text:
\section{Introduction}

Understanding the formation of massive young stars in the immediate
vicinity of massive black holes is challenging. Two plausible
models for  the origin of the disk of massive stars
orbiting Sgr A*, the 4$\times10^6$ M$_{\odot}$ black hole
at the Galactic center,
have been proposed,
namely, in-situ star formation and the dynamical
migration of star clusters (see Genzel, Eisenhauer and Gillessen
2010; Levin and Beloborodov
2003; Gerhard 2001; Nayakshin et al. 2007). It has become clear that the
in-situ star formation model can account for present observations better than
the migration scenario in which a young star cluster undergoes
dynamical friction and spirals  toward the Galactic center. The question then
arises as to what extent disk formation near Sgr A* can
provide insight in the formation of sub-parsec gaseous disks orbiting
supermassive black holes in AGNs. To address this question, we will first
focus on the origin of Galactic center stellar and molecular disks near
Sgr A* followed by AGN disks in the context of partial cloud capture by
the massive black hole. We then discuss observational signatures
such as the scaling relation between the mass of the black hole and the size of
the disk as well as
the recoil of the black
hole
in the context of the cloud capture  scenario.  A more detailed account of the
results presented here can be found in Wardle and Yusef-Zadeh (2008, Paper
I), Yusef-Zadeh et al. (2009, Paper II) and Wardle and Yusef-Zadeh (2011,
Paper III).

\section{Galactic Center Young Stellar Disks}

Observations of our Galactic center indicate that there are about 100 massive young stars
distributed
within one or two disks  with a sharp inner edge (Paumard et al. 2006; Lu et al. 2010).
In the in-situ formation scenario, an interstellar cloud is tidally disrupted and captured by Sgr A* (Nayakshin,
Cuadra \& Spingel 2007).
There are two issues   that are of interest in the context of
this mode  of star formation.
One  is  related to
the mechanism in  which  massive stars are formed in a disk.
If the gas disk is significantly massive, it can become
gravitationally
unstable
resulting in the fragmentation and formation of stars.
A cooling self-gravitating gas disk around a black hole becomes unstable to
fragmentation on a dynamical time scale if
Toomre's  Q$<1$.
In this picture,  the strong  tidal force by the black hole plays a dual
role. On the one hand,
tidal shear acting  against self-gravity
stretches  the cloud in the radial direction, making it
more difficult
for the cloud to fragment. On the other hand,
the gas is tidally squeezed in  the vertical direction,
parallel to the disk axis,
thus,  making it easier to resists the gravitational stress by
increasing  the gas density to the Roche's critical value.
As the cooling time is comparable to the dynamical time scale, stars in a hot disk
are formed in self-gravitating  clumps
with a range of eccentricities and
inclinations as the disk circularizes (Nayakshin et al. 2007;
Wardle and Yusef-Zadeh 2008; Bonnel and Rice 2008; Alig et al. 2011).
Simulations
of the capture of a cloud
suggests that star formation during such an
event will occur before the disk is  fully circularized and
becomes dynamically cold (Mapelli et al.\ 2008).
This is in contrast to a cold self-gravitating disk that
forms stars with  small eccentricities.
Large eccentricities could not easily be built up from initial circular orbits in a
cold disk, thus, the hot disk scenario may better explain the observed
stellar kinematics

The second  issue  is related the mechanism in which a cloud loses angular momentum
to form a disk  so close to Sgr A*.  The cloud has no means of getting rid of its
angular momentum and it is difficult and rare to capture a
compact cloud by a massive black hole  without being engulfed.
However, nature provides an easier mechanism to bring the
gaseous material closer in to the black hole. This is done
 by the capture of material from an extended cloud passing  on opposite sides of
the black hole, thus allowing
the loss of much of the  angular momentum  of gravitationally
focused gas.
The gaseous material with large impact parameters can
settle much closer to the black hole, thus higher gas density is achieved.
Given  the level of asymmetry and  inhomogeneity in the spatial  distribution
of  the cloud,
the cloud capture event may even account for
multiple
counter-rotating disks  with different inclinations.
Figure 1 shows a diagram of a cloud impacting Sgr A*. The gravitational focusing of an incoming
molecular cloud is shown in the top panel whereas the outer  region of the cloud that is
not captured continuous its motion in the direction away from Sgr A*.
The inner region of the cloud is carved out, captured and circularized to form a disk.

\section{Galactic Center Molecular Disk}

Multi-wavelength studies of the
Galactic center  show that
a 2-parsec clumpy molecular ring
circles Sgr A*  with a rotational
velocity of about 100 km s$^{-1}$ (Christopher et al. 2005).
The observed CO  and HCN (G\"usten et al.\ 1987) emission indicates
a total mass of $\sim 10^5$
M$_{\odot}$.  However,
HCN
observations imply that there is high density material close to the inner
edge (Christopher  et al. 2005) suggesting that the
mass may be closer to $10^6$ M$_{\odot}$.
The application of the formation  scenario to the
circumnuclear ring of gas argues that this disk was recently
captured, is currently  settling down  and is on
the verge of forming stars (Paper I, Paper III).

The extent of the ring suggests an initial migrating cloud speed towards
the lower end of the 50--100 km s$^{-1}$  range.
The Hoyle-Lyttleton
radius is about 12\, pc which is
similar to  the  outer radius of the molecular ring.
 On this scale, one expects
considerable asymmetry in the cloud material passing by Sgr A* during the
capture event, with a corresponding reduction in the net cancellation of
angular momentum during the capture process (cf.\ Bottema \& Sanders 1986).
At first sight our model suggests that the circumnuclear ring could  become
 unstable to gravitational fragmentation (Paper I),
but this assumes that it
has kinematically relaxed.  The velocity dispersion of the ring is $\sim$30 km
s$^{-1}$, so that it is not unstable unless its mass is $10^6$\,M$_{\odot}$.

Methanol and
water masers have recently been detected
suggesting that  star formation is taking place
(Paper II).  It
appears that the circumnuclear ring is still in the process of settling
down soon after formation.  The ring's orbital time scale at 2 pc is $\sim
10^5$\,yr, so this implies that the age of the ring is $\leq 10^6$\,yr.
If this is so, the remains of the original interloper cloud should lie
within $\sim 100$\,pc of Sgr A*. One candidate is the +50 km s$^{-1}$\ molecular
cloud which extends along the plane from the Galactic center to
l$\approx0.2^0$ and consists of a number of bound cloudlets with a total
mass of $\sim10^6$ M$_{\odot}$. This cloud is
thought to lie about 30\,pc behind Sgr A*, consistent with an interaction
$\sim3\times10^5 $ years ago.

\section{AGN Megamaser Disks}

Recent VLBA observations have discovered several sub-parsec  megamaser disks with high inclinations
in the nuclei of Seyfert 2
galaxies (Herrnstein et al. 2008; Kuo et al. 2010).
The inner and outer radii are determined by milli-arcsecond observations.
The mass of the disks are measured accurately
because these
disks lie well within the sphere of influence of their host black holes
and are not self-gravitating.
Figure 2 shows an
empirical linear correlation between the disk radius and the black hole mass.
There is a well-defined upper envelope to the maser disk radii which scales linearly with black hole mass, given
approximately by
    $\rm R_\mathrm{max} \sim 0.3\,\,M_7\;\mathrm{pc} \,, $
where the central black hole mass is
$M=M_7\times10^7$\,M$_\odot$.

The remarkable similarity of size scale of the stellar disk surrounding Sgr A* and the megamaser
disks suggest that they could be formed the same way. Paper III shows that  for plausible
estimates of
the mass and angular momentum of the captured material, this process naturally reproduces the
empirical linear relationship between maser disk size and black hole mass.  The capture of clouds
with column densities $\leq 10^{23.5}$ cm$^{-2}$ results in a non-self-gravitating disks of the
correct scale and sufficient column density to allow X-ray irradiation from the central source to
reproduce thin megamaser disks.  By contrast, the capture of a cloud with higher column density
would instead create a self-gravitating disk giving rise to rapid star formation.

In the context of disk formation, the disk size scales with black hole
mass. The reason for such a scaling is as follows. The mass of the disk
depends on the Hoyle-Littelton capture radius and the column density of
the initial cloud. The size of the disk depends on the capture radius
which itself depends on the mass of the black hole and the angular
momentum cancellation. Thus, the cloud capture model implies
that the radius of the disk depends
linearly on
the mass of the black hole.

\section{Cloud Migration}

How do molecular  clouds migrate toward Galactic nuclei?
The inner 200\,pc of the Galaxy is rich in dense molecular clouds, many of which
are on eccentric orbits (Bally et al.\ 1988; Oka et al.\ 1998; Martin et al.\ 2004; Jones et al. 2011).  In addition to
the +50 km
s$^{-1}$ molecular cloud and other members of a disk population of molecular clouds distributed within the inner
30\,pc of Galactic center.  Their non-circular, elongated motion is thought to be induced by the Galaxy's barred
potential (see Kim et al. 2011), with dynamical
friction
aiding migration to the central regions of the Galaxy.
The bar potential of the
Galaxy
can apply  a torque to the clouds, thus trigger infall
toward the nucleus (see F. Combes in these proceedings).
Recent simulations also suggest that gas supplied to galactic
centers is controlled by angular momentum
transfer from one massive gas clump to another during gravitational encounters (Namekata \& Habe 2011).
In the context of a transition from
X1 to X2 orbits, the gas clouds lose angular momentum spiraling in toward
the central region of the Galaxy. In order to bring gaseous material close in to the inner
few pc,  the bar must be  nested (Namekata et al. 2009).

Some of these inward-moving clouds may interact with their host supermassive black holes.
In our own
Galaxy, the circumnuclear molecular ring (e.g.\ Christopher et al. 2005) at a distance of 1.7\,pc
from Sgr A*, the 50 km s$^{-1}$ molecular cloud,
and the circumnuclear rings found on scales of several parsecs from
the center of
numerous Seyfert galaxies suggest an ample supply of material.
The rate of
migration of molecular material is estimated to be about $10^4-10^5$ {\hbox{M$_\odot$}}
per $10^6-10^7$ years.
The age of the stellar disk  (Paumard et al.\ 2006), and the relative youth
of the
circumnuclear ring (Paper II) is consistent with the age estimate  implying
that the rate of encounters of
massive clouds with Sgr A* is
$\sim 10^{-6}\ $ yr$^{-1}$.
This may have been been ongoing for a significant fraction of the Galaxy's lifetime as the stellar population in
the central parsec is consistent with roughly constant star formation over the past 12\,Gyr (Maness et al.\
2007).

\section{Black Hole Recoil}

The partial capture of a cloud with incident  velocity $V_{initial}$
imparts momentum to the system of black hole with a mass M$_{BH}$ and gaseous
disk with  a mass  $M_{Disk}$,
implying    a kick velocity
\begin{equation}
V_{kick} = \frac{M_{Disk}\times\,  V_{initial}} {M_{BH} +  M_{Disk}}
\end{equation}
to the black hole.
Given that black holes like Sgr A* are embedded in their host  nuclear cluster, the black hole
is expected to move with respect to the center of the cluster
and exchanges heat with the cluster due to dynamical friction.
The recoil is of the order of few km s$^{-1}$ and is
likely to be damped via  dynamical friction on the
surrounding stars, on a
timescale of the  stellar crossing time across the sphere of influence, $\sim 10^3$\,years.
However, the parameter space for  the significance of the recoil
to the black hole in different
nuclear cluster environment  has not been explored.

\section{Conclusions }

In summary, we have investigated the capture  of  gas clouds by massive black holes via
the Hoyle-Lyttleton  process.
We applied this mechanism to three different evolutionary phases of cloud capture scenario.
One is a subset of AGN megamaser disks with high inclinations.  There is
no apparent star formation in these
disks which lie  within the sphere of influence of their host black holes.
Second  application of the cloud capture scenario
is to the  2-parsec molecular disk orbiting Sgr A* where the gaseous disk  is
young. It has been argued that  this system is
showing  early  signatures of star formation. Lastly,
sub-parsec stellar disk orbiting Sgr A* where massive star formation
has already taken  place a
few million years ago.

The lack of star formation in  megamaser disk  systems could be due to
strong magnetic fields acting against self-gravity of the disk
(Johansen and Levin 2008; Gaburov, Johansen and Levin 2011).
Alternatively, the low column density may be responsible.
Assuming that  the tidal shear by the black hole is accounted for, then the mass-to-flux ratio
is an important parameter for the comparison of  self-gravity
and the magnetic field.  Thus, the lack   of  star formation depends
on the column density of incoming clouds and the magnetic field of the disks  rotating around  massive black
holes.  Future  molecular line and magnetic field observations of
thermal gas in these  disks  should be quite useful.

The physical relationship that threads through these different
systems is the capture of a cloud by
engulfing  the massive black hole. This is an effective way to
get rid of the angular momentum of the incoming molecular cloud.
The  engulfing scenario can also be applied when a star
approaches the tidal disruption radius of a massive black hole.
We speculate that these  processes  could operate in
galaxy mergers, dense stellar cusps around massive black holes, leading
to starburst activity, black hole growth  and powerful  flaring activity
 in the vicinity of  central massive black holes.

We found a  scaling relation between the radius of the captured disk and the massive
black hole which  appears to be supported
by the Hoyle-Lyttleton  capture process. The outer radius of the captured cloud is understood
in terms of a physical truncation of the disk because the scale determined
kinematics of cloud capture depends linearly on the black hole mass.
The apparent  inner radius of the captured disk  can be understood
if the disk is warped in such a way that the inner disk does not get
sufficient exposure to the central source of
X-rays, to  produce
22\,GHz H$_2$O  (Maloney et al. 2002).
As for the  disk of stars orbiting Sgr A*, the inner radius  is 0.03pc.
In this case, it is possible that the stars that are formed within the inner 0.03pc
are influenced by
dynamical processes. In fact, there is a cluster of B-type stars with eccentric orbits
distributed isotropically within the inner radius
but with a completely different distribution than that of the disk of stars.
Alternatively, it is possible that  the captured gas within the inner radius
is   dissipated to high temperature and does not have sufficient density to overcome
the tidal stress.  This idea could be relevant to the formation of the
inner radius of the
circumnuclear molecular ring where  hot  stars of  the disk are thought  to have ionized the inner 1.7pc of molecular gas
and created  a cavity of
molecular gas in this region.

\section{References}

\medskip

redpajama_set_name: RedPajamaArXiv


i have all the lyrics to my favorite miles davis songs. i made them up of course. and i forget them and put on the music again (and again). reinventing them. and so it goes. each moment moves from one old joke to another. bad jokes. the stuff of life they are.
#Haiku Happenings #7: Mike Rehling's #Haibun 96!


text:
Agent Vaughn to J.J. Abrams: How Dare You Reboot Alias?
Adam-Troy Castro
Tag: Alias
Remember last month when we reported that ABC and J.J. Abrams had plans to reboot the spy series Alias? Well, Michael Vartan, who played Agent Vaughn on the show during its entire 2001-2006 run, is calling BS.
If there's going to be another Alias, he says he's still available.
"I heard rumors of it, and to be honest with you, I find it absolutely preposterous," Vartan said in a conference call on June 7, while he was promoting the medical drama Hawthorne. "I'm still young enough to run down a hallway, and so is Jennifer [Garner]. What is this nonsense of recasting Alias? Give us 20 years at least. How dare they?"
He's being sarcastic there, and he says it with a laugh, but there is a kernel of truth to Vartan's rant. Wouldn't getting Vartan and Garner back for some butt-kicking adventures be better than starting over?
"It just feels a little soon to reboot Alias," Vartan continued. "But hey, you know what? Stranger things have happened, so we'll just have to wait and see. The one little thing I heard is that it would be with a new cast, which I find kind of weird, because like I said, we're all still young enough to do that."
Maybe Vartan is onto something. Would the original Alias-ers be game for a reunion? Now it's time to put your money where your mouth is, Vaughn. If ABC comes calling, will you really sign up?
"To be honest with you, it would have to be the entire returning cast from the original series, and I venture to say that would be impossible to put together," Vartan said. "People are scattered; their careers have changed. Some people are not even in the business anymore. Some people are movie stars. Of course, it's work, and if you get a chance to work with a talented group of people, that's always something I'd be interested in."
We say go for it. Garner is better in kick-ass roles than in those romantic comedies with Matthew McConaughey and Ashton Kutcher. Alias starred Garner as a college student working undercover as a spy. Her life only got more complicated from there. The original series developed into a complex mythology about an inventor named Rambaldi and the magical artifacts he created.
Vartan is now focused on his new show, and he closed with another joke about Hollywood reboots. "I heard that they're rebooting Hawthorne. I'd be much more interested in getting on that."

redpajama_set_name: RedPajamaCommonCrawl


text:
Everton confirm the signing of midfielder Fabian Delph from Manchester City for £10million
Lionesses channel their male counterparts as they splash about in the swimming pool on inflatable unicorns after win over Japan sealed progress to World Cup last-16
After beating Japan, England's Lionesses enjoyed some time off in the pool
Phil Neville's squad used inflatable unicorns for entertainment on Thursday
England finished top of their Women's World Cup group after beating Japan
By Nathan Salt For Mailonline
England's Lionesses channeled the spirit of their male counterparts as they enjoyed a splash with inflatable unicorns at their base in Route des Dolines.
The likes of Harry Maguire, Jesse Lingard and Eric Dier spent much of their off-time during the 2018 World Cup in Russia in the pool with the brightly coloured inflatables.
And in a bid to channel the spirit that saw Southgate's side reach the semi-finals in Russia, Phil Neville's squad hopped aboard the unicorns as they relaxed at the Mouratoglou Resort & Spa in Route des Dolines.
England's Lionesses enjoyed some free time on Thursday with inflatable unicorns in the pool
The unicorns became popular last summer with the men's team while away at the World Cup
'The momentum is coming along nicely': England captain Steph... Japan 0-2 England PLAYER RATINGS: Rachel Daly excelled in a... The greatest World Cup scorer of all time: Record-breaking... 'Some of the crowds have been really disappointing':...
Neville's side will soon be busy preparing for the last-16 at the World Cup in France but the former Manchester United and Everton defender allocated some time for his squad to relax on Thursday.
Victory over Japan on Wednesday night ensured England top the group and they await to find out who their opponent will be in the knockout stages.
The unicorns were popular last summer and Neville and Co will hope the good luck will rub off on them as they look to go the distance.
There was lots of laughter in the pool as defenders Steph Houghton and Millie Bright looked to document their fun on a waterproof video camera.
Steph Houghton (front) and Millie Bright documented their fun in the pool on a video camera
Keira Walsh showed off a big smile as she was photographed in the pool on Thursday
As well as acting as a recovery session, it was also a good chance to alleviate some pressure with expectations growing as to England's chances at World Cup glory.
Speaking after victory over Japan secured top spot, Houghton said: 'We're really happy. Three big wins. I don't think you can ever really call a performance perfect - I think there's always going to be times when the other team has the upper hand.
'But the thing is, we know we can play better, which is a good thing, even though we are still winning.
'I think when it gets to this World Cup stage, playing against these sorts of opponents, it's important to make sure we win, no matter what, and I feel as though there have been glimpses of what we can do with the ball.
'The momentum is coming along nicely. I think everybody is getting excited and as players we feel like we're in a good position where we can look forward to the game on Sunday.'
The free time acted as a recovery session following an impressive 2-0 win against Japan
Expectations are rising but the free day on Thursday allowed the Lionesses to relive pressure
Lionesses splash about in swimming pool on inflatable unicorns as they prepare for World Cup last-16


text:
What Tools Did a Colonial Tailor Use?
Tailor Tools - Tailor Tools Sold Direct - ebay.com
Looking For Tailor Tools? We Have Almost Everything On eBay. But Did You Check eBay? Check Out Tailor Tools On eBay.
Colonial tailors were experts with needles, thread, shears, coal-heated irons and specialized pressing tools such as clappers and blocks. Many of the tools used by colonial-era tailors were not very different from those being used in the modern era, with the notable exception of pressing and measuring tools.
Tailor's needles, thread and shears have not changed much since the 18th century, although technology has advanced the industry since then. The most immediately recognizable differences between a colonial tailor's tools and the ones used by a modern tailor are in the measuring and pressing tools used. Having no access to flexible tape measures made from modern materials, the measures from the colonial era are wooden. Some examples of wooden measures include linear, curved and t-square measures.
Pressing and ironing garments after modification was an involved task in the colonial era. Coal-heated irons had to be kept at a consistent temperature and used at regular intervals to provide consistent pressing. Additionally, early tailors had to make use of a wide variety of pressing tools, such as clappers and blocks. Clappers were used exclusively on the seams and creases of a garment, while blocks were designed in a variety of shapes to accommodate garment sleeves and trousers.
How Does the Spinning Jenny Function?
What Is the Best Way to Kill Tree Suckers?
How Can You Tell What Kind of Pine Tree You Have?
What Is Colonial Literature?


text:
Macrodiplosis niveipila är en tvåvingeart som först beskrevs av Osten Sacken 1862.  Macrodiplosis niveipila ingår i släktet Macrodiplosis och familjen gallmyggor.

Artens utbredningsområde är District of Columbia. Inga underarter finns listade i Catalogue of Life.

Källor

Gallmyggor
niveipila

redpajama_set_name: RedPajamaWikipedia


text:
Call for Application: Postdoctoral and Postgraduate Funding Opportunities in 'Law, Equality and Social Justice', Wits School of Law
Stand-Alone Posts
Wits School of Law
NRF SARChI Chair in Equality, Law and Social Justice
Postdoctoral and Postgraduate Funding Opportunities in 'Law, Equality and Social Justice'
The NRF funded South African Research Chair in 'Law, Equality and Social Justice', based at the School of Law, University of the Witwatersrand, Johannesburg, invites applications for postdoctoral fellowships and postgraduate bursaries in the broad field of equality, law, rights and social justice to commence in 2022. NRF PhD and LLM bursaries 2022 Applications are invited for PhD and LLM bursaries in equality, public law, human rights and social justice. The value of the NRF PhD bursary in 2022 is R120 000.00 (general funding) or R160 000.00 (means tested funding) which should be held as primary funding towards the degree. Applicants should intend to study full-time at Wits University, under the supervision of the Chair, and be South African (preferably) or from other African countries.
To apply, please submit the following documents:
a covering letter stating why you are interested in the bursary and your field of study
A summary research proposal of one to two pages
A C.V.
Full academic records
The contact details of two academic referees
Once you are accepted by the Chair, you will also need to apply to the NRF online. Details will be provided.
Closing date: 20 June 2021
NRF Postdoctoral Fellowships 2022
Applications are invited for postdoctoral fellowships for an initial period of twelve months. Successful applicants may be renewed for a second year. The value of the fellowship in 2022 is R220 000.00. This is a full-time position and fellows may not hold full-time salaried employment during the tenure of the fellowship, and are expected to be based at the University for at least 80 per cent of the period of the Fellowship. All fellowship awards should be held as primary funding.
Applicants should engage in research in the field of equality, public law, human rights and social justice, broadly construed, and preferably with a South African focus. Successful candidates will be required to publish at least two accredited articles per annum and to contribute to the work of the Chair
Applicants must have completed their doctoral degrees within the last five years and have proven ability in research and writing. South African citizens and permanent residents may apply, as well as outstanding international candidates, who wish to undertake postdoctoral research in South Africa.
To apply, please submit the following documents to claire.joseph@wits.ac.za:
a covering letter stating why you are interested in the fellowship
A summary research/publications proposal of two pages
A short piece of recent written work, or publication.
CLOSING DATE – 30 AUGUST 2021
Enquiries and applications
Enquiries on the scope and content of the research field and fellowship/bursary criteria should be made to Professor Cathi Albertyn (cathi.albertyn@wits.ac.za).
You may also consult the following webpages: On the SARChI Chair, see here.
On the NRF criteria, see here
On Wits Postdoctoral expectations, see here
All applications should be sent to cathi.albertyn@wits.ac.za as soon as possible and by the specified closing dates.


text:
Our mission is to use the power of Black Art to transform individuals, create and build community and foster cultural understanding.
Our Mission and Core Values come to LIFE in 2 ways:
Arts Education and Family / Public Programming
Do You See What I See? by Ron St. Clair
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Who We Are & What We Do
Cake and Creating
Rashawn's birthday was tomorrow. We had class again on the following day. I offered to have a party like we did for Iyonna. Rashawn didn't want to do...
On Exhibit - Photos by C. Ron St. Clair | Do You Hear What I See?
In honor of Black Music Month Do You Hear What I See? Photos by C. Ron St. Clair June 9 - July 31, 2018 "Do You Hear What I See?" is a special...
Lessons from the Elders
By: Emile Holland. Emile Holland is a sophomore at Central High School, and one of Art Sanctuary's high school interns. He recently shared his...
By: Lorene Cary We're halfway through the dedication of the National Museum of African American History and Culture by the time the violins swell and...
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The "All-American Eclipse," as some astronomers refer to the coming event, marks the first path in recorded history to pass exclusively across the continental US. After first touching Earth in the Pacific Ocean, it comes aground on the Oregon coast. The centerline of visibility then crosses the state and country at a diagonal swath approximately seventy miles wide, traversing Idaho, Wyoming, Nebraska, Kansas, Missouri, Illinois, Kentucky, Tennessee, North Carolina, Georgia, and South Carolina, before fading into the Atlantic. The whole event will take less than two hours. Everyone in the US will see at least a partial eclipse, but the difference between a partial and a total eclipse, according to Jay Pasachoff, the astronomer who holds the world record for most eclipses viewed, is like standing outside the opera house versus attending it.
"The mind—the culture—has two little tools," Dillard explains in the same essay. These tools are "grammar and lexicon: a decorated sand bucket and a matching shovel." We make sense of life, society, and natural phenomena by scooping morphemes into syntax and patting them into castles of meaning. Scientific and literary writers use different buckets, but at times they apply joint efforts to the same wonders. This August's eclipse provides a prime opportunity for the discourses to complement one another.
The most obvious contribution is science's ability to predict the eclipse's path with mathematical precision, but the power of scientific observation only begins here. Scientists have also characterized a number of visual effects we can expect to see. The founder of solar physics, Francis Baily, was the first to recognize the phenomenon now known as Baily's beads, which occurs just as the moon squeezes out the last light of the sun and beads of light spill a partial necklace overhead. Baily's beads follow the diamond ring effect, which is when a ring of light remains of the sun along with the last brilliant piece of orb forming a fifty-carat diamond for it. Both events precede the grand finale when the corona becomes visible after the moon's body covers the sun completely.
Some understanding of the science of eclipses also increases our sense of mystery that a total eclipse can happen at all. The sun is roughly four hundred times the diameter of the moon that blocks it, but it is also four hundred times farther away from Earth. Add to these calculations the elliptical orbits of the moon and the Earth, which change the distance from the sun and the moon's relative size, and partial eclipses seem inevitable, as when more common annular eclipses make of the sun a ring of fire. Yet every 375 years or so, on average, for any particular city or house on Earth, the shadow forms a perfect fit.
It had been like the death of someone, irrational, that sliding down the mountain pass and into the region of dread. It was like slipping into fever, or falling down that hole in sleep from which you wake yourself whimpering.
Pink faces went green, and it became colder than ever. This was the defeat of the sun . . . The shadow growing darker and darker over the moor was like the heeling over a boat, which, instead of righting itself at the critical moment, turns a little further and then a little further on its side; and suddenly capsizes.
Awe shatters sense. Scientists like Baily accommodate for that human limitation by organizing bands of people beforehand to focus their attention, so that each viewer is assigned a separate aspect of the phenomenon so as not to be distracted from its climax by the appearance of another. Poets and essayists turn to literary forms to process complex, multifaceted experiences and to gather their emotional significance. For it is only by being paired with emotion, Virginia Woolf writes, that an image becomes memorable.
All the convalescences and respites of life seemed rolled into one. Yet, at first, so light and frail and strange the colour was, sprinkled rainbow-like in a hoop of colour, that it seemed as if the earth could never live decked out in such frail tints.
Her great relief is sharpened by a contrasting awareness of what would have been had the sun not reemerged. The fearful possibility has overtaken more than one mind and even life during a total eclipse, but if social media makes us less susceptible to being caught off guard by the sight, it still offers what Dillard calls "a wake up . . . from our sleeping lives," which charges us with language to shape what sense we can of this "clockwork of loose spheres" with all available tools at hand.


A growing body of evidence suggests that psychological factors play an important role in determining whether an athlete makes a successful return to sport following injury. Physical therapist Keith Cronin, DPT, OCS, CSCS, says it is important for parents to support an injured athlete but to empower, not coddle them during the rehabilitation process.
Many young athletes, particularly females, suffer from chronic knee pain. Pain becomes common with running, jumping, and, with later progression, even a flight of stairs. Sometimes this condition is associated with Patellar Instability, a combination of structural abnormalities and maltraking of the kneecap. Sometimes, surgery may be necessary.


Just as recap, these are the cupcake recipes so far on my blog: lemon cupcakes with lemon curd filling, the best chocolate cupcakes, and pumpkin cupcakes with caramel. Finally today I am going to present lavender cupcakes. Because you also need cupcakes in summer. Because I love the scent of lavender. Because cupcakes are perfect for any potluck, picnic or even beach. Please give these beauties a try, as stated this is a basic vanilla cupcake with lavender scent and some buttercream with blueberries, so yummy!
I love that you can prepare cupcakes a few days in advance. They are really easy to prepare. If kept in an airtight container, you can make them two days in advance, same holds true for the buttercream. I only recommend the cupcakes shortly before serving.
For the cupcakes boil milk and add one teaspoon of lavender. Take off stove, cover and let steam for a few hours or overnight. It is also good to prepare the blueberries for the buttercream by boiling them until soft. Set aside.
Line 12 muffin tins with paper and preheat oven to 180 degrees Celsius.
Strain milk and add the milk and remaining ingredients slowly, only mix until combined. Pour into muffin tins and bake for about 15-18min or inserted toothpick comes out clean.
Beat the butter for about five minutes or until lighter in color and add the cooled off flour mix, one tablespoon at a time. Then add the blueberries. Once everything is combined, beat for another minute.
Pipe buttercream on cupcakes, I used an M tip, you should be able to frost the cupcakes generously.


Bruhat Bengaluru Mahanagara Palike or BBMP for short is the municipal body for the city of Bangalore. If you settling down in the city of lakes then this the organization which you will be interacting with for all you Property tax related matters. BBMP has taken various steps to provide multiple methods through which a citizen can pay the property tax. A property owner can pay property tax via Bangalore One Centers, Banks notified by BBMP and Online. It's a good decision to make full payment of the property tax for a financial year in one go to avail 5% rebate given by BBMP. Late payment of property tax invites a penalty of 2% per month or 24% per annum.
Offline Payment of Property Tax: In order to make payment of property tax offline through Bangalore One Centers or Banks you need to follow the below procedure.
To start with the offline method you need to fill up one among the following forms based on the condition you qualify for mentioned in front of each form below.
Form I: If you have a Property Identification Number(PID) then this form is for you. PID is an unique number assigned by BBMP to the properties in Bangalore.
Form II: If you have a Khatha Number and do not have a PID then this is the form for you. This number is available on the Khatha certificate of the property.
Form III: This form is applicable to you if you do not have PID or Katha number. This form is for unauthorized property built without the approval of planning authorities at BBMP.


text:
NonProfitFacts.com » Texas » Southern Sector Health Initiative
Southern Sector Health Initiative in Dallas, Texas (TX)
Organization representatives - add corrected or new information about Southern Sector Health Initiative »
Non-representatives - add comments about Southern Sector Health Initiative»
Southern Sector Health Initiative
Name of Organization Southern Sector Health Initiative
Address 2001 Bryan St Ste 600, Dallas, TX 75201-3062
Foundation Organizations operated solely for the benefit of and in conjunction with organizations described in 10 through 16 above
Assets $1,000,000 to $4,999,999
Income $1,000,000 to $4,999,999
Asset Amount $4,045,154
Amount of Income $4,327,268
Form 990 Revenue Amount $4,141,627
National Taxonomy of Exempt Entities (NTEE) Health - General and Rehabilitative: Single Organization Support
Amount of income in 2013: $4,327,268 (it was $4,719,115 in 2012)
Assets in 2013: $4,045,154 (it was $4,244,828 in 2012)
Southern Sector Health Initiative:
Expenses in 2013: $4,075,479
Employees paid over $100,000 in 2013: 13.7%
Did the organization engage in lobbying activities, or have a section 501(h) election in effect during the tax year? Yes Yes
Did the organization report an amount for other assets that is 5% or more of its total assets? Yes Yes
Did the organization's separate or consolidated financial statements for the tax year include a footnote that addresses the organization's liability for uncertain tax positions under FIN 48 (ASC 740)? Yes Yes
Did the organization report more than $15,000 total of fundraising event gross income and contributions? Yes Yes
The number reported in Box 3 of Form 1096 24 20
Did the organization comply with backup withholding rules for reportable payments to vendors and reportable gaming (gambling) winnings to prize winners? Yes Yes
The number of employees reported on Form W-3, Transmittal of Wage and Tax Statements, filed for the calendar year ending with or within the year covered by this return 62 51
Did the organization file all required federal employment tax returns? Yes Yes
Total reportable compensation from the organization $628,720 $1,133,492
Total estimated amount of other compensation from the organization and related organizations $121,854 $114,351
Total revenue $4,621,400 $4,633,096 $4,141,627
Contributions, Gifts, Grants and Other Similar Amounts $4,619,838 $4,661,123 $4,220,119
Program Service Revenue $0 $17,080 $58,430
541900 $13,480 $46,954
611600 $1,800 $11,476
Net income/loss from fundraising events $0 $-43,022 $-137,043
Gross income from fundraising events $0 $14,370 $19,761
Less: direct expenses $0 $57,392 $156,804
Net income/loss from sales of inventory $1,562 $-2,085 $121
Gross sales of inventory, less returns and allowances $17,766 $26,542 $28,958
Less: cost of goods sold $16,204 $28,627 $28,837
Total functional expenses $4,245,046 $5,187,857 $4,075,479
Compensation of current officers, directors, trustees, and key employees $279,946 $806,020 $295,427
Other salaries and wages $1,474,031 $1,431,626 $1,409,648
Pension plan accruals and contributions $50,638 $49,439
Other employee benefits $194,807 $155,983
Payroll taxes $117,439 $153,346 $115,172
Other $1,449,291 $1,110,955
Advertising and promotion $32,392 $14,097
Office expenses $146,235 $96,372
Information technology $0 $209
Occupancy $480,578 $503,256
Travel $32,498 $12,215
Conferences, conventions, and meetings $22,706 $6,365
Depreciation, depletion, and amortization $276,620 $265,771
Other expenses $4,130 $921
Other expenses $42,938 $84
Total assets $4,547,113 $4,244,828 $4,045,154
Cash - non-interest-bearing $217 $600
Savings and temporary cash investments $60,198 $200,654
Land, buildings, and equipment: cost or other basis $3,499,632 $3,251,838
Other assets $684,781 $592,062
Total liabilities $269,895 $500,793 $327,689
Accounts payable and accrued expenses $341,628 $327,689
Deferred revenue $159,165 $0
Total net assets or fund balances $4,277,218 $3,744,035 $3,717,465
Unrestricted net assets $3,059,254 $3,125,403
Temporarily restricted net assets $684,781 $592,062
The organization is not a private foundation because it is: An organization organized and operated exclusively for the benefit of, to perform the functions of, or to carry out the purposes of one or more publicly supported organizations described in section 509(a)(1) or section 509(a)(2)
Would you recommend Southern Sector Health Initiative to others? (optional)
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1 Svh Supportco 406 Botulph Ln Ste 2, Santa Fe, NM 87505-6971 NM 2009-03 $28,879,096
2 Tarrant County Indigent Carecorporation 612 E Lamar Blvd No 6th Fl, Arlington, TX 76011-4121 TX 2009-09 $58,649,726
3 Santa Rosa Childrens Hospital Endowment Fund 343 W Houston Street Suite 505, San Antonio, TX 78205 TX 2010-07 $27,733,437
4 Heart Of Texas Healthcare System 2008 Nine Rd, Brady, TX 76825-7210 TX 2011-08 $21,228,814
5 Shannon Business Services Inc 120 E Harris Ave, San Angelo, TX 76903-5904 TX 2004-12 $7,925,085
6 Southern Sector Health Initiative 2001 Bryan St Ste 600, Dallas, TX 75201-3062 TX 2009-09 $4,327,268
7 Rgh - Barbara Jordan Center Inc 3204 Ennis St, Houston, TX 77004-3213 TX 2014-07 $1,800,000
8 Southwestern Medical District 5323 Harry Hines Blvd Stop 9171, Dallas, TX 75390-9171 TX 2006-12 $1,181,350
9 Rgh Casa Center Inc 3204 Ennis St, Houston, TX 77004-3213 TX 2014-08 $797,045
10 Winnie Coastal Medical Foundation Inc 528 Broadway, Winnie, TX 77665 TX 2010-12 $566,544
11 True Vineyard Ministries Inc 317 W San Antonio St, San Marcos, TX 78666-5514 TX 2007-05 $462,285
12 Texas Scottish Rite Hospital For Children Foundation 2222 Welborn St, Dallas, TX 75219-3924 TX 2013-07 $448,653
13 Snowdrop Foundation Inc 7155 Old Katy Rd Ste N270, Houston, TX 77024-2284 TX 2006-06 $437,639
14 Riverside General Hospital Foundation Inc 3204 Ennis St, Houston, TX 77004-3213 TX 2001-10 $301,248
15 Santa Maria Hostel Foundation 2005 Jacquelyn Dr, Houston, TX 77055-1717 TX 2007-03 $289,200
16 Sid Peterson Memorial Hospital Auxiliary, Peterson Regional Med Ctr Aux 551 Hill Country Dr, Kerrville, TX 78028-6085 TX 2006-06 $159,489
17 Titus Regional Medical Foundation Inc 2001 N Jefferson, Mount Pleasant, TX 75455-2338 TX 2004-07 $58,799
18 The@endowment Fund Of Beth Avot- Asociacion Israelita De Quito PO BOX 1882, Bellaire, TX 77402-1882 TX 2008-07 $58,142
19 Socialmine Foundation 2221 E Lamar Blvd Ste 900, Arlington, TX 76006-7457 TX 2012-09 $26,000
20 Sabine Valley Center Foundation Inc PO BOX 6800, Longview, TX 75608-6800 TX 2001-04 $22,630
NonProfitFacts.com is not associated with, endorsed by, or sponsored by Southern Sector Health Initiative and has no official or unofficial affiliation with Southern Sector Health Initiative


text:
Інна Іон Будештян ( 3 лютого 1987) — молдовська футболістка, воротар.

Клубна кар'єра
У 2006 році перейшла до «Нафтохіміка». У футболці калуського клубу ставала бронзовю призеркою (2006) та переможницею чемпіонату України (2007). По ходу сезону 2008 року залишила західноукраїнський клуб.

Потім переїхала до Литви, де підсилила місцевий «Гінтра Універсітетас». П'ятиразова чемпіонка Литви (2010—2014). У 2013 році мала поповнити «Іллічівку», проте перехід не відбувся. У 2015 році переїхала до Швеції, де підписала контракт за клубом «Естерсундс». У новій команді дебютувала 12 квітня 2015 року в програному (1:2) виїзному поєдинку 1-о туру Елітеттану проти «Лімгамн Бюнкефлу 07». Інна вийшла на поле в стартовому складі та відіграла увесь матч. У футболці «Естерсундса» зіграла 16 матчів у чемпіонаті Швеції. Про подальшу кар'єру дані відсутні.

Кар'єра в збірній
Викликалася до складу національної збірної Молдови.

Стиль гри
Впевнено діє на лінії воріт, проте невпевнено грає ногами.

Досягнення
«Нафтохімік»
  Вища ліга України
  Чемпіон (1): 2007
  Бронзовий призер (1): 2006

«Гінтра Універсітетас»
  А-Ліга
  Чемпіон (5): 2010, 2011, 2012, 2013, 2014

Примітки

Посилання
 Профіль гравчині на офіційному сайті УЄФА

 Профіль гравчині на сайті soccerdonna.de
 Профіль гравчині на сайті soccerpunter.com
 Профіль гравчині на сайті worldfootball.net
 Профіль гравчині на сайті «Жіночий футбол України»

Молдовські футболістки
Гравчині збірної Молдови з футболу
Футбольні воротарі
Молдовські футбольні легіонери
Футбольні легіонерки в Україні
Футбольні легіонери в Литві
Футбольні легіонери у Швеції
Футболістки «Кодру» (Кишинів)
Футболістки «Нафтохіміка»
Футболістки «Гінтри»


These drinks satisfy thirst with light, delightful flavors.
Veg-Friendly Brewery: Sanctuary Brewing Co.
In France, there's an after-dinner tradition called the tisane. Tisane is another way of saying "tea," and more specifically, "herbal infusion." I've adopted the ritual for several reasons, beginning with the fact that it tastes good, but I also love that I can use almost any herb for the job.


You, your staff, guests and/or suppliers travel periodically to Würzburg?
Then we would like to suggest you our advantage prices for companies based on your annual booking volume.
Corporate prices are bookable through our website or direct at the hotel.
Is your annual booking volume too small for a contract?
Then use our "personal customer number".
The discounted rates are at www.cityhotel-wuerzburg.de or per telephone bookable. They are valid from the first night on. Please contact us for your registration. After that you will receive a customer and contract number. With the respective booking code you and your staff will be able to book rooms for the discounted prices.
Get to know the attractive conditions of our hotel for corporate customers.
For further information please contact the City Hotel Würzburg.
« Contact our Experts !


text:
Shared mechanisms for confidence judgements and error detection in human decision making
Yeung N., Summerfield C.
© 2014 Springer-Verlag Berlin Heidelberg. All rights reserved. People give accurate evaluations of their own choices and decisions: they are often aware of their mistakes without needing feedback, and report levels of confidence in their choices that correlate with objective performance. These metacognitive judgements guide current and future behaviour, helping people to avoid making the same mistake twice and to evaluate whether they have enough information on which to base a reliable choice. Here we review progress in characterising the neural and mechanistic basis of these related aspects of metacognition-confidence judgements and error monitoring-and identify several points of convergence between methods and theories in the two fields. This convergence promises to resolve key debates in the separate literatures, to identify productive new lines of enquiry, but also to highlight shared limitations in the two research fields. In particular, future theories of choice and metacognitive evaluation may need to look beyond simple, discrete decisions to model the structure and fluidity of real-world decisions and actions that are embedded in the broader context of evolving behavioural goals.
10.1007/978-3-642-45190-4_7
The Cognitive Neuroscience of Metacognition


text:
\section{Introduction} \label{sec:introduction}

Arguably one of the most important aspects of health and medical research is
being able to understand and predict patient outcome in order to improve
patient management and ultimately extend their life span or time in remission
\citep{hosny_deep_2018}.
Survival analysis is used for these purposes to study time-to-event information
relating to for example death, response to treatment, adverse treatment effects,
disease relapse, and the development of new disease \citep{collett2015modelling}.
Traditional approaches, such as Cox Proportional Hazards (\textit{cf.}~ Section~\ref{sec:relatedwork}),
relied on tabular features and are not amenable to analyze high-dimensional non-tabular data
such as medical images. With recent advances in computer vision and deep leaning, there has been increasingly
more interest in performing survival analysis directly from high-dimensional data in order to
automatically learn patterns that stratify patients based on their outcome without the need
for feature engineering.

In this paper we present DCTM, a framework for parametric and semiparametric survival analysis
rooted in statistical modeling. DCTM{s} allow the specification of non-linear and non-proportional
hazards for both tabular and non-tabular (image or text) data. We will describe in
detail the formalization of our proposed models and apply them to a real dataset of medical images.
Additionally, we describe how DCTMs can be used as generative models for the generation of
semi-synthetic data. To the best of our knowledge, this paper is the first to cover deep survival
regression from the DCTM point of view.

\section{Deep transformation models for survival outcomes} \label{sec:method}

In the following, we introduce deep conditional transformation models (DCTMs) for survival
outcomes. We briefly recap survival analysis and conditional transformation models.
Then we describe how to setup, fit, evaluate and sample from our proposed models.
Fig.~\ref{fig:method} is an overview of the proposed class of models.

\paragraph{Survival analysis}
Survival analysis characterizes the distribution of the positive real-valued event
time $T$ conditional on covariates $X$, usually on the scale of the survivor function,
$S_{T \mid X = x}(t) = 1 - F_{T \mid X = x}(t)$, where $F_{T \mid X = x}$ denotes the
cumulative distribution function (CDF) of $T \mid X = x$. One of the most popular choices
is the Cox proportional hazards (Cox PH) model \citep{cox1972regression}
\begin{align} \label{eq:coxph}
    F_{T \mid X = x}(t) = 1 - \exp(-\Lambda(t \mid x)) =
    1 - \exp(-\Lambda_0(t)\exp(x^\top\beta)),
\end{align}
where $\Lambda(t \mid x)$ denotes the positive, monotone increasing cumulative hazard
function. The hazard function is assumed to be decomposable into a baseline hazard $\Lambda_0$,
independent of the covariates, and a hazard ratio $\exp(x^\top\beta)$. The hazard ratio models
the influence of the covariates on the survivor function. The hazard function
$\lambda(t \mid x) = \frac{\mathrm{d}}{\mathrm{d} t} \Lambda(t \mid x)$ measures the instantaneous risk
of an event after time $t$ conditional on the covariates $x$ and having survived until $t$
\citep{collett2015modelling}.

The Cox PH model is commonly estimated using the maximum partial likelihood obtained from
profiling out $\Lambda_0$ \citep{cox1975partial}. The connection to transformation models
for distributional regression is drawn next.

\paragraph{Conditional transformation models}
CTMs are parametric distributional regression models of the form
\citep{hothorn2014conditional}
\begin{align} \label{eq:ctm}
    F_{T\mid X = x}(t) = F_Z(h(t \mid x)),
\end{align}
where the conditional distribution of the response $T \mid X = x$ is decomposed into
an \emph{a priori} chosen and parameter-free target distribution $F_Z$ and a conditional
transformation function $h$, which depends on the input data $x$. In order for $F_T$
to be a valid CDF, $h$ needs to be monotonically increasing in $t$ \citep{hothorn2018most}.

CTMs can be estimated via maximum likelihood and allow various kinds of responses
and uninformative censoring. The model in \eqref{eq:ctm} suggests a close connection
to the Cox PH model in \eqref{eq:coxph}, namely for $F_Z(z) = 1 - \exp(-\exp(z))$
(the minimum extreme value distribution) and $h(t \mid x) = \log\Lambda(t \mid x)$,
the two models coincide.

\paragraph{DCTMs for survival analysis}
In DCTMs, the transformation function is parameterized via (deep) neural networks.
For instance, let $\phi: \mathcal{X} \to \mathbb{R}^d$ denote a feature extractor,
which maps the input $x$ to a feature vector of dimension $d$. We can then choose
different parameterizations for the transformation function, depending on the desired
complexity of the model. For example,
\begin{align}
    h(t \mid x; \phi) = \alpha + \beta\log(t) + \phi(x)^\top w, \quad \beta > 0,
\end{align}
together with $F_Z(z) = 1 - \exp(-\exp(z))$ is a Weibull proportional hazards model
with non-linear log hazard-ratios depending on the input $x$ (for instance, medical images).
However, also non-proportional (time-varying) hazards can be realized in DCTMs, via
\begin{align}
    h(t \mid x; \phi) = \alpha + g(\phi(x)^\top w) \log(t),
\end{align}
where $g: \mathbb{R} \to \mathbb{R}_+$, \textit{e.g.},~ the soft-plus function, ensures a valid CDF.
In Section~\ref{sec:param}, we describe the parameterization of the DCTMs used in this
paper. An overview of the proposed method is given in Figure~\ref{fig:method}.

A parametric version of the Cox PH model can be estimated in the DCTM framework.
Here, the log cumulative baseline hazard function is estimated as a smooth basis expansion
$a(t)^\top\vartheta$, instead of using the non-parametric estimate. A common choice
are Bernstein polynomials, which are easily constrained to be monotonically increasing
(see Section~\ref{sec:experiments}).

\begin{figure}[!ht]
    \centering
    \includegraphics[width=\textwidth]{figures/method_figure-01.png}
    \caption{Proposed DCTM model architecture. The inputs to the model consist of
    tabular or non-tabular explanatory variables associated with survival data
    in terms of exact or right-censored times to event. The explanatory variables
    can be mapped to a latent feature space via a feature extractor. In the case
    of non-tabular data such as images, the feature extractor will consist of a
    non linear mapping such as a convolutional neural network. The extracted
    features are then fed to the transformation layer. The network is optimized by
    minimizing the negative log-likelihood (NLL). In the figure we show the
    transformation function along with the cumulative density function (CDF),
    probability density function (PDF) and NLL for an exact event and a
    right-censored example.}
    \label{fig:method}
\end{figure}

\paragraph{Fitting DCTMs}
DCTMs are fitted by optimizing the empirical negative log-likelihood (NLL) via stochastic
gradient descent (SGD). The likelihood contribution of a single observation $(t, x)$ can
be expressed in terms of the general transformation model
\begin{align}
    \mathcal{L}(h; t, x) = \begin{cases}
        f_Z(h(t \mid x))h'(t \mid x) & t \mbox{ exact event}, \\
        1 - F_Z(h(t \mid x)) & t \mbox{ right censored}.
    \end{cases}
\end{align}
However, also interval- and left-censored observations can be handled with the proposed
method \citep[see \textit{e.g.},~][]{hothorn2018most}. For a general choice of the transformation
function $h(t \mid x)$ and error distribution $F = \sigma$, we have the following likelihood
function
\begin{align}
    \mathcal{L}(h; t, x) = \begin{cases}
        \sigma(h(t \mid x)) (1 - \sigma(h(t \mid x)) h'(t \mid x) & t \mbox{ exact event}, \\
        1 - \sigma(h(t \mid x)) & t \mbox{ right censored}.
    \end{cases}
\end{align}
Lastly, the NLL
\begin{align} \label{eq:nll}
    \NLL = - \sum_{i=1}^{n_t} \log \mathcal{L}(h; t_i, x_i),
\end{align}
is minimized via SGD, where $n_t$ denotes the training sample size.

\paragraph{Evaluating DCTMs}
After fitting a DCTM, the conditional survivor function of a test observation can be computed from
the estimated parameters via $\hat{F}_{T \mid X = x}(t) = F_Z(\hat h(t \mid x))$. Now, all
evaluation metrics can be computed from (some form of) the predicted conditional distribution.

Evaluating models that predict conditional distribution of survival times are not straight-forward
to evaluate, due to censoring and their probabilistic nature \citep{collett2015modelling}. For instance,
mean squared error or median absolute deviation are insensible for a right-censored observation
$((t, +\infty], x)$ and prediction $\hat t$, for instance the conditional median survival time.

The c-index \citep{harrell1982cindex}
\begin{align}
    c = \frac{\sum_{i,j}\mathds{1}_{T_j<T_i}\cdot
    \mathds{1}_{\eta_j>\eta_i} \cdot \delta_j}{\sum_{i,j}\mathds{1}_{T_j<T_i}\cdot \delta_j},
\end{align}
overcomes at least the issue of censoring. However, the c-index does not encourage faithful probabilistic
predictions, because it is not a proper scoring rule \citep{blanche2018cindex}.

Proper scoring rules \citep{gneiting2005weather,gneiting2007strictly} are explicitly designed to
evaluate probabilistic predictions and can inherently deal with censoring. A score is proper, if
its average w.r.t. the data-generating distribution is minimized when predicting exactly this
distribution, \textit{i.e.},~ if $T \sim \mathbb{P}_{T \mid X = x}$,
\begin{align} \label{eq:proper}
    \mathbb{E}_{\mathbb{P}_{T \mid X = x}}[S(p; T)] \leq \mathbb{E}_{\mathbb{P}_{T \mid X = x}}[S(q; T)].
\end{align}
Here, $\mathbb{P}_{T \mid X = x}$ denotes the data-generating probability distribution with density $p$ and
$q$ is another predicted density. A score is called \emph{strictly proper}, when the above inequality holds if
and only if $p = q$.

The c-index does not fulfill \eqref{eq:proper}, whereas the negative log-likelihood
\begin{align} \label{eq:logscore}
   S_{\mathrm{NLL}}(\hat F, t) = - \delta \log \hat f(t) - (1 - \delta) \log \hat S(t)
\end{align}
does \citep{good1952rational}. Here, $\delta \in \{0, 1\}$ denotes an exact ($\delta = 1$) or a censored
($\delta = 0$) survival time. In fact, the NLL is the only strictly proper local scoring rule
\citep[up to affine transformations,][]{brocker2007scoring}.
However, since DCTMs are fitted by minimizing the empirical NLL, a comparison based solely on this
score could be deemed unfair, if the competing method optimizes a different score, say the c-index.
For this reason, we also compute the continuous ranked probability score \citep[see \textit{e.g.},~][]{avati2020crps}
\begin{align} \label{eq:crps}
   S_{\mathrm{CRPS}}(\hat F, t, \delta) =
       \int_0^t \hat F^2(u) \; \mathrm{d} u + \delta \int_t^\infty (1 - \hat F(u))^2 \; \mathrm{d} u.
\end{align}

\paragraph{DCTMs as generative models}
DCTMs model the entire conditional distribution of $T \mid X = x$. Consequently, one can sample from
the estimated distribution $\hat F_{T \mid X = x}(t)$, \textit{e.g.},~ via inversion sampling (see Figure~\ref{fig:sampling}).
In more detail, given a real sample and a fitted DCTM, the sample's CDF can be generated. Next, random uniform
probability values can be drawn and mapped back to time via the inverse CDF (Figure~\ref{fig:sampling}b).
The usefulness of sampling from DCTMs is illustrated in our semi-synthetic experiments
in Section~\ref{sec:results}.
\begin{figure}[!ht]
    \centering
    \includegraphics[width=0.95\textwidth]{figures/sampling_figure.png}
    \caption{Generation of semi-synthetic data via inversion sampling for DCTMs. a) Fitting of
    real data with three DCTM parametrizations of increasing complexity. The more flexible models
    reach a lower NLL. b) Example of a patient's fitted CDF and one sampled synthetic time.
    c) Distribution of 1,000 sampled times for the previous CDF. d) Generated semi-synthetic
    datasets based on the three DCTM parametrizations compared to the real data.}
    \label{fig:sampling}
\end{figure}

\section{Related work} \label{sec:relatedwork}

We summarize the concurrent literature on deep learning for survival analysis and
transformation models.

\paragraph{Deep learning for survival analysis}
We distinguish Bayesian and frequentist approaches and the loss function involved in fitting
the models.

Several DL approaches to survival analysis are inspired by the Cox PH model.
One of the earliest approaches using (shallow) neural networks for survival analysis is
\citet{Liestbl1994}. The authors use the partial likelihood as a loss function and
even describe extensions to piece-wise constant, or non-proportional hazards and non-linear
effects.
A direct extension to deep Cox PH models is ``DeepSurv'' \citep{katzman2018deepsurv}, which
optimizes the $\ell_2$-regularized log partial-likelihood.
Also, \citet{Nagpal2021} proposes a mixture of Cox models together with an expectation
maximization (EM) algorithm to optimize the partial likelihood and the evidence lower bound
(ELBO) of a variational auto-encoder for the features.

In contrast to the semi-parametric approaches derived from the Cox PH model,
a fully parametric framework for survival analysis was given in \citet{nagpal2020deep}.
The authors model the survivor function as a mixture distribution and fit the model
using an ELBO for exact and censored responses.
\citet{Ranganath16} present a generative (Bayesian) Weibull model for survival times.
Some approaches based on pseudo-values exist \citep{zhao2020dnnsurv,rahman2020pseudo}.
\citet{Fornili2014} employ piece-wise exponential hazard functions in a penalized
likelihood loss.

``DeepHazard'' proposed by \citet{Rava2020}, uses a squared error loss based on the
underlying counting process, which takes into account censoring. The model allows for
time-varying covariates and non-linear effects, as well as non-proportional hazards.

A different branch of literature treats survival regression as a classification problem.
\citet{fotso2018deep} introduce ``neural multi-task logistic regression'' (N-MTLR),
which splits the positive real line into $K$ sub-intervals and fits a softmax last-layer
model to the event indicators. The authors evaluate their model using proper scoring rules,
namely the weighted and integrated Brier score (which is equivalent to the CRPS).
\citet{lee2019dynamic} propose ``dynamic DeepHit'', which is based on ``DeepHit''
\citep{lee2018deep} and again uses a softmax last-layer activation. (Dynamic) DeepHit is able
to deal with competing risks and non-linear effects.

DL for survival analysis has been shown to be useful in medical applications. For instance,
\citet{Lao2017} use DL together with radiomics features for prediction of glioblastoma
multiforme survival. A comparison between a deep learning and the classical Cox PH
can be found in \citep{Matsuo2019}. DeepSurv has been applied and compared against the Cox PH
model and survival random forests for oral cancer \citep{kim2019deepsurvapplication}
and non-metastatic clear cell renal cell carcinoma \citep{byun2021deepsurvapplication}
survival prediction.

\paragraph{Deep conditional transformation models}
Our proposed class of models belongs to the family of DCTMs. DCTMs extend the flexible class
of CTMs \citet{hothorn2014conditional,hothorn2018most} with deep neural networks and SGD to
handle non-tabular data, such as images. TMs are distributional regression models, which
capture the entire conditional distribution instead of a single or few moments thereof
\citep{kneib2021rage}. More detail on TMs in given in Section~\ref{sec:method}.

DCTMs were first introduced by \citet{sick2020deep}, where the authors used a series
of nested functions to model the transformation function and the standard normal CDF as the
target distribution. \citet{baumann2020deep} extended the work on DCTMs for continuous
distributions with exact observations. \citet{kook2020ordinal} treated ordinal regression
from the DCTM point of view. The authors view the ordinal response as an interval censored
version of a latent logistic distribution. By imposing structural assumptions on the
transformation function, such as additivity, DCTMs retain interpretability of certain parts
of the models, \textit{e.g.},~ parameters for a single data modality. DCTMs were also developed for
time series, \textit{i.e.},~ serially correlated data \citep{rugamer2021timeseries}.
DCTMs are all fitted by minimizing the empirical NLL via some form of SGD.

\section{Experimental setup} \label{sec:experiments}

In the following, we describe the details of the experimental setup
including parameterization of the DCTMs and the use of ensemble estimates for
improving prediction performance.

\subsection{Model parametrizations} \label{sec:param}

We employ different parameterizations of the transformation function, namely a
linear shift, a linear scale, and general shift and scale models with a non-linear
function in $t$ using Bernstein polynomials.
For all experiments, we choose the standard logistic CDF $\sigma(z) = (1 + \exp(-z))^{-1}$
or the standard minimum extreme value CDF (also called Gompertz) $F_{\mathrm{MEV}}(z) = 1 - \exp(-\exp(z))$
as the target distribution. Consequently, the transformation function can be interpreted
on the log-odds or log-hazard scale, respectively.

For the linear shift parameterization, the transformation function is parameterized as
\begin{equation}
    \begin{split}
        h(t \mid x; \phi) = a + b\log t + \phi(x)^\top w, \mbox{ where} \\
        \phi: \mathcal{X} \to \mathbb{R}^P, a \in \mathbb{R}, b \in \mathbb{R}, w \in \mathbb{R}^P,
    \end{split}
\end{equation}
where $h$ denotes the transformation function, with a linear basis in $t$ parameterized via
$a$ and $b$, and a feature extractor $\phi$ representing a neural network with linear last-layer
activation and weights $w$.
Here, the extracted features enter linearly on the scale of the transformation function.
In turn, the conditional distribution function changes only in terms of location, but not
in terms of scale or any higher moments. That is, $F_{T \mid X = x}$ is restricted to the
same family of distributions as the target distribution $F$. Hence, this model is not
distribution-free. For $F_Z = F_{\rm MEV}$, the linear shift model is equivalent to a Weibull
model. Similarly, $F_Z = \operatorname{expit}$, yields a log-logistic model.

For the linear scale model, we have
\begin{equation}
    \begin{split}
        h(t \mid x; \phi) = a + \operatorname{softplus}(\phi(x)^\top w) \cdot \log t, \mbox{ where} \\
        \phi: \mathcal{X} \to \mathbb{R}^P, a \in \mathbb{R}, w \in \mathbb{R}^P,
    \end{split}
\end{equation}
in which the neural network models the scale of $F_{T \mid X = x}$, which allows for linear
non-proportional hazards. Still, the model is not distribution-free, the resulting distributions
are again Weibull or log-logistic.

The general shift transformation model parameterizes the transformation function using Bernstein
polynomials,
\begin{equation}
    \begin{split}
        h(t \mid x; \phi) = b(\log t)^\top\vartheta + \phi(x)^\top w, \mbox{ where}, \\
        \phi: \mathcal{X} \to \mathbb{R}^{P}, b: [0, 1] \to \mathbb{R}^{K + 1},
    \end{split}
\end{equation}
which requires $\vartheta$ to be increasing, \textit{i.e.},~ $\vartheta_{k+1} > \vartheta_k$, $k = 1,
\dots, K$, for all $x$ to ensure monotonicity of $h(t \mid x; \phi)$ in $t$ \citep{hothorn2014conditional}.
Monotonicity can be ensured by transforming
\begin{align*}
    \vartheta = g(\gamma) = \left(\gamma_1, \gamma_1 + \operatorname{softplus}(\gamma_2),
    \dots, \gamma_1 + \sum_{k = 2}^{K+1} \operatorname{softplus}(\gamma_k) \right).
\end{align*}
The general shift transformation model allows a flexible baseline hazard function.
The transformation function influences all higher moments of $F_{T \mid X = x}$ and the
model is distribution-free. Thus, the general shift model can be viewed as a parametric
version of the Cox proportional hazards model.

The shift-scale transformation model,
\begin{equation}
    \begin{split}
        h(t \mid x; \phi) = \operatorname{softplus}(\phi(x)^\top \beta) \cdot
        b(\log t)^\top\vartheta + \phi(x)^\top w, \mbox{ where} \\
        \phi: \mathcal{X} \to \mathbb{R}^{P}, b: [0, 1] \to \mathbb{R}^{K+1},
    \end{split}
\end{equation}
allows for non-proportional hazards, explicitly modelling the scale of $F_{T \mid X = x}$.
The model is distribution-free \citep{siegfried2022distribution}.

Allowing the parameters of the Bernstein polynomials to fully flexibly depend on $x$, we
arrive at the most flexible transformation model
\begin{equation}
    \begin{split}
        h(t \mid x; \vartheta) = b(\log t)^\top\vartheta(x), \mbox{ where} \\
        \phi: \mathcal{X} \to \mathbb{R}^{P}, b: [0, 1] \to \mathbb{R}^{K+1}
    \end{split}
\end{equation}

It is important to note that for all of the above $u = \log t$ is scaled to
$\tilde u = \frac{u - a}{b - a}$ where $a, b$ are chosen appropriately, \textit{e.g.},~ min and max.

\subsection{Ensemble predictions} \label{sec:ensembling}

The linear shift and linear scale parameterizations induce strong
distributional assumptions on $T \mid X = x$. Nevertheless, these distributional
assumptions can help prevent overfitting and lead to more stable predictions.
Using the Bernstein polynomial basis loosens assumptions, but is prone to
overfitting. However, deep ensembles have been shown to improve prediction
performance in both cases \citep{lakshminarayanan2016deepensembles}.

Let $\hat F_1, \dots, \hat F_M$ be $M$ estimates of the conditional distribution
of $T \mid X = x$, \textit{e.g.},~ obtained by optimizing $M$ instances of the same DCTM via SGD
and early stopping on different bootstrapped data samples. The ensemble estimate is
the point-wise average of those $M$ estimates, and denoted by $\bar F_M$,
\begin{align}
    \bar F_M = M^{-1} \sum_{m = 1}^M \hat F_m.
\end{align}
The ensemble distribution is then used for evaluation. When having access to $B > M$
estimates and selecting $M$ based on their validation loss, we refer to $\bar F_M$
as the top-$M$ ensemble estimate.

\subsection{Data} \label{sec:data}

\subsubsection{Real data}

The real data used in this study comprised 959 stage 4 lung cancer patients from Memorial
Sloan Kettering Cancer Center (MSKCC) diagnosed from Oct 2010 through Mar 2018. The data
used included pre-treatment PET/CT images of the subjects, overall survival time and
censoring information. 768 of the patients (80\%) experienced a terminal event, while 191
(20\%), were right-censored. The patients comprise a real-world, clinical grade cohort
collected over many years on a wide selection of scanners, with cases reviewed by many
different clinicians, and patients prescribed varying treatment regimens. The
retrospective data use was approved by the local ethics committee at MSKCC, and
informed consent was waived since the study was deemed minimum risk.

\subsubsection{Semi-synthetic data}
The DCTM architecture was used to model the conditional time to event distribution of the
real data described above. Three different DCTM parametrizations were used of increasing
complexity: linear shift, linear scale, and fully flexible Bernstein. The entire real
data dataset was used to train each DCTM model for a predetermined number of epochs.
The fitted models were then used to generate new semi-synthetic time-to-event data. If a
time was predicted beyond the real data's range, it was right-censored to the maximum
value. For each patient we sampled 10 new data points, resulting in datasets 10 times
larger than the original (see Figure~\ref{fig:sampling}d).

\subsection{Computational details} \label{sec:compdetails}

All experiments were performed on the high-performance computing (HPC) cluster at MSKCC.
Training scripts were written in python using PyTorch \citep{paszke_automatic_2017} for
model definition and optimization. Model optimization was performed with SGD and training
learning rates were chosen via a hyperparameter grid search on a single data
training/validation partition. For the DCTM models, different learning rates were used for
the CNN feature extractor and the DCTM survival layer. The full list of learning rates used
for all experiments is presented in \ref{tab:lr}.

\begin{table}[!ht]
\centering
 \caption{\label{tab:lr}List of learning rates used to train models for all experiments in this study.}
 \begin{tabular}{llrr}
 \toprule
 \bf Parametrization & \bf CDF & \bf lr CNN & \bf lr DCTM \\
 \midrule
 Deepsurv & & 0.0005 & \\

 Baseline & Sigmoid & & 0.1\\
 Linear shift & Sigmoid & 0.001 & 0.01 \\
 Linear scale & Sigmoid & 0.001 & 0.1 \\
 Bernstein shift & Sigmoid & 0.001 & 0.1 \\
 Bernstein shift/scale & Sigmoid & 0.001 & 0.01 \\
 Bernstein & Sigmoid & 0.001 & 0.1 \\

 Baseline & Gompertz & & 0.01\\
 Linear shift & Gompertz & 0.001 & 0.01 \\
 Linear scale & Gompertz & 0.001 & 0.01 \\
 Bernstein shift & Gompertz & 0.001 & 0.01 \\
 Bernstein shift/scale & Gompertz & 0.001 & 0.01 \\
 Bernstein & Gompertz & 0.001 & 0.1 \\
 \bottomrule
 \end{tabular}
\end{table}

\section{Results} \label{sec:results}

\subsection{Real Data}

Experiments were carried out to test the performance of DCTM models of increasing complexity.
As a baseline a Bernstein non conditional model, where the same output is associated to every
sample, was used. DCTM results were also compared with DeepSurv. Since DeepSurv does not
compute the full likelihood, only the c-index can be compared in this case.
Figure~\ref{fig:results_real}a reports the distributions of validation NLL for each experimental
condition in order of complexity, starting with the baseline at the top and finishing with the
fully flexible Bernstein model at the bottom. It can be observed that, for both CDF functions,
the NLL decreases with model complexity, as expected. In addition, it is apparent that the
Gompertz experiments resulted in wider NLL
distributions, highlighting the underlying training instability we observed for this subset of
experiments.
Figure~\ref{fig:results_real}b reports the c-index results. The baseline results are by definition
0.5, since all patients are assigned the same output time-to-event. It is interesting to note that
while the NLL decreased with model complexity, a slight trend of decreasing c-index can be observed.
Compared to DeepSurv, the DCTM models perform on par or better, except in one condition.
Finally, Figure~\ref{fig:results_real}c reports the results in terms of CRPS. In concordance with
the NLL results, a slight trend of decreasing CRPS with model complexity can be noted.

\begin{figure}[!ht]
    \centering
    \includegraphics[width=1\textwidth]{figures/results_real.png}
    \caption{Experimental results for the real data. The performance of different parametrizations
    of DCTM are shown compared to DeepSurv where possible. For DCTM, the sigmoid and Gompertz
    functions were tested. a) Distribution of validation NLL. b) Distribution of validation
    c-index. c) Distribution of validation CRPS.}
    \label{fig:results_real}
\end{figure}

\subsection{Simulated Data}

To analyze the behavior of DCTMs when the interaction between inputs and survival comes from
different distributions, three semi-synthetic datasets of increasing complexity were generated
as described earlier. In Figure \ref{fig:results_synth} are shown the results of the experiments
performed on the semi-synthetic data.
Figure \ref{fig:results_synth}a shows the distribution of validation resuts in terms of NLL for
the three datasets fitted with various DCTM parametrizations. In all the experiments, the sigmoid
function was used as CDF. While it is expected that data of lower complexity would be easier to fit,
the opposite effect can be observed, where the linear shift generated data resulted in a higher NLL,
while the flexible bernstein generated data resulted in lower NLLs. Additionally, unlike our results
on the real data, the simplest DCTM parametrization resulted in the lowest NLL in each of the three
datasets. Figures \ref{fig:results_synth}b,c show similar trends in terms of c-index and CRPS
respectively. In figure \ref{fig:results_synth}b it can be noted that DCTM achieves similar performance
as DeepSurv on the three datasets.

\begin{figure}[!ht]
    \centering
    \includegraphics[width=1\textwidth]{figures/results_synth.png}
    \caption{Results of the experiments performed on the semi-synthetic data. For each of the three
    datasets, the performance of different parametrizations of DCTM are shown compared to DeepSurv
    where possible. a) Distribution of validation NLL. b) Distribution of validation c-index.
    c) Distribution of validation CRPS.}
    \label{fig:results_synth}
\end{figure}

\section{Discussion} \label{sec:outlook}

In this work we have introduced DCTMs as a novel framework for parametric and semiparametric survival
analysis that can leverage the power of deep learning to learn patient stratification strategies directly
from high-dimensional non-tabular data. Techniques such as this are necessary in the medical domain to
advance the understanding of disease generation and progression.
Modelling time-to-event outcomes directly from non-tabular medical data such as radiology images, as presented
here, has the potential to shed light in the biological processes underlying complex diseases such as cancer,
and change how patients are treated ultimately improving patient outcomes. Extensions to time-varying
covariates and competing risks exist for transformation models with tabular data \citep{fokas2017} and can be carried
over to DCTM{s}, which we leave for future work.

\section*{Acknowledgments}

The authors are grateful for the generous computational support given by the Warren Alpert
foundation, and the project management support of Christina M. Virgo. GC, IH, and TF were
supported in part through the NIH/NCI Cancer Center Support Grant (grant number P30 CA008748).
The research of LK was supported by Novartis Research Foundation (FreeNovation~2019) and by
the Swiss National Science Foundation (grant no. S-86013-01-01 and S-42344-04-01).
TH was supported by the Swiss National Science Foundation (SNF) under the project
``A Lego System for Transformation Inference'' (grant no. 200021\_184603).
TF is a founder, equity owner, and Chief Scientific Officer of Paige.AI.


A novella written by Mary Hayley Bell and originally illustrated by Owen Edwards, first published in 1959. The central characters are three children - Swallow, Brat and Poor Baby - who find a man in their barn who they believe is Jesus. The book was filmed to great success (becoming the 8th most popular movie at the UK box office in 1961), starring the author's daughter, Hayley Mills.


Dreaming of Death, Dead Persons and Reports Given by them.
Death : Death in the dream symbolises corruption of a person's Deen while there will be glory, rank and honour for him in the world if such death is not accompanied by mourning, weeping, the carrying of a bier or corpse or the act of burying.
On the contrary, if death is not accompanied by anything that suggest burial, mourning, weeping, giving of ghusl, takfeen, the carrying of the bier or corpse, it may mean that a portion of his house will be destroyed, or its wall or its timber will fall down. Some interpreters have said that perhaps he will weaken in the matter of his Deen and he will lose his insight and prudence.
Alive in the Grave : If a person sees himself as alive in the grave he will either be imprisoned or he will find himself in some straitened circumstances.
Digging One's Own Grave : Seeing oneself digging one's own grave means one will build for oneself a house in that town or place.
Speaking to the Dead : If a person sees himself as asking a dead person about anything regarding the dead persons' or another's condition then the answer of the dead person will be true to its word- whether good or bad- for the dead person dwells in the world of truthfulness (ie. Aakhirah) as opposed to the world of falsehood (ie dunya). Thus, he does not speak a lie in whatever report he gives.
Seeing a Deceased Person as Happy : Seeing a deceased person in a good condition such as donning white or green clothes while he is laughing or giving glad tidings means that he, the dead man is in peaceful and happy conditions.
Seeing a Deceased person as Unhappy : Seeing a dead person as disheveled with dust on his body or donning old, torn and tattered clothes or as angry means that he is not in a peaceful condition in the herafter.
To see him as ill means he is burdened with sins.
Dying for the Second Time : If a dead person is seen as dying again and there is weeping without screaming and mourning it means a relative of his will get married and the marriage will bring great happiness and pleasure.
But is there is screaming and mourning then it means a close family member will die.
Digging the Grave of a Dead Person : If a person sees himself digging the grave of a dead person who is known to him it means he will follow in his footsteps in worldly as well as religious matters. If he is unknown to him, he will pursue a matter wherein he will not succeed.
An Incident : It is related that when Imaam Aboo Haneefah (RA) was still a child, he dreamed tht he was digging the grave of Rasoolullah 9Sallallaahu-alayhi-wasallam). He related the dream to one of his tutors in the maktab. The teacher said to him: "My child, if your dream is genuine then you will follow in the footsteps of Rasoolullah 9Sallallaahu-alayhi-wasallam) and you will also do great research in his shari'ah". Every word of the interpretation manifested itself to be true and correct as is known by one and all.
Accepting from or Giving to the Deceased Something : Accepting something from the dead is regarded as good while giving him something is regarded as bad.
If a person sees a dead person giving him something of this world it mean he will acquire livelihood from an unimaginable source. And if he sees himself giving a dead person clothes normally worn by living persons and he accepts such clothes and wears them it means he (the giver) has a short life span.
Carrying the Dead : if a person sees himself carrying a dead person in any manner other than the normal manner of carrying a bier or corpse it means he will carry a burden of haraam wealth. Some interpreters say that the same dream could mean that he is spending his wealth on some pervert.
If a person sees himself as carrying a dead person in a normal way it means he will either obey and follow the ruler of the time or he will take upon himself some of his responsibilities.
Embracing a Dead Person : If a person sees a dead persons embracing him, squeezing him or killing him it means he will attain a good old age.
Entering an Unknown House with the Dead : Entering an unknown house in the company of a dead person means he will die soon and thus join the dead person.
A Dead Person Entering the Home of a Sick Person : Either his sickness will prolong or he will die soon.
Giving the Dead Roti, Bread or a Ring : It means a son will be born to him and he will die, or if he is wealthy he will lose his wealth.
And Allah, The Pure and Sublime knows best.


text:
Jan Eskil Magnusson, född 5 september 1950 i Tönnersjö i Halmstads kommun,<ref name="Lännerberg 2000 m citat">Lännerberg 2000. Citat:
"Det är Jans och frun Ninas barn Alexander, Natalia och Anja. [---] Familj: Frun Nina, sonen Alexander 21 år och döttrarna Natalia 19 och Anja 9."</ref> är en svensk redaktör och författare. Han var Bamses chefredaktör 1990–2002, där han efterträdde tidningens ursprunglige upphovsman Rune Andréasson.

 Biografi
 Uppväxt
Magnusson är uppvuxen i Halmstads kommun. Han är son till hemmansägare Carl Magnusson (1893–1969) och dennes hustru Karin (1913–2004).Föräldrarnas tilltalsnamn och stavningsform: se fotografiskt sökresultat på "karin johanna elisabet magnusson" på Gravar.se. Läst 2019-02-25. När Jan Magnusson var fem år fick han sin första bok:

 Tidig karriär
Magnusson arbetade först som högstadielärare  och utbildade sig sedan till journalist. Han var verksam som radiojournalist på Radio Malmöhus och Radio Halland, och var därefter frilansande dagspressjournalist åt bland annat Resumé, innan han anställdes som informationssekreterare på läkemedelsföretaget Draco.
När karriären som serietidningsredaktör tog vid (1990) hade han även en bakgrund som lektör åt Bibliotekstjänst.

 Tidningsredaktör

Efter att ha sökt en utannonserad tjänst som Kalle Anka & Co-redaktör blev Jan Magnusson, ett halvår senare, tillfrågad av samma förlag om han istället ville bli Bamses chefredaktör, detta efter att tidningens ursprungliga upphovsman Rune Andréasson (med familjeföretaget Bamseförlaget) sålt utgivningsrättigheterna till danska mediekoncernen Gutenberghus (från 1992: Egmont). På den vägen blev Magnusson redaktör för totalt 153 utgåvor av Bamse från 1990 till 2002. Anställningen tog sin början under kalenderåret 1990. Under Magnussons redaktörstid sjösattas också sidopublikationerna Bamses julalbum (1991–), Bamse-Extra (1992–), Bamses naturvänner (1995–1996), Bamses brandskola (1996) och faksimilbokserien Bamsebiblioteket (2000–2015).

Det var Jan Magnusson som hittade på att Bamses yngsta dotter Brumma, till skillnad från andra figurer i serien, varken blir stark eller får ont i magen av att äta dunderhonung.

Magnusson tog adjö av läsarna på "Bamses brevsida" i nr 9/2002: "Nu kommer jag inte att skriva mer på den här sidan, för jag har bestämt mig för att sluta som redaktör för BAMSE. Jag vill göra andra saker i livet." Att Magnusson lämnat posten som chefredaktör blev offentligt känt genom Göteborgs-Posten den 6 mars 2002, om inte förr. Samma år blev Jan Magnusson redaktör för tidningen Bolibompa.

 Författande och undervisning

Som en följd av sin redaktörstjänst på Egmont började Magnusson spökskriva Bamse-berättelser, och så småningom också historier om andra kända barnboksfigurer, såsom Alfons Åberg och Lilla spöket Laban.Roijer 2013, s. C8.

Under sina tolv år på Bamseredaktionen skrev Magnusson ofta seriemanus i samarbete med Rune Andréassons äldsta son Dan.

Magnusson framhöll Burre som sin favorit bland Bamse-figurerna: "Han kan vara elak, men innerst inne är han snäll", förklarade han i en tidningsintervju år 2000.

Sedan Magnusson lämnat Bamseredaktionen 2002 har han sporadiskt fortsatt att skriva Bamse-böcker (både med och utan Dan Andréasson) samt skapat nya barnbokskoncept ihop med sina tidigare Bamse-kollegor Kenneth Hamberg, Kerstin Hamberg och Alicja Björk. Hans "första helt egna barnbok" var Lilla Snöret upptäcker världen (2010), illustrerad av Alicja Björk.

Magnusson har vid sidan av sin skönlitterära produktion också skrivit en guidebok om Kroatien.

Under 2010-talet har han åter till viss del arbetat som lärare inom grundskolan (mellan- och högstadiet).Eriksson 2014.

 Familj
Jan Magnusson var tidigare gift med läraren Nina Kuprijanko (född 1951). Tillsammans fick de tre barn. Samtliga barn var manusmedarbetare i Bamse under Magnussons redaktörstid, samt fungerade under uppväxtåren som en stor inspirationskälla i faderns arbete.

 Redaktörsinsatser
Bamse
 1990–2002 – Bamse (1990:8–2002:5; dvs. utgåvorna #201–353)
 1996 – Bamses brandskola 2000–01 – Bamsebiblioteket (volym 1–3)
 2018 – Egmont miniböcker (bearbetning och nedkortning):
 Bamse och Gluff-Gluff – (text: Lisbeth Wremby efter manus av Rune Andréasson; bild: Andreas Qassim; tusch: Kerstin Hamberg)
 Bamse och Tutelutt – (text: Mårten Melin efter manus av Rune Andréasson; bild: Thomas Holm)
 Bamse och Reinard Räv – (text: Mårten Melin; bild: Adam Blomgren; tusch: Kerstin Hamberg)
 Bamse och luringarna från Galna Galaxen – (text: Mårten Melin; bild: Adam Blomgren; tusch: Kerstin Hamberg)
 Bamse och det märkliga huset – (text: Mårten Melin; bild: Ted Johansson; tusch: Kerstin Hamberg)
 Bamse och Nina Kanin på äventyr – (text: Joakim Gunnarsson; bild: Thomas Holm)
 Bamse och Brummelisa – (text: Joakim Gunnarsson; bild: Lars Bällsten; tusch: Ann Härdfeldt)
 Bamse och Hoppa-Tossa – (text: Karin Didring; bild: Thomas Holm)

Roliga historier
 2005 – Fler roliga historier: Norge, frågisar, Bellman, gåtisar, flabbisar, alla barnen (tills.m. Göran Criborn)
 2007 – Mixade maxade historier: Norge, flabbisar, alla barnen, gåtisar, frågisar, Bellman (tills.m. Göran Criborn; ill: Kenneth Hamberg)
 2007 – Ännu fler roliga historier: flabbisar, frågisar, Bellman, alla barnen, gåtisar, Norge (ill: Kenneth och Kerstin Hamberg)

Övrigt
 Bolibompa (2002–?)

 Bibliografi som skönlitterär författare

 Bibliografi som facklitterär författare
 Förord (i böcker)
 1998 – Maxine (seriealbum av David Liljemark m.fl.)
 2001 – Bamsebiblioteket volym 2

 Reselitteratur
 2005 – Kroatien: fantasi och fakta (tills.m. Monica Brundin Danielsson, Lars Brundin och Elizabeta Glasnovic Raguz)

 För barn
 2006 – Coola kalla fordon och maskiner i snö 2017 – Lär dig skriva! Bokstäver och ord (ill: Kerstin och Kenneth Hamberg)
 2018 – Lär dig skriva! Ord och meningar (ill: Kerstin och Kenneth Hamberg)
 2018 – Stora maskiner på gården Översättningar

 Priser och utmärkelser
 2000 – Svenska Serieakademins Adamson-diplom (för sin regi av serietidningen Bamse, "där han med skicklighet och djupt engagemang arbetar i Rune Andréassons anda, men också har lyckats modernisera tidningens innehåll")

 Referenser
Kommentarer

 Noter

 Citat

 Tryckta källor

 Magnusson, Jan (2002). "Hej, kära vänner!", Bamse 2002:9, s. 2.

 Melin, Mårten (2006). "Den 'nya' Bamse", i Gunnarsson Joakim, red., Bamsebiblioteket: Bamses bästa'' (Malmö: Egmont Kärnan) 2: sid. 4–5.

Svenska serieskapare
Bamsetecknare och -författare
Svenska författare under 1900-talet
Svenska författare under 2000-talet
Författare från Halmstad
Födda 1950
Levande personer
Män


Let's have the discussion about what is violence and what isn't.
I think it is interesting that in my experience, it is the white males (the dominant originators, perpetrators & perpetuaters of violence against life) that are normally obsessed with and susceptible to media spins (oh they're sooooo violent...) labeling protestors and their actions violent.
My understanding - largely from my participation in those civil rights demonstrations I did participate in - is that "non-violence" was defined as "no violence against human beings, specifically reacting to police and counter-protestors (as kkk, etc.) with violence".
Direct actions by people standing up to power have ALWAYS been characterized at some point or another as "violence" i.e. sitting at a lunch counter, entering a school, blocking a doorway - where the action of power, i.e. separate but equal, armed individuals named police/military, the hogging for some and deprivation for others of resources, are rarely defined as "violence"
For me, the appearance of a cop wearing many objects of lethal weapons IS violence, the huge mansions with wisteria-laced iron fences is violence, the expensive restaurants oozing special food and overflowing garbage cans is violence.
A building that stands empty, that formerly provided services to people without those services IS violence; the taking over of that building is justice.
Furthermore, if we are truly building alliances and not dominating actions, our first job is to deeply trust ourselves, individuals and groups we are allying with are competent, thoughtful, compassionate and passionate activists that have thought about whatever they are deciding to do and are entitled to make their own choices sin condemnation - whether theirs is the act we personally would carry out or not.
I also think we can fall into grandiose superiority/inferiority traps - the under/thru/overpinnings of racism, sexism, classism, all isms in our society - where we can feel sooooo superior in our knowledge of which action is best, which is not.
This is not to say we do not have judgments, critical thinking, as well as experiences and we learn & grow from them. But it is to say that NO ONE really knows for sure what are the best tools for demolishing the empire.
I think we should embrace the original meaning and intent of "non-violent" as "no violence against human beings" and divorce it from it's modern & media-inflamed definition to include property: this marriage of life & property is distracting at best, extremely divisive at worse.


text:
Q. Who is Mr. Smarty Plants?
A: There are those who suspect Wildflower Center volunteers are the culpable and capable culprits. Yet, others think staff members play some, albeit small, role. You can torture us with your plant questions, but we will never reveal the Green Guru's secret identity.
Help us grow by giving to the Plant Database Fund or by becoming a member
Did you know you can access the Native Plant Information Network with your web-enabled smartphone?
Ask Mr. Smarty Plants
Ask Mr. Smarty Plants is a free service provided by the staff and volunteers at the Lady Bird Johnson Wildflower Center.
Search Smarty Plants
See a list of all Smarty Plants questions
Please forgive us, but Mr. Smarty Plants has been overwhelmed by a flood of mail and must take a break for awhile to catch up. We hope to be accepting new questions again soon. Thank you!
Need help with plant identification, visit the plant identification page.
rate this answer
Monday - May 21, 2012
From: Mahopac, NY
Topic: Diseases and Disorders, Trees
Title: Reason for tree canopy dieback from Mahopac NY
Answered by: Barbara Medford
Dear Mr. Smarty Plants: Not a questions, just sharing, re person in Texas whose Ash Jupiter appeared to be dying "canopy very thin on top". We moved to Putnam Co. NY in 1970. Our house was shaded by 2 beautiful, huge, American Elms. In approx. 1995 we noticed a thinning canopy on each. The canopies of these trees spread over two roads (corner property) and 2 houses (incl. ours). Contacted a NYS who sent a "ranger" to look at them. To make a long story short, he said that the trees had "started dying" when the 2 roads and then houses had been put in, severely damaging the roots. They both had to come down in early 2000s. It broke my heart!
Often when we are asked about mysterious symptoms in plants, especially trees, we suspect some interference with the roots or crowding by foundation or sidewalks. There is no way to tell if this is going on, especially if you were not present when the tree was planted or the structures built around it.
Still, credit where credit is due. Follow this link Ulmus americana (American elm) to our webpage on the tree. It does speak favorably about the tree but notes that Dutch Elm Disease has decimated the species. It also notes that this is a fast-growing tree, and fast growing trees are usually short-lived. If this tree was already shading your house in 1970 and didn't have to be cut down until 2000, it would appear that it lived a good long life.
We appreciate your offering this example of the difficulty of diagnosing (especially from a distance, as in our case) maladies or deaths of plants without a readily apparent reason.
Ulmus americana
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text:
Peter Boyd (born 1950) is a world champion American bridge player. He has won one world championship, finished second in another, and won 17 North American bridge championships.

Boyd was born in Washington, DC and still lives there. He graduated from Harvard. He is a retired computer programmer.

Bridge accomplishments

Awards

 Mott-Smith Trophy (1) 1987

Wins

 Rosenblum Cup (1) 1986
 North American Bridge Championships (17)
 Lebhar IMP Pairs (1) 2001
 North American Pairs (3) 1985, 2016, 2017
 Grand National Teams (3) 1984, 1988, 1992
 Jacoby Open Swiss Teams (2) 1986, 2012
 Vanderbilt (3) 1987, 1991, 1997
 Senior Knockout Teams (1) 2012
 Keohane North American Swiss Teams (1) 2013
 Mitchell Board-a-Match Teams (2) 1989, 1994
 Reisinger (1) 1986

Runners-up

 d'Orsi Senior Bowl (1) 2011
 North American Bridge Championships
 von Zedtwitz Life Master Pairs (1) 1987
 Lebhar IMP Pairs (1) 2004
 Blue Ribbon Pairs (1) 1982
 Nail Life Master Open Pairs (1) 1988
 Grand National Teams (2) 1985, 2011
 Vanderbilt (2) 1992, 1999
 Spingold (1) 1992

Notes

External links

1950 births
Living people
American contract bridge players
People from Washington, D.C.
Harvard University alumni
Date of birth missing (living people)