Bulgaria Built a 5,150-HP Electric Hypercar and it's Out of This World
In our roundup of 2017's best and worst hypercars last year, we declared that the 5,007 horsepower, 16-cylinder Devel Sixteen was the worst of the group. Besides having a seemingly-undrivable amount of power, it was the worst offender in the current trend of small companies producing hypercar concepts and renderings and never actually building the vehicles, or building a one-off concept study. Thankfully Devel showed us proof that it wanted to produce its satanic supercar, but there are still plenty of startups out there generating a lot of hype but rarely ever a car.
We're interested to see where the new Alieno Arcanum lands on the spectrum of hypercar fact or fiction. This Lamborghini-like vehicle was unveiled Friday by Alieno, which was founded in 2015 in Sofia, Bulgaria, and claims that it builds "hypercars from the future." Looking at the Arcanum's detailed press release, this car seems to be the real deal and not some alien conspiracy, although those videogame-like renderings aren't helping its case.
The Arcanum, whose name means "the secret of the secrets" in Latin, is an all-electric, two-seater hypercar capable of 303 miles per hour in its most powerful form. Alieno is offering four variants of the car, denoted by their Raw Power (RP) indexes: the least powerful RP2 has 2,575 horsepower (mechanical) and 3,245 pound-feet of torque, the RP3 has 3,433 hp and 4,366 pound-feet of torque, the RP4 has 4,291 hp and 5,458 pound-feet of torque, and the top-tier RP5 has 5,150 hp and 6,549 pound-feet of torque. It looks like the new Tesla Roadster has some competition.
This ridiculous power and torque output comes thanks to Alieno's direct drive powertrain, which features a minimum of three and a maximum of six electric motors (depending on RP) powering each wheel. This multi-motor system means the Arcanum has some excellent active torque vectoring and can provide all of its torque at any point in the rev range, from zero to maximum rpm.
These motors are powered by Alieno's own battery made from a combination of Graphene LiPo cells and supercapacitors. Buyers can choose from three different batteries, each with a different role. The 180-kilowatt-hour Street battery pack provides maximum range at 634 miles, while the 120-kilowatt-hour Track battery is optimized to allow for several miles on the track and not much else. The 60 kilowatt-hour Race battery is used to shed the most amount of weight from the car. Depending on the battery used, the Arcanum can run one to three full laps of the grueling 12.9-mile Nordschleife circuit at the Nürburgring on a single charge.
CHRIS CONSTANTINE


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There seems to be no Rateplan here, are you sure you do not need to create a new one?
{% extends 'base.html' %}
{% block title %} Rateplans {% endblock %}
{% block content %}
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| {{ column }} | {% endfor %}
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| {{ value }} | {% endfor %}


Figures show how 'lack of staff' is impacting on ambulance turnaround times, say FF
by By Digital Desk staffFianna Fáil is calling for action to address the deterioration in ambulance turnaround times over the past two years.
The party's health spokesperson Stephen Donnelly TD has said a lack of staff is to blame.
Ambulance turnaround times measure the time from ambulance arrival at a hospital to when the crew is ready to accept another call.
New figures received by Deputy Donnelly show that the HIQA 20-minute target was only met in 15.9% of cases nationwide while the HSE 30-minute target was achieved in 37.1% of cases.
In Kerry, just 1.7% of ambulances managed the 20-minute turnaround. Another five hospitals nationwide failed to achieve the 5% level.
Deputy Donnelly claims the main reason for the delay is because emergency departments are too busy with too few staff to process a patient coming in by ambulance.


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4 Vertical profiles
In this section you will learn to compute, interpret and analyze vertical profiles (vp). A vp consists of the (bird) density, speed and directions at different altitudes at the location of a single radar. It is typically calculated for all data within a cylinder of 35 km radius around the radar, i.e. only containing data at relatively short distances, where the radar beam is still sufficiently narrow to resolve altitude information.
Section 3 has examples that show how to process polar volume data into vertical profiles. To save time, we will start below with a list of pre-processed vertical profiles for the Brownsville radar in Texas (KBRO).
4.1 Loading processed vertical profiles
# Usually we would load processed vertical profiles (vp files) by:
# my_vplist <- read_vpfiles("./your/directory/with/processed/profiles/goes/here")
# my_vplist contains after running the command a list of vertical profile (vp) objects
# To save time, we load these data directly from file
<- readRDS("data_vpts/KBRO20170514.rds")
my_vplist # print the length of the vplist object. It should contain 95 profiles
length(my_vplist)
4.2 Inspecting single vertical profiles
Now that you have loaded a list of vertical profiles, we can start exploring them. We will start with plotting and inspecting single vertical profiles, i.e. a single profile from the list of vp objects you have just loaded.
# let's extract a profile from the list, in this example the 41st profile:
<- my_vplist[[41]]
my_vp # print some info for this profile to the console
my_vp# test whether this profile was collected at day time:
check_night(my_vp)
# plot the vertical profile, in terms of reflectivity factor
plot(my_vp, quantity = "dbz")
# plot the vertical profile, in terms of (linear) reflectivity
plot(my_vp, quantity = "eta")
eta
and dbz
are closely related, the main difference is that reflectivity factors are logarithmic, and reflectivities linear. You can convert one into the other using eta_to_dbz()
and dbz_to_eta()
functions, which follows this simple formula:
eta = (radar-wavelength dependent constant) * 10^(dbz/10)
The reflectivity factor dBZ
is the quantity used by most meteorologist. It has the useful property that at different radar wavelengths (e.g. S-band versus C-band) the same amount of precipitation shows up at similar reflectivity factors. The same holds for insects, as well as any other target that is much smaller than the radar wavelength (S-band = 10 cm, C-band = 5 cm), the so-called Rayleigh-scattering limit.
In the case of birds we are outside the Rayleigh limit, because birds are of similar size as the radar wavelength. In this limit reflectivity eta
is more similar between S-band and C-band. eta
is also more directly related to the density of birds, since eta
can be expressed as (bird density) x (radar cross section per bird). For these two reasons, for weather radar ornithologists reflectivity eta
is the more conventional unit.
# let's plot the vertical profile, in terms of bird density
plot(my_vp, quantity = "dens")
# print the currently assumed radar cross section (RCS) per bird:
rcs(my_vp)
Exercise 5: If you change your assumption on the bird’s radar cross section in the previous example, and assume the RCS is 10 times as large, what will be the effect on the bird density profile?
The assumed radar cross section can be changed as follows:
# let's change the RCS to 110 cm^2
rcs(my_vp) <- 110
Exercise 6: Verify your answers on the previous two questions, by re-plotting the vertical profiles for the bird density quantity.
4.3 Plotting vertical profile time series
We will now examine multiple vertical profiles at once that are ordered into a time series, e.g. the vertical profiles obtained from a single radar over a full day.
# convert the list of vertical profiles into a time series:
<- bind_into_vpts(my_vplist)
my_vpts # time series objects can be subsetted, just as you may be used to with vectors
# here we subset the first 50 timesteps:
1:50]
my_vpts[# here we extract a single timestep, which gives you back a vertical profile class object:
100]
my_vpts[# to plot the full time series:
plot(my_vpts)
# check the help file for the plotting function of profile time series
# Because profile timeseries are of class 'vpts', it's associated plotting function
# is called plot.vpts:
?plot.vpts
Let’s make a plot for a subselection of the time series:
# filter our vpts for night time
<- filter_vpts(my_vpts, night=TRUE)
my_vpts_night # plot this smaller time series:
plot(my_vpts_night)
Exercise 7: Interpret the wind barbs in the profile time series figure: what is the approximate speed and direction at 1500 meter at 6 UTC? In the speed barbs, each half flag represents 2.5 m/s, each full flag 5 m/s, [each pennant (triangle) 25 m/s, not occurring in this case].
Exercise 8: Extract the vertical profile at 6 UTC from the time series and plot the vertical profile of ground speed (quantity ff
). Hint: use function filter_vpts()
to extract the 6 UTC profile. Check whether your answer to the previous question was approximately correct.
4.4 Vertical and time integration of profiles
Often you will want to sum together all the migrants in the vertical dimension, for example if you want a single index of how many birds are migrating at a certain instant. There are at least two ways in which you can do that:
- by calculating the vertically integrated bird density (VID), which is surface density as opposed to a volume densities you have been plotting in the previous exercises: this number gives you how many migrants are aloft per square kilometer earth’s surface (unit individuals/km\(^{2}\)), obtained by a vertical integration of the volume densities (unit individuals/km\(^{3}\)).
- Note that the VID quantity doesn’t depend on the speed of the migrants. A common measure that reflects both the density and speed of the migration is migration traffic rate (MTR). This is flux measure that gives you how many migrants are passing the radar station per unit of time and per unit of distance perpendicular to the migratory direction (unit individuals/km/hour).
We will be using bioRad’s integrate_profile()
function to calculate these quantities:
# Let's continue with the vpts object created in the previous example.
# The vertically integrated quantities are calculated as follows:
<- integrate_profile(my_vpts)
my_vpi # The my_vpi object you created is a vpi class object, which is an acronym for "vertical profile integrated". It has its own plot method, which by default plots migration traffic rate (MTR):
plot(my_vpi)
# you can also plot vertically integrated densities (VID):
plot(my_vpi, quantity = "vid")
# the gray and white shading indicates day and night, which is calculated
# from the date and the radar position. You can also turn this off:
plot(my_vpi, night_shade = FALSE)
# plot the cumulative number of birds passing the radar, i.e. migration traffic (mt):
plot(my_vpi, quantity = "mt")
# execute `?plot.vpi` to open the help page listing all the options.
?plot.vpi
The following questions only require pen and paper. Assume a night migration event in which the volume density of birds from 0-1 km above ground is 200 birds per cubic kilometer, and from 1-1.5 km 100 birds per cubic kilometer. Above 1500 meter there are no birds.
Exercise 9: What is in this case the bird’s vertically integrated density (VID)? Give your answer in units birds/km\(^2\).
Exercise 10: Let’s assume that in the lower layer birds fly at 50 km/hour, and in the upper layer at 100 km/hour. What is in this case the migration traffic rate across a transect perpendicular to the direction of movement? Give your answer in units birds/km/hour.
Exercise 11:Let’s assume migration continued for exactly three hours after sunset, and then halted abruptly. How many birds have passed a 10 km transect perpendicular to the direction of movement in this night? Give your answer in terms of migration traffic (mt) in units birds/km.
Both MTR, VID and MT depend on the assumed radar cross section (RCS) per bird. If you are unwilling/unable to specify RCS, alternatively you can use two closely related quantities that make no assumptions RCS:
# instead of vertically integrated density (VID), you can use vertically integrated reflectivity (VIR):
plot(my_vpi, quantity = "vir")
# instead of migration traffic rate (MTR), you can use the reflectivity traffic rate (RTR):
plot(my_vpi, quantity = "rtr")
# instead of migration traffic (MT), you can use the reflectivity traffic (RT):
plot(my_vpi, quantity = "rt")
VIR gives you the total cross-sectional area of air-borne targets per square kilometer of ground surface, whereas RTR gives you the total cross-sectional area of targets flying across a one kilometer line perpendicular to the migratory flow per hour.
4.5 Inspecting precipitation signals in profiles
Precipitation is known to have a major influence on the timing and intensity of migration, therefore it is a useful skill to be able to inspect profiles for presence of precipitation.
Also, although automated bird quantification algorithms become more and more reliable, distinguishing precipitation from birds remains challenging for algorithms in specific cases. It is therefore important to have the skills to inspect suspicious profiles. That may help you to identify potential errors of the automated methods, and prevent your from overinterpreting the data.
An easy way of doing that is plotting the vertical profile of total reflectivity (quantity DBZH), which includes everything: birds, insects and precipitation. Precipitation often has higher reflectivities than birds, and also extends to much higher altitudes.
# load a time series for the KBGM radar in Binghamton, NY
<- readRDS("data_vpts/KBGM20170527-20170602.rds")
my_vpts # print the loaded vpts time series for this radar:
my_vpts# plot the bird density over time:
plot(my_vpts, quantity = "dens")
Exercise 12: Compare the above plot for bird density (quantity dens
) with a profile plot for total reflectivity (quantity DBZH
, showing birds and precipitation combined). Compare the two plots to visually identify periods and altitude layers with precipitation.


Because this inspection requires global code analysis it is only available for Analyze|Inspect Code or Analyze|Run Inspection by Name and it will not report in the editor.
Use the field below to specify the minimum number of classes a package may have.


{% extends "base.html" %} {% block title %}{{ education.abbreviation }}{% endblock title %} {% block content %} education
{{ education.date_started|date:"M Y" }}
{{ education.date_ended|date:"M Y" }}
Present
{{ education.description }}
Published {{ education.publish }}


---
title: Roadmap
type: dev
---
Wallaroo Roadmap
The following gives you an outline of some of the features which are envisaged, post Wallaroo 0.8.
Features
- Add an option to use a non-intrusive mechanism at least for the creation mechanism.
- Check of the associations cardinality / optional associations [done in v. 0.3]
- Loading the classes from a dynamic loaded library (.dll or .so) [done in v. 0.4]
- (Optionally) using C++11 in the API [done in v. 0.2]
Improvements
- Add the choice whether to use shared_ptr or weak_ptr for wallaroo::Collaboration [done in v. 0.8]
- The xml wiring file is too verbose. Add a new more hermetic [custom] format [done in v. 0.8]
- XML and JSON without BOOST libraries
- Improve or change the device/plug metaphor. [done in v. 0.7]
- Remove the boost dependencies for C++0x compilers (i.e.: don't rely on boost for XML and JSON parsing)?
- Separate the creation mechanism from the Catalog class?
- Consider to pass the constructor parameters in another way. Maybe with a generic set property method or with a properties bag passed in the ctor. [done in v. 0.6]
- I definitely don't like MultiplePlug. Above all, I don't like MultiplePlug deriving from std::list. [solved in v. 0.2]
- Improve (or change) the syntax of the xml loading file. [done in v. 0.3]
Documentation and Samples
- More documentation: tutorial page and API documentation.
- More exhaustive samples [done in v. 0.3]


|
Standard Reference Data Program |
Data Gateway |
Chemistry WebBook |
Go To: Top, Constants of diatomic molecules, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled as indicated in comments:
LL - S.G. Lias and J.F. Liebman
LLK - S.G. Lias, R.D. Levin, and S.A. Kafafi
RDSH - H.M. Rosenstock, K. Draxl, B.W. Steiner, and J.T. Herron
View reactions leading to FGa+ (ion structure unspecified)
| IE (eV) | Method | Reference | Comment |
|---|---|---|---|
| 10.7 ± 0.6 | EI | Feather, Buchler, et al., 1972 | LLK |
| 9.6 ± 0.5 | EI | Zmbov and Margrave, 1967 | RDSH |
| 10.6 ± 0.4 | EI | Murad, Hildenbrand, et al., 1966 | RDSH |
| 10.64 | PE | Grabandt, Mooyman, et al., 1990 | Vertical value; LL |
Go To: Top, Gas phase ion energetics data, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled by: K.P. Huber and G. Herzberg
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| C 1Π | 47365.7 | (542.35) (Z) | 9.55 1 | -0.6 | (0.358) | (0.00535) 2 | (1.778) | C ↔ X RV | (47324.1) (Z) | |||
| missing citation; Barrow, Jacquest, et al., 1954; Barrow, Dodsworth, et al., 1957 | ||||||||||||
| B 3Π1 | 33427.8 | 662.1 Z | 1.45 3 | -0.433 | 0.37198 4 5 | 0.00302 | 1.7444 | B ↔ X V | 33448.12 Z | |||
| missing citation; Barrow, Jacquest, et al., 1954; Barrow, Dodsworth, et al., 1957 | ||||||||||||
| A 3Π0+ | 33105.5 | 663.02 Z | 2.18 | -0.31 | 0.37098 4 | (0.00302) | 1.7467 | A ↔ X V | 33126.17 Z | |||
| missing citation; Barrow, Jacquest, et al., 1954; Barrow, Dodsworth, et al., 1957 | ||||||||||||
| X 1Σ+ | 0 | 622.2 Z | 3.2 3 | 0.3595161 | 2.8642E-3 6 | 0.0000102 | 5.0E-7 | 1.774369 7 | ||||
| Hoeft, Lovas, et al., 1970; Honerjager and Tischer, 1974 |
| 1 | This state may have a small potential maximum of ~ 0.26 eV Murad, Hildenbrand, et al., 1966. |
| 2 | Rotational constants estimated from observed R-Q or P-Q head separations and B". |
| 3 | missing note |
| 4 | Recalculated from Barrow, Dodsworth, et al., 1957 with the more accurate ground state constants of Hoeft, Lovas, et al., 1970. |
| 5 | Λ-type doubling, BRP - BQ ~ +6E-5. |
| 6 | missing note |
| 7 | Microwave sp. 9 |
| 8 | Thermochemica1 value (mass-spectrom.) Murad, Hildenbrand, et al., 1966. |
| 9 | μel(v=0) = 2.45 D Hoeft, Lovas, et al., 1970; eqQ(69Ga) = -[107.07 - 1.09(v+1/2)]MHz Hoeft, Lovas, et al., 1970, Honerjager and Tischer, 1974; gJ(v=0) = -0.06012 μN Honerjager and Tischer, 1974. |
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Feather, Buchler, et al., 1972
Feather, D.H.; Buchler, A.; Searcy, A.W.,
The vapor pressures of gallium trifluoride monomer and dimer,
High Temp. Sci., 1972, 4, 290. [all data]
Zmbov and Margrave, 1967
Zmbov, K.F.; Margrave, J.L.,
Mass spectrometric studies at high temperatures. XXI. The heat of atomization of galium oxyfluoride,
J. Inorg. Nucl. Chem., 1967, 29, 2649. [all data]
Murad, Hildenbrand, et al., 1966
Murad, E.; Hildenbrand, D.L.; Main, R.P.,
Dissociation energies of group IIIA monofluorides-the possibility of potential maxima in their excited H states,,
J. Chem. Phys., 1966, 45, 263. [all data]
Grabandt, Mooyman, et al., 1990
Grabandt, O.; Mooyman, R.; De Lange, C.A.,
He(I) photoelectron spectroscopy of the gallium monohalides,
Chem. Phys., 1990, 143, 227. [all data]
Barrow, Jacquest, et al., 1954
Barrow, R.F.; Jacquest, J.A.T.; Thompson, E.W.,
The ultra-violet emission spectra of the gaseous monofluorides of gallium and indium,
Proc. Phys. Soc. London Sect. A, 1954, 67, 528. [all data]
Barrow, Dodsworth, et al., 1957
Barrow, R.F.; Dodsworth, P.G.; Zeeman, P.B.,
Rotational analysis of bands of the A3Π0+, B3Π1-X1Σ+ systems of gallium monofluoride,
Proc. Phys. Soc. London Sect. A, 1957, 70, 34. [all data]
Hoeft, Lovas, et al., 1970
Hoeft, J.; Lovas, F.J.; Tiemann, E.; Torring, T.,
Microwave absorption spectra of AlF, GaF, InF, and TlF,
Z. Naturforsch. A, 1970, 25, 1029. [all data]
Honerjager and Tischer, 1974
Honerjager, R.; Tischer, R.,
Magnetische Konstanten der Molekeln CuF und GaF,
Z. Naturforsch. A, 1974, 29, 1919. [all data]
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, References
Copyright for NIST Standard Reference Data is governed by the Standard Reference Data Act.
|
Standard Reference Data Program |
Data Gateway |
Chemistry WebBook |
If you have comments or questions about this site, please contact us.


NIDC 2021 Workshops
On Thursday 8th October, we will be running a workshops day. While there will be a nominal fee for workshops, which will be donated to charity, it is an absurdly tiny fraction of their street value. Spaces will be very limited, so sign up as soon as you can!
We have {{ len $workshops }} workshops on offer, including Event Sourcing, Data Science and TypeScript, and one for anyone who wants to learn how to turn meetings into decisions:
-
{{ range $workshops }}
- {{ .Title }} from {{ .Params.provider }} ({{ .Params.duration }}) {{ end }}


Click the button to see how many attributes the button element has:
Note: In Internet Explorer 8 and earlier, the attributes property will return a collection of all possible attributes for the element, and will, in this example, display a much higher number than 1.
The result should be 2 (the button element's onclick and class attribute).


Prototyping
For this week's assignment, we were tasked to develop a simple prototype using cardboard, in this case, I chose to do up a phone holder.
Research
This was made when I was sec 1 for one of my D&T projects. With this along with reference to what I found online, I tried to make it foldable.
Process
|
|
- I sketched out the dimensions in 3D roughly on paper and outlined it with a black marker for better visibility. My intention was to make a whole piece with folds so that it could become a box.
- I drew out all the parts onto the cardboard in one long continuous strip as shown in the picture below:
- I use stripes to indicate which areas I need to cut out and remove.
- After cutting them out using a penknife, scissors and a ruler, I scored lines where I needed the cardboard to fold as well as for the flaps.
- Fold into a box and make a valley on the parts where your phone should rest on.
|
Hero Shots
Pros
It can withstand the weight of the phone while it rests on its length
small, can fit into bag
can stored small trinkets inside, even tissue if possible
Cons
Not as tight fitting as I would liked (some gaps)
Did not manage to achieve my goal of it being foldable as I realized in order for the flaps to fit securely, the base needs to be glued together.
Can’t hold the weight of the phone when its placed vertically


From:Campos To:Cordes; Sellers Sent:2017-01-11T04:37:52.0000000Z Subject:O&M/Capital Review with Stan
Below are the times for the O&M/Capital Review with Stan scheduled for Wednesday, September 5, 2001 in EB49C2.
Commercial 8:30 - 9:30 AM
Gas Logistics 9:30 - 10:00 AM
Information Technology 10:00 - 10:30 AM
Operations 10:30 - 11:30 AM
Northern Border Pipeline 11:30 - 12:30 PM
Legal, HR, Reg Affairs 12:30 - 1:00 PM
F & A 1:00 - 1:30 PM
If for some reason there is a problem with your appointed time please send Tracy Geaccone or myself an email.
Thank You,
Kathy Campos
***********
EDRM Enron Email Data Set has been produced in EML, PST and NSF format by ZL Technologies, Inc. This Data Set is licensed under a Creative Commons Attribution 3.0 United States License <http://creativecommons.org/licenses/by/3.0/us/> . To provide attribution, please cite to "ZL Technologies, Inc. (http://www.zlti.com)."
***********
California


--- layout: post status: publish published: true title: MacOS HD TreeMap Tool author: display_name: Fabio Pereira login: admin email<EMAIL_ADDRESS>url: http://fabiopereira.me author_login: admin author_email<EMAIL_ADDRESS>author_url: http://fabiopereira.me wordpress_id: 57 wordpress_url: http://fabiopereira.me/blog/?p=57 date: '2008-12-07 22:01:58 +0' date_gmt: '2008-12-08 05:01:58 +0' categories: - Technical tags: - Tool - Mac comments: [] ---
If you have a Mac and you are running out of space on your HD or you want to know how you are using your space (Photos? Applications? Videos?) Disk Inventory X is a great free tool that shows a treemap of your files grouping them by smart categories.
I was running out of space, now I know why...
Solution: 1 TB external HD


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Note: updated December 2018 for Julia 1.1
Julia makes it easy to write elegant and efficient multidimensional algorithms. The new capabilities rest on two foundations: an iterator called CartesianIndices
, and sophisticated array indexing mechanisms. Before I explain, let me emphasize that developing these capabilities was a collaborative effort, with the bulk of the work done by Matt Bauman (@mbauman), Jutho Haegeman (@Jutho), and myself (@timholy).
These iterators are deceptively simple, so much so that I've never been entirely convinced that this blog post is necessary: once you learn a few principles, there's almost nothing to it. However, like many simple concepts, the implications can take a while to sink in. It's also possible to confuse these techniques with Base.Cartesian
, which is a completely different (and more painful) approach to solving the same problem. There are still a few occasions where Base.Cartesian
is helpful or necessary, but for many problems these new capabilities represent a vastly simplified approach.
Let's introduce these iterators with an extension of an example taken from the manual.
You may already know that there are two recommended ways to iterate over the elements in an AbstractArray
: if you don't need an index associated with each element, then you can use
for a in A # A is an AbstractArray
# Code that does something with the element a
end
If instead you also need the index, then use
for i in eachindex(A)
# Code that does something with i and/or A[i]
end
In some cases, the first line of this loop expands to for i =
1:length(A)
, and i
is just an integer. However, in other cases, this will expand to the equivalent of
for i in CartesianIndices(A)
# i is now a CartesianIndex
# Code that does something with i and/or A[i]
end
Let's see what these objects are:
julia> A = rand(3,2)
julia> for i in CartesianIndices(A)
@show i
end
i = CartesianIndex(1, 1)
i = CartesianIndex(2, 1)
i = CartesianIndex(3, 1)
i = CartesianIndex(1, 2)
i = CartesianIndex(2, 2)
i = CartesianIndex(3, 2)
A CartesianIndex{N}
represents an N
-dimensional index. CartesianIndex
es are based on tuples, and indeed you can access the underlying tuple with Tuple(i)
.
A CartesianIndices
acts like an array of CartesianIndex
values:
julia> iter = CartesianIndices(A)
3×2 CartesianIndices{2,Tuple{Base.OneTo{Int64},Base.OneTo{Int64}}}:
CartesianIndex(1, 1) CartesianIndex(1, 2)
CartesianIndex(2, 1) CartesianIndex(2, 2)
CartesianIndex(3, 1) CartesianIndex(3, 2)
julia> supertype(typeof(iter))
AbstractArray{CartesianIndex{2},2}
As a consequence iter[2,2]
and iter[5]
both return CartesianIndex(2, 2)
; indeed, the latter is the recommended way to convert from a linear index to a multidimensional cartesian index.
However, internally iter
is just a wrapper around the axes
range for each dimension:
julia> iter.indices
(Base.OneTo(3), Base.OneTo(2))
As a consequence, in many applications the creation and usage of these objects has little or no overhead.
You can construct these manually: for example,
julia> CartesianIndices((-7:7, 0:15))
15×16 CartesianIndices{2,Tuple{UnitRange{Int64},UnitRange{Int64}}}:
# remaining output suppressed
corresponds to an iterator that will loop over -7:7
along the first dimension and 0:15
along the second.
One reason that eachindex
is recommended over for i = 1:length(A)
is that some AbstractArray
s cannot be indexed efficiently with a linear index; in contrast, a much wider class of objects can be efficiently indexed with a multidimensional iterator. (SubArrays are, generally speaking, a prime example.) eachindex
is designed to pick the most efficient iterator for the given array type. You can even use
for i in eachindex(A, B)
...
to increase the likelihood that i
will be efficient for accessing both A
and B
. (A second reason to use eachindex
is that some arrays don't starting indexing at 1, but that's a topic for a separate blog post.)
As we'll see below, these iterators have another purpose: independent of whether the underlying arrays have efficient linear indexing, multidimensional iteration can be a powerful ally when writing algorithms. The rest of this blog post will focus on this latter application.
Let's suppose we have a multidimensional array A
, and we want to compute the "moving average" over a 3-by-3-by-... block around each element. From any given index position, we'll want to sum over a region offset by -1:1
along each dimension. Edge positions have to be treated specially, of course, to avoid going beyond the bounds of the array.
In many languages, writing a general (N-dimensional) implementation of this conceptually-simple algorithm is somewhat painful, but in Julia it's a piece of cake:
function boxcar3(A::AbstractArray)
out = similar(A)
R = CartesianIndices(A)
Ifirst, Ilast = first(R), last(R)
I1 = oneunit(Ifirst)
for I in R
n, s = 0, zero(eltype(out))
for J in max(Ifirst, I-I1):min(Ilast, I+I1)
s += A[J]
n += 1
end
out[I] = s/n
end
out
end
(Note that this example is only for Julia versions 1.1 and higher.)
Let's walk through this line by line:
out = similar(A)
allocates the output. In a "real" implementation, you'd want to be a little more careful about the element type of the output (what if the input array element type is Int
?), but we're cutting a few corners here for simplicity.
R = CartesianIndices(A)
creates the iterator for the array. Assuming A
starts indexing at 1, this ranges from CartesianIndex(1, 1, 1, ...)
to CartesianIndex(size(A,1), size(A,2), size(A,3), ...)
. We don't use eachindex
, because we can't be sure whether that will return a CartesianIndices
iterator, and here we explicitly need one.
Ifirst = first(R)
and Ilast = last(R)
return the lower (CartesianIndex(1, 1, 1, ...)
) and upper (CartesianIndex(size(A,1), size(A,2), size(A,3), ...)
) bounds of the iteration range, respectively. We'll use these to ensure that we never access out-of-bounds elements of A
.
I1 = oneunit(Ifirst)
creates an all-1s CartesianIndex
with the same dimensionality as Ifirst
. We'll use this in arithmetic operations to define a region-of-interest.
for I in R
: here we loop over each entry of R
, corresponding to both A
and out
.
n = 0
and s = zero(eltype(out))
initialize the accumulators. s
will hold the sum of neighboring values. n
will hold the number of neighbors used; in most cases, after the loop we'll have n == 3^N
, but for edge points the number of valid neighbors will be smaller.
for J in max(Ifirst, I-I1):min(Ilast, I+I1)
is probably the most "clever" line in the algorithm. I-I1
is a CartesianIndex
that is lower by 1 along each dimension, and I+I1
is higher by 1. However, when I
represents an edge point, either I-I1
or I+I1
(or both) might be out-of-bounds. max(Ifirst, I-I1)
ensures that each coordinate of J
is 1 or larger, while min(Ilast, I+I1)
ensures that J[d] <= size(A,d)
.
Putting these two together with a colon, Ilower:Iupper
, creates a CartesianIndices
object that serves as an iterator.
The inner loop accumulates the sum in s
and the number of visited neighbors in n
.
Finally, we store the average value in out[I]
.
Not only is this implementation simple, it is also surprisingly robust: for edge points it computes the average of whatever nearest-neighbors it has available. It even works if size(A, d) < 3
for some dimension d
; we don't need any error checking on the size of A
.
For a second example, consider the implementation of multidimensional reductions. A reduction takes an input array, and returns an array (or scalar) of smaller size. A classic example would be summing along particular dimensions of an array: given a three-dimensional array, you might want to compute the sum along dimension 2, leaving dimensions 1 and 3 intact.
An efficient way to write this algorithm requires that the output array, B
, is pre-allocated by the caller (later we'll see how one might go about allocating B
programmatically). For example, if the input A
is of size (l,m,n)
, then when summing along just dimension 2 the output B
would have size (l,1,n)
.
Given this setup, the implementation is shockingly simple:
function sumalongdims!(B, A)
# It's assumed that B has size 1 along any dimension that we're summing,
# and otherwise matches A
fill!(B, 0)
Bmax = last(CartesianIndices(B))
for I in CartesianIndices(A)
B[min(Bmax,I)] += A[I]
end
B
end
The key idea behind this algorithm is encapsulated in the single statement B[min(Bmax,I)]
. For our three-dimensional example where A
is of size (l,m,n)
and B
is of size (l,1,n)
, the inner loop is essentially equivalent to
B[i,1,k] += A[i,j,k]
because min(1,j) = 1
.
As a user, you might prefer an interface more like sumalongdims(A,
dims)
where dims
specifies the dimensions you want to sum along. dims
might be a single integer, like 2
in our example above, or (should you want to sum along multiple dimensions at once) a tuple or Vector{Int}
. This is indeed the interface used in sum(A; dims=dims)
; here we want to write our own (somewhat simpler) implementation.
One possible bare-bones implementation of the wrapper looks like this:
function sumalongdims(A, dims)
sz = [size(A)...]
sz[[dims...]] .= 1
B = Array{eltype(A)}(undef, sz...)
sumalongdims!(B, A)
end
Obviously, this simple implementation skips all relevant error checking. However, here the main point I wish to explore is that the allocation of B
turns out to be non-inferrable: sz
is a Vector{Int}
, the length (number of elements) of a specific Vector{Int}
is not encoded by the type itself, and therefore the dimensionality of B
cannot be inferred.
Now, we could fix that in several ways, for example by annotating the result:
B = Array{eltype(A)}(undef, sz...)::Array{eltype(A),ndims(A)}
or by using an implementation that is inferrable:
function sumalongdims(A, dims)
sz = ntuple(i->i ∈ dims ? 1 : size(A, i), Val(ndims(A)))
B = Array{eltype(A)}(undef, sz...)
sumalongdims!(B, A)
end
However, here we want to emphasize that this design — having a separate sumalongdims!
from sumalongdims
— often mitigates the worst aspects of inference problems. This trick, using a function-call to separate a performance-critical step from a potentially type-unstable precursor, is sometimes referred to as introducing a function barrier. It allows Julia's compiler to generate a well-optimized version of sumalongdims!
even if the intermediate type of B
is not known.
As a general rule, when writing multidimensional code you should ensure that the main iteration is in a separate function from type-unstable precursors. (In older versions of Julia, you might see kernel functions annotated with @noinline
to prevent the inliner from combining the two back together, but for more recent versions of Julia this should no longer be necessary.)
Of course, in this example there's a second motivation for making this a standalone function: if this calculation is one you're going to repeat many times, re-using the same output array can reduce the amount of memory allocation in your code.
One final example illustrates an important new point: when you index an array, you can freely mix CartesianIndex
es and integers. To illustrate this, we'll write an exponential smoothing filter. An efficient way to implement such filters is to have the smoothed output value s[i]
depend on a combination of the current input x[i]
and the previous filtered value s[i-1]
; in one dimension, you can write this as
function expfilt1!(s, x, α)
0 < α <= 1 || error("α must be between 0 and 1")
s[1] = x[1]
for i = 2:length(x)
s[i] = α*x[i] + (1-α)*s[i-1]
end
s
end
This would result in an approximately-exponential decay with timescale 1/α
.
Here, we want to implement this algorithm so that it can be used to exponentially filter an array along any chosen dimension. Once again, the implementation is surprisingly simple:
function expfiltdim(x, dim::Integer, α)
s = similar(x)
Rpre = CartesianIndices(size(x)[1:dim-1])
Rpost = CartesianIndices(size(x)[dim+1:end])
_expfilt!(s, x, α, Rpre, size(x, dim), Rpost)
end
function _expfilt!(s, x, α, Rpre, n, Rpost)
for Ipost in Rpost
# Initialize the first value along the filtered dimension
for Ipre in Rpre
s[Ipre, 1, Ipost] = x[Ipre, 1, Ipost]
end
# Handle all other entries
for i = 2:n
for Ipre in Rpre
s[Ipre, i, Ipost] = α*x[Ipre, i, Ipost] + (1-α)*s[Ipre, i-1, Ipost]
end
end
end
s
end
Note once again the use of the function barrier technique. In the core algorithm (_expfilt!
), our strategy is to use two CartesianIndex
iterators, Ipre
and Ipost
, where the first covers dimensions 1:dim-1
and the second dim+1:ndims(x)
; the filtering dimension dim
is handled separately by an integer-index i
. Because the filtering dimension is specified by an integer input, there is no way to infer how many entries will be within each index-tuple Ipre
and Ipost
. Hence, we compute the CartesianIndices
s in the type-unstable portion of the algorithm, and then pass them as arguments to the core routine _expfilt!
.
What makes this implementation possible is the fact that we can index x
as x[Ipre, i, Ipost]
. Note that the total number of indexes supplied is (dim-1) + 1 + (ndims(x)-dim)
, which is just ndims(x)
. In general, you can supply any combination of integer and CartesianIndex
indexes when indexing an AbstractArray
in Julia.
The AxisAlgorithms package makes heavy use of tricks such as these, and in turn provides core support for high-performance packages like Interpolations that require multidimensional computation.
It's worth noting one point that has thus far remained unstated: all of the examples here are relatively cache efficient. This is a key property to observe when writing efficient code. In particular, julia arrays are stored in first-to-last dimension order (for matrices, "column-major" order), and hence you should nest iterations from last-to-first dimensions. For example, in the filtering example above we were careful to iterate in the order
for Ipost ...
for i ...
for Ipre ...
x[Ipre, i, Ipost] ...
so that x
would be traversed in memory-order.
CartesianIndex
es are not broadcastable:
julia> I = CartesianIndex(2, 7)
CartesianIndex(2, 7)
julia> I .+ 1
ERROR: iteration is deliberately unsupported for CartesianIndex. Use `I` rather than `I...`, or use `Tuple(I)...`
Stacktrace:
[1] error(::String) at ./error.jl:33
[2] iterate(::CartesianIndex{2}) at ./multidimensional.jl:154
...
When you want to perform broadcast arithmetic, just extract the underlying tuple:
julia> Tuple(I) .+ 1
(3, 8)
If desired you can package this back up in a CartesianIndex
, or just use it directly (with splatting) for indexing. The compiler optimizes all these operations away, so there is no actual "cost" to constucting objects in this way.
Why is iteration disallowed? One reason is to support the following:
julia> R = CartesianIndices((1:3, 1:3))
3×3 CartesianIndices{2,Tuple{UnitRange{Int64},UnitRange{Int64}}}:
CartesianIndex(1, 1) CartesianIndex(1, 2) CartesianIndex(1, 3)
CartesianIndex(2, 1) CartesianIndex(2, 2) CartesianIndex(2, 3)
CartesianIndex(3, 1) CartesianIndex(3, 2) CartesianIndex(3, 3)
julia> R .+ CartesianIndex(2, 17)
3×3 CartesianIndices{2,Tuple{UnitRange{Int64},UnitRange{Int64}}}:
CartesianIndex(3, 18) CartesianIndex(3, 19) CartesianIndex(3, 20)
CartesianIndex(4, 18) CartesianIndex(4, 19) CartesianIndex(4, 20)
CartesianIndex(5, 18) CartesianIndex(5, 19) CartesianIndex(5, 20)
The underlying idea is that CartesianIndex(2, 17)
needs to act, everywhere, like a pair of scalar indexes; consequently, a CartesianIndex
has to be viewed as a single (scalar) entity, rather than as a container in its own right.
As is hopefully clear by now, much of the pain of writing generic multidimensional algorithms is eliminated by Julia's elegant iterators. The examples here just scratch the surface, but the underlying principles are very simple; it is hoped that these examples will make it easier to write your own algorithms.


LUCIE AUBRAC A film review by Steve Rhodes Copyright 1999 Steve Rhodes RATING (0 TO ****): *** 1/2
May 14th. For couples deeply in love there is frequently something other than their wedding rings that represents their bond and their undying love. For the Aubracs, it is May 14th. Long along they agreed that for as long as they live, they will be together on that day. May 14 is rapidly approaching, and the resistance fighter husband, Raymond Aubrac (Daniel Auteuil from QUEEN MARGOT), is in jail. His resourceful and loving wife, Lucie (Carole Bouquet from FOR YOUR EYES ONLY), is willing to try anything in an attempt to get him released.
LUCIE AUBRAC, based on a true story, weaves a fascinating tale of the French resistance in World War II that's both an intriguing thriller and a touching love story. Avoiding the clichés and excessive melodrama normally associated with such stories, writer/director Claude Berri creates an intensely moving story full of subtlety and grace.
Focusing on the minutia of the underground collaboration rather than on the grand plans, the movie makes palpable the fear and the intense and unquestioning dedication of each of the freedom fighters. The result is a story that has a freshness and an honesty that allows the viewer to see that era in ways that he probably hasn't before.
The first part of the story contains scenes of the troubling normalcy of the life that many lived. In some ways things hadn't changed even in 1943 Nazi-occupied France in which the picture is set. People go to work, to school, to the tailors and even to the seashore. How hard this must have been with friends, relatives and neighbors being routinely rounded up and shot?
("It's a terrible thing to say, but I can't help being happy," Raymond confesses to his wife during a blissful day with their young son, nicknamed Booboo, at the ocean. He and his wife frolic together in the water while their son digs nearby in the sand. An absolutely perfect day if you could just forget that you might be tortured and killed at any moment.)
As the husband, Daniel Auteuil delivers a warm, compassionate performance as a man who is willing to die for a cause but who'd be much happier holding his wife or playing with his son. With a brow creased by horrific worries, Auteuil, in a delicately nuanced performance, displays the husband's pain and desire. A man who seeks no glory but shirks no obligation, he will do whatever is asked of him.
As the strong wife, Carole Bouquet gives an equally strong performance. With intense, penetrating eyes, she's a woman who accomplishes what she sets out to do regardless of the risks involved. The chemistry between them is genuine, and both avoid numerous opportunities to overact.
LUCIE AUBRAC never manipulates the viewer's emotions, but don't be surprised if you get swept up in the tragedy and the intrigue. Full of tension, the story relies on the small events more than the larger ones to create its excitement.
LUCIE AUBRAC runs 1:56. The film is in French with English subtitles. It is rated R for violence and would be fine for teenagers.
The film opens nationwide in the United States on Friday, October 8. In the San Jose area it will be playing at one of the Camera Cinemas.
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belongs to the author.
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Related links: index of all rec.arts.movies.reviews reviews


The Duplicator will create a unique copy of a GoogleDrive file for every student in your GoogleClass.
The duplicated assignments will be placed in a new folder located in your root directory. Each copy will be renamed with the student's name pre-pended and appropriate permissions added to allow the students to retreive the file.
Each student will also receive an email with a link to their individual copy of the file.


Let’s revisit arrow functions.
Arrow functions are not just a “shorthand” for writing small stuff. They have some very specific and useful features.
JavaScript is full of situations where we need to write a small function that’s executed somewhere else.
For instance:
arr.forEach(func)
– func
is executed by forEach
for every array item.setTimeout(func)
– func
is executed by the built-in scheduler.It’s in the very spirit of JavaScript to create a function and pass it somewhere.
And in such functions we usually don’t want to leave the current context. That’s where arrow functions come in handy.
As we remember from the chapter info:object-methods, arrow functions do not have this
. If this
is accessed, it is taken from the outside.
For instance, we can use it to iterate inside an object method:
```js run let group = { title: “Our Group”, students: [“John”, “Pete”, “Alice”],
showList() { ! this.students.forEach( student => alert(this.title + ‘:’ + student) ); /! } };
group.showList(); ```
Here in forEach
, the arrow function is used, so this.title
in it is exactly the same as in the outer method showList
. That is: group.title
.
If we used a “regular” function, there would be an error:
```js run let group = { title: “Our Group”, students: [“John”, “Pete”, “Alice”],
showList() { ! this.students.forEach(function(student) { // Error: Cannot read property ‘title’ of undefined alert(this.title + ‘:’ + student); }); /! } };
group.showList(); ```
The error occurs because forEach
runs functions with this=undefined
by default, so the attempt to access undefined.title
is made.
That doesn’t affect arrow functions, because they just don’t have this
.
``warn header="Arrow functions can't run with
new" Not having
thisnaturally means another limitation: arrow functions can't be used as constructors. They can't be called with
new`.
```smart header="Arrow functions VS bind"
There's a subtle difference between an arrow function `=>` and a regular function called with `.bind(this)`:
- `.bind(this)` creates a "bound version" of the function.
- The arrow `=>` doesn't create any binding. The function simply doesn't have `this`. The lookup of `this` is made exactly the same way as a regular variable search: in the outer lexical environment.
Arrow functions also have no arguments
variable.
That’s great for decorators, when we need to forward a call with the current this
and arguments
.
For instance, defer(f, ms)
gets a function and returns a wrapper around it that delays the call by ms
milliseconds:
```js run function defer(f, ms) { return function () { setTimeout(() => f.apply(this, arguments), ms); }; }
function sayHi(who) { alert(“Hello,” + who); }
let sayHiDeferred = defer(sayHi, 2000); sayHiDeferred(“John”); // Hello, John after 2 seconds ```
The same without an arrow function would look like:
function defer(f, ms) {
return function (...args) {
let ctx = this;
setTimeout(function () {
return f.apply(ctx, args);
}, ms);
};
}
Here we had to create additional variables args
and ctx
so that the function inside setTimeout
could take them.
Arrow functions:
this
arguments
new
super
, but we didn’t study it yet. We will on the chapter info:class-inheritanceThat’s because they are meant for short pieces of code that do not have their own “context”, but rather work in the current one. And they really shine in that use case.


upc_trace - the UPC/GASNet trace summarization tool, version 2.22.0
Synopsis
Description
Options
upc_trace [options] trace-file(s)
UPC trace file summarization script, v2.0 (GASNet v1.26.0)
trace-file(s) may include any mix of UPC trace files and local memory reports
-h -? -help See this message. -o [filename] Output results to file. Default is STDOUT. -report [r1][r2].. Indicate which reports to generate: PUT, GET, BARRIER, MEMORY, and/or TI_ARRAY_COPY. Default: all reports. -sort [f1],[f2]... Sort output by one or more fields: TOTAL, AVG, MIN, MAX, CALLS, TYPE, or SRC. (for GET/PUT/MEMORY, TOTAL, AVG, MIN, and MAX refer to size in bytes: for BARRIERS, to time spent in barrier). Default: sort by SRC -filter [t1],[t2].. Filter out output by one or more types: LOCAL, GLOBAL, WAIT, WAITNOTIFY. -p -[no]peer Output per-peer break down for PUT and GET. -t -[no]thread Output detailed information for each thread. -i -[no]internal Show internal events (such as the initial and final barriers) which do not correspond to user source code. -f -[no]full Show the full source file name. -d Enable debugging output for the parsing script.
As of version 2.0, Berkeley UPC includes upc_trace, a tool for analyzing the communication behavior of UPC programs. When run on the output of a trace-enabled Berkeley UPC program, upc_trace provides information on which lines of code in your UPC program generated network traffic: how many messages the line caused, what type (local and/or remote gets/puts), what the maximum/minimum/average/combined sizes of the messages were.
How to use upc_trace:
o Tracing must be enabled in order to work. By default, tracing is enabled for debug compilations (i.e. if upcc -g is used), but not otherwise (as it incurs some overhead). If you wish to also trace non-debug executables, you must rebuild your UPC system and pass --with-multiconf=+opt_trace to configure.
o You must run your application with upcrun -trace ... or upcrun -tracefile TRACE_FILE_NAME .... Either of these flags causes your UPC executable to dump out tracing information while it executes. The -trace flag causes one file per UPC thread to be generated, with the name the UPC threads number. The -tracefile NAME option lets you specify your own name for the tracing file(s): if the name contains a % character, one trace file per thread is generated, with the % replaced with the UPC threads number. Otherwise, all threads will write to the same file.
Note that running with tracing may slow down your application considerably: the exact amount depends on your filesystem, and the ratio of communication/computation in your program. If you are only interested in a subset of trace information, consider setting GASNET_TRACEMASK and/or GASNET_TRACELOCAL as described in the Berkeley UPC Users Guide.
o After your application has completed, you may run upc_trace on one or more of the trace files generated by your program run:
Running upc_trace on a trace file generated by a single UPC thread shows the information only for that thread. If you pass multiple files from the same application run, the information for the various threads is coalesced, so passing in all the tracefiles generated by a run allows you to see information for the entire application.
There are a number of flags to upc_trace which control what kinds of information is reported, and how it is sorted. See upc_trace --help for details.
Note that upc_trace may take a while to run, especially on large tracefiles. We plan to optimize its performance in the future.
Here is example output from upc_trace for a 4-thread, 2-node test program:
$ upc_trace -t upc_trace-*
Parsing thread info for upc_trace-testtrace-4-14739-0.. Parsing tracefile for upc_trace-testtrace-4-14739-0.. done Parsing thread info for upc_trace-testtrace-4-14739-1.. Parsing tracefile for upc_trace-testtrace-4-14739-1.. done Generating reports..
GET REPORT: SOURCE LINE TYPE MSG:(min max avg total) CALLS ============================================================================= testtrace.upc 9 GLOBAL 4 B 4 B 4 B 8 B 2 Thread 0 4 B 4 B 4 B 4 B 1 Thread 2 4 B 4 B 4 B 4 B 1 testtrace.upc 9 LOCAL 4 B 4 B 4 B 8 B 2 Thread 1 4 B 4 B 4 B 4 B 1 Thread 3 4 B 4 B 4 B 4 B 1 testtrace.upc 18 GLOBAL 100 B 100 B 100 B 200 B 2 Thread 1 100 B 100 B 100 B 100 B 1 Thread 3 100 B 100 B 100 B 100 B 1 testtrace.upc 18 LOCAL 100 B 100 B 100 B 200 B 2 Thread 0 100 B 100 B 100 B 100 B 1 Thread 2 100 B 100 B 100 B 100 B 1 testtrace.upc 20 GLOBAL 100 B 100 B 100 B 200 B 2 Thread 0 100 B 100 B 100 B 100 B 1 Thread 2 100 B 100 B 100 B 100 B 1
PUT REPORT: SOURCE LINE TYPE MSG:(min max avg total) CALLS ============================================================================= testtrace.upc 7 GLOBAL 4 B 4 B 4 B 8 B 2 Thread 1 4 B 4 B 4 B 4 B 1 Thread 3 4 B 4 B 4 B 4 B 1 testtrace.upc 7 LOCAL 4 B 4 B 4 B 8 B 2 Thread 0 4 B 4 B 4 B 4 B 1 Thread 2 4 B 4 B 4 B 4 B 1 testtrace.upc 13 GLOBAL 4 B 4 B 4 B 8 B 2 Thread 1 4 B 4 B 4 B 4 B 1 Thread 3 4 B 4 B 4 B 4 B 1 testtrace.upc 13 LOCAL 4 B 4 B 4 B 8 B 2 Thread 0 4 B 4 B 4 B 4 B 1 Thread 2 4 B 4 B 4 B 4 B 1 testtrace.upc 15 GLOBAL 4 B 4 B 4 B 8 B 2 Thread 1 4 B 4 B 4 B 4 B 1 Thread 3 4 B 4 B 4 B 4 B 1 testtrace.upc 15 LOCAL 4 B 4 B 4 B 8 B 2 Thread 0 4 B 4 B 4 B 4 B 1 Thread 2 4 B 4 B 4 B 4 B 1 testtrace.upc 19 GLOBAL 100 B 100 B 100 B 200 B 2 Thread 1 100 B 100 B 100 B 100 B 1 Thread 3 100 B 100 B 100 B 100 B 1 testtrace.upc 19 LOCAL 100 B 100 B 100 B 200 B 2 Thread 0 100 B 100 B 100 B 100 B 1 Thread 2 100 B 100 B 100 B 100 B 1 testtrace.upc 20 GLOBAL 100 B 100 B 100 B 200 B 2 Thread 1 100 B 100 B 100 B 100 B 1 Thread 3 100 B 100 B 100 B 100 B 1
BARRIER REPORT: SOURCE LINE TYPE MSG:(min max avg total) CALLS ============================================================================= testtrace.upc 8 WAIT 151.0 us 165.0 us 158.0 us 632.0 us 4 Thread 0..1 165.0 us 165.0 us 165.0 us 165.0 us 1 Thread 2..3 151.0 us 151.0 us 151.0 us 151.0 us 1 testtrace.upc 8 NOTIFYWAIT 43.0 us 95.0 us 69.0 us 276.0 us 4 Thread 0..1 95.0 us 95.0 us 95.0 us 95.0 us 1 Thread 2..3 43.0 us 43.0 us 43.0 us 43.0 us 1 testtrace.upc 11 WAIT 241.0 us 330.0 us 285.5 us 1.1 ms 4 Thread 0..1 241.0 us 241.0 us 241.0 us 241.0 us 1 Thread 2..3 330.0 us 330.0 us 330.0 us 330.0 us 1 testtrace.upc 11 NOTIFYWAIT 25.0 us 27.0 us 26.0 us 104.0 us 4 Thread 0..1 25.0 us 25.0 us 25.0 us 25.0 us 1 Thread 2..3 27.0 us 27.0 us 27.0 us 27.0 us 1 testtrace.upc 12 WAIT 142.0 us 164.0 us 153.0 us 612.0 us 4 Thread 0..1 164.0 us 164.0 us 164.0 us 164.0 us 1 Thread 2..3 142.0 us 142.0 us 142.0 us 142.0 us 1 testtrace.upc 12 NOTIFYWAIT 34.0 us 44.0 us 39.0 us 156.0 us 4 Thread 0..1 34.0 us 34.0 us 34.0 us 34.0 us 1 Thread 2..3 44.0 us 44.0 us 44.0 us 44.0 us 1 testtrace.upc 23 WAIT 167.0 us 368.0 us 267.5 us 1.1 ms 4 Thread 0..1 368.0 us 368.0 us 368.0 us 368.0 us 1 Thread 2..3 167.0 us 167.0 us 167.0 us 167.0 us 1 testtrace.upc 23 NOTIFYWAIT 30.0 us 56.0 us 43.0 us 172.0 us 4 Thread 0..1 56.0 us 56.0 us 56.0 us 56.0 us 1 Thread 2..3 30.0 us 30.0 us 30.0 us 30.0 us 1 testtrace.upc 29 WAIT 80.0 us 424.0 us 252.0 us 1.0 ms 4 Thread 0..1 80.0 us 80.0 us 80.0 us 80.0 us 1 Thread 2..3 424.0 us 424.0 us 424.0 us 424.0 us 1 testtrace.upc 29 NOTIFYWAIT 18.0 us 32.0 us 25.0 us 100.0 us 4 Thread 0..1 18.0 us 18.0 us 18.0 us 18.0 us 1 Thread 2..3 32.0 us 32.0 us 32.0 us 32.0 us 1
Puts and gets (accesses via pointer-to-shared) are each reported based on the source line that performed the access with a count and message size statistics. The type (LOCAL vs GLOBAL) indicates whether the access was performed locally using shared memory or using network communication.
The barrier report lists each barrier executed by the program run, grouped by
source line number with a count and timing statistics. Each barrier operation
has two corresponding entries - NOTIFYWAIT indicates the time interval between
the upc_notify and corresponding upc_wait operation for the barrier (will be
very small in the case of upc_barrier), and WAIT indicates the time interval
spent blocking at the upc_wait operation awaiting barrier completion. High
WAIT times generally indicate load imbalance, which could possibly be resolved
by separating the upc_notify and upc_wait operations to increase the NOTIFYWAIT
time and thereby overlap some of the barrier time with useful computation.
REPORTING BUGS
We are very interested in fixing any bugs in upc_trace. For bug reporting instructions, please go to http://upc.lbl.gov.
upcc(1), upcrun(1)
The Berkeley UPC Users Guide (available at http://upc.lbl.gov)
| Berkeley UPC | UPC_TRACE (1) | October 2015 |


The Buterin Questions, #1 Bitmain and Affiliated Pools Now have Approximately 53% of all Bitcoin Hashpower. Isn’t this a Really Big Problem?
By David Ritter, Arnaud Bauer and Steve Melnikoff on Tue, Jul 17, 2018
Introduction: WeChat has some excellent channels for lively and informative discussions focussing on blockchain technologies. Ethereum co-founder Vitalik Buterin recently posted a set of blockchain ‘hard questions’ to one of these, and we are publishing responses here in Medium from Penta Global as a way to extend the conversation across the wider blockchain community, with hopes of furthering the conversation and a productive exchange of ideas.
Q: Bitmain and affiliated pools now have approximately 53% of all bitcoin hashpower. Isn’t this a really big problem?
A: Mining pools are an existential challenge to ‘proof of work’ (PoW) blockchain consensus mechanisms — basically they function like cartels. They concentrate ‘decision making capacity’ in the hands of an elite few, whether through mining pool hashpower or super node ‘proof of stake’ (PoS) structures. For many, clustering together this power is antithetical to principles of decentralization, which we view to be a core tenet of the Blockchain Movement. A key contribution to ‘socioeconomic evolution’ is placed at risk if blockchain platforms abandon the quest to become truly decentralized autonomous communities (DAOs are similar to these).
Ori Brafman and Rod Beckstrom published ‘The Starfish and the Spider’ in 2006, about ‘the unstoppable power of leaderless organizations’.  But if you cut off a starfish’s leg it grows a new one, and the old leg can grow into an entirely new starfish.’ Our own group Penta has adopted these sublime ideas as we deploy our company’s blockchain technology platform. A related treatise also adapted is Eric Raymond’s ‘the Cathedral and the Bazaar.’ Published about a decade earlier than Starfish, it too has helped clarify thinking on ‘decentralization’ in the context of blockchain.
There is strength and robustness in decentralisation as blockchain has shown, and hopefully a bright future ahead for communities bravely taking that journey. But, beyond profiteering, is there anything to be gained from cartel behaviour? Are they simply ‘conspiracies against the public?’ Our opinion, the 53% and increasing control of bitcoin hashpower held by Bitmain-like ‘spiders’ exerts a regulatory influence on BTC. For better or worse, they have become centralized and private self-managers of chains operating under PoW or PoS consensus mechanisms, just like cartels in other industries.
At the start of the California and Australian (one of the authors resides in Melbourne) gold rush eras everyone holding a pickaxe and simple gold pan had opportunity to benefit. But just like after those first heady months 150 years ago, with Bitcoin the accumulation of hashpower and the formation of mining cartels is threatening the existence of lone miners to profit. For proof of stake systems there is similar pressure towards centralisation of control, but perhaps for slightly different reasons involving transactions per second (tps) rates.
Maybe cartels are a natural element of business, and history is repeating itself. A problem for those projects engaged in building peer-to-peer, decentralised ecosystems? Most certainly, and these issues bring into sharp relief a vulnerability (‘flaw’) of Nakamoto’s ‘Bitcoin: A Peer-to-Peer Electronic Cash System’. Empirically, PoW and related consensus mechanisms appear to equilibrate over time to cooperative cartel systems, rather than sustaining themselves through decentralised competition. Maybe now we should seek fresh approaches to point the way forward, and a new generation of technologies to meet this challenge.
The Starfish and the Spider: The Unstoppable Power of Leaderless Organizations, Ori Brafman and Rod Beckstrom 2006; https://www.amazon.com/exec/obidos/ASIN/1591841437/1n9867a-20
The Cathedral and the Bazaar, Eric Raymond 1997; http://www.catb.org/esr/writings/cathedral-bazaar/


There's a simple answer: the regression tests these regression tests actually run under the standard python prompt, so you add a test, run it in standard python, then compile it and test it in the browser.
we are also working to get the regression tests to run under spidermonkey (the mozilla js command-tool), python-spidermonkey (the python bindings to the spidermonkey library) and pyv8 (the python bindings by flier liu - http://code.google.com/p/pyv8 - to the google v8 library).
once _that_ is done, then there is the plan to start running the STANDARD http://python.org regression tests, all 25,000+ of them, through the pyjamas compiler. yes, this is possible. basically, pyjamas becomes a python accelerator, by translating to javascript and using the JIT google v8 engine to execute the resultant code.
Ultimately, though: trust is always given. In other words: it's entirely up to you.


The JDK has extensive APIs for developing custom tools to observe, monitor, profile, debug, and diagnose issues in applications that are deployed in the JRE. The development of new tools is beyond the scope of this document. Instead this section provides a brief overview of the APIs available.
All the packages mentioned in this section are described in the Java SE API specification.
Refer also to example and demonstration code that is included in the JDK download.
The following sections describe packages, interface classes, and the Java debugger that can be used as custom diagnostic tools for troubleshooting.
The Java Platform Debugger Architecture (JPDA) is the architecture designed for use by debuggers and debugger-like tools. It consists of two programming interfaces and a wire protocol.
The Java Virtual Machine Tool Interface (JVM TI) is the interface to the virtual machine, see JVM Tool Interface.
The Java Debug Interface (JDI) defines information and requests at the user code level. It is a pure Java programming language interface for debugging Java programming language applications. In JPDA, the JDI is a remote view in the debugger process of a virtual machine in the process being debugged. It is implemented by the front end, where as a debugger-like application (for example, IDE, debugger, tracer, or monitoring tool) is the client.
The Java Debug Wire Protocol (JDWP) defines the format of information and requests transferred between the process being debugged and the debugger front end, which implements the JDI.
For a complete description of JDPA connection and invocation details, see Java Platform Debugger Architecture (JDPA) documentation.
The jdb
utility is included in the JDK as an example command-line debugger. The jdb
utility uses the JDI to launch or connect to the target VM. For more information about the jdb
utility, see The jdb Utility.
In addition to traditional debugger-type tools, the JDI can also be used to develop tools that help in postmortem diagnostics and scenarios where the tool needs to attach to a process in a noncooperative manner (for example, a hung process).


--- layout: default title: About permalink: '/about/' ---
Got developer of the year three times in a row.


Dawah Academy
HTML • CSS • Wordpress
A website I created using the Elementor plugin within WordPress.
HTML • CSS • Wordpress
A website I created using the Elementor plugin within WordPress.
HTML • CSS • JavaScript
A tip calculator project from Frontend Mentor that works out the tip amount and total per amount of people.
HTML • CSS • JavaScript
A calculator project that does simple arithmetic based on the user's input and then displays the value.
HTML • CSS • JavaScript
A page which shows the day and a live digital clock with hours, minutes and seconds displayed.
HTML • CSS • JavaScript
A basic image carousel that can cycle back and forth through an array of 5 images depending on which button is clicked.
HTML • CSS • JavaScript
A simple project that increases or decreases the counter depending on the button clicked.
HTML • CSS • JavaScript
A simple project to change the background colour of the page by cycling through an array of colours when the button is clicked.


Half-Life: Alyx has been officially announced, first details, screenshots and gameplay trailer
by John PapadopoulosAnd the time has finally come. Valve has officially revealed its new Half-Life VR game, Half-Life: Alyx. The company unveiled the first details about it, as well as its first screenshots. Furthermore, you can find below its debut gameplay trailer.
Half-Life: Alyx is set in the 20 year time gap between Half-Life and Half-Life 2. The game will be using Source 2 Engine and will feature a single-player, story-driven linear FPS campaign. The game will also heavily utilize physics and will include a physical player body.
As Valve noted, Half-Life: Alyx is a new full-length game built from the ground up by Valve for virtual reality.
As the game’s description reads:
“Immerse yourself in deep environmental interactions, puzzle solving, world exploration, and visceral combat.
Lean to aim around a broken wall and under a Barnacle to make an impossible shot. Rummage through shelves to find a healing syringe and some shotgun shells. Manipulate tools to hack alien interfaces. Toss a bottle through a window to distract an enemy.
Last but not least, a set of Source 2 tools for building new environments will ship with the game. These tools will enableany player to build and contribute new environments for the community to enjoy.
Half-Life Alyx will come out in March 2020.
Enjoy!


An enthusiastic Web Developer based in Wolverhampton, looking to bring value to your business through my ever expanding Python/Django skills matched with my years of people skills in high paced retail roles. I am also experienced in customer facing roles, with noted customer service and sales skills throughout multiple well known brands. These years spent in retail roles have helped transfer my drive and passion into my web development studies as demonstrated by my recently obtained First Class Honours in Full Stack Web Development course.
Using Django I created myself a Blog Platform from the ground up and writing custom bootstrap for the front end. Currently working and updating on this project, however the latest stable release is currently running. I am also using custom tiered permissions, allowing me to access the tools i've created and hidden in this site.
During lockdown I created GainsCraft to tick two boxes, keeping me moving and learning how to implement front end graphs filled with Django powered back end Database usage.
Evolving my highest marked coursework project into an ever growing text-based RPG.
I socially have played Dungeons and Dragons for years, and upon learning python I started to create tools and databases to help optimise our playing sessions. This allows me to create ever changing tools with weekly testers, helping me build with users in mind
My third project for my Full Stack Course. The remit was to create a database users could perform CRUD funtions for, and in line with the DND app this allowed me to create a project with end users testing and in mind.
First Class Honours
Distiction
While away from my laptop my passions include playing drums which has been promient in my life for as long as I can remember. Nothing fills me with joy more than performing live and meeting like minded people.
I keep tabs on current goings on, mostly through the form of putting my headphones in, listening to a podcast while going walking. At one point in my life I was 305lbs, and getting outside listening to podcasts started my weight loss journey. I'm now sitting at around 200lbs and have used my experiences to inspire others to do the same


Donald Trump proclaims he wants to negotiate nuclear deals with Russia. Backed by Roy Cohn, the political operative who advised Joe McCarthy and Richard Nixon, Trump said “It would take an hour-and-a-half to learn everything there is to learn about missiles. I think I know most of it anyway. You're talking about just getting updated on a situation… You know who really wants me to do this? Roy… I'd do it in a second.”
Source: Washington Post


Hello all.
I want to discuss the importance of Venus Snakes and share how they can possibly affect your life. Oddly, ONLY African Americans has contacted via cell,
text message, or have came up to speak with me in person to tell me that im David Icke, this is however not case.
As you all are aware, I made a article explaining the moon spider existance with excruciating detail. With my epic 7 year long research on the moon spider i
wondered in other planets in our solar system have this oddity, it turns out THEY ALL DO! With these series of articles I plan to spread my message
one article at a time.
Thanks to my insider at SpaceX and NASA and https://www.nasa.gov/ I have collected enough information to provide this very detailed article.
In 2006, NASA conducted an Apollo 20 mission in the Baikonur Cosmodrome, this was undocument, and there is no media coverage of any kind on this mission except this damning evidence.
With this, we can tell that the snake live on the planet venus its self.  Such as the Spider snake, which is an entire spider but has a snakes tail.
There is also the flying snake, yes a snake with wings, now there is no documented images of the flying snake, because who ever has encountered died and did not take a picture of it. Also there is, Aligator snake, bee snake, Lamar snake, invisble snake, and of course, meca-hitler snake.
These snakes only live on the dark side of venus, except for lava snake. The snakes survive on the solar flares of helium causing them to stay alive on venus for so long.
They also eat other snakes.
Now, this is how the snake affects you! because of helium they inhale they can float for only a limited time. If snakes spent at least a year hibernating and
absorbing the helium, they can fly there way to earth, luckly that has not happened yet.

Next article on Mercury Mosquitoes coming 4.16 thank you.


About Me
I am a Full Stack developer from Minneapolis. I've also been doing web development as a freelancer since 2008. In 2007, I won FBLA's Web Development competition for the state of Florida.
I've been fascinated with computers for as long as I can remember. My first exposure to development happened when I was 8 or 9 - my parents gave me their old computer, a Windows 95 machine, because they had just bought a new one. It did not have a connection to the Internet, so I just played with everything that was already installed. One of the programs that was included was Microsoft FrontPage - a visual developing environment that required no programming ability. I would drag elements on to a page, then look at the source code to see what had changed. I learned HTML and CSS that way. I learned JavaScript mostly by reading the source code from Temporary Internet Files. Most of my practices were bad, but over the years I've caught and corrected many of them.
Since those first years, I've learned a lot of other, non-web languages, but I've never forgotten my first love: web development. Hire me as your next developer!


Hi {{ applicant.name }},
This emails confirms you that we received your answers for the step {{ step.label }} for the application process in {{ applicant.process.label }}. We will read them and inform you about its progress. You can still complete the other steps right now.
If you have any question, you can contact us to this email address or go directly into our office (Anaxagora 3-5, Romantso (Office 204), Athens 105 52).
See you soon in Social Hackers Academy!
Social Hackers Academy Team


{% extends 'layout.html' %} {% block content %}
Automatically unfollow Twitter users in a private Twitter list each month.
1. Create a (private) list on Twitter with 'Dodo' in its title
2. Authorize your Twitter account below (so Dodo has permission!)
3. Follow and add Twitter users to your Dodo list
4. Every month, this app will automatically unfollow them for you
1. A ~/.js script that automatically adds and mutes accounts you follow to your Dodo list (script is here)
2. Trapper, a service that automatically follows back users who have followed you throughout the day (runs daily)
3. Our HTTP Dodo-API that mutes and adds an account to your Dodo list
4. Hunter, a service that listens to the firehose of tweets and follows/mutes/adds to dodo list the tweeter


Pick up or Delivery?
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Personalize your pizza! Pick any and all toppings.
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Multi-touch interaction
Tap, Hold or Swipe me 1
Tap, Hold or Swipe me 2
Tap, Hold or Swipe me 3
Start/Stop event logging
Clear the log


Shortly about us
We create awesome movies and other premium video content. Our creative team has members who work together to present excellent videos always.
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We create awesome movies and other premium video content. Our creative team has members who work together to present excellent videos always.
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We create awesome movies and other premium video content. Our creative team has members who work together to present excellent videos always.
Latest Films
Potato Potahto
A divorced couple decides to live together and they seem to be able to pull it off
until they start dating other people
Seven and half dates
A young hardworking lady tries to find love with help from her dad.
She ends up with a lot more than that
Heaven's Hell
A young hardworking lady tries to find love with help from her dad.
She ends up with a lot more than that
My name is not Olosho
A young hardworking lady tries to find love with help from her dad.
She ends up with a lot more than that
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Join now for access to our list of pop-up dinners in the Evanston area.
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Ready to host a PopUp meal at your place? Send us an email and we'll help you through each step to make putting on a successful meal easy as cake!
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Simple properties are source, creator, file, file_date, created and modified. They all are self explanatory and can be accessed/modified by simple classic structure mean like:
>> T.source
>> T.source{:}
>> T.source{1:end}
>> T.modified = now
>> T.creator = 'Your Name'
>> T.creator(1:4) = 'Mine'
Note that you can use either {} or () to access the content for these properties.


30 million euro investment in 405 schools announced
A 30 million euro package for more than 400 schools across Ireland has been announced.
The funding has been allocated to carry out specialist improvements.
The Summer Works Scheme also includes a new climate action focus with schools allocated funding asked to plan for electric vehicle charging points.
Education Minister Joe McHugh described the focus for the scheme as upgrading and improving life safety systems such as fire alarms and detection and emergency lighting, as well as new surfaces on play areas and car parks.
Sorry, this content isn't available on your device.
“In total 405 primary and post-primary schools will benefit from the Summer Works Scheme – that’s more than a tenth of all the schools in the country in one go,” he said.
Meanwhile the climate action initiative will see schools who receive funding for car parking and play areas required to identify a point for electric vehicle charging.
“The climate action element of next year’s summer works is a sensible plan for the future,” Mr McHugh said.
“More and more electric charging points are coming on stream and it is symbolic that schools will be demonstrating how important initiatives like this are.
“The work will be carried out in schools mainly over the summer months, so the disruption to students, teachers and other staff will be kept to a minimum.”
All schools approved for the 2020 Summer Works Scheme are being notified by the Department with further details and instructions on how to proceed.


We buy platforms!
- monetize bricks-and-clicks ROI
- productize vertical partnerships
- engage viral bandwidth
- strategize efficient e-business
- matrix distributed architectures
- incubate innovative ROI
- target real-time content
- whiteboard world-class partnerships
- maximize turn-key convergence
- aggregate open-source interfaces
- productize web-enabled relationships
- matrix interactive content
- syndicate bricks-and-clicks functionalities
- mesh bleeding-edge networks
- incubate impactful e-services


bes(3f) - [M_bessel::INTRO] calculate Bessel functions J(X), Y(X), I(X), K(X) for doubleprecision arguments and integer orders
Synopsis
Description
Options
Authors
Example
subroutine bes(x,no,kode,rslt1,rslt2,t1,t2,ierr)
This routine calculates the Bessel functions J(X),Y(X), I(X), or K(X) for doubleprecision arguments and integer orders. Backwards recurrence techniques are used for the J(X) and I(X) functions except for very small arguments, where double precision series evaluation is used. Forward recurrence is used for the Y(X) and K(X) functions with double precision Chebyshev approximations used for function initialization. Accuracy is between thirteen and fourteen significant figures. For specific functions J0(), J1(), Y0(), Y1(), See BESJ0(), BESJ1(), BESY0(), and BESY1().
Description of parameters
X = input,doubleprecision argument of the Bessel function. The argument may be positive,zero, or negative (neg. arg. for Y(X) or K(X) produces error message since results may be complex.) Restriction on range isFOR J(X), -1100.0 .LE. X .LE. 1100.0 FOR Y(X), 0.0 .LE. X .LE. 1100.0 FOR I(X), -600.0 .LE. X .LE. 600.0 FOR K(X), 0.0 .LE. X .LE. 600.0
NO = Input,integer order of function desired for a single value to be returned, or the maximum order desired (+ or -) if an array of values is to be returned. Let XX = abs(X). Then bounds on orders are
1. For 0.0 .LE. XX .LE. 0.025, The absolute value of maximum order, ANO, and argument supplied (ABS(X)) must satisfy the relation
log(GAMMA(ANO))-ANO*log(XX/2.0) + log(XX)/2.0 .LE. 679.0
For a given argument and an order greater than that allowed by the above relation
JN(X) = 0.0, N.NE.0, AND =1.0 FOR N=0 YN(X) = -INF IN(X) = 0.0, N.NE.0, AND =1.0 FOR N=0 KN(X) = INF 2. FOR 0.025 .LT. XX .LE. 0.20, ABS(NO) .LE. INT(140.0*XX + 83.0) 3. FOR 0.20 .LT. XX .LE. 1.0, ABS(NO) .LE. INT(42.0*XX + 102.0) 4. FOR 1.0 .LT. XX .LE. 20.0, ABS(NO) .LE. INT(0.02*XX**3 - 0.86*XX**2 + 17.15*XX + 124.0) 5. FOR 20.0 .LT. XX .LE. 100.0, ABS(NO) .LE. INT(2.75*XX + 228.0) 6. FOR 100.0 .LT. XX .LE. 400.0, ABS(NO) .LE. INT(1.67*XX + 336.0) 7. FOR 400.0 .LT. XX .LE. 1100.0, ABS(NO) .LE. INT(1.33*XX + 470.0)
KODE = Input,integer indicator for the particular function to be computed.
KODE = 10 -- FUNCTION J(X) ONLY = 11 -- Y(X) ONLY = 12 -- J(X) AND Y(X)
= 20 -- I(X) ONLY = 21 -- K(X) ONLY = 22 -- I(X) AND K(X)
RSLT1 = output,contains the doubleprecision function value for J(X) or I(X) corresponding to the order and argument supplied, depending on the KODE value. This parameter would contain the result if only one function value is to be returned.
RSLT2 = output,contains the doubleprecision function value for Y(X) or K(X) in a manner similar to RSLT1.
T1 = output,a work area which will contain the array oF doubleprecision function values for J(X) or I(X) of orders zero through NO, depending on KODE. T1 must be dimensioned in the calling program and must contain at least M cells of storage, where
M = MAX(ABS(NO),INT(2*ABS(X))) + 51
In using the array, T1(1) = function of order 0, --- T1(NO+1) = function of order NO.
T2 = Output,similar to T1 for the functions Y(X) or K(X). an exception is that if only J(X) or I(X) are called, then T2 needs no dimension in the calling program, but the parameter must still appear in the calling sequence. Otherwise, T2 must be dimensioned at least M.
IERR = Output,error flag for the conditions
-- Normal code =0, Normal - No errors -- Abnormal codes =1, Argument out of range =2, Order too large for argument supplied =3, Argument too large for I(X) and K(X) =4, Negative arguments for Y(X) or K(X) =5, Incorrect parameter KODE
BS is documented for the original version in SC-M-69-336
Based on routines originally from
Sandia Mathematical Program Library Applied Mathematics Division 2642 Sandia Laboratories P. O. Box 5800 Albuquerque, New Mexico 87115 Control Data 6600 Version 5.1, 10 December 1973Written by Ronald D. Halbgewachs, July, 1968. Modified by RDH for increased accuracy, May 8,1973.
| Nemo Release 3.1 | bes (3) | July 22, 2023 |


Kaizer Chiefs coach blasts Zim Warriors technical team over Khama Billiat injury
Outspoken Kaizer Chiefs coach Ernst Middendorp has once again openly attacked the Warriors technical team over talismanic winger Khama Billiat.
Billiat took part in Zimbabwe’s two AFCON 2021 qualfiers against Botswana (at home) and Zambia (away) scoring a brace in the latter but reportedly returned to Naturena with a tight harmstring after the international break, forcing him out of Amakhosi’s Telknom Knockout defeat to Maritzburg United.
After the Maritzburg defeat, the German coach criticised the Joey Antipas-led technical team over the maner in which Billiat was used and yesterday, Middendorp complained once more in that regard.
No, no,” Middendorp said in an interview with Soccer Laduma, when asked if there is an any sort of communication between him and the Warriors technical team.
“Serving the country is important, serving the country in Zambia, in Zimbabwe, in South Africa is important and that’s fine, it is a given situation so I have to send (the players), FIFA rules are there, even if he has a broken arm or leg, we have to send them,” he said.
Middendorp also made made some comparisons between the Zimbabwe technical team and their South African counterparts.
He said: “I don’t even know who is the one to talk to in Zimbabwe or Zambia, meanwhile there is a good communication with Molefi (Ntseki), the Bafana coach and with David Notoane at U23 and I think that it should be that the initiative should come out of the camp of the national team, to look in to who is injured and who has an issue.”
agencies


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3 references to operationCount
Microsoft.Management.Infrastructure.CimCmdlets (3)
CimAsyncOperation.cs (3)
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DebugHelper.WriteLogEx("Disposed {0}, Operation Count {1}", 2, this.Disposed, this.
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bool isActive = (!this.Disposed) && (this.
operationCount
> 0);


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Define planning organizing staffing coordinating of management
In this function coordinating refers to management activities related to achieving an efficient use of resources to attain the organization's goals and objectives.
http://wiki.answers.com/Q/Define_planning_organizing_staffing_coordinating_of_managementFactors for Successful Coordination - - State Services Commission
A useful complement to the present document is Getting Better at Managing for Shared. Outcomes: . Table 1: Advantages and Disadvantages of Coordination .
http://www.ssc.govt.nz/sites/all/files/Factors-publication.pdf
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5 most importance advantages of coordination in management
Jun 14, 2011 . 5 most importance advantages of coordination in management. Coordination helps to improve the efficiency of operations by avoiding .
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Organizational Structure (Encyclopedia of Management) - eNotes.com
Encyclopedia of Management - Organizational Structure. . Yet, despite the advantages of coordination that these structures present, they may hinder tasks that .
http://www.enotes.com/organizational-structure-reference/organizational-structure-176847 -
Benefits of Supply Chain Management Practices A Study of Select ...
the benefits of SCM practices. Keywords: Supply Chain Management, Reduced Lead Time, Cost Saving, Resource. Planning, Increased Coordination between .
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Management - duties, benefits
Management involves the coordination of human, financial, material, and . and to redesign jobs to take advantage of individuals' strengths and weaknesses.
http://www.referenceforbusiness.com/encyclopedia/Kor-Man/Management.html -
Skills and Competencies in Organizational Management
Simply put, coordinating is monitoring and adjusting resources and processes to . Organizational Performance Management (balanced scorecard, TQM, etc.) . Pay and Benefits .
http://managementhelp.org/management/skills.htm


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Dear Delegates,
It gives me immense pleasure to welcome you to the first-ever online Bangalore Junior Model United Nations Conference at Oakridge International School on the 9th and 10th of October.
As your Secretary-General this year, I would like to extend a very warm welcome to all of the new delegates joining us this year, and a very special welcome to all of the delegates returning to the JMUN. My team and I have worked extremely hard over the past month to ensure that you have a safe, enjoyable, and memorable event. With the theme, "Advancing Human Rights during a Pandemic," we hope to inspire fruitful and detailed debate that will allow you to solve some of the world's biggets and most pressing problems. New or old, I hope that the 5th edition of the Bangalore JMUN will be an important milestone in your MUN journey. More information on the JMUN, rules of procedure, and MUN training material is available on the front page of the website and additional details can be found on the conference page.
Please do not hesitate to contact us if you have any queries or concerns at<EMAIL_ADDRESS>I look forward to seeing you all there!
Sincerely,
Aarush Mehrotra
Secretary-General, Bangalore JMUN 2020
The 2020 edition of the Bangalore JMUN will be held virtually over Microsoft Teams.


I finally moved my project "database schema reader" from Codeplex to Github.
Github import was simple and quick. I didn't import the historical issues (the project went on Codeplex in 2010, and it was a couple of years old then). I just added an "upstream" remote so I can still push to Codeplex and keep it updated.
Codeplex comments and discussions are disabled at the moment; "we're anticipating that this functionality will be re-enabled early next week"!  There are many third-party services that integrate with Github, but nothing links into Codeplex.
The main advantage of the move to Github was hooking into Appveyor for CI builds. It took a few builds to experiment with things. I'm using database integration tests with SqlServer, SQLite, PostgreSql and MySql. Now these are working, the tests are more portable - I can easily recreate the databases. The packaging of the builds (dlls into a zip, plus a nuget packages) was also easy, and can create releases within Github. The appveyor.yml file isn't the easiest way to configure builds, and I soon figured out it's better to use the website UI.
Overall, much better than TFS (ugh!) and TeamCity builds. I played a little with Travis CI (building in Mono), but for now it's not worth pursuing.
I tried Coverity for code analysis, which flagged a few (minor) things, but didn't seem to add a lot more than FxCop.
I looked at Coveralls, a code coverage service. Code coverage is 77%, incidentally, which I think is quite good for something that includes code to support Oracle, DB2, Ingres, 3 different Sybase databases, VistaDb, Firebird and Intersystems Cache (for now, these must continue to be tested on my machine only.). I don't believe code coverage is very useful, so for now I won't include this into the Appveyor build.
I'm very impressed, and very happy with Appveyor.


Read Matthew 1:5, 16. Who is the ultimate offspring of this family?
What does Mark 10:45 say about Him?
Rachel did come with us on the Habitat for Humanity build that Saturday. The offer of a Saturday of free babysitting was more than a single mom could resist! She had never worked with construction tools before, but she was able to hammer in a few nails in sheetrock, help prepare lunch, and bring water to other workers on a very hot Texas day. Best of all she met Rosario, the single mom for whom we were helping build the house. Rosario had a sad story of her own, but there she was working alongside us, excited to help finish the first house she and her four kids would get to call home. Hearing Rosario’s story and watching her work so hard alongside those who had come to help her really had an effect on Rachel. Her own story seemed less overwhelming as she focused on someone else’s needs for a few hours. When she returned home that day, nothing in her circumstances had changed, but something in her outlook was definitely shifting in a new direction.
Have you ever felt overwhelmed by grief, hopelessness, or depression? What helped you emerge from that cycle?
We worship a God who serves. He came to earth not as a magnificent king but as a lowly rabbi. When the opportunity presented itself for Him to sit back and be catered to at His last dinner on earth, He instead took the role of servant, washing the feet of those who followed Him. That role of serving those He loves is one He is still acting on today.
Pray About It
Jesus, thank You that instead of insisting on glory and riches, You took on the form of a servant. You didn’t have to humble Yourself and look to serve our greatest needs, but You did, and I am grateful. Make me more like You. Make me a servant. Change my heart and help me to change Your world. Amen.


How to set up new DASD (disk) for use with VM/370 under hercules
I am a bit rusty on my CP/CMS commands so I tried googling the syntax of something regarding DASD. What I found were about 300 endless threads about setting up new DASD for use as Mini Disks for CMS users. Most of the discussion was off on wild tangents and never really answered the newbie that asked the questions. Here is the long and short of it assuming you have the ever popular starter VM/370 system up and running in hercules.
You will have to know a tiny bit of CMS like how to copy files and use the editor but not a whole lot of other things. This is sort of a place holder in case I have to refer some other people to it.
I am assuming you are logged on as MAINT and that you have made a copy of the default directory (I believe it is called “RELEASE6 DIRECT” on MAINT’s 194 device) to USER DIRECT on your A minidisk all you need to do now is run DIRECT USER DIRECT and you should be golden. There is no reason to run DMKFMT card deck unless you are generating a new VM and want to setup a new directory, spool, etc. When you log in to your new user you do need to use the CMS FORMAT 191 A command.
RB


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