Compression Algorithms for Raster Data used in the Gridfour Implementation
This document provides details on the design, methods, and algorithms used by the Gridfour raster (grid) data compression implementation.
One of the goals for the Gridfour software is to provide a testbed for developers who are investigating data-compression techniques for grid-based data. To that end, the Gridfour API includes an implementation of a file format named G93 which provides a file-based system for storing gridded data. Gridfour supports compression through the use of custom codec (coder-decoder) classes that are included in its software distribution. These codecs may be used through the G93 file API or in stand-alone mode depending on the requirements of the applications that use them. Developers may also leverage the Gridfour API to write their own custom codecs. To illustrate how a compression codec could be implemented, Gridfour provides codecs based on the well-known Huffman coding (Huffman, 1952) and Deflate algorithms (Deutsch, 1996).
The Gridfour implementations provide moderate data compression with good access speed, but there is certainly room for improvement. The algorithms used in the current G93 file management software are based on work that was conducted in 1993 for a project called Gem93 (the name "G93" was chosen as a tribute to that work). Clearly, the state of the art has advanced since that time. Many interesting techniques that could be applied to compressing raster data are now available. The information in this document is presented with the hope that it will assist researchers and developers in their own efforts to find newer and even more effective data compression techniques for raster data sets.
The G93 API supports 3 different formats for storing data:
The integer and float formats are both based on the fundamental data types used by contemporary hardware and software systems. Both require 4 bytes. Floating point data is stored using the IEEE-754 standard.
The integer-coded float format converts floating point values to the integer format by multiplying it by a scaling factor and adding an offset. This format can discard some of the precision of the input float values (depending on the scaling factor and the precision of the input data). So it is, in effect, a lossy representation. But, because the integer-coded float approach is used for a number of publically available geophysical data sets, the G93 API implements logic to support it directly.
The G93 API implements lossless (non-lossy) data compression algorithms for both integer and floating-point data. The implementations for the two are much different. In particular, the floating-point data compression does not take advantage of the predictor methods described below. In general, floating-point data tends to be less readily compressed than integer data. This fact is sometimes a motivation for using integer-coded float formats for data storage.
The discussion that follows uses a data set called ETOPO1 to illustrate key points related to raster data compression. ETOPO1 is a global-scale elevation and ocean depth (bathymetry) data set provided on a grid defined by latitude and longitude coordinates. Data is given at a uniform angular spacing of 1 minute of arc. The grid is organized into 10800 rows and 21600 columns and provides over 233 million data points. Elevations are given in the range -10803 meters (below mean sea level) to 8333 meters (above mean sea level). ETOPO1 was selected as an example for a number of reasons. First, it contains a substantial number of sample points and requires enough storage space to be interesting to compress. Second, the surface it describes is highly variable and provides a broad spectrum of test cases ranging from flat plains, to mountainous regions, to sheer drop offs along the Continental Shelf. And, finally, terrain data is something that is familiar to our readers and easily visualized.
It should, however, be noted that G93 is intended to be a general-purpose utility for processing many different kinds of grid-based data sets. It is not limited to geographic or geophysical information and is certainly not limited to Digital Elevation Models (DEMs). The choice of ETOPO1 was a matter of convenience as much as anything else.
The grid specification for many raster data files is large enough that it is often impractical to store the entire content in memory. Even with a relatively compact representation using short integers, the ETOPO1 data set would require close to 500 megabytes of memory. So the G93 File format partitions large rasters using a tiling scheme. In a tiling scheme, the grid is divided into a series of regularly sized subgrids as illustrated in the figure below.
From the perspective of data compression, the tiling scheme presents two influencial features. First, because tiles must be accessed independently, they are compressed individually rather than as a set. In G93, tiles are compressed on a case-by-case basis. This is significant because in many data sets, the statistical properties of the data tends to vary across the domain of the data. Data compression techniques thrive on redundancy and self-similarity in the source data. But raster data sets with larger grids allow more room for variation within the data. In the ETOPO1 elevation/bathymetry example, we would expect to see very different terrain (and very different data compression characteristics) over the Nullarbor Plain in Australia versus the steep drop offs along the Continental Shelf. By partitioning a data set into separate tiles, we reduce the tendenacy for regions of data to be compressed to include a large number of dissimilar features.
On the other hand, partitioning the data into smaller subgrids can have a disadvantage because it reduces the overall size of a block of data to be compressed. Most practical compression implementations include a certain amount of overhead beyond the storage required for the actual data itself. This overhead tends to be of a more-or-less fixed size. For a small data set, that overhead may comprise a significant amount of the overall storage required for the data. But as the size of the data set increases, the relative contribution of the overhead is reduced.
Data compression techniques that work well for text are often ineffective for raster data sets. Virtually all data compression algorithms operate by identifying redundant elements in a data set and replacing them with a more compact representation. Unfortunately, many raster data sets, particularly those containing geophysical information, tend to not present redundancy in a form that conventional data compression tools can exploit. Turning to the elevation example cited above, it is easy to imagine a set of sample points collected along a constant slope. Each elevation value in the set would be unique. So a superficial inspection of the numeric values in the set would not reveal redundant elements. But every sample would reflect the same rate of increase from point to point. And the underlying structure of the data would, in fact, carry a high degree of redundancy. The key to compressing such data is to transform it into a state in which the redundant elements become visible to conventional data compression techniques.
Many raster compression techniques address the problem of non-compliant raster data by using so called predictive techniques. These techniques implement models that predict the value at each grid point in the raster. The residuals from these predictions (actual value minus predicted value), tend to be small in magnitude and more readily compressed than the source data. Thus, in its compressed form, the data is represented using the prediction parameters and the compressed residuals. During decompression, these residuals are used as correction factors that adjust the predicted values to match the original inputs.
The original 1993 implementation used a simple predictor which assumed that the value of the raster data remained constant from grid point to grid point. For that predictor, the residual was just the value of the current grid point minus that of its predecessor. The compressed form of the raster data consisted of an initial seed value followed by a sequence of delta values that could be used to recover the original representation. In G93, this technique is referred to as a Differencing Predictor Model. Other data compression implementations sometimes refer to it as a differencing technique. In the original Gem93 project, the Differencing Predictor approach was inspired by a description of audio delta pulse code modulation in The Data Compression Book (Nelson, 1991, p. 346). Delta pulse coding is a well-known technique that was used in the audio industry as early as the 1950’s (Chaplin, 1952). While the Differencing Model predictor is not especially powerful, it is easy to implement and offers excellent run-time performance.
The Differencing Model predictor makes a critical assumption about the data. It assumes that the values of two points closely located in space will tend to be similar. In other words, it assumes that the values of elements that are closely located spatially (i.e. in terms of grid coordinates) will also be close together numerically. And, thanks to this similarity (e.g. this tendency for neighboring samples to correlate), it is possible to use the values of one or more grid points to predict the value of a neighbor. This assumption is generally true in real-world examples such as elevation data. We expect that two points a few hundred meters apart have a higher probably of being similar than two points placed far apart in much different kinds of terrain. This idea is sometimes referred to as "spatial autocorrelation" and has been extensively studied in Geographic Information Analysis and other fields.
Again let's consider the example of a set of elevation grid points specified on a region with a constant slope. Because the sample points are collected at positions with a uniform spacing, the difference in elevation from point-to-point is constant or nearly constant. These differences are just the residuals from the Differencing Predictor Model. They would exhibit a high degree of redundancy and, thus, would compress to a highly compact form.
There are different ways we can construct a predictive model for raster data, but all of them depend on being able to relate any particular sample to its neighbors. When we consider the Differencing Predictor Model over a single row of data in a grid, identifying neighbors is straight forward. The relevant neighbor point is just the previous or next data point in the sequence. But special handling is required when processing the transition from the end of one row to the beginning of the next. If taken in sequence, these two sample points will not be spatially correlated.
In practice, this requirement for special handling is easily met. In the uncompressed form, G93 stores grid points in row-major order (one row at a time). So in most cases, the predecessor of a grid point is just the sample that preceded it in the row. There is, however, one edge case that requires special handling. In row-major order, the grid point that follows the last point in a row is the first point in the next row. So, a predictor-residual based on the Differencing Model needs to implement special handling for that transition. In G93, the following rules are applied:
The figure below illustrates the pattern. The seed value is shown as a solid dot, the delta values are all shown as circles. The arrows indicate which samples are paired together to compute delta values.
It is worth noting that the use of the Differencing Model for raster data is not unique to this project. It is used in a number of specifications including the GRIB2 raster data format (NCEP 2005, table 5.6) and the TIFF image format (Adobe, 1992, p. 64, "Section 14: Differencing Predictor").
The current version of G93 implements two additional predictor models: the Linear Predictor and the Triangle Predictor.
The Linear Predictor model predicts that the data varies as a linear function. The value for the next sample in a sequence is predicted using a straight-line computed from the two that preceded it. The predictor is applied on a row-by-row basis. The vertical coordinate of the points that precede the target point are assigned the values ZA, ZB respectively. If we assume that the grid points are spaced at equal intervals, then the predicted value, ZP, is given by ZP = 2xZB-ZA.
The Triangle Predictor was described by Kidner & Smith (1992). It uses three neighboring points A, B, and C, to predict the value of a target sample as shown in the figure below. The vertical coordinate of the points are assigned the values ZA, ZB, and ZC respectively. By treating the grid as having a fixed spacing between columns, s, and a fixed spacing between rows, t, the prediction computation is simplified to ZP = ZB+ZC-ZA.
To see how this relationship is derived, start by taking each sample and the predicted point as vectors:
From linear algebra, we can compute the normal to a plane and locate a point on that plane using the following:
When we solve for ZP, the x, y, s, and t variables cancel out and we find the simple computation used by the Triangle Predictor model.
Both the Linear and the Triangle Predictor require special handling to initialize the grid before applying the prediction computations. In the case of the Linear Predictor, G93 uses the seed value and the pattern established for the Differencing Predictor to pre-populate the first two columns of the grid. In the case of the Triangle Predictor, the first row and first column are populated using same approach. Once the grid is initialized, the specific predictors can be used for the remaining grid cells.
Once the residuals are computed using a predictor-residual model, they are passed to compression processes based on conventional data compression algorithms such as the Huffman and Deflate techniques described above. Both the custom Huffman implementation included with the G93 code base and the Deflate API provided as part of the standard Java library are designed to process bytes. But the predictive-residual models produce output in the form of integers. So in order to use them to process and store the outputs from the models, the residuals must somehow be serialized into a byte form. Most of the residuals tend to be close to zero, so the serialization for them is trivial. In some cases, however, the residuals will be in excess of the value that can be stored in a single byte.
While it would be feasible to simply split out the integer residual values into the component bytes, doing so would tend to dilute the redundancy in the output data. Furthermore, a significant number of the residuals are quite small (using the Triangle Predictor, 87.9 percent of the residuals computed for ETOPO1 have an absolute value less than 15). So using 4 bytes to store these small values would be wasteful.
To serialize the residuals, G93 uses a scheme that it calls the M32 code. M32 is an integer-to-byte coding scheme that adjusts the number of bytes in the output to reflect the magnitude of each term in the input. In that regard, it uses an approach similar to that used for the widely used UTF-8 character encoding. As in the case of UTF-8, the first byte in the sequence can represent either a literal value or a format-indicator that specifies the number of bytes to follow. M32 also resembles the variable-length integer code used by SQLite4 (SQLite4, 2019), except that it supports negative values as well as positive. The first byte in the output is essentially a hybrid value. For small-magnitude values ( in the range -126 to +126), it is just a signed-byte representation of the input value. The values -127 and +127 are used to introduce multibyte sequences. And the value -128 is used to indicate the minimum 32-bit integer value, -2147483648, which Gridfour often uses as a null-data code. In the multibyte sequences, the bytes that follow the introducer give bits for the numerical value in big-endian order. Each byte carries 7 bits of information with the high-order bit used to indicate if additional bytes follow. The length of the sequence depends on the magnitude of the residual to be coded. In the worst case, 6 bytes are required to encode large magnitude residual (1 byte for the introducer, 5 bytes for the content).
The M32 coding scheme is effective in the case where the computed residuals tend to be small because it preserves the one-byte-per-value relationship. Again, in the case of larger residuals, the M32 code can actually be longer than the 4 bytes needed for a simple integer. Fortunately, a good predictor will produce small residuals. In fact, in the elevation data sets used when developing G93, the average length of the M32 code sequences is about 1.013 bytes per grid value.
By applying the predictive-residual transformations and M32 serialization, the G93 codecs transform the data to a state where it can be processed by conventional compressor methods. While the transformation-serialization process generally reduces the size of the data (as it did for the ETOPO1 example), its main benefit is that it results in a form with more redundancy than the original. And as the redundancy is increased, the data becomes more suitable for processing by conventional data compression techniques.
As noted above, the two codecs currently implemented in G93 are based on the Huffman coding and Deflate algorithms. API’s that support Deflate are available in most popular software environments and programming languages. G93 uses the Deflate class provided by the standard Java API. For the simpler Huffman coding, G93 uses a custom implementation.
During the compression phase, the current implementation of G93 attempts to compress data using both codecs and all three predictive-residual transformations. It then selects the serialized form that produces the smallest output size. In testing with ETOPO1, the Deflate algorithm was selected in about 65 percent of the tiles with Huffman being selected for the remaining 35.
Huffman coding was originally developed for the compression of text-based data and the terminology associated with it reflects that origin. For these notes, we will stick to the usual conventions and refer to the sequence of data values to be compressed (the M32 serialized bytes) as the "text". Individual elements with the sequence (each M32-serialized byte) will be described as the symbols.
Huffman coding is based on an analysis of the frequency with which certain data values (symbols) appear within the data sequence (text) to be compressed. It provides an efficient way of assigning a unique sequence of bits to each symbol such that the more common symbols have shorter encoding sequences and the less common symbols have longer sequences. Since common symbols can be encoded using short sequences, the overall length of the encoded text is reduced.
One consequence of this approach is that the encoded message must somehow carry information about the frequency table for the symbols it encodes. Traditional Huffman implementations provide this information directly by including a symbol-frequency table at the start of the compressed data sequence. Adaptive Huffman methods embed the information in the compressed sequence itself. In either case, the frequency information adds overhead to the encoded data.
In many cases, the overhead for the frequency information has a fixed size regardless of the length of the encoded text. Thus, as the length of the original text increases, the proportion of the output due to overhead elements decreases. So, under the Huffman encoding, longer text tends to compress more efficiently than shorter text.
On the other hand, in some data sets, the distribution of the symbol frequencies can change over the course of the text. For example, in the ETOPO1 elevation data, the symbol table for a mountainous region behaves differently than that collected over the plains. So if a set of elevation data set contained data for both regions, a single frequency table would not provide an efficient description the two separate regions. In spatial analysis, this tendency of the statistical properties of data to change across a data set is referred to as non-stationarity.
These two considerations have a direct bearing on the size of the tiles specified when creation a G93 file to cover a raster product with non-uniform behavior. A larger tile size reduces the amount of symbol-table overhead compared to the length of the encoded data. But a larger tile also allows for more non-stationarity and thus dilutes the effectiveness of the symbol table. Of course, a larger tile size also increases the memory use by the application. So finding an optimal tile-size choice may require some experimentation. In working with elevation data sets, we have found that a tile size in the range of 10 to 40 thousand grid cells tends is usually a good place to start.
In the classic Huffman algorithm, the symbol-frequency table is used to create a tree structure that serves as a mechanism for encoding or decoding the compressed data. Although many implementations store the frequency data directly, the G93 implementation gains efficiency by storing the structure of the tree itself rather than retaining the actual frequency data.
In the storage phase of processing, the Huffman tree is created using the classic algorithm. Once established, the tree is stored according to the following recursive algorithm which starts from the root node of the tree.
1. Introduce with sequence with an unsigned byte indicating the number
of unique symbols, N, in the tree. Since there will never be zero symbols
in the tree, G93 stores the value N-1 in this byte. Thus one byte is sufficient
to represent all possible symbol counts for a M32 representation.
2. Traverse the Huffman tree starting from the root node using RecusiveStore(rootNode)
3. RecursiveStore(node)
a. If the node is a branch
i. Output a bit with value 0.
ii. Call RecursiveStore on the left child node.
iii. Call RecursiveStore on the right child node.
iv. Return.
b. If the node is a leaf (a terminal)
i. Output a bit with a value 1.
ii. Output the symbol.
iii. Return.
In testing with the ETOPO1 data set, there were typically about 100 unique symbols in a M32-serialized tile. Storing the Huffman tree algorithm averaged about 782 bits per tile.
For simplicity, the tree-encoding algorithm was described above using a recursive approach. In the actual code, it is implemented using a stack. Although the stack-based approach leads to more complicated code, it is necessary because of the potential depth of recursion that might be encountered when storing the tree structure. In rare cases, the depth of the Huffman tree (and thus the depth of recursive calls) could reach 256, which would be too deep for some Java JVM’s. Thus a safe implementation required the use of a stack.
Kidner and Smith (2003) demonstrated improvement in compression ratios by using arithmetic coding rather than Huffman codes. Because arithmetic coding reflects the frequency distribution of symbols in the compressed data more accurately than Huffman, it can achieve better compression ratios than Huffman. Unfortunately, implementing arithmetic coding is more complicated than implementing Huffman coding. Arithmetic encoders also tend to require more processing time than Huffman.
As an experiment, we implemented a compression codes using the Reference Implementation of an adaptive arithmetic encoder (Nayuki, 2020). During the test, we replaced the Huffman codec with the arithmetic codec, but retained the Deflate codec. The relative number of tiles for which arithmetic coding was selected remained roughly the same as for the Huffman case described above. But the arithmetic encoder reduced the size of the compressed data by about 2 percent. On the other hand, arithmetic coding required more processing time than Huffman.
| Method | Bits/Symbol | Time to Read Tiles |
|---|---|---|
| Huffman & Deflate | 4.6 | 1.9 |
| Arithmetic & Deflate | 4.5 | 7.2 |
It is worth noting that the Reference Implementation focuses on correctness of implementation and clarity of code, so lacks some optimizations that would tend to complicate or obscure the logic. So, there may be opportunities for reducing the processing time. Arithmetic coding may be the subject of future investigation for the G93 project.
The introduction to this wiki page made the claim that the G93 package is intended to serve as a testbed for investigators and software developers who wish to experiment with their own solutions for raster data compression. We hope that by describing the current implementations, we demonstrated some of the reasons that we think that claim is valid.
There are many, many promising avenues to explore for better solutions to the raster data compression problem. Kidner and Smith (2003) used a more power predictor based on Legrange multipliers and arithmetic coding. Some commercial solutions (and the JPEG 2000 standard) have explored the use of wavelet functions. Data compression continues to be an area of active interest in the software community, and we fully expect that new techniques are waiting to be discovered.
The G93 project is especially interested in lossless, or nearly lossless, techniques for compressing real-valued data. The current G93 implementation implements compression for floating point data, but the results are not as successful as they are for integers.
If you are investigating raster-based data compression, we wish you the best of luck and hope that insights from G93 can help you on your way. And, as always, we welcome your ideas and suggestions.
Adobe Systems, Inc. (1992). TIFF Revision 6.0 Final – June 3, 1992. Retrieved January 2020 from https://www.adobe.io/open/standards/TIFF.html
Cutler, C. Chapin. (1950). U.S. Patent No. 2605361, "Differential Quantization of Communication Signals". Filed June 29, 1950, issued July 29, 1952
Deutsch, L. Peter (1996). "DEFLATE Compressed Data Format Specification version 1.3". IETF. p. 1. sec. Abstract. doi:10.17487/RFC1951. RFC 1951.
Huffman, D. (1952). "A Method for the Construction of Minimum-Redundancy Codes" (PDF). Proceedings of the IRE. 40 (9): 1098–1101. doi:10.1109/JRPROC.1952.273898.
Kidner, D.B. and Smith, D.H. (1992). "Compression of digital elevation models by Huffman coding". Computers and Geosciences, 18(8), 1013-1034.
Kidner, David B. & Smith, Derek, H. (2003). "Advances in data compression of digital elevation models". Computers & Geosciences 29 (8), 985-1002.
National Weather Service -- National Centers for Environmental Prediction [NCEP], 2005. "NCEP WMO GRIB2 Documentation". Accessed January 2020 from https://www.nco.ncep.noaa.gov/pmb/docs/grib2/grib2_doc/
Nayuki (2020). "Reference Arithmetic Coding". Retrieved January 2020 from https://www.nayuki.io/page/reference-arithmetic-coding
Nelson, M. (1991). The Data Compression Book. M&T Publishing Company, Redwood City, CA.
SQLite4 (2019). "Variable-Length Integers". Retrieved October 2019 from https://sqlite.org/src4/doc/trunk/www/varint.wiki.
Wikipedia (2020). "Differential pulse-code modulation". Retrieved January 2020 from https://en.wikipedia.org/wiki/Differential_pulse-code_modulation


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WITNESS LIST
Environmental Regulation Committee
January 23, 2018 - 9:00 AM
(SUBCOMMITTEE MEETING - Air Quality and Municipal Landfills)
Permitting, siting, and regulatory processes for solid waste landfills
On:
Garcia, Ramiro (TCEQ)
Germain, Anne (National Waste & Recycling Association)
Gregory, Bob (Self)
Holder, Robert Holly (TxSWANA)
Lott, Earl (TCEQ)
Macomb, Chris (Waste management of Texas Inc.)
Minick, Stephen (Republic Services)
Perales, Marisa (Self; Texas campaign for the environment)
Rice, Michael (TXSWANA)
Shelley, Adrian (Public Citizen)
Sinclair, Bryan (TCEQ)
Tatu, Anthony (TCEQ)
Registering, but not testifying:
On:
DeVore, Douglas (United States Air Force)
Goodin, Chance (Tceq)
Keel Linden, Kelly (TCEQ)
Vay, John (Waste Connections, Inc.)
1


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See:
Description
| Interface Summary | |
|---|---|
| BulkUpdateHandler | Defines how bulk update may be done on Graphs. |
| Capabilities | Interface for expressing capabilities. |
| FrontsNode | HasNode - interface for objects that front a Node in some context. |
| FrontsTriple | FrontsTriple (see also FrontsNode) is an interface for things that can be seen as wrappers round triples. |
| GetTriple | this interface describes types that can have a triple extracted using
a getTriple method. |
| Graph | The interface to be satisfied by implementations maintaining collections of RDF triples. |
| GraphAdd | The Add part of Graph's interface. |
| GraphEventManager | The component of a graph responsible for managing events and listeners. |
| GraphListener | Interface for listening to graph-level update events. |
| GraphMaker | A factory for providing instances of named graphs with appropriate storage models. |
| GraphStatisticsHandler | A graph's StatisticsHandler offers access to some statistics about that graph's contents that might be useful for optimisation. |
| NodeVisitor | The NodeVisitor interface is used by Node::visitWith so that an application can have type-dispatch on the class of a Node. |
| Reifier | This interface represents the type of things that can hold reified triples for a Jena Graph. |
| TransactionHandler | Preliminary interface for graphs supporting transactions. |
| TripleBoundary | An interface for expressing a stopping condition on triples, such as in sub-graph extraction. |
| TripleIterator | An extended iterator that can return its next element as a Triple. |
| TripleMatch | Interface for triple matching; may become obsolete. |
| Class Summary | |
|---|---|
| Factory | A factory class for creating Graphs. |
| GraphEvents | GraphEvents is the base class for Jena general graph events. |
| GraphExtract | GraphExtract offers a very simple recursive extraction of a subgraph with a specified root in some supergraph. |
| GraphUtil | An ad-hoc collection of useful code for graphs; starting with findAll, which is graph-specific, and extending to iteratorToSet and iteratorToList, which are here because they are used in tests and in the bulk update handlers. |
| Node | A Node has five subtypes: Node_Blank, Node_Anon, Node_URI, Node_Variable, and Node_ANY. |
| Node_ANY | A Node_ANY (there should be only one) is a meta-node that is used to stand for any other node in a query. |
| Node_Blank | RDF blank nodes, ie nodes with identity but without URIs. |
| Node_Concrete | This is the class of "concrete" nodes, ie those which correspond to actual RDF data - URIs, blank nodes, and literals. |
| Node_Fluid | This is the subclass of "fluid" nodes, ie nodes that are "holes" in pattern matching. |
| Node_Literal | An RDF node holding a literal value. |
| Node_NULL | The Highlander Node_NULL exists for the database code (as a Node that coresponds to a null in database tables for the reification code). |
| Node_URI | RDF nodes with a global identity given by a URI. |
| Node_Variable | "variable" nodes; these are outside the RDF2003 specification, but are used internally for "placeholder" nodes where blank nodes would be wrong, most specifically in Query. |
| Node_Variable.VariableName | |
| NodeCache | A NodeCache caches nodes according to their labels, to reduce store turnover at the expense of some additional computation. |
| Reifier.Util | |
| Triple | Triples are the basis for RDF statements; they have a subject, predicate, and object field (all nodes) and express the notion that the relationship named by the predicate holds between the subject and the object. |
| Triple.Field | A Field is a selector from Triples; it allows selectors to be passed around as if they were functions, hooray. |
| TripleCache | TripleCache caches triples according to their SPO members, to reduce store turnover at the expense of some added computation. |
| TripleMatchFilter | A class to turn a triple (treated as a pattern) into a Filter. |
| TripleMatchIterator | An iterator that selects triples from an underlying iterators of triples It used to take TripleMatch's, but those are obsolete. |
| Exception Summary | |
|---|---|
| Node.NotLiteral | Exception thrown if a literal-access operation is attemted on a non-literal node. |
This package defines the Graph and Node family of classes, which form the underlying datatypes of the Jena system.
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http://www.apstudynotes.org/us-history/outlines/chapter-5-colonial-society-on-the-eve-of-revolution-1700-1775/
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Integrating accountability mechanisms in local government service ...
Elements/ tools for effective local government accountability . and service delivery is characterized by weak legislative and democratic structures, poor . The colonial government established and entrenched a highly centralized state whose .
http://www.kenyalaw.org/klr/index.php?id=910
-
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Representative Democracy - Library of Economics and Liberty
Although there were more aristocratic elements in the southern colonies, yet . Democracy always means self-government of the people; and by the people it .
http://www.econlib.org/library/YPDBooks/Lalor/llCy361.html
-
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Overview of Politics in the Post-Colonial Era - Saylor.org
became increasingly authoritarian and unable to sustain democratic political systems. A . purpose of colonial government was to control the population and ensure the . Patronage came to be a defining element in African politics as .
http://www.saylor.org/site/wp-content/uploads/2012/02/POLSC325-Subunit-2.1-Overview-of-Politics-in-the-Post-Colonial-Era-FINAL.pdf
-
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History of democracy - Wikipedia, the free encyclopedia
In urban governments, all other forms of rule monarchy, tyranny, . Apella, the most democratic element, was the assembly where Spartans above the age . The United States, itself a former colony and emerging colonial power in its own .
http://en.wikipedia.org/wiki/History_of_democracy
-
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Democracy in America Study Guide : Summary and Analysis of Vol. I ...
Likewise, the democratic government "makes the idea of political rights penetrate . States because most colonial settlers were already relatively equal in status, . have a unique capability to mingle an aristocratic element into a democracy.
http://www.gradesaver.com/democracy-in-america/study-guide/section4/
-
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The ANC as Government: Contesting Leadership between ...
The ANC as Government: Contesting Leadership between Democracy and . and the formation of a new political party by leading elements of the African National . with the two main protagonists as symbolic stand-ins in a postcolonial drama.
http://www.za.boell.org/web/publications-343.html
-
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Jackson Turner Main, "Government by the People: The - Academic ...
.fore while colonial theorists recognized the need for some democratic element in the government, they did not intend that the ordinary people .
http://academic.csuohio.edu/humphreyt/History601/601%20Readings/Main.pdf
-
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Development of Press Freedom in South Korea since - Canadian ...
Since Japanese colonial rule, freedom of the press has been . Press freedom is an essential element in democracy because it checks the working of a . outlets have colluded with the government of the day to produce news that reflects the .
http://www.ccsenet.org/journal/index.php/ach/article/download/3045/2811
-
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Democracy and the Origins of the US Constitution
All of these ideas about democracy originated from a number of sources. . Neither self-government nor pluralism, nor for that matter, liberty and equality, are . The Mayflower Compact was the first governing document of Plymouth Colony.
http://www.sullivan-county.com/bush/constitution.htm
-
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African Political Cultures and the Problems of Government
If "liberal democracy" presently has any evolutionary advantages, it will have to adapt . Britain's last colonial governor, about the future government of Uganda and was . Whitaker concluded that "significant elements of the traditional political .
http://www.africa.ufl.edu/asq/v2/v2i3a3.htm
-
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Traditional Leaders part I - Federo
If elements of democracy, accountability and checks and balances indeed existed in. African traditions, why have most African post-colonial governments failed .
http://www.federo.org/downloads/Traditional_Institutions.pdf
-
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Responsible government - Wikipedia, the free encyclopedia
. accountability, the foundation of the Westminster system of parliamentary democracy. . In the history of Canada, responsible government was a major element of the . In his report, one of his recommendations was that colonies which were .
http://en.wikipedia.org/wiki/Responsible_government
-
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B: Elements of Nonviolent Resistance to Colonialism After 1945 ...
B: Elements of Nonviolent Resistance to Colonialism After 1945 . Because of British government responses to events in neighbouring countries, TANU, led . to Egypt, and 1994, when a non-racial democracy was established in South Africa.
http://www.civilresistance.info/bibliography/B
-
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Nigeria - History and Politics
Between the 11th century and European colonial conquest in the late 19th century, the . Yoruba party, now renamed the Nigerian National Democratic Party (NNDP). . government) and the minority, populist Northern Elements Progressive .
http://www.iss.co.za/af/profiles/nigeria/politics.html


{% extends "base.html" %} {% load staticfiles %} {% block title %}Make a donation{% endblock %} {% block main_content %}
Thanks for considering making a donation. zzzz costs money to run, and every little helps to ensure that I don't make too great a loss providing the service for free.
There are five user classes available:
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We at Eco-Ride bring to you the very first 'Mobility as a Service' prototype that attempts to change the way we travel n NCR. The need for a personal vehicle does not exist anymore, no more worries of extended warranties or car repair services! Get your ride from Vroom and drive or be driven to anywhere and everywhere. Moreover, we're paving way for more livable cities and better public spaces.
Our Goal
Digital Movement-Urban Convenience: The primary target that we plan to achieve is the incoming of a new consumer-transport relationship. The process of commuting is one click away and the only things you need are an Eco-Ride subcription and a few personal details that we require to get you your best ride. We truly believe that a full-fledged vehicle rental system can urbanise our transport and make travel convenient.
Reduced Congestion-Cleaner Air: The Eco-Ride initiative also benefits the system through better public spaces, reduced recurrent and non-recurrent congestion on busy routes and a more eco-friendly travel approach that ultimately saves your time and money.


Installing various packages can make your system vulnerable to any known or discovered security issues in the software. Hackers trying to gain access to your machine often can take advantage of such security holes in your system's software. For this reason, it is highly recommended to purge anything on your machine that is not required to be there.
Telnet is an insecure and unencrypted package that allows users to communicate to a system remotely. It has been replaced by the far more secure SSH protocol. This package will very likely need to be removed. (any telnet servers should certainly be removed as well; however, this tutorial only covers the telnet client)
To check if telnet client is installed on your system, you can type dpkg -l telnet.
If the name of the package is preceded by "ii", then it is installed. To remove it, simply type sudo apt-get purge telnet.
That should be it!


Bitcoin (BTC) Price Showing Signs Of Bearish Continuation
- Bitcoin price is struggling to rebound and declining below the $9,300 support against the US Dollar.
- The price is likely to accelerate decline if it breaks the $9,120 support area.
- There is a major bearish trend line forming with resistance near $9,240 on the hourly chart of the BTC/USD pair (data feed from Kraken).
- Similarly, there were bearish moves in Ethereum and ripple in the past three sessions.
Bitcoin price is showing bearish signs below $9,300 and $9,240 against the US Dollar. BTC price could accelerate losses if it continues to struggle below $9,300.
Bitcoin Price Analysis
In the past few hours, there was a steady decline in bitcoin from the $9,440 high against the US Dollar. The last swing high was near $9,374 before the price declined below the $9,300 support area.
Moreover, there was a close below the $9,300 support and the 100 hourly simple moving average. Finally, the price spiked below the $9,120 support area and traded as low as $9,084.
It is currently correcting higher above the $9,120 level. Additionally, it surpassed the 50% Fib retracement level of the recent decline from the $9,374 high to $9,084 low.
However, the price is facing a lot of hurdles on the upside near the $9,240 and $9,300 levels. More importantly, there is a major bearish trend line forming with resistance near $9,240 on the hourly chart of the BTC/USD pair.
The 61.8% Fib retracement level of the recent decline from the $9,374 high to $9,084 low is also capping the upward move. Therefore, a successful break above the trend line and a follow through above $9,300 is needed for a fresh increase.
The next key resistance is near the $9,440 area, above which bitcoin is likely to climb towards the $9,550 and $9,600 levels in the near term.
On the downside, an immediate support is near the $9,120 area. If there is a successful daily close below the $9,120 support, there are chances of more downsides below the $9,020 and $9,000 support levels. The next major support is near $8,920, followed by $8,780.
Looking at the chart, bitcoin is clearly trading in a bearish zone below the $9,300 resistance level. Thus, the price remains at a risk of a bearish break below $9,120 and $9,020. To move into a positive zone and start a decent upward move, the price must settle above $9,300.
Technical indicators:
Hourly MACD – The MACD is likely to move back into the bearish zone.
Hourly RSI (Relative Strength Index) – The RSI for BTC/USD is currently declining and it could test the 25 level.
Major Support Levels – $9,120 followed by $9,020.
Major Resistance Levels – $9,240, $9,300 and $9,440.


Implementing polynomials (elements in the ring R_Q) in double-CRT form. More...
#include <DoubleCRT.h>
Public Member Functions | |
| DoubleCRT (const DoubleCRT &other)=default | |
| DoubleCRT (const NTL::ZZX &poly, const Context &_context, const IndexSet &indexSet) | |
| Initializing DoubleCRT from a ZZX polynomial. More... | |
| DoubleCRT (const zzX &poly, const Context &_context, const IndexSet &indexSet) | |
| Same as above, but with zzX's. More... | |
| DoubleCRT (const Context &_context, const IndexSet &indexSet) | |
| Also specify the IndexSet explicitly. More... | |
| DoubleCRT & | operator= (const DoubleCRT &other) |
| DoubleCRT & | operator= (const zzX &poly) |
| DoubleCRT & | operator= (const NTL::ZZX &poly) |
| DoubleCRT & | operator= (const NTL::ZZ &num) |
| DoubleCRT & | operator= (const long num) |
| long | getOneRow (NTL::Vec< long > &row, long idx, bool positive=false) const |
| Get one row of a polynomial. More... | |
| long | getOneRow (NTL::zz_pX &row, long idx) const |
| void | toPoly (NTL::ZZX &p, const IndexSet &s, bool positive=false) const |
| Recovering the polynomial in coefficient representation. This yields an integer polynomial with coefficients in [-P/2,P/2], unless the positive flag is set to true, in which case we get coefficients in [0,P-1] (P is the product of all moduli used). Using the optional IndexSet param we compute the polynomial reduced modulo the product of only the primes in that set. More... | |
| void | toPoly (NTL::ZZX &p, bool positive=false) const |
| bool | operator== (const DoubleCRT &other) const |
| bool | operator!= (const DoubleCRT &other) const |
| DoubleCRT & | SetZero () |
| DoubleCRT & | SetOne () |
| NTL::xdouble | breakIntoDigits (std::vector< DoubleCRT > &dgts) const |
| Break into n digits,according to the primeSets in context.digits. See Section 3.1.6 of the design document (re-linearization) Returns the sum of the canonical embedding of the digits. More... | |
| void | addPrimes (const IndexSet &s1, NTL::ZZX *poly_p=0) |
| Expand the index set by s1. It is assumed that s1 is disjoint from the current index set. If poly_p != 0, then *poly_p will first be set to the result of applying toPoly. More... | |
| double | addPrimesAndScale (const IndexSet &s1) |
| Expand index set by s1, and multiply by Prod_{q in s1}. s1 is disjoint from the current index set, returns log(product). More... | |
| void | removePrimes (const IndexSet &s1) |
| Remove s1 from the index set. More... | |
| void | setPrimes (const IndexSet &s1) |
| @ brief make prime set equal to s1 More... | |
| const Context & | getContext () const |
| const IndexMap< NTL::vec_long > & | getMap () const |
| const IndexSet & | getIndexSet () const |
| void | randomize (const NTL::ZZ *seed=nullptr) |
| Fills each row i with random ints mod pi, uses NTL's PRG. More... | |
| double | sampleSmall () |
| Coefficients are -1/0/1, Prob[0]=1/2. More... | |
| double | sampleSmallBounded () |
| double | sampleHWt (long Hwt) |
| Coefficients are -1/0/1 with pre-specified number of nonzeros. More... | |
| double | sampleHWtBounded (long Hwt) |
| double | sampleGaussian (double stdev=0.0) |
| Coefficients are Gaussians Return a high probability bound on L-infty norm of canonical embedding. More... | |
| double | sampleGaussianBounded (double stdev=0.0) |
| double | sampleUniform (long B) |
| Coefficients are uniform in [-B..B]. More... | |
| NTL::xdouble | sampleUniform (const NTL::ZZ &B) |
| void | scaleDownToSet (const IndexSet &s, long ptxtSpace, NTL::ZZX &delta) |
| void | FFT (const NTL::ZZX &poly, const IndexSet &s) |
| void | FFT (const zzX &poly, const IndexSet &s) |
| void | reduce () const |
| void | read (std::istream &str) |
| void | write (std::ostream &str) const |
Arithmetic operation | |
Only the "destructive" versions are used, i.e., a += b is implemented but not a + b. | |
| DoubleCRT & | Negate (const DoubleCRT &other) |
| DoubleCRT & | Negate () |
| DoubleCRT & | operator+= (const DoubleCRT &other) |
| DoubleCRT & | operator+= (const NTL::ZZX &poly) |
| DoubleCRT & | operator+= (const NTL::ZZ &num) |
| DoubleCRT & | operator+= (long num) |
| DoubleCRT & | operator-= (const DoubleCRT &other) |
| DoubleCRT & | operator-= (const NTL::ZZX &poly) |
| DoubleCRT & | operator-= (const NTL::ZZ &num) |
| DoubleCRT & | operator-= (long num) |
| DoubleCRT & | operator++ () |
| DoubleCRT & | operator-- () |
| void | operator++ (int) |
| void | operator-- (int) |
| DoubleCRT & | operator*= (const DoubleCRT &other) |
| DoubleCRT & | operator*= (const NTL::ZZX &poly) |
| DoubleCRT & | operator*= (const NTL::ZZ &num) |
| DoubleCRT & | operator*= (long num) |
| void | Add (const DoubleCRT &other, bool matchIndexSets=true) |
| void | Sub (const DoubleCRT &other, bool matchIndexSets=true) |
| void | Mul (const DoubleCRT &other, bool matchIndexSets=true) |
| DoubleCRT & | operator/= (const NTL::ZZ &num) |
| DoubleCRT & | operator/= (long num) |
| void | Exp (long k) |
| Small-exponent polynomial exponentiation. More... | |
| void | automorph (long k) |
| Apply the automorphism F(X) --> F(X^k) (with gcd(k,m)=1) More... | |
| DoubleCRT & | operator>>= (long k) |
| void | complexConj () |
| Compute the complex conjugate, the same as automorph(m-1) More... | |
Friends | |
| std::ostream & | operator<< (std::ostream &s, const DoubleCRT &d) |
| std::istream & | operator>> (std::istream &s, DoubleCRT &d) |
Detailed Description
Implementing polynomials (elements in the ring R_Q) in double-CRT form.
Double-CRT form is a matrix of L rows and phi(m) columns. The i'th row contains the FFT of the element wrt the ith prime, i.e. the evaluations of the polynomial at the primitive mth roots of unity mod the ith prime. The polynomial thus represented is defined modulo the product of all the primes in use.
The list of primes is defined by the data member indexMap. indexMap.getIndexSet() defines the set of indices of primes associated with this DoubleCRT object: they index the primes stored in the associated Context.
Arithmetic operations are computed modulo the product of the primes in use and also modulo Phi_m(X). Arithmetic operations can only be applied to DoubleCRT objects relative to the same context, trying to add/multiply objects that have different Context objects will raise an error.
Constructor & Destructor Documentation
◆ DoubleCRT() [1/4]
|
default |
◆ DoubleCRT() [2/4]
◆ DoubleCRT() [3/4]
| helib::DoubleCRT::DoubleCRT | ( | const zzX & | poly, |
| const Context & | _context, | ||
| const IndexSet & | indexSet | ||
| ) |
Same as above, but with zzX's.
◆ DoubleCRT() [4/4]
Also specify the IndexSet explicitly.
Member Function Documentation
◆ Add()
|
inline |
◆ addPrimes()
| void helib::DoubleCRT::addPrimes | ( | const IndexSet & | s1, |
| NTL::ZZX * | poly_p = 0 |
||
| ) |
Expand the index set by s1. It is assumed that s1 is disjoint from the current index set. If poly_p != 0, then *poly_p will first be set to the result of applying toPoly.
◆ addPrimesAndScale()
| double helib::DoubleCRT::addPrimesAndScale | ( | const IndexSet & | s1 | ) |
Expand index set by s1, and multiply by Prod_{q in s1}. s1 is disjoint from the current index set, returns log(product).
◆ automorph()
| void helib::DoubleCRT::automorph | ( | long | k | ) |
Apply the automorphism F(X) --> F(X^k) (with gcd(k,m)=1)
◆ breakIntoDigits()
| NTL::xdouble helib::DoubleCRT::breakIntoDigits | ( | std::vector< DoubleCRT > & | dgts | ) | const |
Break into n digits,according to the primeSets in context.digits. See Section 3.1.6 of the design document (re-linearization) Returns the sum of the canonical embedding of the digits.
◆ complexConj()
| void helib::DoubleCRT::complexConj | ( | ) |
Compute the complex conjugate, the same as automorph(m-1)
◆ Exp()
| void helib::DoubleCRT::Exp | ( | long | k | ) |
Small-exponent polynomial exponentiation.
◆ FFT() [1/2]
| void helib::DoubleCRT::FFT | ( | const NTL::ZZX & | poly, |
| const IndexSet & | s | ||
| ) |
◆ FFT() [2/2]
◆ getContext()
|
inline |
◆ getIndexSet()
|
inline |
◆ getMap()
|
inline |
◆ getOneRow() [1/2]
| long helib::DoubleCRT::getOneRow | ( | NTL::Vec< long > & | row, |
| long | idx, | ||
| bool | positive = false |
||
| ) | const |
Get one row of a polynomial.
◆ getOneRow() [2/2]
| long helib::DoubleCRT::getOneRow | ( | NTL::zz_pX & | row, |
| long | idx | ||
| ) | const |
◆ Mul()
|
inline |
◆ Negate() [1/2]
|
inline |
◆ Negate() [2/2]
◆ operator!=()
|
inline |
◆ operator*=() [1/4]
◆ operator*=() [2/4]
|
inline |
◆ operator*=() [3/4]
|
inline |
◆ operator*=() [4/4]
|
inline |
◆ operator++() [1/2]
|
inline |
◆ operator++() [2/2]
|
inline |
◆ operator+=() [1/4]
◆ operator+=() [2/4]
|
inline |
◆ operator+=() [3/4]
|
inline |
◆ operator+=() [4/4]
|
inline |
◆ operator--() [1/2]
|
inline |
◆ operator--() [2/2]
|
inline |
◆ operator-=() [1/4]
◆ operator-=() [2/4]
|
inline |
◆ operator-=() [3/4]
|
inline |
◆ operator-=() [4/4]
|
inline |
◆ operator/=() [1/2]
| DoubleCRT & helib::DoubleCRT::operator/= | ( | const NTL::ZZ & | num | ) |
◆ operator/=() [2/2]
|
inline |
◆ operator=() [1/5]
◆ operator=() [2/5]
|
inline |
◆ operator=() [3/5]
| DoubleCRT & helib::DoubleCRT::operator= | ( | const NTL::ZZ & | num | ) |
◆ operator=() [4/5]
| DoubleCRT & helib::DoubleCRT::operator= | ( | const NTL::ZZX & | poly | ) |
◆ operator=() [5/5]
◆ operator==()
|
inline |
◆ operator>>=()
|
inline |
◆ randomize()
| void helib::DoubleCRT::randomize | ( | const NTL::ZZ * | seed = nullptr | ) |
Fills each row i with random ints mod pi, uses NTL's PRG.
◆ read()
| void helib::DoubleCRT::read | ( | std::istream & | str | ) |
◆ reduce()
|
inline |
◆ removePrimes()
|
inline |
Remove s1 from the index set.
◆ sampleGaussian()
| double helib::DoubleCRT::sampleGaussian | ( | double | stdev = 0.0 | ) |
Coefficients are Gaussians Return a high probability bound on L-infty norm of canonical embedding.
◆ sampleGaussianBounded()
| double helib::DoubleCRT::sampleGaussianBounded | ( | double | stdev = 0.0 | ) |
◆ sampleHWt()
| double helib::DoubleCRT::sampleHWt | ( | long | Hwt | ) |
Coefficients are -1/0/1 with pre-specified number of nonzeros.
◆ sampleHWtBounded()
| double helib::DoubleCRT::sampleHWtBounded | ( | long | Hwt | ) |
◆ sampleSmall()
| double helib::DoubleCRT::sampleSmall | ( | ) |
Coefficients are -1/0/1, Prob[0]=1/2.
Sampling routines: Each of these return a high probability bound on L-infty norm of canonical embedding
◆ sampleSmallBounded()
| double helib::DoubleCRT::sampleSmallBounded | ( | ) |
◆ sampleUniform() [1/2]
| NTL::xdouble helib::DoubleCRT::sampleUniform | ( | const NTL::ZZ & | B | ) |
◆ sampleUniform() [2/2]
| double helib::DoubleCRT::sampleUniform | ( | long | B | ) |
Coefficients are uniform in [-B..B].
◆ scaleDownToSet()
| void helib::DoubleCRT::scaleDownToSet | ( | const IndexSet & | s, |
| long | ptxtSpace, | ||
| NTL::ZZX & | delta | ||
| ) |
◆ SetOne()
|
inline |
◆ setPrimes()
|
inline |
@ brief make prime set equal to s1
◆ SetZero()
|
inline |
◆ Sub()
|
inline |
◆ toPoly() [1/2]
| void helib::DoubleCRT::toPoly | ( | NTL::ZZX & | p, |
| bool | positive = false |
||
| ) | const |
◆ toPoly() [2/2]
| void helib::DoubleCRT::toPoly | ( | NTL::ZZX & | p, |
| const IndexSet & | s, | ||
| bool | positive = false |
||
| ) | const |
Recovering the polynomial in coefficient representation. This yields an integer polynomial with coefficients in [-P/2,P/2], unless the positive flag is set to true, in which case we get coefficients in [0,P-1] (P is the product of all moduli used). Using the optional IndexSet param we compute the polynomial reduced modulo the product of only the primes in that set.
◆ write()
| void helib::DoubleCRT::write | ( | std::ostream & | str | ) | const |
Friends And Related Function Documentation
◆ operator<<
|
friend |
◆ operator>>
|
friend |
The documentation for this class was generated from the following files:
- /HElib/include/helib/DoubleCRT.h
- /HElib/src/DoubleCRT.cpp


| 1 |
Li_Z_2018 |
Cellular hnRNP A1 Interacts with Nucleocapsid Protein of Porcine Epidemic Diarrhea Virus and Impairs Viral Replication |
Li, Zhonghua; Zeng, Wei; Ye, Shiyi; Lv, Jian; Nie, Axiu; Zhang, Bingzhou; Sun, Yumei; Han, Heyou; He, Qigai |
2018 |
2018-03-13 |
COMM-USE |
N |
PMC5869520 |
29534017.0 |
10.3390/v10030127 |
prgorr3d |
0.907578 |
Shi_S_2000, Volmer_2010, Li_C_2013, Yasuda-Inoue_2013 |
Zhang_2015 |
| 2 |
Zhang_2014 |
EF1A interacting with nucleocapsid protein of transmissible gastroenteritis coronavirus and plays a role in virus replication |
Zhang, Xin; Shi, Hongyan; Chen, Jianfei; Shi, Da; Li, Changlong; Feng, Li |
2014 |
2014-08-27 |
PMC |
N |
PMC7117464 |
24974120.0 |
10.1016/j.vetmic.2014.05.034 |
lrzshhjd |
0.873350 |
Li_C_2013, Li_C_2014 |
Zhang_2015 |
| 3 |
Zhao_2015 |
The DEAD-box RNA helicase 5 positively regulates the replication of porcine reproductive and respiratory syndrome virus by interacting with viral Nsp9 in vitro |
Zhao, Shuangcheng; Ge, Xinna; Wang, Xiaolong; Liu, Aijing; Guo, Xin; Zhou, Lei; Yu, Kangzhen; Yang, Hanchun |
2015 |
2015-01-02 |
PMC |
N |
PMC7114378 |
25449571.0 |
10.1016/j.virusres.2014.10.021 |
syh53l6q |
0.831128 |
Yasuda-Inoue_2013, Li_C_2013, Liu_H_2009 |
|
| 4 |
Luo_H_2005 |
The nucleocapsid protein of SARS coronavirus has a high binding affinity to the human cellular heterogeneous nuclear ribonucleoprotein A1 |
Luo, Haibin; Chen, Qing; Chen, Jing; Chen, Kaixian; Shen, Xu; Jiang, Hualiang |
2005 |
2005-05-09 |
PMC |
N |
PMC7094256 |
15862300.0 |
10.1016/j.febslet.2005.03.080 |
cxv3m4u1 |
0.804910 |
Shi_S_2000, Volmer_2010, Yasuda-Inoue_2013 |
|
| 5 |
Song_2019 |
EIF4A2 interacts with the membrane protein of transmissible gastroenteritis coronavirus and plays a role in virus replication |
Song, Zhenhui; Yang, Yang; Wang, Li; Wang, Kai; Ran, Ling; Xie, Yilu; Huang, LeiShi; Yang, Zhou; Yuan, Peng; Yu, Qiuhan |
2019 |
2019-04-30 |
PMC |
N |
PMC7111847 |
30583231.0 |
10.1016/j.rvsc.2018.12.005 |
sd5izamc |
0.767673 |
Volmer_2010, Li_C_2013, Li_C_2014 |
Zhang_2015 |
| 6 |
Li_S_2015 |
eEF1A Interacts with the NS5A Protein and Inhibits the Growth of Classical Swine Fever Virus |
Li, Su; Feng, Shuo; Wang, Jing-Han; He, Wen-Rui; Qin, Hua-Yang; Dong, Hong; Li, Lian-Feng; Yu, Shao-Xiong; Li, Yongfeng; Qiu, Hua-Ji |
2015 |
2015-08-10 |
COMM-USE |
N |
PMC4576194 |
26266418.0 |
10.3390/v7082833 |
iv2dcpqj |
0.755303 |
Yasuda-Inoue_2013, Stork_2011 |
Yan_J_2020 |
| 7 |
Sharma_2014 |
Influenza A viral nucleoprotein interacts with cytoskeleton scaffolding protein α‐actinin‐4 for viral replication |
Sharma, Shipra; Mayank, Adarsh K.; Nailwal, Himani; Tripathi, Shashank; Patel, Jenish R.; Bowzard, John B.; Gaur, Pratibha; Donis, Ruben O.; Katz, Jacqueline M.; Cox, Nancy J.; Lal, Renu B.; Farooqi, Humaira; Sambhara, Suryaprakash; Lal, Sunil K. |
2014 |
2014-06-02 |
PMC |
N |
PMC7164065 |
24802111.0 |
10.1111/febs.12828 |
ql6bdnkw |
0.724015 |
Volmer_2010, Li_C_2013 |
|
| 8 |
Li_C_2013 |
The DEAD-box RNA helicase DDX5 acts as a positive regulator of Japanese encephalitis virus replication by binding to viral 3′ UTR |
Li, Chen; Ge, Ling-ling; Li, Peng-peng; Wang, Yue; Sun, Ming-xia; Huang, Li; Ishag, Hassan; Di, Dong-dong; Shen, Zhi-qiang; Fan, Wei-xing; Mao, Xiang |
2013 |
2013-11-30 |
PMC |
N |
PMC7113685 |
24035833.0 |
10.1016/j.antiviral.2013.09.002 |
1cy15tny |
0.699228 |
Yasuda-Inoue_2013, Li_C_2014, Liu_H_2009 |
Yasuda-Inoue_2013, Li_C_2014 |
| 9 |
zhao_2018 |
Host protein CD63 enhances viral RNA replication by interacting with human astrovirus nonstructural protein nsP1a/4 |
wei zhao; Nian liu; Xiao Li Tao; Chun hong Zheng; Xiang yu Li; Man Yu; Yong gang Li |
2018 |
2018-05-27 |
BioRxiv |
N |
|
|
10.1101/331835 |
8r1zb4oc |
0.673747 |
Volmer_2010, Li_C_2013, Li_C_2014 |
Zhang_2015 |
| 10 |
Xue_Q_2019 |
The DEAD-Box RNA Helicase DDX1 Interacts with the Viral Protein 3D and Inhibits Foot-and-Mouth Disease Virus Replication |
Xue, Qiao; Liu, Huisheng; Zeng, Qiaoying; Zheng, Haixue; Xue, Qinghong; Cai, Xuepeng |
2019 |
2019-07-29 |
PMC |
N |
PMC6888807 |
31359346.0 |
10.1007/s12250-019-00148-7 |
9pw9191b |
0.656068 |
Li_C_2013, Yasuda-Inoue_2013, Li_C_2014 |
Li_C_2013, Yasuda-Inoue_2013 |
| 11 |
Gao_W_2010 |
Identification of NCAM that interacts with the PHE-CoV spike protein |
Gao, Wei; He, Wenqi; Zhao, Kui; Lu, Huijun; Ren, Wenzhi; Du, Chongtao; Chen, Keyan; Lan, Yungang; Song, Deguang; Gao, Feng |
2010 |
2010-09-24 |
COMM-USE |
N |
PMC2955716 |
20863409.0 |
10.1186/1743-422x-7-254 |
ss1upwwo |
0.590814 |
Trobaugh_2017, Volmer_2010 |
Zhang_2015 |
| 12 |
Gao_X_2010 |
Tudor-SN interacts with and co-localizes with G3BP in stress granules under stress conditions |
Gao, Xingjie; Ge, Lin; Shao, Jie; Su, Chao; Zhao, Hong; Saarikettu, Juha; Yao, Xuyang; Yao, Zhi; Silvennoinen, Olli; Yang, Jie |
2010 |
2010-08-20 |
PMC |
N |
PMC7127458 |
20643132.0 |
10.1016/j.febslet.2010.07.022 |
2inmn7lb |
0.580357 |
Yasuda-Inoue_2013, Volmer_2010 |
Fitzgerald_2013, Aulas_2015, Jayabalan_2019 |
| 13 |
Li_C_2014 |
Cellular DDX3 regulates Japanese encephalitis virus replication by interacting with viral un-translated regions |
Li, Chen; Ge, Ling-ling; Li, Peng-peng; Wang, Yue; Dai, Juan-juan; Sun, Ming-xia; Huang, Li; Shen, Zhi-qiang; Hu, Xiao-chun; Ishag, Hassan; Mao, Xiang |
2014 |
2014-01-20 |
PMC |
N |
PMC7111930 |
24418539.0 |
10.1016/j.virol.2013.11.008 |
wwkdum94 |
0.569757 |
Yasuda-Inoue_2013, Li_C_2013 |
Li_C_2013 |
| 14 |
Kaewborisuth_2019 |
Porcine Epidemic Diarrhea Virus (PEDV) ORF3 Interactome Reveals Inhibition of Virus Replication by Cellular VPS36 Protein |
Kaewborisuth, Challika; Yingchutrakul, Yodying; Roytrakul, Sittiruk; Jongkaewwattana, Anan |
2019 |
2019-04-24 |
COMM-USE |
N |
PMC6521123 |
31022991.0 |
10.3390/v11040382 |
uabg37n0 |
0.530559 |
Volmer_2010, Trobaugh_2017 |
zhao_2018 |
| 15 |
Trincone_2015 |
Looking for a needle in a haystack: Cellular proteins that may interact with the tyrosine-based sorting signal of the TGEV S protein |
Trincone, Anna; Schwegmann-Weßels, Christel |
2015 |
2015-04-16 |
PMC |
N |
PMC7114463 |
25481285.0 |
10.1016/j.virusres.2014.11.029 |
elway9lp |
0.526017 |
Volmer_2010, Wodrich_2010, Li_C_2014 |
Zhang_2015 |
| 16 |
Yan_J_2020 |
Involvement of VCP/UFD1/Nucleolin in the viral entry of Enterovirus A species |
Yan, Jingjing; Wang, Meng; Wang, Min; Dun, Ying; Zhu, Liuyao; Yi, Zhigang; Zhang, Shuye |
2020 |
2020-07-02 |
PMC |
N |
|
|
10.1016/j.virusres.2020.197974 |
lqu8wm88 |
0.519964 |
Yasuda-Inoue_2013 |
Phongphaew_2017, Sun_D_2016 |
| 17 |
Chen_2009 |
Interaction between SARS-CoV helicase and a multifunctional cellular protein (Ddx5) revealed by yeast and mammalian cell two-hybrid systems |
Chen, Jin-Yan; Chen, Wan-Nan; Poon, Kwok-Man Vincent; Zheng, Bo-Jian; Lin, Xu; Wang, Yong-Xiang; Wen, Yu-Mei |
2009 |
2009-02-18 |
PMC |
N |
PMC7087151 |
19224332.0 |
10.1007/s00705-009-0323-y |
238e30ii |
0.518315 |
Li_C_2013, Yasuda-Inoue_2013, Li_C_2014 |
|
| 18 |
Kwak_2011 |
Annexin A2 Binds RNA and Reduces the Frameshifting Efficiency of Infectious Bronchitis Virus |
Kwak, Hoyun; Park, Min Woo; Jeong, Sunjoo |
2011 |
2011-08-30 |
COMM-USE |
N |
PMC3168876 |
21918681.0 |
10.1371/journal.pone.0024067 |
uqrwq5qk |
0.489446 |
Yasuda-Inoue_2013, Stork_2011, Liu_H_2009 |
Zhang_2015 |
| 19 |
Sungsuwan_2020 |
Nucleocapsid proteins from other swine enteric coronaviruses differentially modulate PEDV replication |
Sungsuwan, Suttipun; Jongkaewwattana, Anan; Jaru-Ampornpan, Peera |
2020 |
2020-01-15 |
PMC |
N |
PMC7112109 |
31756532.0 |
10.1016/j.virol.2019.11.007 |
lkd2mj27 |
0.487595 |
|
Zhang_2015 |
| 20 |
Jiang_2009 |
Polypyrimidine tract-binding protein influences negative strand RNA synthesis of dengue virus |
Jiang, Linbin; Yao, Huiling; Duan, Xiaoqun; Lu, Xi; Liu, Yongming |
2009 |
2009-07-24 |
PMC |
N |
PMC7117538 |
19450550.0 |
10.1016/j.bbrc.2009.05.036 |
0pq2vgwo |
0.475155 |
Li_C_2014, Yasuda-Inoue_2013 |
Zhang_2015 |
| 21 |
Zhang_2015 |
Identification of the interaction between vimentin and nucleocapsid protein of transmissible gastroenteritis virus |
Zhang, Xin; Shi, HongYan; Chen, JianFei; Shi, Da; Dong, Hui; Feng, Li |
2015 |
2015-03-16 |
PMC |
N |
PMC7114421 |
25533531.0 |
10.1016/j.virusres.2014.12.013 |
wrztpeb8 |
0.467284 |
Volmer_2010, Shi_S_2005, Trobaugh_2017 |
Sun_D_2016 |
| 22 |
Guan_2010 |
Interaction of Hsp40 with influenza virus M2 protein: implications for PKR signaling pathway |
Guan, Zhenhong; Liu, Di; Mi, Shuofu; Zhang, Jie; Ye, Qinong; Wang, Ming; Gao, George F.; Yan, Jinghua |
2010 |
2010-10-01 |
PMC |
N |
PMC4875119 |
21204021.0 |
10.1007/s13238-010-0115-x |
8x83dx6k |
0.452342 |
Volmer_2010 |
Zhang_2015, Aweya_2013 |
| 23 |
Shi_S_2000 |
Heterogeneous nuclear ribonucleoprotein A1 regulates RNA synthesis of a cytoplasmic virus |
Shi, Stephanie T.; Huang, Peiyong; Li, Hsin-Pai; Lai, Michael M.C. |
2000 |
2000-09-01 |
PMC |
N |
PMC302072 |
10970862.0 |
10.1093/emboj/19.17.4701 |
6lvn10f4 |
0.451971 |
Yasuda-Inoue_2013, Stork_2011 |
|
| 24 |
Tan_Y_2012 |
Binding of the 5′-untranslated region of coronavirus RNA to zinc finger CCHC-type and RNA-binding motif 1 enhances viral replication and transcription |
Tan, Yong Wah; Hong, Wanjin; Liu, Ding Xiang |
2012 |
2012-02-22 |
NONCOMM |
N |
PMC3367200 |
22362731.0 |
10.1093/nar/gks165 |
d1sgnxc0 |
0.432311 |
Stork_2011, Volmer_2010 |
|
| 25 |
Wang_2010 |
Interactions of SARS Coronavirus Nucleocapsid Protein with the host cell proteasome subunit p42 |
Wang, Qin; Li, Chuan; Zhang, Quanfu; Wang, Tao; Li, Jiandong; Guan, Wuxiang; Yu, Jianshi; Liang, Mifang; Li, Dexin |
2010 |
2010-05-17 |
COMM-USE |
N |
PMC2894783 |
20478047.0 |
10.1186/1743-422x-7-99 |
al8irm9i |
0.425741 |
Volmer_2010 |
Zhang_2015 |
| 26 |
Lai_M_2015 |
DDX3 functions in antiviral innate immunity through translational control of PACT |
Lai, Ming‐Chih; Sun, H. Sunny; Wang, Shainn‐Wei; Tarn, Woan‐Yuh |
2015 |
2015-10-31 |
PMC |
N |
PMC7164078 |
26454002.0 |
10.1111/febs.13553 |
ploi4wh2 |
0.418019 |
Yasuda-Inoue_2013 |
|
| 27 |
Wendt_2020 |
The Ebola Virus Nucleoprotein Recruits the Nuclear RNA Export Factor NXF1 into Inclusion Bodies to Facilitate Viral Protein Expression |
Wendt, Lisa; Brandt, Janine; Bodmer, Bianca S.; Reiche, Sven; Schmidt, Marie Luisa; Traeger, Shelby; Hoenen, Thomas |
2020 |
2020-01-11 |
COMM-USE |
N |
PMC7017048 |
31940815.0 |
10.3390/cells9010187 |
fbw99knd |
0.412709 |
Yasuda-Inoue_2013, Li_C_2014, Stork_2011, Volmer_2010 |
Wulan_2015, Yan_J_2020 |
| 28 |
Carissimo_2019 |
VCP/p97 Is a Proviral Host Factor for Replication of Chikungunya Virus and Other Alphaviruses |
Carissimo, Guillaume; Chan, Yi-Hao; Utt, Age; Chua, Tze-Kwang; Bakar, Farhana Abu; Merits, Andres; Ng, Lisa F. P. |
2019 |
2019-09-24 |
COMM-USE |
N |
PMC6787436 |
31636613.0 |
10.3389/fmicb.2019.02236 |
jj18fyaj |
0.346970 |
Li_C_2014 |
Yan_J_2020, Sun_D_2016, Phongphaew_2017 |
| 29 |
Pan_W_2017 |
EIF3i affects vesicular stomatitis virus growth by interacting with matrix protein |
Pan, Wei; Song, Deguang; He, Wenqi; Lu, Huijun; Lan, Yungang; Li, Hongli; Gao, Feng; Zhao, Kui |
2017 |
2017-12-31 |
PMC |
N |
PMC7117458 |
29173589.0 |
10.1016/j.vetmic.2017.10.021 |
9t8hf89d |
0.341961 |
Trobaugh_2017, Volmer_2010, Yasuda-Inoue_2013 |
Zhang_2015 |
| 30 |
Aweya_2013 |
The p7 protein of the hepatitis C virus induces cell death differently from the influenza A virus viroporin M2 |
Aweya, Jude Juventus; Mak, Tze Minn; Lim, Seng Gee; Tan, Yee-Joo |
2013 |
2013-03-31 |
PMC |
N |
PMC7114515 |
23246447.0 |
10.1016/j.virusres.2012.12.005 |
5wiyjvrc |
0.340199 |
Volmer_2010, Aweya_2015 |
Zhang_2015 |
| 31 |
Cheng_2015 |
Severe acute respiratory syndrome coronavirus protein 6 mediates ubiquitin-dependent proteosomal degradation of N-Myc (and STAT) interactor |
Cheng, Weijia; Chen, Shiyou; Li, Ruiling; Chen, Yu; Wang, Min; Guo, Deyin |
2015 |
2015-04-17 |
PMC |
N |
PMC7091177 |
25907116.0 |
10.1007/s12250-015-3581-8 |
8g6pcfvo |
0.335197 |
|
|
| 32 |
Kou_Y_2006 |
Hepatitis C virus NS4A inhibits cap-dependent and the viral IRES-mediated translation through interacting with eukaryotic elongation factor 1A |
Kou, Yi-Hen; Chou, Shang-Min; Wang, Yi-Ming; Chang, Ya-Tzu; Huang, Shao-Yong; Jung, Mei-Ying; Huang, Yu-Hsu; Chen, Mei-Ru; Chang, Ming-Fu; Chang, Shin C. |
2006 |
2006-08-23 |
PMC |
N |
PMC7088589 |
16927014.0 |
10.1007/s11373-006-9104-8 |
u2lwgyyf |
0.319362 |
Yasuda-Inoue_2013, Stork_2011 |
|
| 33 |
Brunner_2010 |
Delayed kinetics of poliovirus RNA synthesis in a human cell line with reduced levels of hnRNP C proteins |
Brunner, Jo Ellen; Ertel, Kenneth J.; Rozovics, Janet M.; Semler, Bert L. |
2010 |
2010-05-10 |
None |
N |
PMC2844484 |
20189623.0 |
10.1016/j.virol.2010.01.031 |
0eqauqje |
0.310476 |
Shi_S_2000, Volmer_2010, Yasuda-Inoue_2013, Liu_H_2009 |
Shi_S_2000 |
| 34 |
Shi_D_2014 |
Molecular Characterizations of Subcellular Localization Signals in the Nucleocapsid Protein of Porcine Epidemic Diarrhea Virus |
Shi, Da; Lv, Maojie; Chen, Jianfei; Shi, Hongyan; Zhang, Sha; Zhang, Xin; Feng, Li |
2014 |
2014-03-13 |
COMM-USE |
N |
PMC3970149 |
24632575.0 |
10.3390/v6031253 |
mameyzih |
0.303485 |
Volmer_2010, Shi_S_2000, Li_C_2013 |
Zhang_2015 |


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This button determines if the form can be submitted.
This button always submits the form.


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Created by Saurabh Sharma / @saurshaz
Introduction
↓
↓
↓
Why tests ?
A language thing ?
Developer psychology ?
Deck↓
Allen Kelly's claim on TDD and unemployability in 2022 blog
By 2022 it will be not be possible to get a professional programming job if you do not practice TDD routinely.
↓
A different take - DT in sync link
Ultimately what you are looking for is an extremely solid development life-cycle, and TDD does not give that to you in totality. Breaking it down into four simple steps will get you a long way:
Developer psychology ?
Don’t they(tests) take extra time of developer ?
↓
Really? do they ?
Think long term investments
Absolutely :: We all are anyways testing (manually at most times)
↓
Let's look at a simplistic example which involves all stacks
Let us teh codez :-)
Created by Saurabh Sharma / @saurshaz


Qantas to drop Sydney-Beijing route due to competition from Chinese carriers
SYDNEY: Qantas Airways said on Tuesday (Nov 12) it is axing its underperforming Sydney-Beijing route from March due to stiff competition from Chinese airlines and weak business class demand.
The Australian carrier had relaunched the route in 2017 in its third attempt in 35 years to make it viable and had already lowered the number of weekly flights to five from seven in 2018.
It will maintain daily flights from Sydney to Shanghai, where it partners with hub carrier China Eastern Airlines Corp Ltd.
Qantas said since it had reintroduced the direct Sydney-Beijing services in 2017, capacity from Beijing to Australia on Chinese airlines had grown by around 20% and was expected to grow even further in 2020 at a time when broader international capacity to Australia was declining.
"Our flights to Beijing have been underperforming for some time due to weaker demand as well as a big increase in capacity from other airlines," Qantas International Chief Executive Tino La Spina said in a statement.
"China is a significant market for Qantas and our direct services from and to Shanghai are performing well. With Beijing, we're responding to what the market is telling us," La Spina said.
Qantas said it would redeploy the Airbus SE A330 capacity it had been using on the route to elsewhere in Asia.


--- layout: default title: "Divbox" ---
DivBox plugin is simple, easy style format, no need extra markup and is used to overlay images on the current page through the power and flexibility of jQuery´s selector. DivBox is a plugin for jQuery..


toronto: 2 posts
newjersey: 2 posts
chico: 2 posts
bozeman: 2 posts
chicago: 1 posts
losangeles: 1 posts
columbus: 1 posts
provo: 1 posts
pennstate: 1 posts
sarasota: 1 posts
gainesville: 1 posts
atlanta: 2 posts
cleveland: 1 posts
austin: 1 posts
sanantonio: 1 posts
Oct 30 Python/C++ Development Opportunity - (Atlanta, GA)
Oct 30 Python programmer needed - (Charleston)
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Oct 15 Python Developer -- If you know PHP, Ruby, or Java learn Python! - (Manhattan )
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Nov 01 Python Web Developer - (Los Angeles)


A simple app to visualize a rudimentary network of the scientific collaboration between investigators in the biomedical and life sciences field based on their common publications. Depending on the query you entered, the outputed network could represented the network of the most collaborative investigators in a specific area of the biomedical field or represent the collaboration connections for a specific author.
Two scientists are considered connected if they have authored a paper together and explicit networks of such connections are constructed by using data drawn from the NCBI Pubmed database maintained by the Entrez query and database system at the National Center for Biotechnology Information (NCBI). Because the Pubmed database only records biomedical and life sciences journal articles, the networks that can be constructed are limited to scientist having authoring papers in those fields.
This app will consider whatever you entered in the search box as a valid Pubmed query. Pubmed queries can be built with specific keywords to better focus your request (e.g.: if you want to construct the network from the common publications of two specific authors, use the "[author]" keyword, for example "Weiss jn[author] and Bers dm[author]").
If you are not familiar with advanced Pubmed queries, please refer to the PubMed Advanced Search Builder tool to construct the specific query for your need!
For better performance, the outputed network only presents the result from the most recent 60 publications matching the Pubmed query.


Supports
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# of Days for Meals:
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# Breakfasts:
# Lunches:
# Dinners:
Up to a Total of:
# Nights:
# Rooms:
# Nights
# Nights
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Winter Conditions:
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Evacuees
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黒の手番です。61 はどう動かしますか？


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Using Street Image Compare you can compare, for the same place, Google Street View and Mapillary images (if there are available … ) and to move on them having, as map context, both Google Map and OpenStreetMap. Here you're a user session video ... The user can select (at top right in this page ...), the place in three different ways:
The application use Google Maps geocoder as geocoding engine.
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References: created by Cesare Gerbino (cesare.gerbino@gmail.com). Click here for details. The code is available on GitHub under MIT license |


Looking for answers?
Someone once said, “He who has all the answers isn’t asking the right questions.”
We like to think we have both!
Here are some helpful answers to questions we get all the time. Want to talk in person?
Contact Us.
What is Oncal India?
We are an entirely online market place where one can buy and sell as per their convenience and without having to leave the comfort of their home. We promote local trading of products and hence pair up sellers and buyers of the same region. For further details, visit About.
How did you get started?
A group of like minded people originally working for betterment of selling and buying conditions at their own levels came together to broaden the field of work with the belief of together we can.
How can I work at your organisation?
We’re looking for the best, brightest and most passionate people on the planet. Contact Us.
What is your refund/cancellation policy?
If for any reason you would like a refund for any product or service availed, we will ask the seller if they are willing to exchange/take back their product. After that it may take up to 10 business days (depending on your bank) for a refund to appear on your account. Vendors can cancel their subscription anytime by contacting us.
For more queries feel free to contact us and in case of suggestions, visit Feedback.


Viper
INTERFACE
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DATASET
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Gamalon Design System
An engineering-ready design system for Gamalon products.
process
requirements gathering -> competitive analysis -> round table with engineering -> workflow design -> tool exploration (Sketch, XD, Figma, InVision, Plant.io, etc.) -> component library exploration (Material, Ant, Mailchimp, Polaris, etc.) -> stakeholder meeting -> process documentation -> production
team
Jon Linton, Alan deLespinasse, Ira Ladson, Glynnis Kearney, Matt Tharp
duration
2018 / 1 month
Problem Statement
In 2018, Gamalon launched ambitious plans to build multiple products simultaneously, while also growing the product team within the organization. It therefore became important to come up with a consistent user experience across all of our products, and to provide designers and engineers with efficient workflows to translate this vision into their work.
Outcome
The Gamalon Design System is sits on top of the Ant component library. Gamalon has its own colors, gradients, text styles, and illustrations, and these atoms have been injected into Ant components to make our interfaces and interactions seem distinct to Gamalon. The design system is operationalized using a centralized repository of components and an end-to-end workflow that involves the continuous translation of design into code.
Selected Assets
A selection of assets from the prototyping process are presented here.
[Figure 1] When I arrived at Gamalon, it did not have a design system. One of my first tasks was to create the atoms of a design system that engineers could use to start building right away.
[Figure 2] A raw Sketch file showing the Ant Design's components, which Gamalon adapted for its own use.
[Figure 3] A prototype showing how we adapted Ant Design's components to the atoms of Gamalon's own design system.


Since childhood, up until my mid-20’s, I have been told by family and friends that I’ve always been seen as bubbly, bright and inquisitive, always ready to help and lead others and always ready to sing in choirs, speak in church and act - a textbook extrovert. However, I had also always been struggling with bouts of anxiety and inadequacy. After having my mental health and confidence challenged over the past few years, that extroverted side of me has lessened considerably, and I have been gradually building up my confidence to get me to where I am now.
While building up my confidence again, I’ve been reflecting a lot on how some of my core values and identity have stayed the same despite these issues.
Growing up in a very semi-traditional Samoan, and Latter-Day Saint household taught me from a young age to be of service to others, to be humble and reach out to others regardless of any differences. My involvement in church choirs, leading youth groups and teaching children helped reinforce the values of serving, belonging, having accountability, compassion, empathy and humility.
A situation where I have had an ethical decision to make would be when I had to make the decision to resign from my last job in order to get help for clinical depression instead of staying in my role to support my family. As someone who had been working ever since I left high school, this decision was especially hard to make, as the only other person who could work was my mum. The addition of my sister who was studying at the time was also on my mind. As I value supporting, serving and being mindful about the happiness of my family, I had to be honest and let go of being independent, about when I needed help. Being open and honest helped me realise that I didn’t need to be afraid to ask for that help, and led to the consequence of having the support of my family for the next three years, regardless of the extra lack of income.
While evaluating my strengths and limitations, I actually remembered that I had already done the Strengths Finder quiz a few years ago. Despite my own personal changes, the list still applies, but shows in different ways.
| 1. | Ideation | People exceptionally talented in the Ideation theme are fascinated by ideas. They are able to find connections between seemingly disparate phenomena. |
| 2. | Connectedness | People exceptionally talented in the Connectedness theme have faith in the links among all things. They believe there are few coincidences and that almost every event has meaning. |
| 3. | Individualization | People exceptionally talented in the Individualization theme are intrigued with the unique qualities of each person. They have a gift for figuring out how different people can work together productively |
| 4. | Strategic | People exceptionally talented in the Strategic theme create alternative ways to proceed. Faced with any given scenario, they can quickly spot the relevant patterns and issues. |
| 5. | Futuristic | People exceptionally talented in the Futuristic theme are inspired by the future and what could be. They energize others with their visions of the future. |
I think that out of the strengths from that list, the ones that will help me the most with my learning Ideation, Individualization, and Strategy. I actually feel that all five could cross over easily, and be of benefit to me in my journey. Where I lack in focus, calmness, timeboxing, I could use strategies to help combat and overcome those obstacles. The Problem Solving Process and Framework would be beneficial as a strategic guide. Individualization would be really helpful when the time comes to pair with another cohort buddy, an even when I eventually collaborate with a colleague. Having that ability to adapt to other peoples' differences and work with each other effectively, is something I look forward to developing further!
As for an example of trying to work productively, and encountering resistance or tension, I had one issue where someone from my team had been taking the work I was supposed to be doing while I was offsite in another work location, as a part of my role. There had been some tension between us previously, as she had assumed that I should have been at a higher level and that I wasn’t competent enough for my job, even though I had been part of the team for a few weeks, and was still in training. Our boss knew that, and disregarded her complaint when she brought it up during a meeting. So when I had noticed that my work was being taken, I made a plan to still handle the situation civilly and approach her about it, rather than bring it up during a meeting. I also had the support of a couple of colleagues who had noticed the changing work, and they knew that I still do the same work when I’m off-site. When I approached this one colleague, I let her know that I had noticed my work being reassigned by her, without my being consulted first. And she explained that she assumed that on those days that I wasn’t on-site, that I wasn’t doing anything. When I cleared up that I was, in fact, trying to do the work that was assigned to me, she apologised for the misunderstanding, and agreed to not interfere. We actually turned out to be pretty close by the time I had left. I think that just having the approach of being understanding about the situation, rather than acting aggressively or being petty, helped to foster a more favorable outcome.


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|
FAQs - Frequently Asked Questions
Frequently asked questions about breaking into
pharmaceutical sales
The answers provided in this section are
generalities for pharmaceutical sales and do not always (but do
typically) hold true.
- No sales experience
| Q |
I do not have sales experience. Is
there any chance of breaking into pharmaceutical sales without first
gaining this experience? |
| A |
Yes, it's possible. No, it's not
highly likely. Some pharmaceutical companies hire new college
graduates or candidates that have experience in the medical or related
field, but no sales experience. If you do not have successful sales
experience, your chances of breaking into pharmaceutical sales are
more limited, but it is still possible. You will have to put some
extra effort into showing your initiative and preparing
for your pharmaceutical sales interviews.
|
- Too much experience/age
| Q |
I have been in the work force for 15
years <post-graduate>. I hear it is harder to get into
pharmaceutical sales after you've hit a certain age. Is that true? |
| A |
Unfortunately, that does tend to be
true. Although age discrimination is illegal, the pharmaceutical
industry is certainly kinder to younger candidates (generally
speaking). Part of the thinking behind this is that once you've reach
a certain point in your life (or career), you are less likely to be
able to put up with the various egos involved in calling on
physicians. If you are over 35 your chances of breaking in are
certainly lower (in most cases).
|
- Out of work
| Q |
I was downsized this month and I am
committed to breaking into pharmaceutical sales. Will I have more
difficulty getting an interview without having a job? |
| A |
Some pharmaceutical companies &/or
managers are not interested in potential employees unless they are
employed. Given the current state of the economy, there may be a
little more flexibility and understanding in the market. It takes an
average of 4 to 6 months to break into pharmaceutical sales, so if you
are unemployed you should be aware that you may have a bit of a wait
ahead of you. Also, take note that the longer you have been
unemployed, the more difficult it will be to get an interview.
|
- Recent college graduate
| Q |
I just graduated from college. Do
pharmaceutical companies hire people like me, with no related
experience? |
| A |
Some pharmaceutical companies will
hire college graduates with no sales experience. If you have a record
of solid achievement, your odds will be much greater. *Take a look at
a periodical provided by NACE (National Association of Colleges &
Employers) to find out which pharmaceutical companies are targeting
new graduates (check with your local library).
|
- Job hopping/tech industry
| Q |
Because I have been in sales in the
technical industry, my resume shows a very broken work history. Will
this hurt my chances of getting into pharmaceutical sales? |
| A |
There are pharmaceutical companies who
have strict requirements regarding "job hopping" (regardless
of the reason). One company refuses to interview anyone who has had
more than 1 job since college graduation (that gets trickier the
longer you're out of college!). If you have had 4 jobs in the past 5
years (for example), you will have more difficulty getting an initial
interview (order the BOOK or sign up for a Tele-Class
for more NETWORKING tips).
|
- Driving record
| Q |
My driving record is slightly less
than perfect. How clean does your driving record need to be for
pharmaceutical sales? |
| A |
This question comes up a lot. If you
have been convicted of a dui/dwi (driving while intoxicated) in the
past 3-5 years, your chances are close to zero. Different
pharmaceutical companies have different policies. If you have 3 or
more traffic violations within the past 3 years, you will have great
difficulty. If you get to a second or final round interview with a
company, and you are in question about your driving record, call the
company's HR department (anonymously) and ask if they can tell you
what their policy is (you may not get an answer, but it won't hurt to
try). |
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