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--- layout: page title: "About" description: "Hey, this is Haojun." header-img: "img/about-bg.jpg" ---
别人都叫我 大腿君。
大家好，我是 隋昊君，昵称Charles。毕业于 Penn State University 的 Schreyer Honor College，主修计算机科学，数学系统分析，以及应用统计学。
我现在在微软工作，主要帮助公司内部及公司外部客户进行数据分析。
People call me BigLeg.
Hi, here is Haojun Sui. I graduated from Pennsylvania State University with Bachelor Degrees of Computer Science, Mathematics (System Analysis), and Statistics (Applied) in Schreyer Honor College.
I am currently working for Microsoft. As Microsoft IT Data & Decision Sciences (DDSG) software engineers, we drive actionable business intelligence through advanced statistical modeling and business analytics across Microsoft. Data engineers work closely with data scientists, to collectively deliver end-to-end, scenario-based big data analytic solutions. Our goal is to solve Microsoft's internal & external customers' big data problems (e.g. Cybersecurity intrusion detection, IoT telemetry data analysis for Smart building etc.) by using cutting-edge technologies such as HDInsight, SPARK and Cortana Analytics Suite.


Hi, I'm Jasun. I'm originally from northern New Jersey. I graduated with a degree in English Lit, but I've been a bookkeeper for my entire professional career. I am drawn to the creative and problem-solving aspects of coding; and I'm excited by the professional opportunities coding provides
The fields of coding, and technology in general, that are really piquing my interest are:
I love spending time with my wife and two children. I love Japanese food, meeting new people, producing music, drumming, basketball (go Blazers!), bouldering, Alphonse Mucha, Steven Universe, Alan Watts, fastcompany magazine, and medium.com.


{% extends 'index.html' %}
{% block body %}
{% from "includes/_formhelpers.html" import render_field %}
{% from "includes/_history.html" import render_history %}
| First Name: | {{user.first}} |
|---|---|
| Last Name: | {{user.last}} |
| Date Joined: | {{ pst_time(user.join_date) }} |
| Email: | {{user.email}} |


Numpy Implementation of WANNs¶
Feed-Forward Networks¶
The final activation state can be reached by multiplying the initial activation vector (only input nodes and bias is set) with the weight matrix and applying the activation functions. In the implementation only the columns of matrix are used that correspond to the nodes that are currently calculated. The order of calculation is determined by the layers (calculated during genes expression by hierarchically sorting the hidden nodes). Additionaly, only the rows are used that correspond to nodes in layers prior to the current layer. All other rows have to contain zero.
Note
During expression the nodes are topologically sorted. Therefore, the index of a node in the network does not correspond to the index of the same node in the gene.
Recurrent Networks¶
For recurrent networks, two weight matrices are generated. The first corresponds to the weight matrix in a feed-forward network. It also has to be acyclic and determines a topological sorting of the nodes. The second matrix represents the recurrent connections. The recurrent weight matrix does not need to be acyclic since the signal will not be used during forward feeding but in the next step of element processing. Additionally, the recurrent weight matrix can contain connections from output nodes to hidden nodes or output nodes.


Below is a list of all the current members of the YRM 2015 committee. We welcome any questions or comments; please email us at<EMAIL_ADDRESS>We would also like to thank Jo French for her hard work and support.
If you click on a committee member's photo it will take you to their personal website.


ACE_FTS_L2_main
Variables
The table below lists the variables that are present in the HARP product that results from an ingestion of ACE_FTS_L2_main
data.
| field name | type | dimensions | unit | description |
|---|---|---|---|---|
| datetime | double | {time} | [seconds since 2000-01-01] | date and time of occultation 30 km geometric tangent point |
| datetime_start | double | {time} | [seconds since 2000-01-01] | date and time of start of measurement |
| datetime_stop | double | {time} | [seconds since 2000-01-01] | date and time of end of measurement |
| orbit_index | int32 | absolute orbit number | ||
| latitude | double | {vertical} | [degree_north] | latitude of 30 km geometric tangent point for occultation |
| longitude | double | {vertical} | [degree_east] | longitude of 30 km geometric tangent point for occultation |
| altitude | double | {vertical} | [km] | tangent altitude grid for retrieved parameters and species |
| temperature | double | {vertical} | [K] | temperature |
| pressure | double | {vertical} | [hPa] | pressure |
| number_density | double | {vertical} | [cm^-3] | atmospheric density |
| H2O_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for H2O |
| H2O_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for H2O. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| O3_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for O3 |
| O3_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for O3. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| N2O_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for N2O |
| N2O_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for N2O. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| CO_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for CO |
| CO_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for CO. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| CH4_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for CH4 |
| CH4_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for CH4. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| NO_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for NO |
| NO_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for NO. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| NO2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for NO2 |
| NO2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for NO2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| HNO3_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for HNO3 |
| HNO3_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for HNO3. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| HF_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for HF |
| HF_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for HF. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| HCl_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for HCl |
| HCl_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for HCl. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| OCS_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for OCS |
| OCS_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for OCS. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| N2O5_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for N2O5 |
| N2O5_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for N2O5. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| ClONO2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for ClONO2 |
| ClONO2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for ClONO2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| HCN_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for HCN |
| HCN_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for HCN. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| CH3Cl_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for CH3Cl |
| CH3Cl_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for CH3Cl. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| CF4_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for CF4 |
| CF4_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for CF4. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| CCl2F2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for CCl2F2 |
| CCl2F2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for CCl2F2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| CCl3F_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for CCl3F |
| CCl3F_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for CCl3F. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| COF2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for COF2 |
| COF2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for COF2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| C2H6_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for C2H6 |
| C2H6_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for C2H6. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| C2H2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for C2H2 |
| C2H2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for C2H2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| CHF2Cl_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for CHF2Cl |
| CHF2Cl_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for CHF2Cl. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| SF6_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for SF6 |
| SF6_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for SF6. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| ClO_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for ClO |
| ClO_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for ClO. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| HO2NO2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for HO2NO2 |
| HO2NO2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for HO2NO2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| H2O2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for H2O2 |
| H2O2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for H2O2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| HOCl_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for HOCl |
| HOCl_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for HOCl. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| N2_volume_mixing_ratio | double | {vertical} | [ppmv] | volume mixing ratio for N2 |
| N2_volume_mixing_ratio_uncertainty | double | {vertical} | [ppmv] | volume mixing ratio uncertainty for N2. If this value is -888 the vmr was not retrieved but obtained by scaling the a priori value |
| index | int32 | {time} | zero-based index of the sample within the source product |
Mapping description
The table below details where and how each variable was retrieved from the input product.
| field name | mapping description | |
|---|---|---|
| datetime | path | /date |
| description | date field from header section converted to seconds since 2000-01-01 | |
| datetime_start | path | /start_time |
| description | start_time field from header section converted to seconds since 2000-01-01 | |
| datetime_stop | path | /end_time |
| description | end_time field from header section converted to seconds since 2000-01-01 | |
| orbit_index | description | extracted from the filename (assuming ssXXXXX… or srXXXXX… format); set to 0 if extraction of the value was not possible |
| latitude | path | /latitude |
| description | latitude field from header section | |
| longitude | path | /longitude |
| description | longitude field from header section | |
| altitude | path | /data section/z |
| temperature | path | /data section/T |
| pressure | path | /data section/P (atm) |
| number_density | path | /data section/dens |
| H2O_volume_mixing_ratio | path | /data section/H2O |
| H2O_volume_mixing_ratio_uncertainty | path | /data section/H2O_err |
| O3_volume_mixing_ratio | path | /data section/O3 |
| O3_volume_mixing_ratio_uncertainty | path | /data section/O3_err |
| N2O_volume_mixing_ratio | path | /data section/N2O |
| N2O_volume_mixing_ratio_uncertainty | path | /data section/N2O_err |
| CO_volume_mixing_ratio | path | /data section/CO |
| CO_volume_mixing_ratio_uncertainty | path | /data section/CO_err |
| CH4_volume_mixing_ratio | path | /data section/CH4 |
| CH4_volume_mixing_ratio_uncertainty | path | /data section/CH4_err |
| NO_volume_mixing_ratio | path | /data section/NO |
| NO_volume_mixing_ratio_uncertainty | path | /data section/NO_err |
| NO2_volume_mixing_ratio | path | /data section/NO2 |
| NO2_volume_mixing_ratio_uncertainty | path | /data section/NO2_err |
| HNO3_volume_mixing_ratio | path | /data section/HNO3 |
| HNO3_volume_mixing_ratio_uncertainty | path | /data section/HNO3_err |
| HF_volume_mixing_ratio | path | /data section/HF |
| HF_volume_mixing_ratio_uncertainty | path | /data section/HF_err |
| HCl_volume_mixing_ratio | path | /data section/HCl |
| HCl_volume_mixing_ratio_uncertainty | path | /data section/HCl_err |
| OCS_volume_mixing_ratio | path | /data section/OCS |
| OCS_volume_mixing_ratio_uncertainty | path | /data section/OCS_err |
| N2O5_volume_mixing_ratio | path | /data section/N2O5 |
| N2O5_volume_mixing_ratio_uncertainty | path | /data section/N2O5_err |
| ClONO2_volume_mixing_ratio | path | /data section/ClONO2 |
| ClONO2_volume_mixing_ratio_uncertainty | path | /data section/ClONO2_err |
| HCN_volume_mixing_ratio | path | /data section/HCN |
| HCN_volume_mixing_ratio_uncertainty | path | /data section/HCN_err |
| CH3Cl_volume_mixing_ratio | path | /data section/CH3Cl |
| CH3Cl_volume_mixing_ratio_uncertainty | path | /data section/CH3Cl_err |
| CF4_volume_mixing_ratio | path | /data section/CF4 |
| CF4_volume_mixing_ratio_uncertainty | path | /data section/CF4_err |
| CCl2F2_volume_mixing_ratio | path | /data section/CCl2F2 |
| CCl2F2_volume_mixing_ratio_uncertainty | path | /data section/CCl2F2_err |
| CCl3F_volume_mixing_ratio | path | /data section/CCl3F |
| CCl3F_volume_mixing_ratio_uncertainty | path | /data section/CCl3F_err |
| COF2_volume_mixing_ratio | path | /data section/COF2 |
| COF2_volume_mixing_ratio_uncertainty | path | /data section/COF2_err |
| C2H6_volume_mixing_ratio | path | /data section/C2H6 |
| C2H6_volume_mixing_ratio_uncertainty | path | /data section/C2H6_err |
| C2H2_volume_mixing_ratio | path | /data section/C2H2 |
| C2H2_volume_mixing_ratio_uncertainty | path | /data section/C2H2_err |
| CHF2Cl_volume_mixing_ratio | path | /data section/CHF2Cl |
| CHF2Cl_volume_mixing_ratio_uncertainty | path | /data section/CHF2Cl_err |
| SF6_volume_mixing_ratio | path | /data section/SF6 |
| SF6_volume_mixing_ratio_uncertainty | path | /data section/SF6_err |
| ClO_volume_mixing_ratio | path | /data section/ClO |
| ClO_volume_mixing_ratio_uncertainty | path | /data section/ClO_err |
| HO2NO2_volume_mixing_ratio | path | /data section/HO2NO2 |
| HO2NO2_volume_mixing_ratio_uncertainty | path | /data section/HO2NO2_err |
| H2O2_volume_mixing_ratio | path | /data section/H2O2 |
| H2O2_volume_mixing_ratio_uncertainty | path | /data section/H2O2_err |
| HOCl_volume_mixing_ratio | path | /data section/HOCl |
| HOCl_volume_mixing_ratio_uncertainty | path | /data section/HOCl_err |
| N2_volume_mixing_ratio | path | /data section/N2 |
| N2_volume_mixing_ratio_uncertainty | path | /data section/N2_err |


Cormyr [ad6c], city, in Endless Plains [an73], in Imperia
Last updated Turn #145
Cormyr [ad6c], city, in Endless Plains [an73], in Imperia
------------------------------------------------------------------------
11: Elmar [d7q], Pen, with two peasants, 11 workers, ten soldiers,
11: 47 pikemen, 23 wagons, arrived from Endless Plains [an73],
11: accompanied by:
11: Celia [i4d], Pen, with one peasant, 30 lt. xbowmen, four wagons,
11: two wild horses, 14 riding horses
11: Celia [i4d] bought two riding horses [52] from Cormyr [ad6c] for
11: 240 gold.
11: Paid a market tax of 60 gold to Cormyr [ad6c].
12: Elmar [d7q], Pen, with two peasants, 11 workers, ten soldiers,
12: 47 pikemen, 23 wagons, entered Incursos College [u26],
12: accompanied by:
12: Celia [i4d], Pen, with one peasant, 30 lt. xbowmen, four wagons,
12: two wild horses, 16 riding horses
12: Elmar [d7q], Pen, with two peasants, 11 workers, ten soldiers,
12: 47 pikemen, 23 wagons, arrived from Incursos College [u26],
12: accompanied by:
12: Celia [i4d], Pen, with one peasant, 30 lt. xbowmen, four wagons,
12: two wild horses, 16 riding horses
12: Elmar [d7q], Pen, with two peasants, 11 workers, ten soldiers,
12: 47 pikemen, 23 wagons, exited Cormyr [ad6c], accompanied by:
12: Celia [i4d], Pen, with one peasant, 30 lt. xbowmen, four wagons,
12: two wild horses, 16 riding horses
Routes leaving Cormyr:
Out, plain, to Endless Plains [an73], 1 day
Garrison [bz5a], garrison, Imperial Empire, with ten peasants
Cities rumored to be nearby:
Imperial City [aa0c], in Imperial Forest [aq70]
Balatea [ad5j], in Endless Plains [am74]
Thorbardin [ad7b], in Thorbardin Mountains [ao69]
Hyksos [ad7d], in Imperial Mountains [ao73]
Eadweard [ad9f], in Buffalo Plains [aq71]
Market report (tax of 25%):
trade who price qty wt/ea item
----- --- ----- --- ----- ----
buy ad6c 29 20 2 gorgon livers [332]
buy ad6c 27 19 10 giants' tongues [335]
buy ad6c 14 7 5 lizard tails [326]
buy ad6c 10 12 5 dried fish [255]
buy ad6c 4 15 1 woven baskets [94]
sell ad6c 100 5 1,000 oxen [76]
sell ad6c 120 2 300 riding horses [52]
sell ad6c 800 1 5 Manual of Shipcraft [cq1l]
sell ad6c 1,075 1 5 rare book [jj3v]
Inner locations:
Incursos College [u26], Trading Guild, defense 20
Public tower [m34], tower, defense 20
Public tower [q02], tower, defense 20
Senhome [y95], tower, defense 20, 35% damaged


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16-Jul-18 02:04 PM
[Cryptoon#3362] Transfer all to one adress and try to sell
[Cryptoon#3362] It's not really stealing per se
[caex#1831] and later people say that the project did not take off and there were scams and frauds
[Cryptoon#3362] Just not really ethical
[Cryptoon#3362] 'exploiting the system'
[vtestcoin#9955] I have not stolen anything, I have bought and used the faucet with my directions manually and who says something else that proves what it says
[Bo#8264] It's up to the maintainers of the faucet to have an opinion and take action if they want
[caex#1831] nice chainzilla promotion
[brainland#4248] He might have bought the ICO.....
[Cryptoon#3362] the ico isnt live yet
[brainland#4248] Else, explain how he exlpoited the faucet
[Robert Naus#9564] I don’t like this, this should not be possible really,since it is,not much u can do but shouldn’t be.
[Cryptoon#3362] Look at this transaction that went into his address
[Cryptoon#3362] 230 transactions of 0,1 zilla
[brainland#4248] Let the guy be. Go exploit too
[Cryptoon#3362] To his main adress
[Cryptoon#3362] Are you in on it too?
[Cryptoon#3362] Otherwise you can see why this is not really a good way to behave
[caex#1831] he still wanted to sell here
[caex#1831] funny ppl here LOL
[brainland#4248] Am not but I don't know why its now a topic
[caex#1831] 82,25$
[Cryptoon#3362] not really fair for people that want to legitimately claim the faucet with one address
[Cryptoon#3362] But bump into an empty faucet
[Cryptoon#3362] Because some guys are exploiting it like this
[Cryptoon#3362] That's why it's a topic.
[brainland#4248] Has the bot airdrop ended here?
[vtestcoin#9955] Stop accusing, you have no evidence, I have not done anything that is bad, I have claimed as any user in my directions manually the reward of the faucet and I can pass if the owners of the faucet wanted a record of how I made it manually, as well as the purchase agreements I've made, so shut up
[Bo#8264] it's a valid discussion i think
[Cryptoon#3362] This is evidence?
[Cryptoon#3362] There are 235 payments in one transaction, there is not way to do this manually
[vtestcoin#9955] That is not proof of absolutely nothing, just that to save commissions I have made the transactions together
[Cryptoon#3362] 251 payments, sorry
[caex#1831] PTYX appears, let it block this address and faucet
[vtestcoin#9955] If there is a genius, it is called having the Zilla wallet in native mode where you can do that completely manually, stop accusing without having any idea of how it works.
[caex#1831] to check and explain
[vtestcoin#9955] To more than one of here it seems that he would like the centralization and modify the transactions to his liking, it seems that they do not understand what the blockchain is, very sad ...
[Cryptoon#3362] Cryptoon - Today at 16:03
Nah dont block address, that would be blockchain censorship, which I also don't like
[Cryptoon#3362] Is what I said here
[Cryptoon#3362] I just said it wasnt ethical
[vtestcoin#9955] The only evidence you provide is transactions, which do not prove that the addresses of origin are mine or that have not been claimed manually, therefore you only say absurd conspiracies
[caex#1831] @castle32 Maybe you did it by hand but the point is that you wanted to sell it here
[Robert Naus#9564] I know nothing about how it all works but u simply abusing it. Fine u can do that, get away with it but don’t play some kinda hero bcs u just little weasel that just can’t play fair.
[vtestcoin#9955] I want to sell them because I prefer to have KMD that Zilla that give me more liquidity to exchange
[deathsgrip#5269] What’s faucet and how do you use?
[Cryptoon#3362] Post your address once a day or so
[Cryptoon#3362] To get 0,1 zilla free
[Cryptoon#3362] It's intended for people to get familiar with coins


Renders a puzzle description to SVG. Select one of the examples, and/or edit the puzzle definition. Then click "Render" to generate SVG.
This uses puzzle-draw, the source of this app is at puzzle-draw-snap.


Intro¶
Network Overview¶
ScatterBytes is a network storage system designed to distribute data and copies of that data across the internet. Unlike conventional systems which transfer and store data in data centers requiring high transfer and storage capacity at those centers, ScatterBytes transfers data directly between peers on the network, which distributes both the transfer routes and the storage locations.
Nodes¶
There are three node types on the network: the client node, the storage node, and the control node. The client node uploads and downloads data to and from the network. It is the “consumer”. The storage node stores data uploaded from the client, sends data downloaded by the client, and replicates data as requested by the control node. The control node coordinates activity between the client and storage nodes and monitors the network to maintain integrity.
Redundancy¶
Redundancy is configurable by use of pre-defined volumes. A client may create any number of volumes, which also function as a namespace for file names. The mirror count attribute specifies the number of times the file chunks are to be copied to additional storage nodes. One may add no redundancy or as much redundancy as the network will support. For instance, a mirror count of 1 will maintain 2 copies (original + 1) of each file chunk.
Data Security¶
By default, the ScatterBytes client encrypts all data using AES 256 encryption. This means the client is the only one that can read the data uploaded. Neither the storage nodes or the control node can read the stored data. In addition, the client may opt to use his own encryption software and disable the built in encryption.
Communication Security¶
The ScatterBytes network communication is built on Transport Layer Security (TLS) and X.509 certificates. Absolutely all communication is encrypted via TLS and all nodes identities verified via X.509 certificates.
Payments¶
Rates are stated in gigabyte-months with a month being 30 24 hour days. Actual computed rates are based on byte-hours.
Client nodes pay per gigabyte-month per storage node. For instance, if the current storage rate is 2 cents per gigabyte-month (30 day month) and the client opts to mirror the data 2 times, the cost would be 6 cents * number of gigabyte-months used. Initially, only storage costs apply though download and query costs will likely be applied to balance the system.
Storage nodes are paid to store data. The current rate is 75% of the rate charged to the client. For instance, if a storage node stored 1 terabyte of data for 30 days at 0.015 cents per gigabyte-hour, the payment would be $15.36. When a download rate is charged, the storage node will be compensated as well.


Cloudy here, sunny there
by Darren HandschuhTired of being enveloped in low-lying clouds?
Just drive a few minutes, and the skies will clear.
Vernon has been under a blanket of grey the last few days while other areas, like neighbouring Coldstream, basked in sunshine.
Environment Canada meteorologist Bobby Sekhon said the inversion is caused by a ridge of high pressure over the area.
“That can cause clear conditions in the higher elevations, but that can also mean the moisture closer to the ground gets trapped under the inversion,” said Sekhon. “An inversion is basically temperatures that increases with height and any moisture that is trapped under that, stays under that unless there is something to clear it out.”
That something is typically warmth from the sun.
“Now that we are getting close to the winter equinox, we are not feeling as much power from the sun and days are shorter, so we are not getting as much burning off of fog and low cloud from the sun,” said Sekhon.
“So we have seen that low cloud and fog stick around.”


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layout: default
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Written exam questions
- Zipf's Law, its importance for NLP. Language processing in information retrieval: lemmatization,
stemming, Boolean search, inverted indices, execution of Boolean queries on them, skip-lists.
- Language processing in information retrieval: vector space model, cosine distance, TF-IDF.
Common ways of representing texts for machine learning tasks.
- String distances and the algorithms for their computation: the Hamming distance,
the Jaro-Winkler distance,
the Levenshtein distance, the longest common subsequence, the Jaccard distance for character N-grams.
Indices for typos detection/correction in words.
- Edit distances (definitions only). Regular expressions: basic constructions, recommendations for use.
- Markov chains. Ergodic theorem. PageRank and Markov chains. Direct applications in the text analysis.
- Elements of information theory: self-information, bit, pointwise mutual information, Kullback-Leibler divergence,
Shannon entropy, its interpretations. Cross-entropy. Example of an application: collocations extraction.
- Language modeling. N-gram models. Perplexity. The reasons for doing smoothing. Additive (Laplace) smoothing.
Interpolation and backoff. The ideas on which the Kneser-Ney smoothing is based.
- Vector semantics: term-document matrices, term-context matrices, HAL. SVD, LSA, NMF. Methods for quality evaluation
of vector semantics models.
- Vector semantics: what is word2vec (the core principles of the SGNS algorithm and its relationship with
matrix factorization),
word2vec as a neural network. Methods for quality evaluation of vector semantics models.
- Clustering: types of clustering algorithms. KMeans, agglomerative and divisive clustering
(+ ways of estimating the distances between clusters), DBSCAN.
Limitations and areas of applicability of all algorithms.
Methods clustering quality evaluation, the shortcomings of each.
- Duplicates search: statement of the problem, description of the MinHash algorithm. Probability of hashes matching
is equal to Jaccard similarity (with proof).
- Topic modeling. LSA, pLSA, LDA, ARTM. Advantages and disadvantages of each method.
Topic modeling quality evaluation (perplexity, coherence and methods with experts involved).
- Classification. Binary classification quality evaluation.
Metric classification methods. Logical methods of classification. Linear classification methods.
- Quality evaluation of machine learning models (why divide the data set into three parts).
Classification. Multi-class classification quality evaluation.
Naive Bayes Classifier. Ensembles of models of machine learning.
- Sequence tagging. PoS tagging. Named entity recognition. Hidden Markov models.
Estimation of the probability of a sequence of states.
Estimation of the probability of a sequence of observations.
Quality evaluation.
- Sequence tagging. PoS tagging. Named entity recognition. Hidden Markov models.
Decoding of the most probable sequence of states (Veterbi algorithm without proof). Quality evaluation.
- Sequence tagging. PoS tagging. Named entity recognition. Structured perceptron.
Structured perceptron training. Sequente tagging quality evaluation.
- Syntax parsing. Syntax description approaches.
Phrase structure grammar: the principles. Formal grammar.
Chomsky Normal Form. Cocke-Kasami-Younger algorithm, its complexity. Parsing quality evaluation.
- Syntax parsing. Syntax description approaches. Phrase structure grammar: the principles.
Probabilistic context-free grammar. Cocke-Kasami-Younger algorithm for PCFG (without proof), its complexity.
Parsing quality evaluation.
- Syntax parsing. Syntax description approaches. Dependency grammar, core principles.
Parsing quality evaluation. Transition-based dependency parsing: how it works.
The algorithm (everything but the 'oracle').


Interface ITrackingControllerApiSync
Represents a collection of functions to interact with the API endpoints
Inherited Members
Namespace: mailslurp.Api
Assembly: mailslurp.dll
Syntax
public interface ITrackingControllerApiSync : IApiAccessor
Methods
View SourceCreateTrackingPixel(CreateTrackingPixelOptions, int)
Create tracking pixel
Declaration
TrackingPixelDto CreateTrackingPixel(CreateTrackingPixelOptions createTrackingPixelOptions, int operationIndex = 0)
Parameters
| Type | Name | Description |
|---|---|---|
| CreateTrackingPixelOptions | createTrackingPixelOptions | |
| int | operationIndex | Index associated with the operation. |
Returns
| Type | Description |
|---|---|
| TrackingPixelDto | TrackingPixelDto |
Remarks
Create a tracking pixel. A tracking pixel is an image that can be embedded in an email. When the email is viewed and the image is seen MailSlurp will mark the pixel as seen. Use tracking pixels to monitor email open events. You can receive open notifications via webhook or by fetching the pixel.
Exceptions
| Type | Condition |
|---|---|
| ApiException | Thrown when fails to make API call |
CreateTrackingPixelWithHttpInfo(CreateTrackingPixelOptions, int)
Create tracking pixel
Declaration
ApiResponse<TrackingPixelDto> CreateTrackingPixelWithHttpInfo(CreateTrackingPixelOptions createTrackingPixelOptions, int operationIndex = 0)
Parameters
| Type | Name | Description |
|---|---|---|
| CreateTrackingPixelOptions | createTrackingPixelOptions | |
| int | operationIndex | Index associated with the operation. |
Returns
| Type | Description |
|---|---|
| ApiResponse<TrackingPixelDto> | ApiResponse of TrackingPixelDto |
Remarks
Create a tracking pixel. A tracking pixel is an image that can be embedded in an email. When the email is viewed and the image is seen MailSlurp will mark the pixel as seen. Use tracking pixels to monitor email open events. You can receive open notifications via webhook or by fetching the pixel.
Exceptions
| Type | Condition |
|---|---|
| ApiException | Thrown when fails to make API call |
GetAllTrackingPixels(int?, int?, string, string, DateTime?, DateTime?, int)
Get tracking pixels
Declaration
PageTrackingPixelProjection GetAllTrackingPixels(int? page = null, int? size = null, string sort = null, string searchFilter = null, DateTime? since = null, DateTime? before = null, int operationIndex = 0)
Parameters
| Type | Name | Description |
|---|---|---|
| int? | page | Optional page index in list pagination (optional, default to 0) |
| int? | size | Optional page size in list pagination (optional, default to 20) |
| string | sort | Optional createdAt sort direction ASC or DESC (optional, default to ASC) |
| string | searchFilter | Optional search filter (optional) |
| DateTime? | since | Filter by created at after the given timestamp (optional) |
| DateTime? | before | Filter by created at before the given timestamp (optional) |
| int | operationIndex | Index associated with the operation. |
Returns
| Type | Description |
|---|---|
| PageTrackingPixelProjection | PageTrackingPixelProjection |
Remarks
List tracking pixels in paginated form
Exceptions
| Type | Condition |
|---|---|
| ApiException | Thrown when fails to make API call |
GetAllTrackingPixelsWithHttpInfo(int?, int?, string, string, DateTime?, DateTime?, int)
Get tracking pixels
Declaration
ApiResponse<PageTrackingPixelProjection> GetAllTrackingPixelsWithHttpInfo(int? page = null, int? size = null, string sort = null, string searchFilter = null, DateTime? since = null, DateTime? before = null, int operationIndex = 0)
Parameters
| Type | Name | Description |
|---|---|---|
| int? | page | Optional page index in list pagination (optional, default to 0) |
| int? | size | Optional page size in list pagination (optional, default to 20) |
| string | sort | Optional createdAt sort direction ASC or DESC (optional, default to ASC) |
| string | searchFilter | Optional search filter (optional) |
| DateTime? | since | Filter by created at after the given timestamp (optional) |
| DateTime? | before | Filter by created at before the given timestamp (optional) |
| int | operationIndex | Index associated with the operation. |
Returns
| Type | Description |
|---|---|
| ApiResponse<PageTrackingPixelProjection> | ApiResponse of PageTrackingPixelProjection |
Remarks
List tracking pixels in paginated form
Exceptions
| Type | Condition |
|---|---|
| ApiException | Thrown when fails to make API call |
GetTrackingPixel(Guid, int)
Get pixel
Declaration
TrackingPixelDto GetTrackingPixel(Guid id, int operationIndex = 0)
Parameters
| Type | Name | Description |
|---|---|---|
| Guid | id | |
| int | operationIndex | Index associated with the operation. |
Returns
| Type | Description |
|---|---|
| TrackingPixelDto | TrackingPixelDto |
Exceptions
| Type | Condition |
|---|---|
| ApiException | Thrown when fails to make API call |
GetTrackingPixelWithHttpInfo(Guid, int)
Get pixel
Declaration
ApiResponse<TrackingPixelDto> GetTrackingPixelWithHttpInfo(Guid id, int operationIndex = 0)
Parameters
| Type | Name | Description |
|---|---|---|
| Guid | id | |
| int | operationIndex | Index associated with the operation. |
Returns
| Type | Description |
|---|---|
| ApiResponse<TrackingPixelDto> | ApiResponse of TrackingPixelDto |
Exceptions
| Type | Condition |
|---|---|
| ApiException | Thrown when fails to make API call |


Services publish an API or run background services in separate threads in a web application. Services are not accessible directly over any protocol like HTTP or web sockets but can be accessed by controllers by adding them as parameters to one or more controller methods. Services are packaged together with other Java classes and controllers in web applications and instantiated by Nginious when the web application is published.
Services are arbitrary classes which are annotated with the Service
annotation. When a web application is published the server inspects all classes in the web application searching for classes
annotated with the Service>
annotation. The classes are instantiated and made available to controllers in the web
application
A service may optionally implement the java.lang.Runnable
interface. In this case the server starts a separate thread to
execute the service when the web application containing the service is published. When the web application is unpublished the
thread is interrupted and stopped.
Below is an example service which implements the java.lang.Runnable
interface.
@Service(name = "example")
public class CounterService implements Runnable {
private AtomicInteger counter;
public CounterService() {
this.counter = new AtomicInteger(0);
}
public int getCounter() {
return counter.get();
}
public void run() {
Thread serviceThread = Thread.currentThread();
boolean stopped = false;
while(!stopped) {
counter.incrementAndGet();
stopped = serviceThread.isInterrupted();
if(!stopped) {
try {
Thread.sleep(1000L);
} catch(InterruptedException e) {
stopped = true;
}
}
}
}
}


Now made obsolete by rst2slide that ships with docutils, py2slide was a short and sweet slide generator based on reST, focusing on slide reuse. This is no longer available, but if you ask me I'll give you a copy. There is no reason not to use docutils instead.
While attending a Computer Architecture course at IC-Unicamp, I decided to create a tool to aid the teacher. After the course was finished I never had the time (or will) to work on it. So it is available for anybody that might have both. Note that this is a weekend's draft implementation.


27+ Weight Lifting Log Excel Template Pics. To find more books about weight lifting log excel template, you can use related keywords, for examples : Weight lifting find user manuals, quick start guides, product sheets and compliance documentation about :
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14 weight lifting template excel. Looking for training ule template excel free weight lifting log workout chart? Safety training log template on the job training template employee. The first step in weight lifting log template design is to open microsoft word and create a new document.


Workcell Builder¶
This ROS package provides an easy to use Graphical User Interface for generation of a robotic workcell in RViz which serves as the first step in the pipeline for a pick and place task
This ROS package provides an easy to use Graphical User Interface for generation of a robotic workcell in RViz which serves as the first step in the pipeline for a pick and place task


| Date | Time | Event |
|---|---|---|
|
{f:format.date(date: event.startDate, format: 'd')}
{f:format.date(date: event.startDate, format: 'F Y')}
|
{f:format.date(date: event.startDate, format: "H:i")} |
|
You have no upcoming events
{currentSquad.description}
You are not part of any squad


SweetFreeStuff.com
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| Character | Passive Ability | 'Left Shift' Ability | 'E' Ability | Ultimate Ability |
|---|---|---|---|---|
| Cyber-Agility | Swift Strike | Deflect | Dragonblade | |
| No Passive | Combat Roll | Flashbang | Deadeye | |
| No Passive | Jump Jet | Concussive Blast | Barrage | |
| The Reaping | Wraith Form | Shadow Step | Death Blossom | |
| No Passive | Sprint | Biotic Field | Tactical Visor | |
| No Passive | Blink | Recall | Pulse Bomb |
All images in table taken from original, hosted by Gawker.
Used under the Creative Commons License


--- sort_order: 49 tei_id: rdx_v6pf4.p.idm140456983027872 annotation_count: 0 images: small-thumbnail: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6pf4/mini-thumbnail/ json: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6pf4/info/ full: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6pf4/fs/ page: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6pf4/single-page/ thumbnail: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6pf4/thumbnail/ title: Page 45 number: 45 permalink: "/pages/45/" ---


This website Calculates the exact day you were born from the users birthday detailsMost people do know when their birthdays are, but some might not know what day of the week they were born.
Luckily for us, using a very unique method, this website makes it possible to calculate the day of the week from a specific date.
Akan names are derived from Ghanian culture. Frequently in Ghana, children are given their first name as a 'day name' which corresponds to the day in the week they were born.
Here are Ghanian day names.


I enjoy merging art and technology in graphic design + 3D modeling + web design + motion graphics + animation + virtual reality.
I graduated from the University of California, San Diego with a major in speculative design and a minor in computer science. This relates to my interests in the computing aspects of human and technological interaction.
Check out more samples of my work from The Walt Disney Company on my Behance and my illustration sketches on dribbble!
A VR experience where users paint a scene to life with every paint stroke.
https://github.com/TritonXR/Paint-the-Town
Kids are able to build their own obstacles with paper blocks and race through or knock down their creations using Bluetooth controlled Arduino vehicles.
This toy is free-form, modular, and it pairs nostalgia with contemporary hands-on gameplay.
For this project, we were given the prompt to create a toy. Our initial ideas began with cars with lasers that would make gameplay more challenging. If players got shot with the opponent's laser, they would lose health and energy. Due to the lack of time, material, and knowledge, we could not implement the lasers into our vehicles. Nevertheless, once our wireless toy cars were completed, we tested their playability with kids and discovered they still had loads of fun playing without the lasers. The kids enjoyed building their own cities and castles with building blocks, and they had an even more fun time knocking down each other's castles with the cars! Overall, Zoom! aims to spur creative thinking and imagination.
A big problem we faced was weight distribution and friction on our cars. Everything seemed to be working properly, but when we readied the cars to drive they would not move. Our solution came to us by a Round Table pizza delivery man, who randomly stopped by our table and asked if we wanted leftover pizza. Graciously we accepted and found that the pizza saver was perfect to solve our problem. Once we attached the pizza saver onto the rear end of the car, it zoomed!
This project was coded using Processing and was made using Arduinos, Bluetooth modules, bread boards, wires, and batteries. The presentation video was inspired from stop motion videos to create an energetic kid-friendly vibe.
Vitabot is a portable and accessible bot that maintains and attends for the user. The Bot is specially crafted to ensure that users receive maximum amount of care, servitude, protection, and fun.
This prototype can be used in various ways by everyone of all ages. Specifically, it targets children who do not know what to do in emergencies or forget to bring essential medication with them. With technological upgrades, the Bot will ultimately be able to detect when
its user is in an emergency or needs help, scan the enormity of the user's situation, and provide a solution to the problem.
Vitabot is only an idea for a health robot and is based off of Disney's character, Baymax, from Big Hero 6. I used Blender to 3D model the figure and 3D printed it. The head is hollow and stores emergency items inside for convenience.
Close Project
Henry Fuseli's The Nightmare: The Game is a video game proposal based off Henry Fuseli's painting, The Nightmare. This project features a young girl who suffers from sleep paralysis and nightmares. As a player, you, a college student and barista, suffer from sleep paralysis and experience the same nightmare every night. In the nightmare, you are being chased by demons and must surmount multiple obstacles and puzzles throughout the maze in order to escape.
This game provides many plot twists and challenges in gameplay. This game dives into the research and understanding of sleep paralysis and the conditions patients undergo when they experience it.
At the end of the game when the player has defeated all the puzzles and is able to escape the dream world, the player ascends a foreboding flight of stairs. At the top, the player sees a mirror. Looking into the reflection, the player realizes that this whole time they have been
playing the demon trying to escape the dream realm. This allows players to have a desire to replay the game in order to notice the subtleties of being the demon rather than Mara, the college student.
Navigate through Mara's labyrinth by going through her schedule and daily duties. Mara's schedule is itself something you must solve in order to understand the game more. The more time you spend in the nightmare realm, the more subtleties you'll notice.
Made with Unity, The Island & The Island is an abstract game focuses on challenging normal video game environments through the jaws of an alligator. This game incorporates the landscape as the game and challenges the limitations of player movement and assessment of the land. The space is itself a time fold in which overlapping identical areas can be changed by unique individual factors, of which spark separate chain reactions that evolve the entire space. Inspired by China Mieville's novel, The City and The City, this game forces players to reconsider virtual space and question the boundaries in video games.
In Ernest Adam's Designer's Notebook: The Role of Architecture in Videogames, he speaks about
how the primary role of game architecture is to support gameplay. The Island & the Island, however, seeks to challenge this belief and promotes game architecture as the source of gameplay. Game architecture is as vital to the game as the story, characters, and gameplay. According to Jon Brouchoud “architecture can tell a story, evoke emotion and shape player experience more effectively than any other aspect of your game. You can have the best characters, storyline, and UI graphics, but without an equally considerate approach to architecture, your player experience will always fall short of its fullest potential.” Thus, my game entirely focuses on game architecture and highlights game architecture as the game itself.
The Island and the Island deals with concepts regarding space exploration, particularly spaces no one usually explores or touches in video games. Within the game are mini puzzles and obstacles, but the main purpose of the game is to focus on minute changes occurring in the landscape based on the player’s choices. When the player figures out what those changes are, he or she will be able to unlock another dimension of the game. Players depend on the structure of the game's virtual space to guide them through the journey.
The exploration process includes trekking on places that are usually restricted in video games, like the backside of mountains, inside rocks, and underneath islands. Within the island are hidden triggers that teleport the player somewhere else on the islands. The game centers mainly on problem solving and strategic navigation in order to discover hidden Easter eggs and clues on the island. The idea is about uncovering and exposing the island so the player becomes more familiar with the landscape.
Landscapes in typical games are used for supportive roles that act as barriers, aesthetic purposes, or something to get past. This game, however, incorporates the landscape as the game and challenges the limitations of player movement and assessment of the land. Players must have faith in the space that it will guide them to the endgame. From the perspective of the alligator’s mouth, the game also is much harder to navigate and see the environment.
Furthermore, in the Mieville's novel there is a speculation of a third city in between these two cities. Playing around with this concept, my game incorporates a hidden third dimension that can only be found through exploration. The significance of the third space is to challenge the idea of two dimensional space and how space is accepted in today's culture. Space within a virtual game environment is represented as the game itself. Even though I disagree with Adam's notion of game architecture as only support, I do agree that games should have a supportive architecture yet also be a fundamental part of the game itself. Players should feel that the game environment stimulates creative thinking, imagination, and problem solving.
EGO is a fashion-related AI that transforms the way we see fashion by providing several
features to help users with outfit planning. EGO transforms the role of fashion industry in creating personalized clothings tailored to
the user's social media trends. EGO takes on the reflection of the user as its shell. EGO allows you to interact with "yourself" and simulates an out of body experience.
Another one of the many features of EGO is the ability to show the user in multiple outfits without the user actually physically putting them on.
The user selects outfits the mirror recommends and EGO tries on the selected clothes.
Each EGO unit has its own neural network adhered to the user. It relies on reinforcement learning, a model of AI learning that uses rewards and punishments to "reinforce" its knowledge and understanding. EGO can also detect moods and emotional states of the user for better outfit suggestions. All the information recorded in each EGO will be sent into a cloud based system for business research so big fashion industries can learn what styles are trending.
After the first prototypes of EGO were released to test consumers, there seemed to be glitches within the neural network. Some of these included misinterpreting weather conditions, repeating outfits with friends, miscalculating trends, and misjudging age.
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Skin Suits are a second layer of skin made to give the user different identities. Users will have the experience of changing skin color(s)
or pattern(s) to conceal innate blemishes or unwanted scars. The purpose is that by wearing these suits, racial segregation will be diminished as everyone and anyone can be any color they want.
All users of Skin Suits must apply SWEAT (sw-ee-t), a mixture of hydration fluids and antibacterial proteins that decrease the risk of infection upon use.
Skin Suits are developed and cultured in state of the art labs using 3D printing and growth accelerators. With a sample of the customer's skin, full body skin suits are matured and distributed all over the world. DNA inside the nucleus is replaced with genetically modified DNA that changes the color of the epidermal cells. Once the cells have been inserted with the new DNA, the cells begin to multiply and grow on custom Skin Suit molds.
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Yorick Function ReferenceTransposingtranspose(x) transpose the 2-D array x
The permutation is a comma delimited list of cyclic permutations to be applied to the indices of x. Each cyclic permutation may be:
In either case, n or nI can be non-positive to refer to indices relative to the final dimension of x. That is, 0 refers to the final dimension of x, -1 to the next to last dimension, and so on. Thus, transpose(x, [1,0]) swaps the first and last dimensions of x. |