text:
OpenMS  2.6.0

Identifies peptides in MS/MS spectra via Mascot.

 pot. predecessor tools MascotAdapter pot. successor tools any signal-/preprocessing tool (in mzML format) IDFilter or any protein/peptide processing tool

This wrapper application serves for getting peptide identifications for MS/MS spectra. It uses a local installation of the Mascot server to generate the identifications. A second wrapper (MascotAdapterOnline) is available which is able to perform identifications by communicating with a Mascot server over the network. So, it is not necessary to execute MascotAdapterOnline on the same machine as Mascot.

The minimal version of Mascot supported with this server is 2.1.

This wrapper can be executed in three different modes:

1. The whole process of ProteinIdentification via Mascot is executed. Inputfile is a mzData file containing the MS/MS spectra for which the identifications are to be found. The results are written as a idXML output file. This mode is selected by default.

2. Only the first part of the ProteinIdentification process is performed. This means that the MS/MS data is transformed into Mascot Generic Format (mgf) which can be used directly with Mascot. Being in the cgi directory of the Mascot directory calling a Mascot process should look like the following:

./nph-mascot.exe 1 -commandline -f outputfilename < inputfilename

Consult your Mascot reference manual for further details.

This mode is selected by the -mascot_in option in the command line.

3. Only the second part of the ProteinIdentification process is performed. This means that the outputfile of the Mascot server is translated into idXML.

This mode is selected by the -mascot_out option in the command line.

If your Mascot server is installed on the same computer as the TOPP applications the MascotAdapter can be executed in mode 1. Otherwise the Mascot engine has to be executed manually assisted by mode 2 and mode 3. The ProteinIdentification steps then look like:

• execute MascotAdapter in mode 2
./MascotAdapter -in mzDataFile -out mascotGenericFormatFile -mascot_in
• copy mascotGenericFormatFile to your Mascot server
• call your Mascot server process:
./nph-mascot.exe 1 -commandline -f mascotOutFile < mascotGenericFormatFile
• call the script to export your outfile in mascot xml
./export_dat.pl do_export=1 export_format=XML file=mascotOutFile _sigthreshold=0
_showsubset=1 show_same_sets=1 show_unassigned=0 prot_score=0 pep_exp_z=0 pep_score=0
pep_homol=0 pep_ident=0 pep_seq=1 show_header=1 show_queries=1 pep_rank=0 > mascotXMLFile
• copy mascotXMLFile to the server on which the TOPP applications are installed
• execute MascotAdapter in mode 3
./MascotAdapter -in mascotXMLFile -out IdXMLFile -mascot_out

For mode 1 you have to specify the directory in which the Mascot server is installed. This is done by setting the option mascot_dir in the ini file. Furthermore you have to specify a folder in which the user has write permissions. This is done by setting the option temp_data_directory in the ini file. Two temporary files will be created in this directory during execution but deleted at the end of execution.

Note
Currently mzIdentML (mzid) is not directly supported as an input/output format of this tool. Convert mzid files to/from idXML using IDFileConverter if necessary.

The command line parameters of this tool are:

```MascotAdapter -- Annotates MS/MS spectra using Mascot.
Version: 2.6.0 Sep 30 2020, 12:54:34, Revision: c26f752
To cite OpenMS:
Rost HL, Sachsenberg T, Aiche S, Bielow C et al.. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Meth. 2016; 13, 9: 741-748. doi:10.1038/nmeth.3959.

Usage:

Options (mandatory options marked with '*'):
-in <file>*                      Input file in mzData format.
Note: In mode 'mascot_out' a Mascot results file (.mascotXML) is read (va
lid formats: 'mzData', 'mascotXML')
-out <file>*                     Output file in idXML format.
Note: In mode 'mascot_in' Mascot generic format is written. (valid format
s: 'idXML', 'mgf')
-out_type <type>                 Output file type (for TOPPAS) (valid: 'idXML', 'mgf')
-instrument <i>                  The instrument that was used to measure the spectra (default: 'Default')
-precursor_mass_tolerance <tol>  The precursor mass tolerance (default: '2.0')
-peak_mass_tolerance <tol>       The peak mass tolerance (default: '1.0')
-taxonomy <tax>                  The taxonomy (default: 'All entries' valid: 'All entries', '. . Archaea
(Archaeobacteria)', '. . Eukaryota (eucaryotes)', '. . . . Alveolata (alve
olates)', '. . . . . . Plasmodium falciparum (malaria parasite)', '. . .
. . . Other Alveolata', '. . . . Metazoa (Animals)', '. . . . . . Caenorha
bditis elegans', '. . . . . . Drosophila (fruit flies)', '. . . . . . Chor
data (vertebrates and relatives)', '. . . . . . . . bony vertebrates', '.
. . . . . . . . . lobe-finned fish and tetrapod clade', '. . . . . . . .
. . . . Mammalia (mammals)', '. . . . . . . . . . . . . . Primates', '. .
...
ilable')
-modifications <mods>            The modifications i.e. Carboxymethyl (C)
-variable_modifications <mods>   The variable modifications i.e. Carboxymethyl (C)
-charges [1+ 2+ ...]             The different charge states (default: '[1+ 2+ 3+]')
-db <name>                       The database to search in (default: 'MSDB')
-hits <num>                      The number of hits to report (default: 'AUTO')
-cleavage <enz>                  The enzyme descriptor to the enzyme used for digestion. (Trypsin is defaul
t, None would be best for peptide input or unspecific digestion, for more
please refer to your mascot server). (default: 'Trypsin' valid: 'Trypsin',
'Arg-C', 'Asp-N', 'Asp-N_ambic', 'Chymotrypsin', 'CNBr', 'CNBr+Trypsin',
'Formic_acid', 'Lys-C', 'Lys-C/P', 'PepsinA', 'Tryp-CNBr', 'TrypChymo',
'Trypsin/P', 'V8-DE', 'V8-E', 'semiTrypsin', 'LysC+AspN', 'None')
-missed_cleavages <num>          Number of allowed missed cleavages (default: '0' min: '0')
-sig_threshold <num>             Significance threshold (default: '0.05')
-pep_homol <num>                 Peptide homology threshold (default: '1.0')
-pep_ident <num>                 Peptide ident threshold (default: '1.0')
-pep_rank <num>                  Peptide rank (default: '1')
-prot_score <num>                Protein score (default: '1.0')
-pep_score <num>                 Peptide score (default: '1.0')
-pep_exp_z <num>                 Peptide expected charge (default: '1')
-show_unassigned <num>           Show_unassigned (default: '1')
-first_dim_rt <num>              Additional information which is added to every peptide identification as
metavalue if set > 0 (default: '0.0')
-boundary <string>               MIME boundary for mascot output format
-mass_type <type>                Mass type (default: 'Monoisotopic' valid: 'Monoisotopic', 'Average')
-mascot_directory <dir>          The directory in which mascot is located
-temp_data_directory <dir>       A directory in which some temporary files can be stored

Common TOPP options:
-ini <file>                      Use the given TOPP INI file
-threads <n>                     Sets the number of threads allowed to be used by the TOPP tool (default:
'1')
-write_ini <file>                Writes the default configuration file
--help                           Shows options
--helphelp                       Shows all options (including advanced)

```

INI file documentation of this tool:

Legend:
required parameter
+MascotAdapterAnnotates MS/MS spectra using Mascot.
version2.6.0 Version of the tool that generated this parameters file.
++1Instance '1' section for 'MascotAdapter'
in input file in mzData format.
Note: In mode 'mascot_out' a Mascot results file (.mascotXML) is read
input file*.mzData,*.mascotXML
out output file in idXML format.
Note: In mode 'mascot_in' Mascot generic format is written.
output file*.idXML,*.mgf
out_type output file type (for TOPPAS)idXML,mgf
instrumentDefault the instrument that was used to measure the spectra
precursor_mass_tolerance2.0 the precursor mass tolerance
peak_mass_tolerance1.0 the peak mass tolerance
taxonomyAll entries the taxonomyAll entries,. . Archaea (Archaeobacteria),. . Eukaryota (eucaryotes),. . . . Alveolata (alveolates),. . . . . . Plasmodium falciparum (malaria parasite),. . . . . . Other Alveolata,. . . . Metazoa (Animals),. . . . . . Caenorhabditis elegans,. . . . . . Drosophila (fruit flies),. . . . . . Chordata (vertebrates and relatives),. . . . . . . . bony vertebrates,. . . . . . . . . . lobe-finned fish and tetrapod clade,. . . . . . . . . . . . Mammalia (mammals),. . . . . . . . . . . . . . Primates,. . . . . . . . . . . . . . . . Homo sapiens (human),. . . . . . . . . . . . . . . . Other primates,. . . . . . . . . . . . . . Rodentia (Rodents),. . . . . . . . . . . . . . . . Mus.,. . . . . . . . . . . . . . . . . . Mus musculus (house mouse),. . . . . . . . . . . . . . . . Rattus,. . . . . . . . . . . . . . . . Other rodentia,. . . . . . . . . . . . . . Other mammalia,. . . . . . . . . . . . Xenopus laevis (African clawed frog),. . . . . . . . . . . . Other lobe-finned fish and tetrapod clade,. . . . . . . . . . Actinopterygii (ray-finned fishes),. . . . . . . . . . . . Takifugu rubripes (Japanese Pufferfish),. . . . . . . . . . . . Danio rerio (zebra fish),. . . . . . . . . . . . Other Actinopterygii,. . . . . . . . Other Chordata,. . . . . . Other Metazoa,. . . . Dictyostelium discoideum,. . . . Fungi,. . . . . . Saccharomyces Cerevisiae (baker's yeast),. . . . . . Schizosaccharomyces pombe (fission yeast),. . . . . . Pneumocystis carinii,. . . . . . Other Fungi,. . . . Viridiplantae (Green Plants),. . . . . . Arabidopsis thaliana (thale cress),. . . . . . Oryza sativa (rice),. . . . . . Other green plants,. . . . Other Eukaryota,. . Bacteria (Eubacteria),. . . . Actinobacteria (class),. . . . . . Mycobacterium tuberculosis complex,. . . . . . Other Actinobacteria (class),. . . . Firmicutes (gram-positive bacteria),. . . . . . Bacillus subtilis,. . . . . . Mycoplasma,. . . . . . Streptococcus Pneumoniae,. . . . . . Streptomyces coelicolor,. . . . . . Other Firmicutes,. . . . Proteobacteria (purple bacteria),. . . . . . Agrobacterium tumefaciens,. . . . . . Campylobacter jejuni,. . . . . . Escherichia coli,. . . . . . Neisseria meningitidis,. . . . . . Salmonella,. . . . . . Other Proteobacteria,. . . . Other Bacteria,. . Viruses,. . . . Hepatitis C virus,. . . . Other viruses,. . Other (includes plasmids and artificial sequences),. . unclassified,. . Species information unavailable
modifications[] the modifications i.e. Carboxymethyl (C)
variable_modifications[] the variable modifications i.e. Carboxymethyl (C)
charges[1+, 2+, 3+] the different charge states
dbMSDB the database to search in
hitsAUTO the number of hits to report
cleavageTrypsin The enzyme descriptor to the enzyme used for digestion. (Trypsin is default, None would be best for peptide input or unspecific digestion, for more please refer to your mascot server).Trypsin,Arg-C,Asp-N,Asp-N_ambic,Chymotrypsin,CNBr,CNBr+Trypsin,Formic_acid,Lys-C,Lys-C/P,PepsinA,Tryp-CNBr,TrypChymo,Trypsin/P,V8-DE,V8-E,semiTrypsin,LysC+AspN,None
missed_cleavages0 number of allowed missed cleavages0:∞
sig_threshold0.05 significance threshold
pep_homol1.0 peptide homology threshold
pep_ident1.0 peptide ident threshold
pep_rank1 peptide rank
prot_score1.0 protein score
pep_score1.0 peptide score
pep_exp_z1 peptide expected charge
show_unassigned1 show_unassigned
first_dim_rt0.0 additional information which is added to every peptide identification as metavalue if set > 0
boundary MIME boundary for mascot output format
mass_typeMonoisotopic mass typeMonoisotopic,Average
mascot_directory the directory in which mascot is located
temp_data_directory a directory in which some temporary files can be stored
log Name of log file (created only when specified)
debug0 Sets the debug level
threads1 Sets the number of threads allowed to be used by the TOPP tool
no_progressfalse Disables progress logging to command linetrue,false
forcefalse Overrides tool-specific checkstrue,false
testfalse Enables the test mode (needed for internal use only)true,false

You can specify the Mascot parameters precursor_mass_tolerance (the peptide mass tolerance), peak_mass_tolerance (the MS/MS tolerance), taxonomy (restriction to a certain subset of the database), modifications, variable_modifications, charges (the possible charge variants), db (database where the peptides are searched in), hits (number of hits), cleavage (the cleavage enzyme), missed_cleavages (number of missed cleavages) and mass_type (Monoisotopic or Average) via the ini file.

Known problems with Mascot server execution:

• getting error message: "FATAL_ERROR: M00327 The ms-monitor daemon/service is not running, please start it."

• Possible explanations:
• Your ms-monitor is really not running => consult your Mascot reference manual for details about starting the Mascot server.
• (Suppose you have Mascot installed in directory mascot.) mascot/data/mascot.control is not writable for the current user. This has to be changed. Otherwise you will not be able to use the Mascot server via the shell and receive the above error message.
=> Change write permissions of the file mascot/data/mascot.control such that the current user has write permissions to it.
Todo:
This adapter is using antiquated internal methods and needs to be updated! E.g. use MascotGenericFile.h instead of MascotInfile.h....


text:
info

This FAQ focuses on technical questions for users interested in developing applications for Polkadot. If you have a more general question, you may wish to search for the answer on our support Knowledge Base or the main Polkadot network FAQ. If you have a question that is not answered, please feel free to ask on the Polkadot Watercooler Element channel or contact Polkadot Support.

The Genesis block of the Polkadot network was launched on May 26, 2020 at 15:36:21 UTC, as a Proof of Authority (PoA) network, with governance controlled by the single Sudo (super-user) account. During this time, validators started joining the network and signaling their intention to participate in consensus.

The network evolved to become a Proof of Stake (PoS) network on June 18, 2020. With the chain secured by the decentralized community of validators, the Sudo module was removed on July 20, 2020, transitioning the governance of the chain into the hands of the token (DOT) holders. This is the point where Polkadot became decentralized.

The final step of the transition to full-functioning Polkadot was the enabling of transfer functionality, which occurred on Polkadot at block number 1_205_128 on August 18, 2020, at 16:39 UTC.

On August 21, 2020, Redenomination of DOT occurred. From this date, one DOT (old) equals 100 new DOT.

## Validators

### How do I apply to be a validator?

There is no central authority that decides on validators, so there is not per se an application that you can fill out. Registering as a validator is permissionless; in order to become one you must only set up a validator node and mark your intention to validate on chain. For detailed instruction on how to do this you can consult the Kusama validator guide on validating for Kusama or the Polkadot validator guide for validating on Polkadot.

However, once you've set up a validator and have registered your intention it does not mean that you will be included in the active set right away. The validators are elected to the active set based on the results of an election algorithm known as Phragmén's method. Phragmén's method tries to accomplish two goals: 1) select n members from a larger set based on stake-weighted votes and 2) equalize the stake backing each validator as much as possible.

You will likely want to campaign your validator to the community in order to get more backing. You are looking for nominators that will put up their tokens to increase the stake for your validator. For validators who cannot acquire the minimum stake from the community, Parity and Web3 Foundation also run a joint program called Thousand Validators that will nominate validators if they apply and fit the requirements.

### How are validators rewarded?

Validators are rewarded from the inflation of the Relay Chain, transaction fees, and tips. However, they only take a percentage of the former two. More details can be read on the page for validator payouts.

### What is the minimum stake necessary to be elected as an active validator?

The minimum stake that is necessary to be elected as an active validator is dynamic and can change over time. It depends not only on how much stake is being put behind each validator, but also the size of the active set and how many validators are waiting in the pool.

There are a few ways to estimate the minimum stake.

One way can be to navigate to the Polkadot Apps Targets tab. The value at the top of the screen saying "Lowest" is the least staked validator. You need at least this much + 1 to enter the set.

You can also use some tools some to perform estimations.

• Offline Election can provide exact results of running an election on the current set of validators using the same Rust code that is ran in Polkadot.

• Validator stats script can give you an estimate that is based on the currently elected set, as well as some statistics about Kusama validators.

### Why will Polkadot have only 1000 validators while other projects have hundreds of thousands?

Polkadot's goal to have 1000 validators is set to be something that is practically achievable in the short term with high confidence of good performance in a live environment. Furthermore, validators in Polkadot are not the only stakers, and if we consider the number of stakers that can be possible on Polkadot the number can scale up to hundreds of thousands. Since validators are performing critical consensus work to maintain the security of the chain including all of its shards, a more modest number of validators is estimated to start. Upon later improvements, such as implementing signature aggregation for finalization messages, the number of validators could reasonably scale up. However, increasing validators above one thousand remains a goal for later iterations of Polkadot.

It is also worth mentioning that one thousand validators is more than the number of validators of similar PoS chains with comparable levels of economic security as Polkadot. The closest contenders are operating with around 150 validators, while Polkadot is already securely running with validators.

Additionally, other projects sometimes have a different definition of validator that approximates more closely to remote signing keys without the full operation of a validating node. On Polkadot, each validator is running their own validating node and performing full verification of the Relay Chain, voting on finality, producing blocks in their decided slots, and verifying parachain state transitions. Other projects may consider validators and "validating nodes" as separate entities.

Finally, individuals may participate in the block production process indirectly by nominating validators. In this way, individuals who are not running a node can still share in staking rewards.

## Relay Chain

### What is the block time of the Relay Chain?

Both the Kusama and Polkadot networks are currently operating at a rate of one block every six seconds.

This may be changed in the future. It may go as low as two to three seconds after optimizations, or potentially increase in order to handle the capacity of the parachain networking in a live environment.

### Does Polkadot have smart contracts?

No - and yes. The Polkadot Relay Chain does not implement smart contracts natively. The reason for not having smart contracts on the Relay Chain is part of the design philosophy for Polkadot that dictates that the Relay Chain should be the minimal logic required to accomplish its job.

However, Polkadot will be a platform for other chains that do implement smart contracts. It's possible for parachains to enable smart contract functionality and then benefit from the security and interoperability features of Polkadot. Additionally, existing smart contract chains can connect to Polkadot as a parachain, or via a bridge.

While the Polkadot Relay Chain does not implement smart contracts directly, undoubtedly there will be parachains that do. So it's better to say that the Polkadot ecosystem has smart contracts versus "Polkadot has smart contracts."

### How will the Polkadot Relay Chain connect to external chains in the ecosystem?

One of the cornerstone interoperability technologies being researched and developed for deployment on Polkadot is cross-chain bridges. Bridges come in a variety of flavors with varying levels of trust associated with them. Polkadot is predominantly researching the trust-minimized flavor that imposes economic costs on the operators of the bridge, and therefore makes it economically secure. Bridge efforts are being worked on in concert with other projects in the ecosystem. Eventually, there will be bridges between Polkadot and most of the other major chains.

## DOT

### What is the difference between DOT (old) and new DOT?

The DOT (old) unit on Polkadot was at twelve decimal places, otherwise known as 1e12 Plancks. On 21 August, 2020, Denomination Day, the DOT (old) value was redenominated to 1e10 (10_000_000_000, or ten billion) Plancks, meaning that the new DOT was valued at ten decimal places. Following the redenomination, the new DOT is called DOT.

### What is the inflation rate of the DOT?

The inflation rate is approximately 10% per year.

A portion of the inflation is rewarded to validators for performing their duties, while another portion may go directly to the treasury. The exact percentage that goes into both varies and is based on the amount of DOT that are staked. Please see the article on inflation for more information.

### Why can't crowdloaned DOT be staked?

DOTs contributed to a sucessful crowdloan campaign by a parachain are bonded for the entire lease period, which is two years on Polkadot. The crowdloaned DOT cannot be used for any other DOT utility functionalities like staking and democracy. In exchange to the lost staking rewards or liquidity of DOTs, the parachain team may offer rewards to the contributor.

The utility of crowdloaned DOT is to provide a lease for a parachain. The utility of staked DOT is to secure the network through a reward/slash mechanism. Allowing crowdloaned DOT to be staked results in complex consequences like applying a slash on crowdloaned DOT that was meant to be bonded for the entire lease period of a parachain. In a way, the inaccessibility of crowdloaned DOTs and the lack of staking rewards for the entire lease duration encourages the contributors to back projects that are valuable to the ecosystem.

## Governance

### What prevents Polkadot governance from failing?

Polkadot's governance has already been shown to work. Examples can be found in the runtime upgrades that have successfully taken place through on the testnets as well as in a real economic environment on Kusama and Polkadot itself.

It is fair to say that the field of on-chain blockchain governance is still new, and no one can claim to know exactly what the optimal version of on-chain governance is yet. However, Polkadot takes a brave step forward in pioneering thought-through mechanisms for evolving a blockchain.

Blockchains need a method to adapt and evolve. Therefore, an on-chain governance system was necessary for the long-term success of Polkadot. Ultimately, it is the token holders that are responsible for preventing Polkadot's governance from failing by using their economic value and conviction to sway the progression of the protocol.

### What prevents Polkadot governance from becoming plutocratic?

A savvy reader might have noticed that the answer to the previous question endowed the token holder with the ultimate responsibility to ensure that Polkadot's governance does not fail. By following the train of this assertion, one might assume that Polkadot's governance is susceptible to becoming ruled by a few large token holders (called whales in trading parlance) and therefore become a mere plutocracy (rule of the rich).

There are several other mechanisms that are built-in to the governance system to resist this plutocratic tendency. One of these mechanisms is called conviction voting, and imbues greater voting power to token holders who are willing to lock their tokens on the protocol for longer lengths of time. Longer lock-ups display conviction in a vote. Conviction voting could allow a highly determined minority to overrule the vote of an apathetic majority in certain situations. Another mechanism is known as Adaptive Quorum Biasing. This makes proposals have a varying threshold for approval or rejection based on what part of the governance protocol the proposal originated in. For details on the subtleties of Polkadot's governance system, please see the governance page.

## Parachains

### How do parachain economics work?

Parachains have the flexibility to implement their own monetary system or incentive structure for collators. However, this is not strictly necessary. Since the collator's job is to continue to give recent state transitions to the validators on the Relay Chain who validate each transition, the security of the parachain and the Polkadot network is completely separate from parachain economics. Parachains need collators to continue to progress, so it wouldn't be unreasonable to see them incentivize collator nodes in some way, but the specific mechanism is completely up to parachain implementers.

### Are parachains ephemeral? What happens when a parachain loses the next auction?

Parachains are not ephemeral. As long as someone is keeping the data for a parachain, the parachain can move between being a parachain, a parathread, or a separate sovereign chain at different points of its lifetime. Especially with parathreads, parachains can be decommissioned to only produce blocks when their usage and throughput makes it necessary.

When a parachain loses an auction for renewal, that parachain has a few options. In most cases, becoming a parathread instead would be a suitable choice. Parathreads are still secured by the Relay Chain, but don't need to hold a parachain slot and can produce a block when its economically feasible for them. For more on parachains please see the parachains page and for more on parathreads see the parathreads page.

## Networking

### What is libp2p?

Libp2p is a modular and extensible networking stack that is used by IPFS, Substrate, and many other projects. It is a collection of peer-to-peer protocols for finding peers and connecting to them. Its modules have logic for content routing, peer routing, peer discovery, different transports, and NAT traversals. It is intended to be used by applications for building large scale peer-to-peer networks by only selecting the parts of the protocol suite that are needed.

The Rust implementation of the specification was built and primarily maintained by a team of contributors at Parity Technologies. The Go and JavaScript versions are maintained by Protocol Labs as well as community contributors. A Nim version of the library also exists. Libp2p as a whole is an open source project that is actively developed and expanded on various code repositories hosted on their GitHub.

Yes, since Polkadot is built with Substrate. Substrate uses a networking protocol that is based on libp2p (specifically the Rust libp2p library). However, Substrate uses a mix of standard libp2p protocols and protocols that are homegrown and not official libp2p standards. Of the standards protocols, those which are shared with other implementations of libp2p such as IPFS, are connection-checking (ping), asking for information on a peer (identity), and Kademlia random walks (kad).

Of the protocols that are custom to Substrate, there are the legacy Substrate stream, a request-response for getting information on blocks (sync), a light client protocol, a notification protocol for transactions, and block announcement. For detailed information on how Substrate uses libp2p and the standard and custom protocols, please see the networking documentation.

### How does libp2p differ from IPFS?

The Interplanetary File System (IPFS) is a peer-to-peer hypermedia protocol used primarily for storage of files. It allows one to upload a file onto the network and share it with its content addressable URI. IPFS, like Substrate, is an application of libp2p and exists higher on the technology stack. Although both IPFS and Substrate use libp2p, it cannot be said that Substrate "uses" IPFS since besides sharing the underlying library for networking there is no native integration between the two applications.

## Kusama

### What is the minimum amount of KSM / DOT I can have in my account?

base_fee + (tx_length * length_fee) + WeightToFee(weight)

format: plain


text:
# Computer currency

ISSN: 0736-3761

Article publication date: 27 June 2008

## Citation

(2008), "Computer currency", Journal of Consumer Marketing, Vol. 25 No. 4. https://doi.org/10.1108/jcm.2008.07725dab.001

## Publisher

:

Emerald Group Publishing Limited

## Computer currency

Article Type: Computer currency From: Journal of Consumer Marketing, Volume 25, Issue 4

Edited by Dennis A. PittaUniversity of Baltimore

In this issue we are privileged to have a review of a mature update of one of the premier pieces of statistical programs, Systat 12.0.

Systat 12.0

Several years ago, statistical applications were limited for the use of the specialists; now with greater availability of graphical software within easy reach of the computer user, it is becoming easier and easier to use statistics. Systat 12 brings us a step closer to using basic as well as advanced statistical tests. Considering various statistical tests that a survey researcher is likely to use, Systat is amongst the major software programs such as SPSS or SAS.

Installation

The program comes in a single CD. The installation is quick and without any problems. The CD offers an option to read the installation instructions. For those needing installation instructions or an overview of the process prior to installation, it is a good idea to click on this icon. I started directly by clicking the “install Systat 12” icon and chose various options as they became available.

Program overview

Once you start the program, it opens up three major windowpanes. The top ribbon shows various menu items like any other windows program. To the left is a vertical pane called workspace. This shows the major headings of output sections. The major portion of the screen shows data window, graph window or the output window, depending on the usage and or selection by the user. The third pane or the lower section is for running interactive commands or viewing the log of executed commands. For those familiar with any other statistical program, the interface is very intuitive. For those not familiar with such programs, I found the tutorial under help menu to be extremely useful.

The interactive options in commandspace work very well. As the user becomes more familiar with the program and the interactive commands, one can use the commandspace just as or more effectively than the graphical interface. For example, just typing CORR (abbreviation for correlations), followed by PEARSON prints out the correlations of all variables. Typing help in commandspace brings out the help window.

Default view

The default view of Systat shows three main windows: the data window (appearance of a spread sheet), the work window (shows major headings of output), and syntax or command window. The data window has further views - data or variable view, whereas the command Window has three views - interactive, log and untitled.

Customization

There are several useful customization features. One of them is the “theme.” The theme is not just for selecting a color scheme; it changes the items in the main ribbon or the menu items. For example, the default menu items are: file, edit, view, data, utilities, graph, analyze, advanced, quick access, addons, window, and help. Each of these menu items has several action items. This default theme can be changed under the menu of utilities, and then themes. The theme changes the menu items. For example, in introductory statistics theme the main ribbon menu items are: file, edit, view, output, data, distributions, and relationships.

Data editor

The data editor window has the familiar look of a spreadsheet. It is similar to Excel with the added feature of “variable view” window which is similar to SPSS. Here one can assign, and edit the variable labels, variable type (string, numeric) and value labels. The full variable label is visible by placing the cursor over the variable name. It is possible to open more than one data file. One user-friendly feature is that the background color of data screen is different for each data file. As a footnote comment, if you click on Systat program through the start, program button in windows while one program is running, it opens another Systat program instead of indicating something like, “the program is already running,” which can be a beneficial feature depending on user’s perspective.

The file, open, data command can open (import) files in different formats such as Excel, SAS, SPSS, Minitab, Statview, Stata, Statistica, and many more. The merge function is very easy to use. Data files can be merged to aggregate data by adding cases or variables. In order for merge function (adding cases) to succeed the two files must be similar in terms of number of variables, name, type (string or numeric), and order of variables.

Utilities

Probability calculator

One of the basic concepts in statistics is the probability density function and the area under the curve. Although basic, it is not easy to communicate or explain to students. The graphical interface of statistical programs makes it easy to calculate the coefficients, the corresponding test ratios such as t-ratios or chi-square and the resulting significance. Students learn simple rules such as p<0.05 is significant, but often they fail to grasp the underpinnings.

The probability calculator helps to overcome this limitation. Under utilities menu, click on the probability calculator, select the appropriate distribution, and specify the values and it calculates the p-value. More than that it also shows the graph of density function (and cumulative density function), so students can see the meaning behind the p-value.

Random sampling

Random sampling can be used to generate a number of samples of given sample sizes of various distributions. I tested the option by generating 20 random samples of size (n) 20 with a mean of zero and standard deviation of one. I then used the graph function to generate one histogram showing overlays of all 20 samples. This can be a useful device to show students the idea of random sampling in survey research and to convey the point of statistical significance and confidence intervals.

Graphics

Systat has several widely used graphical functions such as histogram, scatter plot, density functions, line chart, bar chart. The convenient feature is the ability to change or modify the graph through the interactivity feature. For example, one can start with a scatter plot and then fit various lines of best fit including showing residuals and confidence intervals. In managerial applications of survey research the analyst may want to show the mean values of a variable plotted against time (X axis) or another independent variable. This can be done easily and the graph can be “cut and pasted” into another document. Most of the programs I could execute without reading the manual. However, for some graphical applications and data manipulations I found that reading the manual was very helpful.

Analyze

In addition to the commonly used statistical tests such as descriptive statistics, regression, correlation, discriminant, cluster, factor analyses, etc., the analyze command also includes time series analyses. Furthermore the time series includes several types of time series analyses, e.g. autocorrelation, partial auto correlation, cross correlation, trend analyses, Fourier series, ARIMA, etc. The analyze command also contains several non-parametric tests such as Friedman, Kruskal-Wallis, Wilcox, Sign and many more. It is one of the more complete statistical set of options.

The advanced statistics menu option includes more specialized programs. Amongst these are: perceptual mapping software such as perceptual mapping and multi dimensional scaling, and special statistics. Other programs are conjoint, structural equation modeling (Ramona), test item analyses, response surface analyses, survival analyses, trees (multiple classification analyses), and missing value analyses. Several of the items mentioned under the advanced statistics can be found as self-standing software from competing software suppliers. For example, various Conjoint programs are available from Sawtooth Software (www.sawtoothsoftware.com) amongst others, missing value analyses (stand alone from SPSS.com), path analyses (Lisrel from Scientific Software), and so on. Thus, all in all, Systat provides a comprehensive set of tools.

Unique features

The software has all (in my usage) statistical programs and also some additional unique features. One of these was the probability calculator (mentioned earlier). Some others less commonly included programs are under the regression option. A couple of these are partial least squares (PLS) and ridge regression. PLS is a specialized option that is often a stand-alone program instead of one you can find in software packages. Ridge regression is a very useful procedure when using linear regression under moderate to high multicollinearity. I have used SPSS ridge regression often. In SPSS[1], it is an additional script not part of the graphical menu interface that needs to be used to estimate ridge trace and ridge coefficients. In contrast, the ridge option in Systat is seamless and works like any other graphical interface option.

My experience in using Systat

I use the analysis of variance often, so I tried the application. It just took a few clicks to specify the dependent and independent variables. There were other options but I stayed with the default options. The output shows the variables in the file, variable codes (independent variables), the multiple R-value, estimates of effects (B coefficients), The ANOVA table, cell means, and overall mean values for various levels of variables. The output also includes applicable graphs showing overall means and cell means, and Durban Watson statistic to check for Auto correlation. One feature I liked about the graph was that they show the error bars (plus or minus 2 standard errors) so one can visualize the significant differences in mean values. At this stage of estimation, the program does not automatically generate post hoc tests. These have to be performed as a separate test after the initial estimation. It just takes a few extra clicks; it is not necessary to re-estimate the model.

In marketing research one often needs to compute the reliability of the scale. The advanced (statistics) menu shows the test item analysis command that has two options for computing the scale reliability: odd-even or split half. The Chronbach’s alpha was not obvious from the menu. I had to look up under help and search. The command was under analyze, correlations, Chronbach’s alpha. It worked fine, and gave me the alpha coefficient. Unlike SPSS, it does not have the option of providing additional statistics such as correlation matrix, and alpha if item deleted. But these coefficients can be obtained by clicking the mouse a few times.

I found the power of the test to be a useful and easy feature to use. In hypothesis testing one discusses the type I and type II errors. Most studies mention type I error or alpha and skip discussing beta (type II error), or power of the test (1-Beta). I found it easy to calculate the sample size needed for a given power or alternatively to calculate the power curve for various sample sizes.

I tried both hierarchical cluster analysis and K-means (there is also a K-median) cluster analysis. Both gave me the output that was quick, simple, and meaningful. I also tried various graphics programs. These were also easy to use and gave the desired results. In survey research the recode command is a must to reverse code the scale values. Systat offers a transform command under data menu and can handle most types of recoding or transformations. I tried some recoding of variables and also created a new variable with “let” command. It worked smoothly.

Help section

The help section is useful and worth running on line. The help menu has separate categories for help on Monte Carlo, quality analysis. The quality analysis is an add-on program that provides quality control and analysis tools like gauge R&R studies, sigma measurements, Taguchi’s loss function, and Taguchi’s online control with the beta correction technique. These features provide additional analyses beyond traditional quality control charts and graphics tool base module of Systat.

One feature I found particularly helpful which would be appreciated by new users especially is the tutorial. It shows use of the program in a video format with actual examples. The video shows the mouse arrow clicking key menu items and the corresponding result of these executions.

When you install the program, it offers the option to install all manuals in PDF form. These manuals can be accessed through the Windows program directory. Although the help items, the tutorials and the manuals are all very good, those familiar with other statistical programs should not have any difficulty in using Systat. I am very familiar with the SPSS and other Windows program interfaces and found that transferring from one program to the other was without any incidence

Technical support or contact Systat

Technical support is available through help under main menu, Systat web site (www.systat.com). There is discussion forum also. In addition, Systat support representatives can be reached via e-mail or telephone. I called the technical support twice. Both the times, the phone was answered quickly. In one case, the tech support gave an answer instantly and in the other case, the support person did some research and got back to me via email on the same day. I was very pleased with the help.

Available from: Systat Software, Inc., 1735, Technology Drive, Ste 430, San Jose, CA 95110, USA. Web site: www.systat.com; Sales: 800-797-7401; Fax: 800-797-7406; E-mail: info-usa@systat.com Support: techsupport@systat.com

Price

Considering the number of statistical tests, both the $1,299 commercial price, and the$999 price for a single user government or academic license are reasonable.

Conclusion

Overall, I like the software. It is easy to use and has all the functionality I need. It also has some unique features not readily found in other packages and is very reasonably priced. I am considering using it for my classes. If I were to buy statistical software, Systat would be on top of my list. Considering the number of different tests it can perform, and the price, it is a great product.

This review is not meant to be a systematic comparison of SPSS and Systat, rather a few anecdotal comments based on my usage of these programs. Of course, each software has its own unique strengths and shortcomings.


text:
# 91. Use the information in the adjusted trial balance for Stockton Company to answer the...

91. Use the information in the adjusted trial balance for Stockton Company to answer the questions that follow.

Stockton Company

For the Year Ended December 31, 20XX

Cash$6,030 Accounts Receivable2,100 Prepaid Expenses700 Equipment13,700 Accumulated Depreciation$  1,100

Accounts Payable1,900

Notes Payable4,200

Capital Stock2,000

Retained Earnings10,940

Dividends790

Fees Earned8,750

Wages Expense2,500

Rent Expense1,960

Utilities Expense775

Depreciation Expense250

Miscellaneous Expense85

Totals$28,890$28,890

Determine the total liabilities for the period.
A. $1,900 B.$6,100
C. $4,200 D.$19,040

92. The balance sheet should be prepared
A. before the income statement and the retained earnings statement
B. before the income statement and after the retained earnings statement
C. after the income statement and the retained earnings statement
D. after the income statement and before the retained earnings statement

93. The retained earnings statement begins with the beginning balance followed by
A. net income (loss) and dividends
B. net income (loss) and issuances of capital stock
C. issuances of capital stock and dividends
D. issuances of capital stock, net income (loss), and dividends

94. The income statement will include
A. revenues less expenses (ordered largest  to smallest amount) with miscellaneous expense listed last
B. revenues less expenses (ordered smallest to largest amounts) with miscellaneous expense listed last
C. revenues less expenses (ordered in alphabetical order)
D. revenues less expenses (order is not important)

95. The classified balance sheet will subsection the assets as follows
A. Current Assets and Other Assets
B. Current Assets and Property, Plant, and Equipment
C. Current Assets and Long-Term Assets
D. Other Assets and Property, Plant, and Equipment

96. The classified balance sheet will have liabilities divided into the following subsections
A. Current Liabilities and Long-Term Liabilities
B. Current Liabilities and Other Liabilities
C. Other Liabilities and Long-Term Liabilities
D. Present Liabilities and Tomorrow’s Liabilities

97. Current liabilities are those liabilities that
A. will be paid in less than one year
B. are due to be paid in 5 to 10 years
C. are due to be paid in more than one year
D. are owed to the stockholders and will never be paid

98. On the balance sheet, stockholders’ equity is
A. added to assets and the two are equal to liabilities
B. added to liabilities and the two are equal to assets
C. subtracted from liabilities and the net amount is equal to assets
D. subtracted from assets and the net amount is equal to net income

99. Balance sheet accounts
A. represent amounts accumulated during a specific period of time
B. are called real accounts
C. have zero balances after the closing entries have been posted
D. are equal to assets and liabilities

100. On which financial statement will Income Summary be shown?
A. retained earnings statement
B. balance sheet
C. income statement
D. none of these


text:
is_formula() tests whether x is a call to ~. is_bare_formula() tests in addition that x does not inherit from anything else than "formula".

Note: When we first implemented is_formula(), we thought it best to treat unevaluated formulas as formulas by default (see section below). Now we think this default introduces too many edge cases in normal code. We recommend always supplying scoped = TRUE. Unevaluated formulas can be handled via a is_call(x, "~") branch.

is_formula(x, scoped = NULL, lhs = NULL)

is_bare_formula(x, scoped = TRUE, lhs = NULL)

## Arguments

x An object to test. A boolean indicating whether the quosure is scoped, that is, has a valid environment attribute and inherits from "formula". If NULL, the scope is not inspected. A boolean indicating whether the formula has a left-hand side. If NULL, the LHS is not inspected and is_formula() returns TRUE for both one- and two-sided formulas.

## Dealing with unevaluated formulas

At parse time, a formula is a simple call to ~ and it does not have a class or an environment. Once evaluated, the ~ call becomes a properly structured formula. Unevaluated formulas arise by quotation, e.g. ~~foo, quote(~foo), or substitute(arg) with arg being supplied a formula. Use the scoped argument to check whether the formula carries an environment.

## Examples

is_formula(~10)
#> [1] TRUEis_formula(10)
#> [1] FALSE
# If you don't supply lhs, both one-sided and two-sided formulas
# will return TRUE
is_formula(disp ~ am)
#> [1] TRUEis_formula(~am)
#> [1] TRUE
# You can also specify whether you expect a LHS:
is_formula(disp ~ am, lhs = TRUE)
#> [1] TRUEis_formula(disp ~ am, lhs = FALSE)
#> [1] FALSEis_formula(~am, lhs = TRUE)
#> [1] FALSEis_formula(~am, lhs = FALSE)
#> [1] TRUE
# Handling of unevaluated formulas is a bit tricky. These formulas
# are special because they don't inherit from "formula" and they
# don't carry an environment (they are not scoped):
f <- quote(~foo)
f_env(f)
#> NULL
# By default unevaluated formulas are treated as formulas
is_formula(f)
#> [1] TRUE
# Supply scoped = TRUE to ensure you have an evaluated formula
is_formula(f, scoped = TRUE)
#> [1] FALSE
# By default unevaluated formulas not treated as bare formulas
is_bare_formula(f)
#> [1] FALSE
# If you supply scoped = TRUE, they will be considered bare
# formulas even though they don't inherit from "formula"
is_bare_formula(f, scoped = TRUE)
#> [1] FALSE


text:
259 views

The virtual memory system uses the demand paging for its implementation. The probability of getting page faults is $0.25$, the normal memory access time is $200$ nanoseconds. If it takes $2$ millseconds to service a page fault, then what is effective memory access time?

1. $500000$ ns
2. $500075$ ns
3. $500150$ ns
4. $500250$ ns

E.M.A.T. = (1 - p) * ma + p * page fault service time     ,   where p = page fault rate
EMAT = [ 0.75 * 200  + 0.25 * 2000000 ]ns =  500150 n.s
by

yes,  we consider memory access time .

in this formula Effective Memory Access Time

= (1 - p) * ma + p * page fault service time

we use memory access time as ma .

Sir,

We should use hierarchical  approach

as page fault service time to move page from disk to memory and update page table,

after that again memory reference takes place.

For those who are confused about which formula to use.

https://gateoverflow.in/41917/confusion-in-effective-memory-access

1 vote


text:
## Sunday, 18 March 2012

### Centripetal Force

Centripetal force is a force that makes a body follow a curved path: it is always directed orthogonal to the velocity of the body, toward the instantaneous center of curvature of the path.

In simple terms, centripetal force is defined as a force which keeps a body moving with a uniform speed along a circular path and is directed along the radius towards the centre. The mathematical description was derived in 1659 by Dutch physicist Christiaan Huygens. Isaac Newton's description was: "A centripetal force is that by which bodies are drawn or impelled, or in any way tend, towards a point as to a centre."

The magnitude of the centripetal force on an object of mass m moving at a speed v along a path with radius of curvature r is:

$F = ma_c = \frac{m v^2}{r}$
where $a_c$ is the centripetal acceleration. The direction of the force is toward the center of the circle in which the object is moving, or the osculating circle, the circle that best fits the local path of the object, if the path is not circular. This force is also sometimes written in terms of the angular velocity ω of the object about the center of the circle:
$F = m r \omega^2 \,$
Expressed using the period for one revolution of the circle, T, the equation becomes:
$F = m \frac{4\pi^2r}{T^2}.$

Mass performing vertical circular motion under gravity
Consider a mass m performing circular motion under gravity, the circle with radius r .
The centripetal force on the mass varies at different positions on the circle.

Conical pendulum
Problems concerning the conical pendulum assume no air resistance and that the string has no mass and cannot be stretched.
Solution of problems involves resolving forces on the mass vertically and horizontally. In this way the speed of the mass, the tension in the string and the period of revolution can be ascertained.


text:
# zbMATH — the first resource for mathematics

##### Examples
 Geometry Search for the term Geometry in any field. Queries are case-independent. Funct* Wildcard queries are specified by * (e.g. functions, functorial, etc.). Otherwise the search is exact. "Topological group" Phrases (multi-words) should be set in "straight quotation marks". au: Bourbaki & ti: Algebra Search for author and title. The and-operator & is default and can be omitted. Chebyshev | Tschebyscheff The or-operator | allows to search for Chebyshev or Tschebyscheff. "Quasi* map*" py: 1989 The resulting documents have publication year 1989. so: Eur* J* Mat* Soc* cc: 14 Search for publications in a particular source with a Mathematics Subject Classification code (cc) in 14. "Partial diff* eq*" ! elliptic The not-operator ! eliminates all results containing the word elliptic. dt: b & au: Hilbert The document type is set to books; alternatively: j for journal articles, a for book articles. py: 2000-2015 cc: (94A | 11T) Number ranges are accepted. Terms can be grouped within (parentheses). la: chinese Find documents in a given language. ISO 639-1 language codes can also be used.

##### Operators
 a & b logic and a | b logic or !ab logic not abc* right wildcard "ab c" phrase (ab c) parentheses
##### Fields
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Approximately multiplicative maps between Banach algebras. (English) Zbl 0652.46031
A pair ($𝒜,ℬ\right)$ of Banach algebras is said to have the property AMNM (almost multiplicative maps are near multiplicative maps), if on bounded subsets of L($𝒜,ℬ\right)$ (the Banach space of bounded linear operators from $𝒜$ into $ℬ\right)$ for any $ϵ>0$ there exists a $\delta <0$ such that for any $T\in L\left(𝒜,ℬ\right)$ the inequality $\parallel T\left(ab\right)-T\left(a\right)T\left(b\right)\parallel \le \delta \parallel a\parallel \parallel b\parallel \left(a,b\in 𝒜\right)$ implies $\parallel T-{T}^{\text{'}}\parallel \le ϵ$ for some multiplicative map T’$\in L\left(𝒜,ℬ\right)$. This paper is devoted to the question, which pairs of Banach algebras are AMNM pairs. As a central result this property is proven, when $𝒜$ is an amenable algebra (these are studied by the author in [Cohomology in Banach algebras, Mem. Am. Math. soc. 127 (1972; Zbl 0256.18014)]) and $ℬ$ is the dual of a $ℬ$-bimodule. This leads to results for the combination of group algebras with commutative algebras. Further positive answers are obtained for the case where $ℬ$ is the algebra of all continuous functions on a compact Hausdorff space. Finally it is shown that the property AMNM holds, if $𝒜$ and $ℬ$ both equal to the algebra of all bounded linear operators on a separable Hilbert space. A corresponHeisenberg group. This class is substantially larger than in the one-dimensional case, but the additional condition of invariance under affine automorphisms distinguishes two nontrivial algebras on ${H}^{n}$ analogous to the Phragmén-Lindelöf algebra (this is due to the nontriviality of the center of the group ${H}^{n}\right)$.
Reviewer: J.B.Prolla

##### MSC:
 46H05 General theory of topological algebras 46H25 Normed modules and Banach modules, topological modules


text:
# Angular Velocity and its relation with linear velocity

Typical particle (at a point P) of the rigid body rotating about a fixed axis (taken as the z – axis). The particle describes a circle with a centre C on the axis. The radius of the circle is r, the perpendicular distance of the point P from the axis. We also show the linear Read more about Angular Velocity and its relation with linear velocity[…]


text:
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## Generalization of the ball-collision algorithm

#### Carmelo INTERLANDO [1] , Karan KHATHURIA [2] , Nicole ROHRER [3] , Joachim ROSENTHAL [4] , Violetta WEGER [5]

In this paper we generalize the ball-collision algorithm by Bernstein, Lange, Peters from the binary field to a general finite field. We also provide a complexity analysis and compare the asymptotic complexity to other generalized information set decoding algorithms.
Coding theory, ISD, Ball-collision
• [1] A. Al Jabri, A statistical decoding algorithm for general linear block codes, In IMA International Conference on Cryptography and Coding, pages 1–8, Springer, 2001.
• [2] A. Ashikhmin, A. Barg, Minimal vectors in linear codes, IEEE Trans. Inform. Theory 44(5) (1998) 2010–2017.
• [3] M. Baldi, M. Bianchi, F. Chiaraluce, J. Rosenthal, D. Schipani, Enhanced public key security for the McEliece cryptosystem, J. Cryptology 29 (2016) 1–27.
• [4] G. Banegas, P. SLM Barreto, B. Odilon Boidje, P.-L. Cayrel, G. Ndollane Dione, K. Gaj, C. Thiécoumba Gueye, R. Haeussler, J. Belo Klamti, O. N’diaye, et al. DAGS: Key encapsulation using dyadic GS codes, J. Math. Cryptol. 12(4) (2018) 221–239.
• [5] A. Barg, E. Krouk, H. C. A. van Tilborg, On the complexity of minimum distance decoding of long linear codes, IEEE Trans. Inform. Theory 45(5) (1999) 1392–1405.
• [6] A. Becker, A. Joux, A. May, A. Meurer, Decoding random binary linear codes in 2n/20: How 1+ 1= 0 improves information set decoding, In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 520–536. Springer, 2012.
• [7] E. Berlekamp, R. McEliece, H. van Tilborg, On the inherent intractability of certain coding problems (Corresp.), IEEE Trans. Inform. Theory 24(3) (1978) 384–386.
• [8] D. J. Bernstein, T. Lange, C. Peters, Smaller decoding exponents: ball-collision decoding, In Annual Cryptology Conference, pages 743–760, Springer, 2011.
• [9] J. Bolkema, H. Gluesing-Luerssen, C. A. Kelley, K. Lauter, B. Malmskog, J. Rosenthal. Variations of the McEliece Cryptosystem, In Algebraic Geometry for Coding Theory and Cryptography, pages 129–150. Springer, 2017.
• [10] A. Canteaut, F. Chabaud, A new algorithm for finding minimum-weight words in a linear code: application to McEliece’s cryptosystem and to narrow-sense BCH codes of length 511, IEEE Trans. Inform. Theory 44(1) (1998) 367–378.
• [11] A. Canteaut, N. Sendrier, Cryptanalysis of the original McEliece cryptosystem, In International Conference on the Theory and Application of Cryptology and Information Security, pages 187–199. Springer, 1998.
• [12] F. Chabaud, Asymptotic analysis of probabilistic algorithms for finding short codewords, In Eurocode’ 92, pages 175–183, Springer, 1993.
• [13] I. I. Dumer, Two decoding algorithms for linear codes, Problemy Peredachi Informatsii, 25(1) (1989) 24–32.
• [14] M. Finiasz, N. Sendrier, Security bounds for the design of code-based cryptosystems, In International Conference on the Theory and Application of Cryptology and Information Security, pages 88–105, Springer, 2009.
• [15] C. T. Gueye, J. B. Klamti, S. Hirose, Generalization of BJMM-ISD using May-Ozerov nearest neighbor algorithm over an arbitrary finite field $\mathbb{F}_q$, In Said El Hajji, Abderrahmane Nitaj, and El Mamoun Souidi, editors, Codes, Cryptology and Information Security, pages 96–109, Springer, 2017.
• [16] S. Hirose, May–Ozerov algorithm for nearest-neighbor problem over $\mathbb{F}_q$ and its application to information set decoding, In International Conference for Information Technology and Communications, pages 115–126, Springer, 2016.
• [17] N. Howgrave-Graham, A. Joux, New generic algorithms for hard knapsacks, In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 235–256. Springer, 2010.
• [18] K. Khathuria, J. Rosenthal, V. Weger, Weight Two Masking of the Reed- Solomon Structure in Conjugation with List Decoding. In Proceedings of 23rd International Symposium on Mathematical Theory of Networks and Systems, pages 309–314, Hong Kong University of Science and Technology, Hong Kong, 2018.
• [19] E. A. Kruk, Decoding complexity bound for linear block codes, Probl. Peredachi Inf. 25(3) (1989) 103–107.
• [20] P. J. Lee, E. F. Brickell, An observation on the security of McEliece’s public-key cryptosystem, In Workshop on the Theory and Application of of Cryptographic Techniques, pages 275–280, Springer, 1988.
• [21] J. S. Leon, A probabilistic algorithm for computing minimum weights of large error–correcting codes, IEEE Trans. Inform. Theory 34(5) (1988) 1354–1359.
• [22] A. May, A. Meurer, E. Thomae, Decoding random linear codes in $\mathcal{O}(2^{0.054 n})$, In International Conference on the Theory and Application of Cryptology and Information Security, pages 107–124, Springer, 2011.
• [23] A. May, I. Ozerov, On computing nearest neighbors with applications to decoding of binary linear codes, In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 203–228. Springer, 2015.
• [24] R. J. McEliece, A Public-Key Cryptosystem Based on Algebraic Coding Theory, Technical report, DSN Progress report, Jet Propulsion Laboratory, Pasadena, 1978.
• [25] A. Meurer, A coding-theoretic approach to cryptanalysis, PhD thesis, Bochum-Ruhr University, 2012.
• [26] R. Niebuhr, E. Persichetti, P.-L. Cayrel, S. Bulygin, J. Buchmann, On lower bounds for information set decoding over Fq and on the effect of partial knowledge, Int. J. Inf. Coding Theory 4(1) (2017) 47–78.
• [27] C. Peters, Information-set decoding for linear codes over Fq, In International Workshop on Post- Quantum Cryptography, pages 81–94, Springer, 2010.
• [28] E. Prange, The use of information sets in decoding cyclic codes, IRE Transactions on Information Theory 8(5) (1962) 5–9.
• [29] A. Schönhage, V. Strassen, Schnelle multiplikation großer zahlen, Computing 7(3) (1971) 281—292.
• [30] J. Stern, A new identification scheme based on syndrome decoding, In Annual International Cryptology Conference, pages 13–21, Springer, 1993.
• [31] J. van Tilburg, On the McEliece public-key cryptosystem, In Conference on the Theory and Application of Cryptography, pages 119–131, Springer, 1988.
Primary Language en Engineering Articles Orcid: 0000-0003-4928-043XAuthor: Carmelo INTERLANDO Institution: San Diego State UniversityCountry: Canada Orcid: 0000-0002-9886-2770Author: Karan KHATHURIA Institution: University of ZurichCountry: Switzerland Author: Nicole ROHRER Institution: University of ZurichCountry: Switzerland Orcid: 0000-0003-4545-3559Author: Joachim ROSENTHAL Institution: University of ZurichCountry: Switzerland Orcid: 0000-0001-9186-2885Author: Violetta WEGER Institution: University of ZurichCountry: Switzerland Publication Date : May 7, 2020
 Bibtex @research article { jacodesmath729477, journal = {Journal of Algebra Combinatorics Discrete Structures and Applications}, issn = {}, eissn = {2148-838X}, address = {}, publisher = {Yildiz Technical University}, year = {2020}, volume = {7}, pages = {195 - 207}, doi = {10.13069/jacodesmath.729477}, title = {Generalization of the ball-collision algorithm}, key = {cite}, author = {Interlando, Carmelo and Khathurıa, Karan and Rohrer, Nicole and Rosenthal, Joachim and Weger, Violetta} } APA Interlando, C , Khathurıa, K , Rohrer, N , Rosenthal, J , Weger, V . (2020). Generalization of the ball-collision algorithm . Journal of Algebra Combinatorics Discrete Structures and Applications , 7 (2) , 195-207 . DOI: 10.13069/jacodesmath.729477 MLA Interlando, C , Khathurıa, K , Rohrer, N , Rosenthal, J , Weger, V . "Generalization of the ball-collision algorithm" . Journal of Algebra Combinatorics Discrete Structures and Applications 7 (2020 ): 195-207 Chicago Interlando, C , Khathurıa, K , Rohrer, N , Rosenthal, J , Weger, V . "Generalization of the ball-collision algorithm". Journal of Algebra Combinatorics Discrete Structures and Applications 7 (2020 ): 195-207 RIS TY - JOUR T1 - Generalization of the ball-collision algorithm AU - Carmelo Interlando , Karan Khathurıa , Nicole Rohrer , Joachim Rosenthal , Violetta Weger Y1 - 2020 PY - 2020 N1 - doi: 10.13069/jacodesmath.729477 DO - 10.13069/jacodesmath.729477 T2 - Journal of Algebra Combinatorics Discrete Structures and Applications JF - Journal JO - JOR SP - 195 EP - 207 VL - 7 IS - 2 SN - -2148-838X M3 - doi: 10.13069/jacodesmath.729477 UR - https://doi.org/10.13069/jacodesmath.729477 Y2 - 2020 ER - EndNote %0 Journal of Algebra Combinatorics Discrete Structures and Applications Generalization of the ball-collision algorithm %A Carmelo Interlando , Karan Khathurıa , Nicole Rohrer , Joachim Rosenthal , Violetta Weger %T Generalization of the ball-collision algorithm %D 2020 %J Journal of Algebra Combinatorics Discrete Structures and Applications %P -2148-838X %V 7 %N 2 %R doi: 10.13069/jacodesmath.729477 %U 10.13069/jacodesmath.729477 ISNAD Interlando, Carmelo , Khathurıa, Karan , Rohrer, Nicole , Rosenthal, Joachim , Weger, Violetta . "Generalization of the ball-collision algorithm". Journal of Algebra Combinatorics Discrete Structures and Applications 7 / 2 (May 2020): 195-207 . https://doi.org/10.13069/jacodesmath.729477 AMA Interlando C , Khathurıa K , Rohrer N , Rosenthal J , Weger V . Generalization of the ball-collision algorithm. Journal of Algebra Combinatorics Discrete Structures and Applications. 2020; 7(2): 195-207. Vancouver Interlando C , Khathurıa K , Rohrer N , Rosenthal J , Weger V . Generalization of the ball-collision algorithm. Journal of Algebra Combinatorics Discrete Structures and Applications. 2020; 7(2): 195-207.

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#has-images

### Logarithm and exponential [ edit ]

Let be the multiplicative group of positive real numbers, and let be the additive group of real numbers.

The logarithm function satisfies for all , so it is a group homomorphism. The exponential function satisfies for all , so it too is a homomorphism.

The identities and show that and are inverses of each other. Since is a homomorphism that has an inverse that is also a homomorphism, is an isomorphism of groups.

Because is an isomorphism, it translates multiplication of positive real numbers into addition of real numbers. This facility makes it possible to multiply real numbers using a ruler and a table of logarithms, or using a slide rule with a logarithmic scale.

If you want to change selection, open document below and click on "Move attachment"

Isomorphism - Wikipedia, the free encyclopedia
and exponential 1.2 Integers modulo 6 1.3 Relation-preserving isomorphism 2 Isomorphism vs. bijective morphism 3 Applications 4 Relation with equality 5 See also 6 Notes 7 References 8 Further reading 9 External links Examples <span>Logarithm and exponential Let be the multiplicative group of positive real numbers, and let be the additive group of real numbers. The logarithm function satisfies for all , so it is a group homomorphism. The exponential function satisfies for all , so it too is a homomorphism. The identities and show that and are inverses of each other. Since is a homomorphism that has an inverse that is also a homomorphism, is an isomorphism of groups. Because is an isomorphism, it translates multiplication of positive real numbers into addition of real numbers. This facility makes it possible to multiply real numbers using a ruler and a table of logarithms, or using a slide rule with a logarithmic scale. Integers modulo 6 Consider the group , the integers from 0 to 5 with addition modulo 6. Also consider the group , the ordered pairs where the x coordinates can be 0 or 1, and the


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# Math Help - kinematics

1. ## kinematics

a car comes to a stop from a speed of 30m/s in a distance of 804m. the driver brakes so as to produce a deceleration of 1/2 m/s/s to begin with, then brakes harder to produce a deceleration of 3/2 m/s/s. Find the speed of the car at the instant the decelaration is increased, and the total time it takes for the car to stop.

i've toiled over this for a whole day. im sure there's something im missing! i dont understand how i can get v without t! so i drew up a graph and tried to combine all these equations but there are just too many unknowns for me! can someone help me solve this step by step?

2. Hello furor celtica
Originally Posted by furor celtica
a car comes to a stop from a speed of 30m/s in a distance of 804m. the driver brakes so as to produce a deceleration of 1/2 m/s/s to begin with, then brakes harder to produce a deceleration of 3/2 m/s/s. Find the speed of the car at the instant the decelaration is increased, and the total time it takes for the car to stop.

i've toiled over this for a whole day. im sure there's something im missing! i dont understand how i can get v without t! so i drew up a graph and tried to combine all these equations but there are just too many unknowns for me! can someone help me solve this step by step?
Suppose that the speed of the car when the deceleration changes is $v$, and that the distance travelled at this point is $s$. Then using:
$v^2=u^2+2as$
we get, for the first part of the motion:
$v^2 = 30^2-s$ (1)
and for the second part
$0=v^2-3(804-s)$
$=900-s -2412+3s$, from (1)
$\Rightarrow 2s = 1512$

$\Rightarrow s = 756$

$\Rightarrow v^2=900-756$

$\Rightarrow v = 12$
So the speed when the deceleration changes is $12$ m/s, and it takes $(30-12)\div\frac12=36$ seconds for the first part and $12\div\frac32=8$ seconds for the second part; total $44$ secs.


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# Monthly Archives: November 2011

## Help: stemming and stem completion with package tm in R

November 3, 2011
By

I came across a problem below when doing stemming and stem completion with package tm in R. Word “mining” was stemmed to “mine” with stemDocument(), and then completed to “miners”with stemCompletion(). However, I prefer to keep “mining” intact. For stemCompletion(), … Continue reading

## Webinar on Portfolio Rebalancing with R and Sybase

November 3, 2011
By

R users in the financial industry may be interested in the following webinar hosted by Revolution Analytics' partner Sybase on November 10: Portfolio Rebalancing Using R and Sybase RAP for Intraday Risk Management With volatility and violent intraday swings becoming the new normal, intraday risk controls are now needed to not only reduce your exposures across multiple asset classes,...

## Modern Portfolio Optimization Theory: The idea

November 3, 2011
By

We were recently given a lecture (by Dr. Susan Thomas) on Harry Markowitz portfolio optimization theory, and I was really fascinating with the noble laureate's story of how he found it difficult to convince his guide about the importance of h...

## Variability of volatility estimates from daily returns

November 3, 2011
By

Investment Performance Guy has a post “Periodicity of risk statistcs (and other measures)” in which it is wondered how valid volatility estimates are from a month of daily returns. Here is a quick look.  Figure 1 shows the variability (and a 95% confidence interval) of volatility estimates for the S&P 500 index in January 2011.  … Continue reading...

## Maximizing Omega Ratio

November 3, 2011
By
$Maximizing Omega Ratio$

The Omega Ratio was introduced by Keating and Shadwick in 2002. It measures the ratio of average portfolio wins over average portfolio losses for a given target return L. Let x.i, i= 1,…,n be weights of instruments in the portfolio. We suppose that j= 1,…,T scenarios of returns with equal probabilities are available. I will

## Some Simple but Propably Useful Regex Examples with R-Package stringr…

November 3, 2011
By

I found that examples for the use of regex in R are rather rare. Thus, I will provide some examples from my own learning materials - mostly stolen from the help pages, with small but maybe illustrative adaptions.ps: I will extent this list of examples...

## First thoughts on R

November 2, 2011
By

Having worked just a little with R, I have some first impressions to share.  I'll give you some links to resources I found helpful with writing the previous project.

First, the documentation is not very good.  I struggled on previous attempts to figure things out.  I still find it crap shoot when I Google, looking for an answer....

## Code Optimization: One R Problem, Ten Solutions – Now Eleven!

November 2, 2011
By

Earlier this year I came across a rather interesting page about optimisation in R from rwiki. The goal was to find the most efficient code to produce strings which follow the pattern below given a single integer input n: From this we can see that the general pattern for n is: It is rather heart

November 2, 2011
By

If you are creating maps then for goodness sake Use sensible colours!  I was helping some undergraduates with some work the other day, and they decided to use the following colour scheme for representing river depth: Deep water: Red Medium-depth water: Bright green Shallow water: Pink Why did they do this? Well, either they were


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# Tag Info

## Hot answers tagged statistical-mechanics

5

A quick google search leads one immediately to the wikipedia page on this particular theorem. The first paragraph of this page states: The Bohr–van Leeuwen theorem is a theorem in the field of statistical mechanics. The theorem states that when statistical mechanics and classical mechanics are applied consistently, the thermal average of the ...

5

No. You wouldn't say that pair of beams has a temperature. Temperature is defined by the zeroth law of thermodynamics, which states that if $A$ is in thermal equilibrium with $B$ and $B$ is in thermal equilibrium with $C$ then $A$ is in thermal equilibrium with $C$ and $A$, $B$ and $C$ are said to have the same temperature. Temperature is fundamentally a ...

4

It's the differential relationship between internal energy and entropy: \begin{align} dU &= T\,dS + \cdots \\ \frac{\partial S}{\partial U} &= \frac 1T \end{align} As energy is added to a system, its internal entropy changes. Remember that the (total) entropy is $$S = k \ln\Omega,$$ where $\Omega$ is the number of available microscopic states that ...

3

I will give you the argument that is presented in the book I learned from, Physical Gas Dynamics. For reference, it's page 104, Chapter 4 section 6. I present it instead because it does not rely on the Boltzmann distribution for the derivation so perhaps there is some additional insight for you. They established in section 5 that: $$\frac{N_j^*}{C_j} = ... 3 What is entropy, more than disorder. Mathematically, entropy is just a measure of spread of a probability distribution: The lower the entropy, the more spiked the distribution. In statistical mechanics, a state is generally only partially defined via some macroscopic constraints, and entropy is a measure of microscopic indeterminacy. Maximizing entropy ... 3 I believe it was Boltzmann who first made the connection between entropy and micro states. chapter 12 of "Classical and Statistical Thermodynamics" by Ashley H. Carter discusses Boltzmann's arguments. To summarize from that book: Entropy (S) corresponds to a particular configuration of an ensemble of particles called a macro state. A macro state can be ... 3 Hints: Define difference \delta:=\Delta-\Delta_0. Deduce from |\delta|\ll |\Delta_0| that the lhs. of eq. (1) is$$\tag{A}\text{lhs}~\approx~ -\frac{\delta}{\Delta_0}.$$Substitute \xi=x\Delta  in the integral on the rhs. of eq. (1). Deduce using \hbar \omega_D \gg \Delta that the rhs. is$$\tag{B} \text{rhs}~\approx~ \int_{\mathbb{R}} \! ...

3

Let us decompose the formula to better understand what it means: $\hbar \mathbf k/m$ is the velocity of the electrons $\epsilon_k - \mu$ is the energy relative to the temperature, so if particles with higher energy than the temperature move in a direction, they produce a positive thermal energy flux, particles with lower energy an negative flux. ...

3

We have a perfectly unambiguous definition of temperature for canonical ensembles, and this temperature may be negative in bounded-energy systems. This kind of negative temperature is indisputable, and some would argue it has been realized in spin-inversion experiments. The problem is that there are two decent but imperfect definitions for the entropy of a ...

3

What I am asking, then, is whether someone on StackExchange might be able to shed some light on the matter as to how there can be a disagreement about something that seems should be a mathematical fact. The main disagreement seems to be about which definition of the word "entropy" in the context of statistical physics is "correct". Definition is an ...

2

Simply the thermodynamical quantities used in the original paper were not suitable for that problem. They in particular calculated $T=\frac{\partial U}{\partial S}$ where $U$ is the internal energy and $S$ the entropy. However a wrong definition of entropy has been used. Mathematicians has proved that the use of that specific entropy was wrong and that ...

2

For BE or FD statistics you have the additional constrained that you are dealing with a fixed number of particles (or fixed mean number). That gives you a normalization condition $$\int d\epsilon \ n(\epsilon) = N$$ Now, for large T $\beta \epsilon$ is small, i.e. a large fraction of the possible energy states is actually accessible, i.e. could possibly ...

2

inelastic collisions are necessary in order to properly distribute energy among the internal molecular degrees of freedom (vibration, rotation). They are, but the ideal gas (nominally) does not have such internal degrees of freedom.1 Allowing them is a simple extension that is often made without announcing it2 and with that extension you get some ...

2

Yes, these equations exist and can be derived from the partition function in JGab's answer. The internal energy per spin is: $$u(\beta) = - \frac{\partial}{\partial \beta} \left( \ln(2) + \frac{1}{8 \pi^2} \int_{0}^{2\pi} \mathrm{d} q_1 \int_{0}^{2\pi} \mathrm{d} q_2 \\\ln \left[ \big( 1 - \sinh(2 \beta J) \big)^2 + \sinh(2 \beta J) \left( 2 - \cos q_1 - ... 2 What is entropy, more than disorder? Don't look at entropy as disorder. Thinking of it as disorder has long been a source of confusion. Many texts are moving away from using the disorder description. Macroscopically, it's better to think of entropy as a measure of energy dispersion rather than as a measure of disorder. Microscopically, it's better to think ... 2 1. Hawking-Bekenstein entropy of a black hole is given by S_{\text{BH}} = \frac{kAc^3}{4\hbar G} where A is the area of the event horizon. Assuming a non-rotating black hole, there holds r_s=\frac{2GM}{c^2} for the Schwartzschild radius, and therefore A=4\pi r_s^2=\frac{16\pi G^2M^2}{c^4}, which results in$$ S_{BH}=\frac{4kGM^2}{\hbar c} $$For ... 1 Thermal velocity is the velocity that a particle in a system would have if its kinetic energy were equal to the average energy of all the particles of the system. Take an ideal gas in three dimensions as an example. In equilibrium there is a distribution of velocities among all of the particles. Some move "fast" others move "slowly". That means that ... 1 For a system of atoms to have a meaningful temperature, I would say there has to be uncertainty in their state, and there must be a way (at least hypothetically) for the system to exchange energy with some other system. The first example you give of the two beams is an idealized state with no uncertainty, so assigning a temperature would be impossible. You ... 1 This may be the relevant paper that would answer your question: http://journals.aps.org/prb/abstract/10.1103/PhysRevB.57.8472 1$$-\left(\frac{\partial^2\Omega}{\partial H^2}\right)_\mu=\left(\frac{\partial M}{\partial H}\right)_\mu=\left(\frac{\partial M}{\partial H}\right)_N+\left(\frac{\partial M}{\partial N}\right)_H\left(\frac{\partial N}{\partial H}\right)_\mu In principle, there is a difference between these quantities, at least in ferromagnets (otherwise the magnetization ...

1

Christoph gives a good answer from the point of view of statistical physics, but the first context we actually encounter entropy is in classical thermodynamics. It is useful even without the interpretation of being "the measure of disorder". This got slightly out of hand and is now quite technical, but I think it is still digestible and provides a complete ...

1

I'm not sure if you're talking about probabilities here but if you are then I found some problems online: 1) In how many ways can 8 people line up for concert tickets? 2) There are 5 women running a race. How many different ways could 1st, 2nd, 3rd place finishers occur? 3) There are 13 members on a board of directors. If they must form a subcommittee ...

1

When studying dynamical systems you consider a low-dimensional phase space that only includes macroscopic variables. In this phase space dissipation does indeed cause volume contraction - but only because the energy that has been lost has been transferred to the far bigger phase space including all the microscopic variables. In this space energy must be ...

1

I made a very simple mistake of plotting Specific heat and not Specific heat per spin. It is specific heat per spin that scales as $L^{\alpha/\nu}$. And hence, the actual value from the data of my previous simulations is $2.44-2 = 0.44$. Using system sizes $10$ and $12$, one in fact gets a value $0.3$.

1

According to my limited understanding of density functional theory. Coulomb interaction is one of the correlation effects. Besides Coulomb interaction, there are interaction due to Pauli exclusion principle and change of kinetic energy compared with that of non-interacting electron gas.

1

This is a very difficult problem. I try to explain why. If we want to obtain the mathematical proof of the second law, we must consider the mathematical proof of the entropy first, as a state function. Clausius’ definition $dS=δQ/T$ cannot be proven in mathematics, as an exact differential, so the definition $dS=δQ/T$ can only depend on imaginary reversible ...

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