This phenomenon may be related to the formation of galaxies, as well as their spiral structure. Black holes can also create strange effects in their immediate vicinity. Quasars, the brightest objects known to astronomy, are believed to consist of a super-hot vortex of gas and material detritus rapidly spinning around a supermassive black hole. This notion is extremely hypothetical, however, since the closest quasars are billions of light years away from our own galaxy. This distance also suggests that quasars are very old, possibly forming shortly after the Big Bang. There are many theories about exactly what we mean when we say "Big Bang," and none of them are 100 percent certain (or anywhere close). Many of these theories propose that the entire universe began as a singularity -- the ultimate black hole -- which then exploded/expanded/inflated into our universe for reasons which are entirely unclear. Black holes may come in some exotic flavors, such as the hypothetical "naked singularity," which could theoretically be directly observed from the outside (unlike a black hole singularity, which is hidden by the blackness and the holeness). Naked singularities have been proven mathematically feasible, which is not to say that you're especially likely to pass one while driving home from work. All black holes are singularities, but not all singularities are black holes. A singularity simply refers to the point in a physical process where the equations break down. There are theoretically other non-black hole singularities which can occur in quantum physics, at the very small scales where reality gets weird. One possible singularity was observed recently in the Relativistic Heavy Ion Collider in Brookhaven, New York. Whilst scientists were smashing tiny particles together just to see what would happen, a small black-hole-like phenomenon popped up in the middle of a tiny fireball. The fireball was more or less intentional, but the baby black hole was apparently unexpected. Scientists at RHIC hastened to explain that the black hole was not the same kind of black hole as the giant, star-swallowing, life-exterminating variety, and that no one was ever in any danger. However, it's pretty easy to say after the fact that the mini-black-hole couldn't have swallowed the entire Earth and ended all human life -- because it didn't happen. It's quite another proposition to suggest that nothing could possibly go wrong in the game of cosmic dice-rolling that goes on inside a particle accelerator. Quantum physics experiments are by definition unpredictable. And the behavior of a singularity is also unpredictable -- again by definition. So they're using one inherently unpredictable phenomenon to create another inherently unpredictable phenomenon, then predicting that nothing could possibly wrong. It doesn't take a doctorate in nuclear physics to spot the hole in this argument. If you wake up one morning, and half the planet seems to have been sucked into a state of mathematical nonexistence, you won't even have the admittedly petty satisfaction of calling the folks over at the Relativistic Heavy Ion Collider to see their sheepish grins. They'll be on the other side of the event horizon, from which no information can escape. Bastards.
The Other SingularityIn addition to its traditional scientific use, the word "Singularity" with a capital S has been applied to the only somewhat flaky notion that humanity is rapidly approaching a major event which will radically transform pretty much everything as we know it. The Singularity was coined as a specific phrase by mathematicisn/sci-fi writer Vernor Vinge.Vinge basically makes a case that things are getting whacky and we should expect the unexpected, and that some sort of new intelligence is about to emerge on (or in the general vicinity of) Earth. This seems reasonable, but awfully non-specific. Nevertheless, you can find plenty of people who have articulated some variation the same thing with greater or lesser degrees of credibility, including Jack Parsons, Grant Morrison, Terence McKenna, Arthur C. Clarke and Philip K Dick. |


Reports expressions that seem to use an inappropriate method for determining array equality or calculating their hashcode.
The following method calls are reported:
- Object.equals() for any arrays
- Arrays.equals() for multidimensional arrays
- Arrays.hashCode() for multidimensional arrays
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Cholera Toxin
InterPro Domain Architecture:
|
InterPro Entry |
Method Accession |
Graphical Match |
Method Name |
|
IPR001144 |
PF01375 |
|
Enterotoxin_a |
|
IPR001144 |
PR00771 |
|
ENTEROTOXINA |
|
Classification |
PDB Chain/ Domain ID |
PDB Chain/Structural Domains |
|
|
1s5d |
1s5dA |
|
|
|
<IP_ADDRESS>.1 |
1xtcA0 |
|
|
|
d.166.1.1 |
d1s5da_ |
|
From
the graphical match above, you can see that the signatures (method accession)
are grouped into one InterPro entry for Vibrio cholerae enterotoxin A
chain, namely IPR001144 representing the heat-labile
enterotoxin A chain family. IPR001144
has two signatures, PF01375 from the PFAM database, and PR00771 from the PRINTS database.
This entry groups together proteins related in sequence to enterotoxin A
chains from a variety of different toxins, several of which can be found in
different strains of Escherichia coli.
The remaining three entries in the table above are from the structural database PDB (green stripe), and from the structural classification databases CATH (pink stripe) and SCOP (black stripe) (the names such as d1s5da_ being derived from the PDB entry upon which it is based, here PDB entry 1s5d, chain A). The graphical match for the PDB entry 1s5d displays the length of the original PDB entry, which covers almost the entire protein. The CATH (1xtcA0) and SCOP (d1s5da_) databases give information on the classification of this protein.
InterPro Domain Architecture:
|
InterPro Entry |
Method Accession |
Graphical Match |
Method Name |
|
IPR001835 |
PD012805 |
|
Enterotoxin_B |
|
IPR001835 |
PF01376 |
|
Enterotoxin_b |
|
IPR001835 |
PR00772 |
|
ENTEROTOXINB |
|
IPR008992 |
SSF50203 |
|
Bact_endotox |
|
Classification |
PDB Chain/ Domain ID |
PDB Chain/Structural Domains |
|
|
3chb |
3chbD |
|
|
|
3chb |
3chbE |
|
|
|
3chb |
13chbF |
|
|
|
3chb |
3chbG |
|
|
|
3chb |
3chbH |
|
|
|
<IP_ADDRESS>.1 |
3chbD0 |
|
|
|
b.40.2.1 |
d3chbd_ |
|
From
the graphical match above, you can see that the signatures are divided into two
InterPro entries for Vibrio cholerae enterotoxin B chain. IPR001835 represents the heat-labile
enterotoxin B chain family, and has three signatures, PF01375 from the PFAM database, PR00772 from the PRINTS database, and PD012805 from the ProDom database.
This entry groups together proteins related in sequence to enterotoxin B
chains from a variety of different toxins, several of which can be found in
different strains of Escherichia coli. The
InterPro entry IPR008992 represents the bacterial enterotoxin
domain and has one signature, SSF50203 from the SUPERFAMILY database. IPR008992 groups together many proteins that
are structurally related to the cholera enterotoxin B chain, including E.
coli heat-labile protein, verotoxin-1, pertussis toxin, and several Staphylococcal
enterotoxins. Unlike the proteins making
up IPR001835, those in IPR008992 may have low sequence identities with one
another, but should still have a common evolutionary origin.
The graphical match for the PDB entry 1chb displays five chains that together represent the five identical peptides making up the cholera enterotoxin pentamer. The CATH (3chbD0) and SCOP (d3chbd_) databases give information on the classification of this protein.
Structures of the Vibrio cholerae enterotoxin A and B chains have been determined, and can be viewed using AstexViewer®, which is linked from the InterPro Match Table of each protein via the logo (please note, there is no link directly from this page to the AstexViewer® for the protein discussed above, therefore you need to go to the link on the InterPro pages for P01555 or P10556). The AstexViewer® displays the PDB structure with the particular CATH or SCOP domain highlighted in yellow. There are several structures associated cholera toxin in the Protein Data Bank (PDB). A detailed description and visualisation of the structural features of cholera toxin can be found at the PDB ‘Molecule of the Month’, providing insights into the molecular basis of action for this enterotoxin.


Cornell Hacking Club
Fall 2018 Info Session
What we do
- Compete in CTF competitions
- Host CTFs
- Hack things!
Recruitment
- We will be recruiting early next semester
- To get an interview, just solve one of the challenges on our website!
- Try to solve more than one, if you can
Current Projects
- I-Clicker Spoofing
- Network Attacks
- Whatever you think is vulnerable!


A PDF document may include general information such as the document’s title, author, and creation and modification dates.
Historically this information is stored using special Info structure. This structure is available for read and writing as an associative array using properties public property of ZendPdf\PdfDocument objects:
1 2 3 4 5 6 7 | $pdf = ZendPdf\PdfDocument::load($pdfPath);
echo $pdf->properties['Title'] . "\n";
echo $pdf->properties['Author'] . "\n";
$pdf->properties['Title'] = 'New Title.';
$pdf->save($pdfPath);
|
The following keys are defined by PDF v1.4 (Acrobat 5) standard:
Title- string, optional, the document’s title.
Author- string, optional, the name of the person who created the document.
Subject- string, optional, the subject of the document.
Keywords- string, optional, keywords associated with the document.
Creator- string, optional, if the document was converted to PDF from another format, the name of the application (for example, Adobe FrameMaker®) that created the original document from which it was converted.
Producer- string, optional, if the document was converted to PDF from another format, the name of the application (for example, Acrobat Distiller) that converted it to PDF..
CreationDate- string, optional, the date and time the document was created, in the following form: “D:YYYYMMDDHHmmSSOHH’mm’”, where:
- YYYY is the year.
- MM is the month.
- DD is the day (01–31).
- HH is the hour (00–23).
- mmis the minute (00–59).
- SS is the second (00–59).
- O is the relationship of local time to Universal Time (UT), denoted by one of the characters +, −, or Z (see below).
- HH followed by ‘ is the absolute value of the offset from UT in hours (00–23).
- mm followed by ‘ is the absolute value of the offset from UT in minutes (00–59).
The apostrophe character (‘) after HH and mm is part of the syntax. All fields after the year are optional. (The prefix D:, although also optional, is strongly recommended.) The default values for MM and DD are both 01; all other numerical fields default to zero values. A plus sign (+) as the value of the O field signifies that local time is later than UT, a minus sign (−) that local time is earlier than UT, and the letter Z that local time is equal to UT. If no UT information is specified, the relationship of the specified time to UT is considered to be unknown. Whether or not the time zone is known, the rest of the date should be specified in local time.
For example, December 23, 1998, at 7:52 PM, U.S. Pacific Standard Time, is represented by the string “D:199812231952−08‘00’”.
ModDate- string, optional, the date and time the document was most recently modified, in the same form as CreationDate.
Trapped- boolean, optional, indicates whether the document has been modified to include trapping information.
- TRUE- The document has been fully trapped; no further trapping is needed.
- FALSE- The document has not yet been trapped; any desired trapping must still be done.
- NULL- Either it is unknown whether the document has been trapped or it has been partly but not yet fully trapped; some additional trapping may still be needed.
Since PDF v 1.6 metadata can be stored in the special XML document attached to the PDF (XMP -Extensible Metadata Platform).
This XML document can be retrieved and attached to the PDF with ZendPdf\PdfDocument::getMetadata() and ZendPdf\PdfDocument::setMetadata($metadata) methods:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | $pdf = ZendPdf\PdfDocument::load($pdfPath);
$metadata = $pdf->getMetadata();
$metadataDOM = new DOMDocument();
$metadataDOM->loadXML($metadata);
$xpath = new DOMXPath($metadataDOM);
$pdfPreffixNamespaceURI = $xpath->query('/rdf:RDF/rdf:Description')
->item(0)
->lookupNamespaceURI('pdf');
$xpath->registerNamespace('pdf', $pdfPreffixNamespaceURI);
$titleNode = $xpath->query('/rdf:RDF/rdf:Description/pdf:Title')->item(0);
$title = $titleNode->nodeValue;
...
$titleNode->nodeValue = 'New title';
$pdf->setMetadata($metadataDOM->saveXML());
$pdf->save($pdfPath);
|
Common document properties are duplicated in the Info structure and Metadata document (if presented). It’s user application responsibility now to keep them synchronized.
The source code of this file is hosted on GitHub. Everyone can update and fix errors in this document with few clicks - no downloads needed.