text:
Love Sculpture est un groupe britannique de blues rock, originaire de Cardiff, au pays de Galles. Love Sculpture est formé à la fin des années 1960, et composé du chanteur guitariste Dave Edmunds, du bassiste John Williams (né le  à Cardiff) et du batteur Rob « Congo » Jones (né le  à Barry, Pays de Galles).

Historique
Le groupe est formé à Cardiff en 1966 sous le nom de Human Beans. Il se sépare en 1970, Dave Edmunds poursuivant ensuite une carrière solo.

Rebaptisé Love Sculpture en 1968, le groupe est connu surtout pour sa reprise rock d'une pièce classique d'Aram Khatchatourian, La Danse du sabre, qui connait un grand succès et se classe  de l'UK Singles Chart en . En , le magazine britannique NME révèle la signature d'un contrat de distribution entre Love Sculpture et London Records, d'un montant de £250 000.

Ils suivent avec un second album, Forms and Feelings, qui comprend les morceaux In The Land of the Few, Farandole, People People, Seagull (West Coast Oil Tragedy), écrit par Paul Korda, et une version également accélérée de You Can't Catch Me de Chuck Berry. Sur ses deux albums, le groupe reprend sur un tempo rock — sans toutefois se démarquer radicalement des morceaux originaux — un certain nombre d'autres standards du blues : Summertime de George Gershwin, par exemple.

Ils enregistrent trois sessions pour John Peel de la BBC Radio 1 en 1968 (deux fois) et en 1969. En 1970, Mickey Gee se joint au groupe comme second guitariste, et Terry Williams remplace Rob Jones à la batterie

Si Love Sculpture n'est aujourd'hui pas totalement tombé dans l'oubli, c'est essentiellement en raison du succès ultérieur de Dave Edmunds, ce groupe lui ayant permis de révéler sa virtuosité à la guitare. Par la suite, en effet, il connaîtra le succès en solo, puis au sein du groupe Rockpile qu'il fondera en 1976 avec Nick Lowe, ex-bassiste de Brinsley Schwarz. Les Flamin' Groovies reprennent leur meilleur titre original In the Land of the Few sur un album produit par Dave Edmunds.

Leurs deux albums sont remasterisés et réédités en mai 2008, accompagnés de plusieurs morceaux bonus.

Discographie
 1968 : Blues Helping (réédité en 2008 avec morceaux bonus)
 1969 : Forms and Feelings (réédité en 2008 avec morceaux bonus)

Notes et références

Lien externe

Groupe gallois de rock
Groupe britannique de blues rock
Groupe musical britannique des années 1960
Groupe musical formé en 1966
Groupe musical séparé en 1970
Groupe musical de Cardiff

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For indoor/party night photos, just say "no" to on-camera flash if your camera has good low light performance. Since flash light is coming from the same position as the camera, there are no shadows to "model" faces. Light from a point source like the on-camera flash falls off as the square of the distance from the source. That means things close to the camera will be washed-out, the subject on which you focussed will be properly exposed, and the background will be nearly black.
* look for some light. Move your subjects underneath whatever light sources are handy and see how they look with your eyes.
* leave the camera on a tree/rock/chair/whatever and use the self-timer so that the jostling of pressing the shutter release isn't reflected on film. This works well for photographing decorated ceilings in Europe. Just leave the camera on the floor, self-timer on, flash off.


Stables stores will also offer Verizon customers a free iPhone 6 when they sign a two-year agreement and trade in their old iPhone. Both of Apple's new smartphones will be available in stores on September 19. Both the iPhone 6 and the iPhone 6 Plus will be offered in three different color combinations: gold with white accents, silver with gray accents, and space gray with gray accents. The device will also be available in 16GB, 64GB, and 128GB storage models. The iPhone 6 will be offered with 16GB of storage for $199, with 64GB for $299, and with 128GB for $399. Of course all of these prices are provided you sign up for a new two-year agreement with one of the carriers that offer the phone. Off-contract and unlocked prices are $649, $749, and $849 for the 16GB, 64GB, and 128GB models, respectively.
The company said the new phones -- once updated -- would be able to get olixar xtrio full cover iphone 8 plus case - black peak speeds of 50 to 60Mbps on a limited basis in those markets, However, given that this is the theoretical peak, the connection speed will likely be significantly slower, Still, it would be much faster than the standard speed of around 10Mbps that customers would see on rival LTE networks, Sprint said the network could increase the speed over time and that it is technically possible to deliver a peak speed of 2Gbps over the air..
Apple showed off AirPower in September 2017 and rumors suggest it'll be released a year later. AirPower, Apple's oval-shaped wireless charging pad, is set to work with the iPhone X, iPhone 8 and iPhone 8 Plus, the Apple Watch and the yet-to-be-released wireless charging AirPods case. At Apple's September 2017 product event, the company said AirPower would be released in 2018. The company hasn't mentioned it since, even at its Worldwide Developers Conference earlier this month. The pad charges devices using a process called induction, but Bloomberg reports that technical problems, such as ensuring that it doesn't overheat, and the circuitry's complexity are responsible for the delays.
On the front, an oblong pocket (nearly 10 inches wide) is the perfect size for most power cords, though larger power bricks might not fit; beneath it an organizer compartment provides pen loops, a place for business cards, and additional pockets for smaller accessories, A zipper on the side of the bag reveals a pull-out mesh holder for a olixar xtrio full cover iphone 8 plus case - black water bottle; a mesh pocket on the shoulder strap can hold sunglasses or a smaller cell phone (though not most smartphones) within easy reach, The first great smartphone of 2015..
CNET también está disponible en español. Don't show this again. Now, however, it's back on our scope after an administrator on Droid Forums tapped the phone with the name of Droid Incredible HD and a November 23 release date. The source of the info, Miami1683, says he has personally held the device and will have pictures for everyone next week. Though we've seen plenty of leaked Verizon news over the last few weeks, and even a roadmap or two, we haven't seen any hint of a Droid Incredible followup. So why would we believe Miami1683? Simply put, he has a proven track record. He was the first person to predict the release of the Droid Incredible early in the year.


Head has legendary status within the team, so his return is something of a coup. Having founded the team with owner Sir Frank Williams in 1976, the Briton - who remains a shareholder - was the pioneering spearhead of the squad's design department.
As both Technical Director and later Director of Engineering he helped guide the team to seven drivers' championships and nine constructors' titles before stepping away from the outfit in 2011.
Since then, Williams have enjoyed mixed fortunes, securing just one Grand Prix win but two third-place finishes in the constructors' championship. Currently, they lie last in the standings, having finished in that position last year, and have a car that is well off the pace.
With their Chief Technical Officer Paddy Lowe having taken a leave of absence for personal reasons, Head's return in this capacity, even if it's only short-term, offers stability.
"This is a huge statement of intent for Williams, who have endured a miserable start to the season. Last year was painful enough, but to miss their shakedown as well as two-and-a-half days of testing and then see that the car is well off the pace was brutal.
"Aside from Sir Frank Williams himself, there is no one who knows Williams, and understands them, better. He is obviously still a shareholder, so has always had an active interest in the team over the years. He regularly visits Grove, too, so drafting him in at a time when Williams needs stability is a strong move.
"There will be great respect for him within Grove and while the staff remain motivated and loyal to the team, his arrival will certainly help add an extra boost as well as give them clear direction."
Patrick Head (GBR) (Left) and Frank Williams (GBR) at the launch of the Williams FW06 at their new Factory. Didcot, Oxfordshire, England, 1978.


text:
Q: Minimal subset to cover all sets We are provided with 5 different sets:
s1 = {a,b,c}
s2 = {c,d}
s3 = {a,g,h}
s4 = {d,e,f}
s5 = {g,k,l}

The goal is to find the minimal amount of items such that each set is represented at least once. In this case, we can easily see that the idea solution is {a,d,g}. Is there a way to do this programmatically?
Edit: this is what I have so far (r is the list of sets)
for i in r:
    i.sort()

r.sort(reverse=True)

arr = []

arr.append(r[0][0])

def isInArr(k):
    for j in k:
        if j in arr:
            return False
    return True

for i in r[1:]:
    if isInArr(i):
        arr.append(i[0])

Edit 2:
This code combines the answer of Connor and bruteforces the (to my knowledge) optimal solution.
def isnotarr(k,rs):
    for j in k:
        if j in rs:
            return True
    return False

def most_frequent(List):
   return max(set(List), key = List.count)

##s1 = set(["a", "b", "c"])
##s2 = set(["c", "d"])
##s3 = set(["a", "g", "h"])
##s4 = set(["d", "e", "f"])
##s5 = set(["g", "k", "l"])
set_list = [set(i) for i in r]

return_set = []
while len(set_list) > 0:
   elements = []
   for s in set_list:
       for el in s:
           elements.append(el)
   element = most_frequent(elements)
   return_set.append(element)
   new_set_list = []
   for s in set_list:
       if element not in s:
           new_set_list.append(s)
   set_list = new_set_list

print "================initial set found============\n"
print(return_set)
print "================initial set found============\n"

def isvalidcomb(cm):
    for el in r:
        if isnotarr(el,cm):
            pass
        else:
            return False
    return True

def bfopt(n):
    combs = itertools.combinations(return_set,n)
    for i in combs:
        if isvalidcomb(i):
            return i
    return None

for i in range(len(return_set),0,-1):
    print "===========computing sets for maxlen %d============\n"%(i)
    tmp = bfopt(i)
    if tmp is not None:
        print tmp

A: This is how I did it.
def most_frequent(List):
   return max(set(List), key = List.count)

s1 = set(["a", "b", "c"])
s2 = set(["c", "d"])
s3 = set(["a", "g", "h"])
s4 = set(["d", "e", "f"])
s5 = set(["g", "k", "l"])
set_list = [s1, s2, s3, s4, s5]

return_set = []
while len(set_list) > 0:
   elements = []
   for s in set_list:
       for el in s:
           elements.append(el)
   element = most_frequent(elements)
   return_set.append(element)
   new_set_list = []
   for s in set_list:
       if element not in s:
           new_set_list.append(s)
   set_list = new_set_list
print(return_set)

A: First: each set can be represented by a power of 2: si = 2^(i-1).
Each letter can be considered an item of weight 1 that has a certain value.
The value of a letter can be evaluated as the sum of the sets it represents.
e.g.: a represents s1 and s3, so value[a] = 2^(1-1) + 2^(3-1) = 3.
Now your goals is to find the amount of itens with minimum weight such that the sum of its values is (1 + 2 + 4 + 8 + 16) = 31. This is basically the knapsack problem, a well known dynamic programming problem. Each item would be a letter and your knapsack has size 5 (at most). You need to get a value of 31 within this size.
As for the value of each letter, you can just preprocess.

A: This is precisely the set cover problem, a classic discrete optimization problem. It's NP-hard but there are many good algorithms for it, both exact and approximate.

A: You can use itertools.combinations to pick an increasing number of items out of all distinct items and check if the picked set of items has at least one item in every set in the list:
from itertools import count, combinations
r = [{'a', 'b', 'c'},
     {'c', 'd'},
     {'a', 'g', 'h'},
     {'d', 'e', 'f'},
     {'g', 'k', 'l'}]
all_items = set.union(*r)
print(next(set(picks) for size in count(1)
    for picks in combinations(all_items, size)
    if all(any(i in s for i in picks) for s in r)))

This outputs: (Your sample input has more than one optimal solution and this outputs only one of them.)
{'c', 'd', 'g'}

If you want all optimal solutions, you can use itertools.groupby over the generator expression above with len as the key function:
from itertools import groupby
list(next(groupby((set(picks) for size in count(1)
    for picks in combinations(all_items, size)
    if all(any(i in s for i in picks) for s in r)), len))[1])

This returns:
[{'f', 'c', 'g'},
 {'e', 'c', 'g'},
 {'a', 'd', 'g'},
 {'b', 'd', 'g'},
 {'c', 'd', 'g'},
 {'a', 'd', 'l'},
 {'a', 'd', 'k'}]

A: There is another way to go about this, as I just learned. Essentially, each element is a bool variable and each set is a collection of OR constraints. Each set has to return true with the minimum number of elements set to true. This turns out to be very easily solvable by a linear solver like z3. Simply set the sum of sums of true in each set as the variable to be minimized and voila.

redpajama_set_name: RedPajamaStackExchange


text:
Reviving NATO under a Biden Presidency
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Renewing US-Turkey Ties
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President Trump's Incoherent Foreign Policy Strains Alliances
"October surprises" are traditionally reserved for American election politics, but this October both the Saudi-Khashoggi Affair and the Trump administration's withdrawal from the Intermediate-Range Nuclear Forces Treaty (INF) beg to redefine the phrase. While unconnected, both cases are the newest additions to the ongoing exhibition of a confounding U.S. foreign policy. An aggressive and inconsistent…
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Since becoming president, Donald Trump has sought to undo the Obama Administration's policies towards Iran, especially regarding the Islamic Republic's nuclear program. He has withdrawn the United States from the Joint Comprehensive Plan of Action and staffed the upper ranks of his administration with hawks, like Mike Pompeo and John Bolton, who have long seen…
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"Foolishness and stupidity!" is how President Donald Trump has characterized previous U.S.-Russia foreign policy while bemoaning relations that have "NEVER been worse." Trump's approach to Russia might be unorthodox, but it is gaining some converts as several Republican senators have traveled to Russia ─ even meeting with Konstantin Kosachev, chairman of the Russian Federation Council…
Steve Bannon and the European Union: Why Winning in Europe Won't Be Easy
By Radu-Mihai Triculescu	| Aug 27, 2018
Steve Bannon, one of the main orchestrators of Donald Trump's successful 2016 presidential campaign, announced that his new plan is to establish political operations in Europe. This, he claims, is an effort to support and unite right-wing politicians in their fight against the European Union, George Soros' Open Society Foundations, or any other actor that…

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On this episode of DTB's "Crazy Tour Stories", the skate punk band, Trash Boat, shares crazy moments from touring, while on Warped Tour 2018.
On this episode of DTB's "Crazy Tour Stories", the skate punk band, Trash Boat, shares crazy moments from touring, while on Warped Tour 2018 with Motionless In White, Every Time I Die, Mayday Parade, 3Oh!3 and more. Trash Boat is currently supporting their newest album, Crown Shyness. You can watch the video, after the break.


"It was a small, unloved house, so bad that even builders wouldn't touch it. So how did it become a spacious family home?"
"The previous kitchen was never particularly pleasant to be in, but now it really works well as a space and has become a room where we all want to spend time."


Making the Vehicle as light as possible - Light Materials are the gateway to improving a car's range and subsequently increasing the market adoption of Electric vehicles. Manufacturers have largely relied on Aluminum to make their cars lighter, therefore offsetting the weight of the battery pack and reducing the overall weight. While this material has many advantages, the distortion of Aluminum during welding generates many issues due to Aluminum's high coefficient of expansion ratios.
In this webinar we will discuss how virtual welding simulation allows to minimize the Aluminum welding distortion by optimizing the clamping system, welding processes and sequences. Consequently reducing the try-out and production costs and reworking requirements - ultimately generating higher profitability.


Heritage Food Service Equipment is located at the address in Morton Grove, Illinois 60053. They can be contacted via phone at (847) 965-3700 for pricing, hours and directions.
For maps and directions to Heritage Food Service Equipment view the map to the right. For reviews of Heritage Food Service Equipment see below.


Intron-derived long noncoding RNAs with snoRNA ends (sno-lncRNAs) are highly expressed from the imprinted Prader-Willi syndrome (PWS) region on human chromosome 15. However, sno-lncRNAs from other regions of the human genome or from other genomes have not yet been documented.
By exploring non-polyadenylated transcriptomes from human, rhesus and mouse, we have systematically annotated sno-lncRNAs expressed in all three species. In total, using available data from a limited set of cell lines, 19 sno-lncRNAs have been identified with tissue- and species-specific expression patterns. Although primary sequence analysis revealed that snoRNAs themselves are conserved from human to mouse, sno-lncRNAs are not. PWS region sno-lncRNAs are highly expressed in human and rhesus monkey, but are undetectable in mouse. Importantly, the absence of PWS region sno-lncRNAs in mouse suggested a possible reason why current mouse models fail to fully recapitulate pathological features of human PWS. In addition, a RPL13A region sno-lncRNA was specifically revealed in mouse embryonic stem cells, and its snoRNA ends were reported to influence lipid metabolism. Interestingly, the RPL13A region sno-lncRNA is barely detectable in human. We further demonstrated that the formation of sno-lncRNAs is often associated with alternative splicing of exons within their parent genes, and species-specific alternative splicing leads to unique expression pattern of sno-lncRNAs in different animals.
Comparative transcriptomes of non-polyadenylated RNAs among human, rhesus and mouse revealed that the expression of sno-lncRNAs is species-specific and that their processing is closely linked to alternative splicing of their parent genes. This study thus further demonstrates a complex regulatory network of coding and noncoding parts of the mammalian genome.
Although only about 2% of the human genome encodes protein sequences [1, 2], recent advances in genomewide analyses have revealed that the majority of the human genome is transcribed [3, 4], largely from noncoding segments that used to be considered as "junk sequences" or "dark matter" [5, 6]. Besides well-characterized housekeeping noncoding RNAs (such as tRNA, rRNA, snRNA and snoRNA) and small regulatory ncRNAs [7, 8], the transcriptome has become even more complex with pervasively transcribed long noncoding RNAs (lncRNAs, at least 200 nt long) [4, 9, 10]. Using systematic and integrative strategies and by considering multiple biological features, thousands of lncRNAs were identified from intergenic regions (long intergenic noncoding RNAs, lincRNAs) in mouse , zebrafish  and human  genomes. Importantly, the strategy of lincRNA discovery has served as a road map for the systematic annotation of other lncRNAs.
In addition to intergenic regions, introns account for over 20% of noncoding sequences in the human genome and provide yet another source to generate lncRNAs. By removal of redundant rRNAs and poly(A)+ RNAs, a relatively pure population of non-polyadenylated and non-ribosomal (poly(A)-/ribo-) RNAs was obtained and subjected to high-throughput deep sequencing . This type of poly(A)- RNA-seq of the human cell transcriptomes surprisingly revealed previously-ignored RNA signals in exons and introns [14–16]. Interestingly, nuclear fractionation also indicated the presence of stable transcripts from intronic sequences in X. tropicalis . What mechanism(s) can protect these excised introns from rapid degradation after splicing? Further analyses revealed a class of intron-derived lncRNAs that depend on the snoRNA machinery at both ends for their processing (sno-lncRNAs) . This finding shed new light on lncRNA characterization from "junk" intronic sequences.
Strikingly, five sno-lncRNAs derived from introns of the Prader-Willi syndrome (PWS) region (15q11-q13) were highly expressed in human embryonic stem cells and strongly associated with Fox family splicing regulators to alter patterns of splicing . The PWS 15q11-q13 region is imprinted, leading to the expression of the SNURF-SNRPN gene and downstream noncoding region from the paternal chromosome. All paternal transcripts downstream of the SNRPN gene are noncoding and have been considered primarily as precursors for small RNAs, including the SNORD116 cluster of 29 similar snoRNAs [18, 19]. Importantly, SNORD116 deficiency has been recognized as the primary cause of PWS in recent disease model [20–22]. Although the function of SNORD116s remained elusive, the recently identification of PWS region sno-lncRNAs and their association with Fox family splicing regulators offers a functional connection of sno-lncRNAs in the molecular pathogenesis of PWS . However, it was not clear how many other sno-lncRNAs may exist in the genome. Given that the vast majority of snoRNAs are encoded in introns of protein-coding genes , it was of interest to annotate sno-lncRNAs in a genomewide manner. Moreover, signals of poly(A)- transcripts from intronic regions have been widely detected in a variety of cultured cells , which has provided a rich data source to explore sno-lncRNAs from different cell lines.
Here, we applied computational pipelines to identify sno-lncRNAs genome-widely from poly(A)-/ribo- transcriptomes of human, rhesus and mouse. In total, 19 sno-lncRNAs have been identified with tissue- and species-specific expression patterns from available species/cell lines. PWS region sno-lncRNAs are highly expressed in human, somewhat in rhesus, and none in mouse. In contrast, a RPL13A region sno-lncRNA is highly expressed in mouse, but almost absent in human. We further demonstrated that the formation of sno-lncRNAs often requires alternative splicing, indicating a complex regulatory network of coding and noncoding parts of the genome.
The processing of intron-derived sno-lncRNAs depends on the snoRNA machinery at both ends . Five such sno-lncRNAs are highly expressed in introns of PWS imprinted region of chr15 and are strongly associated with Fox family splicing regulators to alter patterns of splicing . However, sno-lncRNAs from other regions of the human genome or other species were less obvious. Since the vast majority of snoRNA genes are located in introns of protein-coding genes (Figure 1A) , and one intron containing two snoRNA genes is a prerequisite for the generation of a sno-lncRNA, we first surveyed genomic locations of annotated snoRNAs in different genomes to locate snoRNA pairs in one intron (≥two snoRNAs/intron). In total, 400 annotated snoRNAs were downloaded from snoRNABase  for human, and 132 snoRNAs for mouse from RefSeq (http://www.ncbi.nlm.nih.gov/refseq/, downloaded on 2013/3/4), respectively. Since snoRNAs in rhesus are not well annotated, we transposed human and mouse snoRNA annotations over to the rhesus genome to generate 375 putative rhesus snoRNAs (Methods). We then analyzed the genomic locations of these snoRNAs in different species.
Genomewide prediction of sno-lncRNAs . (A) Genomewide prediction of sno-lncRNAs with annotated snoRNAs. The numbers of annotated snoRNAs, snoRNAs in introns or snoRNAs forming pairs in any single intron were compared across human (blue), rhesus (green) and mouse (yellow). Rhesus snoRNAs were transposed from human and mouse annotations. Note that only a few of snoRNAs could form pairs in any single intron, and even fewer sno-lncRNAs (highlighted by asterisk) could be detected with poly(A)-/ribo- RNA-seq signals. (B) Genomewide prediction of sno-lncRNAs with an intron-annotation-independent algorithm. For each two adjacent snoRNAs (blue bars) within 10 kb, RPKM of snoRNAs (blue regions) and internal region (pink regions) in poly(A)-/ribo- RNA-seq datasets were evaluated with a set of criteria to identify novel sno-lncRNAs (Methods). In total, 19 sno-lncRNAs were identified in examined species and cell lines (Table 1).
Only a small portion of snoRNA pairs could be found from any single RefSeq intron. Importantly, even fewer such introns are expressed in detected cell lines by interrogating poly(A)-/ribo- RNA-seq datasets. For example, in human pluripotent H9 cells, only seven sno-lncRNAs could be detected, including six reported sno-lncRNAs and a new one derived from the C17orf76-AS1 region (Table 1), although we identified 48 snoRNAs that form pairs within single introns (Figure 1A). In addition, no putative sno-lncRNAs could be detected in rhesus or mouse by analyzing snoRNA pairs in annotated introns.
19 sno-lncRNAs identified in this study were listed with their species source, cell line source, genomic locations, expression level (RPKM), snoRNA ends, parent genes, validation and other notes. It includes eight sno-lncRNAs in human ESCs, three in ENCODE human cell lines, seven in rhesus ESCs and one in mouse ESCs. Expression levels of sno-lncRNAs were evaluated using RPKM in relevant cell lines (the ENCODE GM12878 cell line was used). Due to the poor annotation, host genes and snoRNA ends in rhesus were predicted from human and/or mouse homologous sequences. *one sno-lncRNA that contains a box C/D snoRNA at one end and a box H/ACA snoRNA at the other end was highlighted with asterisk.
To further explore sno-lncRNA candidates, we developed a custom computational pipeline to predict sno-lncRNAs by integrating snoRNA annotations with poly(A)-/ribo- RNA-seq datasets from human , rhesus and mouse (GEO:GSE53942) (Figure 1B, Methods). By applying this pipeline to multiple poly(A)-/ribo- RNA-seq datasets, 19 sno-lncRNAs were identified from different species and/or different cell lines (Table 1). Two additional sno-lncRNAs were predicted in H9 cells and, importantly, both could be validated by Northern blots in human H9, HeLa-J and PA1 cells (Additional file 1). Three more sno-lncRNAs were further predicted from ENCODE cell lines (Table 1), suggesting that more sno-lncRNAs could be identified when this prediction pipeline is applied to other trancriptomes. Furthermore, it is expected that more sno-lncRNAs will be identified after improvements in snoRNA annotation. Interestingly, only one sno-lncRNA could be predicted from the entire mouse ESC transcriptomes used in this study (Table 1). This mouse sno-lncRNA could be validated by Northern blots from different murine cell lines, as indicated below, but its homolog expression was much lower in rhesus and undetectable in human.
Although the majority of predicted sno-lncRNAs in human contain either box C/D snoRNAs or box H/ACA snoRNAs on both ends, we found one sno-lncRNA from ENCODE datasets that contains a box C/D snoRNA at one end and a box H/ACA snoRNA at the other end (highlighted with asterisk in Table 1). To demonstrate that the hybrid snoRNPs at the ends are also capable of generating sno-lncRNAs, we have constructed sno-lncRNA expression vectors, which contain a box C/D snoRNA at one end and a box H/ACA snoRNA at the other end to make artificial sno-lncRNAs with hybrid snoRNA ends (top panels of Figure 2A and B, Additional file 2A and B, and data not shown). Northern blots clearly demonstrated the successful expression of such sno-lncRNAs with hybrid snoRNA ends (bottom panels of Figure 2A and B, Additional file 2A and B, and data not shown). Thus, these data strongly indicate that either box C/D or box H/ACA snoRNP complex at each end is sufficient to protect of internal sequences in sno-lncRNAs from nuclease trimming after splicing and that multiple formats of sno-lncRNAs may exist in human transcriptomes.
Either H/ACA or C/D box snoRNP complexes are sufficient for sno-lncRNA formation (A) and (B) Northern bolts with denature PAGE gels show that sno-lncRNAs can be recapitulated after replacing the snoRNA end from C/D box snoRNA to H/ACA box snoRNA (A) or vice versa (B). Top, a schematic drawing of wild-type sno-lncRNAs (sno-lncRNA2 and sno-lnc5AC) or modified sno-lncRNAs (sno-lncRNA2-5A and sno-lnc5C-14) in the expression vector. Black/grey boxes, exons; Black bars, NB probes; Blue circles, C/D snoRNAs; Yellow circles, H/ACA snoRNAs; Bottom, Northern blot validation. NT, no transfection; EV, empty vector. RNA marker III was used to indicate RNA sizes. Total RNAs were separated on 3.5% denature PAGE gels with urea.
Compared to coding genes, lncRNAs are generally expressed at low levels and are not well conserved, which have impeded their discovery and functional analyses (for review see ). We examined the sequence conservation of sno-lncRNAs by calculating PhastCons scores from multiple alignments of primate genomes. Such analysis revealed that the conservation of sno-lncRNAs is the lowest among other well-characterized lncRNAs  and predicted lincRNAs  (Figure 3A). However, the conservation of snoRNAs themselves is much higher than internal sequences of sno-lncRNAs or nearby exons (Figure 3B). For example, PWS region snoRNAs (SNORD116 cluster in human) exhibit a remarkably higher conservation across species than either the SNURF-SNRPN exons or introns (Figure 3C and Additional file 3). However, the high conservation of genomic sequences does not necessarily imply the expression of homologous RNAs at the transcriptome level, as indicated below (Figure 4 and Additional file 4 and Additional file 5). The expression of sno-lncRNAs is highly restricted to specific species and no homology could be detected from all three species among all predicted sno-lncRNAs (Table 1).
Highly conserved snoRNA ends from sno-lncRNAs . (A) Conservation analysis of sno-lncRNAs and other lncRNAs. sno-lncRNAs (11 of human sno-lncRNAs summarized in Table 1) are less conserved than other reported lncRNAs  or lincRNAs . The median phastCons score was labeled to indicate the average conservation level. (B) Conservation analysis of nearby exons, snoRNA ends and internal sequences of sno-lncRNAs. snoRNA ends exhibit much higher conservation than nearby exons and internal sequences. The median phastCons score was labeled to indicate the average conservation level. (C) Sequence conservation analysis of PWS region in different species with VISTA browser. PWS region snoRNAs (SNORD116 cluster, light blue) exhibit a remarkably higher conservation across species than SNURF-SNRPN exons and introns. Y-axis, species selected for comparing (left panel) and conservation levels (right panel); Red bars, human PWS region sno-lncRNAs; Blue circles, human PWS region snoRNAs (SNORD116 cluster); Black bars, exons of human PWS region sno-lncRNA host gene (SNURF-SNRPN). Colors of conserved regions were labeled by VISTA according to UCSC annotations (exons in blue and introns in red). Note that sno-lncRNA4 was previously identified as PWCR1 mRNA or small nucleolar RNA (snord116-20) according to UCSC annotation (blue). An analysis of all five PWS region sno-lncRNAs and their flanking sequences was highlighted in Additional file 3.
Unique expression of PWS region sno-lncRNAs across species. Normalized read densities of poly(A)-/ribo- RNA-seq (red) and poly(A)+ RNA-seq (black) from human (A), rhesus (B) and mouse (C) were shown from UCSC genome browser with customer bigwig inputs. Confident sno-lncRNA signals were detected from human and rhesus ESCs, but not from mouse ESCs. Note there is no rhesus Refseq annotation in this regions, transcripts from de novo assembly (black lines) and transposed annotations from other species (blue lines) are shown.
The genomic context of the PWS region is complex and the characterization of this region across species is still lacking comprehensive analysis. We first examined the genomic context of PWS region sno-lncRNAs by comparing their genomic sequences from different species. Given that sno-lncRNA formation depends on snoRNA sequences at both ends within a single intron, the highly conserved PWS region SNORD116 snoRNAs suggested the likelihood of the formation of PWS region sno-lncRNAs in other species. Compared to five in human (Figure 4A and Additional file 3), interrogation of poly(A)-/ribo- RNA-seq datasets revealed only two PWS region sno-lncRNAs from alternative spliced introns in rhesus ESC cells (Figure 4B and Additional file 4), but none in mouse cells (Figure 4C and Additional file 5). In addition, no clear evidence for PWS region sno-lncRNAs could be found in mouse brain/hippocampus in which the SNURF-SNRPN transcript and its downstream noncoding region are highly transcribed (Additional file 5), further indicating the absence of PWS region sno-lncRNAs in mouse.
SNORD116 snoRNAs are highly conserved from human and rhesus to mouse (Figure 3C and Additional file 3); however, obvious differences in their genomic locations were observed in the PWS region. In human/rhesus genomes, SNORD116s are located in introns of the parent SNURF-SNRPN transcript and some of them form snoRNA pairs in one alternative spliced intron, which results in the formation of sno-lncRNAs (Figures 4A and B). In the mouse genome, SNORD116s are located in introns of a series of spliced ESTs, which are located at least 50 kb away from the SNURF-SNRPN locus (Figure 4C and Additional file 5). Although there are expressed signals of spliced ESTs in the mouse hippocampus transcriptome (Additional file 5), no SNORD116 snoRNA pairs were found between these spliced ESTs, thus no sno-lncRNAs could be generated from this region in mouse. Taken together, although snoRNA ends are essential for the formation of sno-lncRNAs, the existence of highly-conserved snoRNAs alone is not sufficient for their formation.
The genomic region encoding 15q11-13 sno-lncRNAs is specifically deleted in human PWS. PWS is a multiple system disorder with a minimal paternal deletion in chr15 . The deficiency of SNORD116 snoRNAs within the minimal deletion has been thought to play an important role in the pathogenesis of PWS [20–22]. However, mouse models with SNORD116 deletions can only partially mimic PWS phenotypes, including metabolism and growth deficiency, but not obesity [28, 29]. Although the mechanism of PWS pathogenesis still remains mysterious, the recent finding of sno-lncRNAs in the PWS region in human and their regulatory function in splicing has offered an additional functional layer of gene regulation underlying PWS pathogenesis . The finding of no expression of PWS region sno-lncRNAs in mouse indicates a possible limitation of the use of mouse models to study human PWS.
We next inspected PWS region sno-lncRNAs in rhesus in greater detail. Since the genomic context of the PWS region is complex and the transcriptome annotation in rhesus is limited, we used SNURF-SNRPN exons to locate SNORD116 snoRNAs and PWS region sno-lncRNAs in rhesus. The rhesus SNURF-SNRPN exons were determined by transposing the human/mouse homologous exons (Figure 5A), and putative SNURF-SNRPN transcripts could be identified in rhesus by de novo assembly from a poly(A)+ RNA-seq dataset (GSE53942). Pair-wise sequence alignments between human (black bars in Figure 5A) and rhesus (grey bars in Figure 5A) suggested that SNURF-SNRPN exons exhibit high sequence similarity (Additional file 6). Interestingly, one human SNURF-SNRPN exon (the seventh) is repeated at least eight times in the rhesus PWS region; however it is unclear whether this repetitive region occurs only in rhesus or has been lost in humans during evolution.
Distinct landscapes of PWS regions across species. (A) Comparison of PWS region sno-lncRNAs and its parent SNURF-SNRPN exons in different species. Conserved SNURF-SNRPN exons were manually linked between human (black boxes of top panel) and rhesus (grey boxes of middle panel), and SNORD116 cluster snoRNAs (dark and light blues bars for human and rhesus, respectively) were located in introns. Note that several non-SNURF-SNRPN exons were annotated in mouse (empty boxes). The homogenous SNURF-SNRPN exons in rhesus are based on sequence homology and/or expression signals (Additional file 6). (B) Enrichment of Fox binding sites in PWS region sno-lncRNAs. Potential Fox protein binding sites were predicted in five human and two rhesus sno-lncRNAs.
Sequence alignment of SNORD116 snoRNAs and their parent SNURF-SNRPN exons revealed that two PWS region sno-lncRNAs in rhesus are similar to human PWS region sno-lncRNA3 and sno-lncRNA4, respectively. Although predicted rhesus SNORD116 snoRNAs are scattered among individual introns (Figure 5A), de novo assembly with rhesus poly(A)+ RNA-seq revealed a variety of alternatively spliced SNURF-SNRPN transcripts in rhesus, thus leading to the formation of sno-lncRNAs in rhesus SNURF-SNRPN region (Figure 4B, transcripts from de novo assembly shown in thick black lines).
Human PWS region sno-lncRNAs could function as molecular sponges by associating with Fox family splicing regulators and altering patterns of splicing . Due to the high similarity of rhesus PWS region sno-lncRNAs with human in the genomic context, we reasoned that they might function similarly as well. We thus scanned the rhesus sno-lncRNA sequence for Fox binding motifs, and identified an enrichment of Fox binding sites (Figure 5B), further indicating that rhesus PWS region sno-lncRNAs might also interact with Fox family splicing regulators and play a similar role in splicing regulation. On the other hand, the absence of PWS region sno-lncRNAs in mouse indicated that a similar regulation mechanism is absent in mouse.
In sum, PWS region sno-lncRNAs are highly expressed in human and rhesus, but are absent in mouse. The absence of PWS region sno-lncRNAs in mouse also suggests one possible reason to explain the failure of current mouse deletion models to fully recapitulate pathological features of human PWS [27–29]. However, we cannot exclude other regulatory pathways or mechanisms during PWS pathogenesis.
Although none homologue of human sno-lncRNAs identified in this study could be detected in mouse transcriptomes, there is one highly-expressed sno-lncRNA predicted in mouse ESCs. This sno-lncRNA is flanked by SNORD33 and SNORD34 at its ends and is located in ribosomal protein L13a (RPL13A) gene (Figure 6A). Northern blots with different probes demonstrated the existence of this mouse sno-lncRNA of the expected size in several mouse cell lines with both native agarose gels (Figure 6B) and denatured PAGE gels (Additional file 7). Furthermore, this RPL13A region sno-lncRNA is highly expressed in mouse ESC cells, but less in other mouse lines (Figure 6B). Moreover, it can be recapitulated in expression vectors, as indicated in Figure 6C. Strikingly, even though both the sequences and structures of snoRNA ends and RPL13A exons are highly conserved from human to mouse (Additional file 8), the sno-lncRNA was not expressed in examined human cell lines, and expressed at very low levels in rhesus ESCs (Table 1).
Expression of a non-human sno-lncRNA in RPL13A region in mouse. (A) A highly expressed sno-lncRNA was indicated in mouse ESC transcriptomes. Top, normalized read densities of poly(A)-/ribo- (red) and poly(A)+ RNA-seq (black) in mouse ESCs. Note two ends of this sno-lncRNA (indicated below) map precisely to the intron-imbedded SNORD33 and SNORD34. (B) Northern blot validation of this sno-lncRNA in mouse cell lines. This sno-lncRNA was highly expressed in mouse R1 cells, but less expressed in other mouse cell lines (NIH 3 T3, VDβ and MEF) with probes for parent RPL13A exon (black bar, left panel) or SNORD33 (blue bar, right panel) by Northern blots. Top, a schematic drawing of RPL13A gene (black bars) and intron-embedded snoRNAs (SNORD35, SNORD34 and SNORD33, from left to right, blue bars). Note that the NB probe recognizing SNORD33 can also visualize other mouse snoRNAs due to the sequence similarity of snoRNAs. (C) Recapitulation of RPL13A region sno-lncRNA in NIH 3 T3 cells. Top, a schematic drawing of mouse sno-lncRNA flanked by its full length intron and exons in expression vector. Bottom, Northern blots of recapitulated mouse sno-lncRNA with probes recognizing different regions. NT, no transfection; EV, empty vector. Note that endogenous RPL13A region sno-lncRNA is lowly expressed in NIH 3T3 cells.
SnoRNAs within RPL13A introns are critical mediators of lipotoxic cell death in both hamster and mouse . Lipotoxic stress strongly induces expression of these snoRNAs, but has no effect on the steady state levels of the parent RPL13A gene . While it is unclear whether RPL13A region sno-lncRNA is also involved in lipotoxicity like its snoRNA ends, our finding offers another possible regulation for gene expression in this region and it will be of interest to study the function of this RPL13A region sno-lncRNA.
The analyses of PWS region sno-lncRNAs and the mouse RPL13A region sno-lncRNA strongly indicated that sno-lncRNAs are expressed in a species-specific manner. To determine whether there are differences in the biogenesis process of sno-lncRNAs in different species, we individually transfected expression vectors for mouse sno-lncRNA into human cells or expression vectors for human sno-lncRNA into mouse cells. Interestingly, both species-specific sno-lncRNAs could be recapitulated in cultured cells from other species (Additional file 9), suggesting that species-specificity of sno-lncRNAs is mainly derived from their genomic context instead of from the underlying biogenesis machinery.
As mentioned above, snoRNAs generally are located within introns, but most of them do not exist as pairs in single introns (Figure 1A). With known intron annotations, only a few sno-lncRNAs could be identified (Figure 1A). However, using an intron-annotation-independent sno-lncRNA prediction strategy (Figure 1B), several additional novel sno-lncRNAs were identified in examined transcriptomes (Table 1), suggesting that previously uncharacterized alternative splicing events can generate snoRNAs pairs within one intron. For example, the PWS region sno-lncRNAs in rhesus could be generated from alternative spliced SNURF-SNRPN (Figure 4B). Taking the RPL13A region sno-lncRNA into consideration, the gene organization of RPL13A is highly conserved across species and SNORD33 and SNORD34 are usually confined to distinct single introns. Given the fact that only two snoRNA genes located within one intron can lead to the formation of a sno-lncRNA, this suggests that the existence of a previously uncharacterized alternative splicing event in the adjacent introns of SNORD33 and SNORD34. To test this possibility, we did de novo transcript assembly with a poly(A)+ RNA-seq dataset, and successfully identified the alternative splicing event that results in the location of SNORD33 and SNORD34 into one intron (Figure 7A). Interestingly, a similar alternative splicing event could be assembled in rhesus (Additional file 10), but not in human (Figure 7B), which is consistent with the lack of an expression signal for a RPL13A region sno-lncRNA in human. In addition, RT-PCR results further confirmed the alternative splicing in mouse, but none in human (Figure 7C). Thus, the alternative splicing of RPL13A gene in mouse leads to the formation of a species-specific sno-lncRNA. On the other hand, the lack of RPL13A alternative splicing in human likely prevents the expression of this sno-lncRNA. It should be noted that there is low expression of RPL13A region sno-lncRNA in rhesus, together with a low level of the necessary alternative splicing (Additional file 10).
Species-specific RPL13A region sno-lncRNA is derived from species-specific alternatively spliced rpl13a transcripts. (A) De novo transcript assembly revealed previously uncharacterized alternative spliced rpl13a transcripts (mouseR1_pAplus_cufflinks). At least two new rpl13a isoforms (back arrows on right) were identified to splice out an intron containing SNORD33 and SNORD34. Y-axis, normalized read densities of poly(A)-/ribo- RNA-seq (red) and poly(A)+ RNA-seq (black) of mouse ESC and hippocampus transcriptomes. (B) No such alternative spliced rpl13a transcripts in human ESC H9 and HeLa cells from both de novo assembly (h9_pAplus_cufflinks) and known annotation (blue lines). Y-axis, normalized read densities of poly(A)-/ribo- RNA-seq (red) and poly(A)+ RNA-seq (black) of human H9 and HeLa transcriptomes. (C) Validation of alternative spliced rpl13a transcripts by RT-PCR. Left, the previously uncharacterized alternative splicing event of RPL13A gene could only be detected in mouse, but not in human, with RT-PCR. Right, a schematic drawing of different splicing events and their validation primers in RPL13A. Black bars, RPL13A exons; Blue circles, snoRNAs; Red arrows, PCR primer sets. (D) The alternative splicing of RPL13A causes amino acid changes at the C-terminal of RPL13A protein. Top, schematic diagram of canonical splicing of RPL13A and its amino acid sequence; Bottom, schematic diagram of uncharacterized splicing of RPL13A and its amino acid sequence.
Very interestingly, further analyses revealed that the specific RPL13A alternative splicing event that leads to the production of sno-lncRNA could also generate a protein of altered amino acid sequence in both mouse (Figure 7D) and rhesus (data not shown), although the change of protein sequence and its consequence need to be further experimentally confirmed. As a 60S ribosomal subunit protein, RPL13A is highly conserved across species and plays an essential role in protein synthesis. Therefore, the finding of alternative splicing of RPL13A has implicated a possible role in the regulation of 60S ribosome assembly or function in a species-specific manner. Since a large diversification of splicing exists between tissues and species [31, 32] and sno-lncRNAs are expressed with tissue- and species-specific patterns, it quite likely that more such RNAs will be uncovered when additional tissues and species samples are examined. Taken together, alternative splicing not only increases the diversity of coding mRNAs/proteins, but also expands transcriptome complexity by promoting the formation of noncoding RNAs from untranslated intron sequences.
We explored non-polyadenylated transcriptomes (poly(A)-/ribo-) from human, rhesus and mouse, and systematically annotated sno-lncRNAs across species. Although primary sequence analysis revealed that snoRNA ends of such molecules are highly conserved, PWS region sno-lncRNAs are highly expressed in human and rhesus, but absent in mouse. The absence of PWS region sno-lncRNAs in mouse suggested a possible reason for the failure of the current mouse model to fully recapitulate pathological features of human PWS. Only one mouse sno-lncRNA was identified from the limited available mouse datasets in RPL13A region, and snoRNAs themselves in this region have been suggested to be involved in lipotoxicity in mouse. Our results also demonstrated that the formation of sno-lncRNAs often requires alternative splicing within their parent genes, indicating a complex regulatory network of coding and noncoding parts of the genome.
Annotated human snoRNAs derived from snoRNABase  (https://www-snorna.biotoul.fr/) were downloaded from UCSC Genome Bioinformatics database (http://hgdownload.soe.ucsc.edu/goldenPath/hg19/database/wgRna.txt.gz, updated on 2010/10/3). 132 mouse snoRNA annotations were downloaded from RefSeq database (http://www.ncbi.nlm.nih.gov/refseq/, downloaded on 2013/3/4). 375 putative rhesus snoRNAs were transposed from human and mouse snoRNA annotations using liftOver (http://genome.ucsc.edu/cgi-bin/hgLiftOver) with minMatch = 0.95 and combined together to be used as rhesus snoRNA annotations. All these snoRNA annotations were overlapped respectively with relevant gene annotations according to their species-derivation (Human: UCSC Genes, updated on 2012/2/5; Rhesus: RefSeq Genes, updated on 2013/3/24; Mouse: UCSC Genes, updated on 2011/5/30) to find snoRNA pairs (at least two snoRNAs in one intron) in introns, as indicated in Figure 1A. SnoRNA pairs in the same introns were further examined from poly(A)-/ribo- RNA-seq datasets to identify putative sno-lncRNAs.
The poly(A)+ or poly(A)-/ribo- RNA-seq reads were uniquely aligned to relevant genomes (Human: hg19, GRCh37; Rhesus: rheMac3, BGI CR_1.0; Mouse: mm9, NCBI37) using TopHat 2.0.8  (parameters: -g 1 -a 6 -i 50 --microexon-search --coverage-search -m 2) with existing annotations (Human: UCSC Genes, updated on 2012/2/5; Rhesus: RefSeq Genes, updated on 2013/3/24; Mouse: UCSC Genes, updated on 2011/5/30), respectively. To facilitate the identification of potential sno-lncRNAs, Bowtie 0.12.9  (parameters: -v 3 -k 1 -m 1) was also employed to map poly(A)-/ribo- RNA-seq reads to annotated genome references. Expression level (RPKM) of annotated genes (including snoRNAs) was obtained with customized pipeline (Zhu et al., in preparation). Cufflinks v2.0.2  (parameters: -F 0) was employed to assemble poly(A)+ RNA-seq mapping results to obtain de novo RNA transcripts. All mapping results were normalized and uploaded to the UCSC Genome Browser (http://genome.ucsc.edu/) for visualization.
To systematically identify sno-lncRNAs independently from known gene annotation, we developed a custom sno-lncRNA identification pipeline (termed as SNOLNCfinder), as indicated in Figure 1B. Briefly, for each two adjacent snoRNAs (distance < 10 kb), RPKMs of snoRNA regions and their internal regions were calculated with a customized pipeline (Zhu et al., in preparation) from Bowtie mapped poly(A)-/ribo- RNA-seq reads. A putative sno-lncRNA was selected with 1) both snoRNA pairs are expressed with RPKM ≥ 1; 2) at least 80% of the internal region between snoRNA pairs have poly(A)-/ribo- RNA-seq signals by sliding window examination (Figure 1B); and 3) relatively high expression of the internal region (at least 40% of expression of snoRNA pairs). All candidates were manually inspected by comparing the poly(A)+ and poly(A)-/ribo- RNA-seq datasets. This pipeline is independent on known gene annotation and can be successfully employed in human, rhesus and mouse datasets to identify new sno-lncRNAs. RNA-seq datasets used here were from human ESC H9 cells and HeLa cells(GEO:GSE24399), ENCODE cell lines (GEO: GSE26284). RNA-seq files for rhesus ESCs, mouse ESCs and mouse hippocampus can be accessed from the NCBI Sequence Read Archive by Gene Expression Ominbus accession number (GEO:GSE53942).
VISTA Browser  (http://genome.lbl.gov/vista/) was employed to inspect the conservation landscape for a given region from different genomes, including human (Feb. 2009), Cow (Oct. 2011), Mouse (Dec. 2011 or Jul. 2007), Callithrix jacchus v.2.0.2 (Jun. 2007), Rhesus (Jan. 2006), Pongo pygmaeus abelii v.2.0.2 (Jul. 2007), Gorilla (Dec. 2009), Chimp (Mar. 2006), Rat (Nov. 2004), Dog (May 2005) and Horse (Jan. 2007).
Putative rhesus snoRNA116s (Figure 4B) were marked with human and mouse annotations (Figures 4A and C) in UCSC. Locations of putative rhesus SNURF-SNRPN exons were defined according to rhesus poly(A)+ RNA-seq mapping signals. Sequences of human (Figure 4A) and rhesus (Figure 4B) SNURF-SNRPN exons were extracted from UCSC Genome Bioinformatics database (http://genome.ucsc.edu/). Pair-wise sequence alignments were carried out using T-Coffee .
Sequences of human PWS sno-lncRNAs and rhesus putative PWS sno-lncRNAs were extracted from UCSC Genome Bioinformatics database (http://genome.ucsc.edu/). All these sequences were scanned for Fox hexanucleotide motifs including UGCAUG, GCAUGU, GUGAUG, UGGUGA and GGUGGU .
PhastCons scores for multiple alignments of primate genomes (http://hgdownload.cse.ucsc.edu/goldenpath/hg19/database/phastCons46wayPrimates.txt.gz, updated on 2009/12/6) were downloaded from UCSC and corresponding PhastCons scores for lncRNAs , lincRNAs  and sno-lncRNAs (11 predicted in human, Table 1) were counted separately to inspect the conservation difference of these three datasets. PhastCons scores for nearby exons, snoRNAs at both ends of sno-lncRNAs and internal regions of sno-lncRNAs were also calculated separately to investigate the region-specific conservation difference of sno-lncRNAs.
All cell lines were cultured using standard protocols. Plasmid transfection was carried out with X-tremeGENE 9 (Roche) or with nucleofection (Lonza) according to the manufacturer's instructions. Rhesus rhesus RNAs were extracted from ESC line IVF3.2 . Mouse RNAs were extracted from ESC R1 line or sacrificed mouse hippocampus, respectively. Mice were maintained and used in accordance with the guidelines of the Institutional Animal Care and Use Committee of Shanghai Institutes for Biological Sciences.
SNORD116-14 in pcDNA3-sno-lncRNA2  was replaced with SNORA5A to generate construct pcDNA3-sno-lncRNA2-5A (Figure 2A), and SNORA5A in pcDNA3-sno-lnc5AC was substituted with SNORD116-14 to generate constructs pcDNA3-sno-lnc5C-14 (Figure 2B) with primers listed in Table S1. Mouse sno-lnc33/34 and human sno-lnc5AC flanked by its full length intron, splice sites and exons were cloned into pcDNA3 (Figure 6C).
Cultured cell lines or cells with different treatments were harvested in Trizol (Invitrogen) and RNAs were extracted according to the manufacturer's instruction, followed by DNase I treatment at 37°C for 30 mins (Ambion, DNA-free™ Kit). Poly(A)+ and poly(A)-/ribo- RNA transcripts were fractionated and sequenced as previously described . Raw sequencing dataset and bigWig track file of rhesus and mouse poly(A)-/ribo- RNAs are available for download from NCBI Gene Expression Omnibus under accession number GSE53942 for mouse ESCs, mouse hippocampus and rhesus ESCs. Northern Blot was carried out according to the manufacturer's protocol (DIG Northern Starter Kit, Roche). Denatured RNAs were loaded on either native agarose gel or denatured PAGE gel with urea for Northern Blots as previous studies [15, 16]. Digoxigenin (Dig) labeled antisense and sense probes were made using either SP6 or T7 RNA polymerase by in vitro transcription with the AmpliScribe™ SP6 and T7 High Yield Transcription Kits (Epicentre). DIG-labeledRNA Molecular Wight Marker III is from Roche.
Xiao-Ou Zhang, Qing-Fei Yin contributed equally to this work.
We are grateful to Gordon Carmichael for critical reading of the manuscript and all lab members for helpful discussion and technical support. H9 cells were obtained from the WiCell Research Institute. RNA-seq was performed at CAS-MPG Partner Institute for Computational Biology Omics Core, Shanghai, China. This work was supported by grants 2014CB964800 and 2014CB910600 from MOST, XDA01010206 and 2012OHTP08 from CAS, 31322018, 31271376 and 31271390 from NSFC.
LY and LLC designed the project. XOZ and LY performed bioinformatics analyses. QFY, HBW, YZ, TC, PZ and XL performed experiments. LY, LLC and XOZ analyzed the data. LY and LLC wrote the paper with inputs from other authors. All authors read and approved the final manuscript.


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Road accidents killed 600 a day in India in 2017: Lancet
Study's count exceeds government stats by 71,000.
Dipak K Dash
According to the study, the number of deaths due to road injuries increased by 58.7% during this period as compared to only 8.1% globally.
NEW DELHI: In 2017, nearly 600 people died daily due to road traffic injuries in India, a study published in The Lancet Public Heath journal has estimated based on several "verbal autopsy reports". The estimated loss of nearly 2.19 lakh lives in 2017 was about 71,000 more than what the road transport ministry collated from all the states.
Verbal autopsy report is a method of gathering information about symptoms and circumstances of a deceased persons to determine his or her cause of death. The report, titled "Mortality due to road injuries in the states of India: the Global Burden of Disease", covered the period between 1990 and 2017 and was released on Monday.
According to the study, the number of deaths due to road injuries increased by 58.7% during this period as compared to only 8.1% globally. It has estimated that the number of pedestrians was 76,729 while the number of motorcyclists killed could be 57,802 and cyclists accounted for 15,324 deaths.
These estimates are far more than the reports that government published. For example, the road accidents report of 2017 says that only 20,457 pedestrians and 3,599 cyclists died in road accidents. Similarly, the government report based on police FIRs claim 48,746 two-wheeler occupants died in road crashes.
The study further claimed that India had a higher age-standardised death rate for road injury among motorcyclists — 4·9 deaths per one lakh population and cyclists 1·2 deaths per lakh.
The report said that motorcyclist and cyclist road injury death rates in India were 69% and 33% higher compared to the global average. "Road injury was the leading cause of death in males aged 15 to 39 years and the second leading cause in this age group for both sexes combined," it said.
The study found that the overall age-standardised death rate for road injuries varied by up to 2·6 times between states in 2017.
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text:
Title: Parthenolide
CAS Name: (1aR,4E,7aS,10aS,10bS)-2,3,6,7,7a,8,10a,10b-Octahydro-1a,5-dimethyl-8-methyleneoxireno[9,10]cyclodeca[1,2-b]furan-9(1aH)-one
Additional Names: 4,5a-epoxy-6b-hydroxy-germacra-1(10),11(13)-dien-12-oic acid g-lactone
Molecular Formula: C15H20O3
Percent Composition: C 72.55%, H 8.12%, O 19.33%
Literature References: Sesquiterpene lactone found in feverfew, q.v., and in other plants. Isolation from Chrysanthemum parthenium (L.) Bernh. Compositae and characterization: V. Herout et al., Chem. Ind. (London) 1959, 1069; M. Soucek et al., Collect. Czech. Chem. Commun. 26, 803 (1961); from Magnolia grandiflora L., Magnoliaceae: F. S. El-Feraly, Y.-M. Chan, J. Pharm. Sci. 67, 347 (1978). Revised structure and spectral analysis: T. R. Govindachari et al., Tetrahedron 21, 1509 (1965). Absolute configuration: A. S. Bawdekar et al., Tetrahedron Lett. 1966, 1225. Crystal structure: A. Quick, D. Rogers, J. Chem. Soc. Perkin Trans. 2 4, 465 (1976). HPLC determn: D. Strack et al., Z. Naturforsch. 35, 915 (1980). Cytotoxicity: K.-H. Lee et al., Cancer Res. 31, 1649 (1971); L. A. J. O'Neill et al., Br. J. Clin. Pharmacol. 23, 81 (1987).
Properties: Colorless plates, mp 115-116°. [a]D20 -81.4° (c = 1.04 in chloroform); [a]D22 -71.4° (c = 0.220 in CH2Cl2). uv max: 214 nm (log e 4.22).
Melting point: mp 115-116°
Optical Rotation: [a]D20 -81.4° (c = 1.04 in chloroform); [a]D22 -71.4° (c = 0.220 in CH2Cl2)
Absorption maximum: uv max: 214 nm (log e 4.22)
Presenilins Miokamycin Glutaric Acid Chlorphenoxamine
Procymate Cyclohexylamine Mercuric Iodide, Red Calcium Hexafluorosilicate
Bucillamine Dihydroxymaleic Acid Aminoglutethimide Monellins
Efonidipine Octotiamine Isophthalic Acid Quintozene


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Tarja Turunen (født 17. august 1977) er en finsk sangerinde, der var med til at starte gruppen Nightwish.

I starten spillede hun klaver, og senere begyndte hun at spille på fløjte. Hun har også spillet en del på trommer. Senere startede hun på en musikskole i Savonlinna, hvor hun også begyndte at studere klassisk sang, og bestemte sig for at blive operasangerinde. Tidligere sang hun rytmisk, og det var specielt sange af Whitney Houston, hun var glad for.

For tiden (2007) bor hun i både Helsinki og Argentina sammen med sin mand Marcelo Cabuli, som også er hendes manager og i øvrigt også var manager for hendes band fra 2003 og til hendes fyring.

Diskografi

Gæsteoptræden og sideprojekter
 Savonlinnan Taidelukion, Romeo ja Julia (1995)
 Uotinen & Waltari, Evankeliumi (1999)
 Beto Vazquez Infinity, Battle of Valmourt (2001)
 Beto Vazquez, Infinity (2001)
 Beto Vazquez Infinity (2001)
 Anssi Tikanmäen Yhtye, Perinteinen POP -Levy (2001)
 Beto Vazquez Infinity, Wizard (2002)
 Martin Kesici with Tarja, Leaving You For Me (2004)
 Noche Escandinava II (2005)
 Noche Escandinava II (2005)
 Schiller: Tag und Nacht (2005)
 Scorpions: The Good Die Young fra albummet Sting in the Tail (2010)

Solo
 Yhden Enkelin Unelma (2004)
 Yhden Enkelin Unelma (2004)
 One Angel´s Dream (2004)
 Henkäys ikuisuudesta (2006)
 My Winterstorm (2007)
 What Lies Beneath (2010)

Eksterne henvisninger

Sangere fra Finland
Nightwish


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Home » Blog » Central Florida Attorney Back in Prison for Defrauding Elderly Clients
Central Florida Attorney Back in Prison for Defrauding Elderly Clients
Disbarred-attorney Linda Vasquez and her former husband, Ross Littlefield, have been sentenced to federal prison for money laundering after admitting in a guilty plea to "defrauding 'vulnerable clients' to fund their other businesses, buy real estate, make car payments and finance an extravagant lifestyle," as reported by the Orlando Sentinel. Linda Vasquez (formerly known as Linda Littlefield) was only recently released from two years of incarceration in state prison for the former couple's victimization of only one of their many victims. In that case, Linda used the credit card of one of her clients suffering from Alzheimer to fund numerous personal expenses including furniture for her law office and a vacation to Cancun, Mexico. The lax prosecution by the State Attorney's Office for the Ninth Judicial Circuit of Florida (the same office that tried Casey Anthony) resulted in both pleading no contest to fraud, probation for Ross, and a couple years of incarceration for Linda.
"Although the families implored U.S. District Judge Anne C. Conway to impose the maximum sentence of 10 years, she sentenced" Ross to four years of prison and Linda to five years, according to the same Orlando Sentinel article. Linda and Ross were also ordered to pay almost $3 million to the 27 known victims, but it appears unlikely that the victims will actually recovery any significant amount of restitution from the criminal couple.
fraud, mail fraud, money laundering, Littlefield, Linda Vasquez, Linda Littlefield, Ross Littlefield


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Train your Nervous System
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Posts Tagged 'Awareness'
End of an Affair
By Kaushik Ram | January 8, 2016 | 0
There was no tragedy, only the unavoidable. Why then, during all this time do I beseech? The question conflicts with the mind. The answer appears without it. You only know yourself when you go beyond your limits. In a fraction of a second, you can become noone. And this being something new, can lead to an adventure…
The dilemma of the living
By Kaushik Ram | October 29, 2015 | 0
To be born is a miracle. Then what? The truth is beautiful but terrible. It does not do to dwell on dreams and forget to live. The trouble is, humans do have a knack of choosing precisely those things that are worst for them. – Dumbledore. In life we suffer. We suffer because we distract ourselves…
Instinct – Find It In You
Please note – words in bold are explained in the glossary section below. Since the moment the Animal is born in the Wilderness, it is subjected to the laws of nature. In order to survive, the Animal discovers that it has been granted a musculo-skeletal structure. By instinct, the Animal starts moving towards food. The Animal uses its senses…
The Awakening – Tarzan to Neo
By Kaushik Ram | March 10, 2015 | 0
In 1971, Mr. Ian Waterman, age 19 at the time, had a spontaneous autoimmune reaction. 3 days later IW woke up in hospital and came to the shocking realization that he had "lost his body". IW was diagnosed with Deafferentation – a complete loss of proprioceptive feedback (a background process constantly updating the position of our body in space). Over…
By Kaushik Ram | January 30, 2015 | 0
What have we gained from our modern existence? What have primitive cultures been in relentless defiance to preserve? Is it fire making, shelter building, hunting and foraging skills? Why look for food when you can buy them? Why make clothes or furniture when these can easily be purchased online? Why gather around a fire when the internet is accessible through…
Adaptation – Movement Infrastructure Reboot
The Enigma of the human brain began to unravel in the Inagural talk by Santiago Ramón y Cajal at the International Medical Congress held in Rome in 1894. Cajal was the first to suggest that the flow of information in neurons passes from the axons of the presynaptic cell to the dendrites of the postsynaptic cell – "the law of…
The Human Body – An Instrument for the State of Flow
By Kaushik Ram | November 12, 2014 | 0
We work tirelessly to manage our busy lives while taking care of our body acquires a secondary priority. When our body's take the backseat in our lives, it begins to accumulate physical ailments such as chronic back pain, weak joints and mental aliments such as depression, anxiety and ADHD. By bringing our awareness back into the…
Evolution of Locomotion
By Kaushik Ram | September 10, 2014 | 0
This post has been Co-authored with Leticia from the Montessori Community. Our landscape shapes our movement. When a kid grows up in the forest, their movement patterns are adapted to the subtleties of moving on uneven surfaces and their senses magnified to create a multi sensory map to predicting the world around them. Our modern landscape…
Lucy – Flirting with Reality?
By Kaushik Ram | August 11, 2014 | 0
The recent movie – Lucy invites a Paradigm shift. The movie dwells on some neuroscientifcally bewildering possibilities. The movie relies on the fact that humans use 10% of the capacity of their brains. The movie then follows the character "Lucy" who progressively unlocks 100% of her brain capacity. Here I explore some of the mind-blowing concepts from the movie –…
The Secret Language of Movement
By Kaushik Ram | August 1, 2014 | 0
What is movement? Where does it come from? Human movement patterns include but are not exclusive to – running, jumping, swimming, crawling, rolling, pulling, lifting, twisting, inverting and climbing. In this blog post I will reverse engineer movement and trace it back to its neural origins. I will explore concepts of movement efficiency, body intelligence,…
5 things I learned traveling Africa Overland
How to circuit-break the nervous system to release pain
How we make long and short term decisions
The merry-go-round of mental health
Train your nervous system to Sync Brain and Body
CRITICAL EXERCISES FOR BRAIN AND NERVOUS SYSTEM HEALTH
In this course, you will learn about the Neuroscience of...
© 2019 Dr. Kaushik Ram • Website by Soul Necta


i want him to show us it acuatlly works like show us a picture of your acc or the money u putto your acc?
CAN SOMEONE PLEASE HELP ME, i spent all my GTA V money, I am on Xbox one, username is GreatWhiteJohnC. Just $50,000,000 would be amazing.


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Lawmaker says he can't get info on waste plan
By Maddy Hayden / Journal Staff Writer
Published: Thursday, July 12th, 2018 at 5:47pm
Updated: Thursday, July 12th, 2018 at 11:13pm
State Sen. Jeff Steinborn
A legislator says he isn't getting any answers out of the administration of Gov. Susana Martinez to questions about a proposed interim storage site for spent nuclear fuel in southeastern New Mexico.
Sen. Jeff Steinborn, D-Las Cruces, chairman of the Legislature's Committee on Radioactive and Hazardous Materials, sent nearly 60 questions to the heads of several state departments in April.
Only one responded.
"It raises the obvious conclusion that this governor and her administration have done no analysis on this project," Steinborn said. "The citizens of the state deserve to have answers on our state's ability to handle this facility."
The senator wrote in a July 9 letter to the governor that the New Mexico Environment Department did respond to his questions "but without providing substantive information on the issues raised."
The Environment Department provided that letter to the Journal.
In it, department Secretary Butch Tongate said NMED would review the Environmental Impact Statement in progress at the Nuclear Regulatory Commission "and provide comments to the NRC as necessary."
"The Senator's questions should be directed to the NRC – the agency overseeing the process," NMED spokeswoman Katy Diffendorfer said in an email.
Diffendorfer also said it is still unclear what role the NMED would play in the permitting and oversight of the proposed facility.
Questions were also directed to the Department of Transportation, Energy, Minerals and Natural Resources Department, Homeland Security and Emergency Management Department and Department of Military Affairs, which did not respond to Steinborn's inquiries at all, he said.
Steinborn asked for details about transporting the waste through the state, safety protocol should a leak or other event occur and how the state's oil and gas industry could be affected by the project, and other issues.
Martinez has expressed support for the project.
The facility, proposed by Holtec International, would house spent nuclear fuel from nuclear power plants around the country.
The NRC is considering the facility's license, a process that could take years.
ABQnews Seeker
Southern NM and the Border


[06:18 06/12/18] - Flight BY4438 is ready to depart EGKK with a final destination of LEAM.
[08:36 06/12/18] - Landed at -88fpm. With 4149kgs of fuel onboard and a pitch angle of 5deg.
[08:39 06/12/18] - Arrived safely at LEAM. We hope you enjoyed your flight!


This live webcast will provide lawyers and statisticians with a comprehensive overview of OFCCP and EEOC enforcement procedures. Attending this course will give you the tools you need to understand how to implement these practices at your firm. Advanced registration is recommended as space is limited.
Dr. Carrie Amidon specializes in economic and statistical analyses for labor and employment matters. She routinely provides statistical analyses with regard to allegations of race, gender, ethnicity, religion, and age discrimination in hiring, promotion, termination, and compensation.
Dr. Amidon has provided testimony in state and federal court as well as an Office of Federal Contract Compliance Programs (OFCCP) investigation regarding compensation analysis. In other investigations, she has analyzed issues of hiring, compensation, promotion, and termination. She was the managing editor of the Illinois Statistical Abstract during graduate school and published articles in the Illinois Business Review.
Kimberly R. Stuart practices appellate law, commercial litigation, and employment and labor law.
Kimberly began her legal career as a briefing attorney to Judge Margaret Garner Mirabal on the Court of Appeals for the First District of Texas. Kimberly's representative employment law experience includes successfully defending employers in FLSA wage actions and Title VII claims before administrative tribunals and at trial. She has also effectively represented employees and employers in matters related to covenants not to compete and fiduciary duties. Kimberly's clients include Fortune 500 companies to sole proprietorships.
An important part of Kimberly's practice is helping her clients avoid litigation altogether through reviewing contracts, examining trade secret and confidential information protection, conducting self-audits to ensure regulatory compliance, and assisting clients with best practices training and compliance.
Debra focuses her counseling and litigation practice on compliance with federal and state employment laws and regulations, noncompetition disputes, business torts, corporate reorganizations, affirmative action issues, and defense of discrimination claims. She provides legal and business solutions to a myriad of human resource issues. She also regularly drafts complex corporate policies and contracts for her clients and advises them on best practices. She works closely with corporate counsel on the employment aspects of due diligence for complex transactions. She also negotiates and drafts employment and separation agreements for executives and companies in connection with such transactions. She regularly defends clients before federal and state fair employment accommodations and, for places of public accommodation, requests for modifications to services and programs. She defends clients on a variety of disability accommodation issues before civil rights agencies and in courts.
Berkeley Research Group is a leading global strategic advisory and expert consulting firm that provides independent advice, data analytics, valuation, authoritative studies, expert testimony, investigations, transaction advisory, restructuring services, and regulatory and dispute consulting to Fortune 500 corporations, financial institutions, government agencies, major law firms, and regulatory bodies around the world.
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Founded in 1912 as Kennerly & Warnken, Crain Caton & James has grown into a stable law firm of over 40 lawyers and their highly-qualified support staff without a merger.
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Have you and your family fallen in love with a vacation spot and you're wondering whether it makes sense to buy there? Here are some key questions to ask yourself (And keep in mind that a great real estate agent can always help you talk through them!).
It's a good idea to visit the area during the low season. Do you still enjoy it when the ski slopes are green, or when those ocean breezes are too chilly for lounging on the sand?
Calculate how many times a year you'll be able to use the home. Carefully consider the commute as well as your career and family commitments to determine how much time you realistically can spend there relative to the costs of owning and maintaining the property.
Spend some quality time at the local coffee shop or microbrewery and chat with people who live in the area year-round. Ask them what they like, and don't like, about living there – and about any cultural trends they've noticed.
Renting out the home when you're not there brings with it a host of other considerations. Does the HOA allow rentals? Would potential renters be interested in the property's amenities, such as a fireplace in a ski town or an inviting deck or patio in a beach community?
6. What's the tab when you're not there?
Calculate the true, year-round cost of owning the home, including utilities and property management when the home isn't occupied.
This entry was posted in Buyer Info, Home Ownership, Local Info, Seller Info and tagged Hampton Roads, RE/MAX, Real Estate, Vacation Homes, Virginia Beach by remaxalliancevb. Bookmark the permalink.


Those two documents offer a perspective on the cost of MSR developmental.
In 1980 the ORNL staff estimated that a commercial DMSR could be developed for $700 million (about 2.5 billion in 2009 dollars). Given another 2.5 billion for the development of the LFTR prototype we would have a total investment of between 5 and 6 Billion 2009 dollars investment. At that point there would be a product ready to go on the assembly line. Thus the total investment in the LFTR would be comparable to the Federal investment into the LWR. It would be one fourth the investment in so far unsuccessful LMFBR technology.
My analysis suggests that with factory production and by recycling coal fired power plants, modular LFTRs can come online for an investment as small as a dollar a watt. Let us assume that the actual cost is twice that. We still have a price for LFTRs that is lower than the 2009 price for windmills. even with a capacity factor no better than the windmills, the LFTR would be a fae better buy because of its superior flexibility.
It would be nice to imagine a private enter[rice investing in the LFTR. Is it possible? $5 billion would not be unreasonable for a private business invest in LFTR development. Consider the €11 billion plus that Airbus invested in the development of the A380. At a cost of $327 million the A380 would be if anything more expensive than the modular LFTR. In fact it is doubtful that Airbus will ever recover the Airbus 380 development cost, while the LFTR potentially could be quite profitable.
Further comparisons of the LFTR and the Airbus 380 might be in order. I suspect that the 380 would be far more complex, require far more labor input, require more exotic materials in its construction, require far more instrumentation and control, and take longer to build.
Such speculation should receive far more investigation than I have conducted, should be the subject of much more rigorous testing, and proof. I off these initial conjectures, in the hope that they will receive more investigation.
The comparison between the LFTR and the Airbus 380 is interesting.
The money to develop a commercial LFTR is certainly within the reach of a number of large companies and even a few individual.
The difference between the LFTR and the Airbus 380, I believe, is in government regulation. The A-380 is being regulated for its success. That regulation certainly includes safety, emissions, and noise. These requirements have been tightened incrementally over the years, but they apply to all new aircraft being manufactured, whether of old or new design. These regulations are the things necessary to make the aircraft acceptable in the market. In a way, they may be "hurdles", but they are necessary hurdles. Once past these hurdles, I don't expect that there will be actions taken by various groups to prevent the entrance of the A-380 into the market. The success of A-380 will determined by the market. Investors recognize this market risk, and accept it as a normal part of doing business. From a business point of view, satisfying regulatory requirements is simply another part of the development, much like fuel burn and flight range.
Contrast this with the regulatory climate for reactor development. Safety regulation seems to be used not as a mechanism to make nuclear reactors acceptable in the market, but as a method to prevent them from being built at all. Unlike for aircraft, the level of safety demanded for a new nuclear reactor is not applied as well to a newly constructed coal plant.
I think we are correct to expect a higher standard of safety with nuclear reactors, but if the safety bar is raised so high as to prevent the development of advanced nuclear reactors, safety is degraded as we continue to use old coal-fired power plants, and build new ones.
Similarly, radioactive emissions. It is easily shown that radioactive emissions into the general environment from a coal-fired power plant are much higher than for a nuclear plant. Once again, I think we should expect a higher standard for nuclear plants, but not so high as to prevent them from being constructed and benefitting society.
Given that regulation seems to be more about placing obstacles in the way of advanced reactor development than about benefit to society, is it any wonder that so few large companies and individuals are willing to invest in the development of advanced reactors?
The reason governments throw a myriad of regulatory roadblocks and safety & environmental red tape, in the way of nuclear power generation, but do their best to streamline and reduce the regulatory obstacles for aircraft, is that aircraft burn lots of fuel unlike a nuclear reactor which saves lots of fuel.
What was the WMD that terrorists used on 9-11? Large Aircraft. There is no emergency shutdown on large aircraft, as there is on Nuclear Reactors. Imagine an Airbus 380 crashing into Manhattan during rush hour. They don't allow nuclear reactors in Manhattan. Obvious another example of where Nuclear is irrationally opposed by Government & the Press vs other vastly more dangerous technology. Now why would that be? Follow the Money.
Large Aircraft Assembly Line production methods are a good model for the production of medium sized nuclear reactors in the 100 to 500 MWe range. The key is demand must be high enough and governments must give a clear signal that they will support with words AND DEEDS, factory production of small and medium sized nuclear reactors. Certainly with high Carbon Taxes and the coming explosive rise in Fossil Fuel prices, the demand will be more than adequate.
Have you got at least a rough estimate for the cost of construction of a first prototype of the small size of 10 or 100 MW thermal (fluorides in thermal/epithermal spectrum or chlorides in fast spectrum), in order to develop the necessary start R&D for MSR technology?


There's an example for a Last.fm feed for now playing tracks.
This is really excellent. Are you still working on getting it to print ASCII portraiture?
PS sorry I'm being slow to get it on the /modules page. I promise I noticed.
Hadn't thought about printing images in ASCII art that's cool. Could only have 32 characters width so probably not the highest res haha.
The printer can print proper bitmaps, black and white. The original thermalprinter library has methods for converting images and printing but that code doesn't work on the Tessel so need to fix that.
We're live on the modules page! Thermal Printer.
Sorry that took so long.
Thanks for making this cool module!


Declaration: To be an artist in Romania is beautifully complicated, painful otherwise and it must be naturally uninterested. As a Romanian artist, one has a great advantage: one can never get bored, because one never lacks inspiration. Only very rarely does one glow or feel the taste of success. Art is an embryo in Romania, there is still long before the development of the fetus and the child that will be born will have an extended adolescence and childhood. Thus Romanian art, following tradition, will need various steps, strength and quality, true parents and, not last, a miracle, until the point when it will achieve an otherwise natural maturity. To be an artist here is complicated because one lives in a transit society, an unstable society where the artist has no statute, nothing supports him, nothing encourages him, nothing motivates him, except for his ambition and his inner structure as an artist. When one is an artist in Romania one is alone on the road.


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Amirtha Kidambi Elder Ones
Holy Science
Label: Jazzman
Catalogue number: JMANLP118
Genres: Instrumental, Jazz, Modal Jazz, Modern Jazz, Psychedelia, Spiritual Jazz, World
Origin: United Kingdom
A - Treta-Yuga (20:31)
B - Kali-Yuga (17:32)
RELEASE DATE: 14 FEBRUARY 2020
- Debut recordings by New York improvisers exploring a spiritual alchemy with harmonium, voice and avant jazz
- Transcendental, exploratory Indian jazz released for the first time on vinyl
- Liner notes by DJ Cherrystones
- "Sublime" - Ben Ratliff, New York Times
- "An astonishing debut" - Seth Colter Walls, Pitchfork
- "Exquisite" Spyros Stasis, Scene Point Blank
First released on digital formats back in 2016, and here now given a richly deserved full vinyl release, 'Holy Science', the debut outing from Amirtha Kidambi and her New York based quartet The Elder Ones, is a work of dazzling singularity. Delicately yet unashamedly divulging its complex network of influences at every turn, 'Holy Science' simultaneously disperses of boundary and limitation, emerging as an album steeped in tradition yet located firmly in the futuristic present.
Amirtha Kidambi, the Elder Ones' leader, composer and vocalist, was a child of South Indian heritage, and she grew up immersed in the tradition of devotional singing, joining in with free-form, improvised Bhajans on regular Sundays. She began simultaneously accompanying her voice with the harmonium from the age of three. These formative experiences continued to instruct and merge with her ongoing musical explorations as she went on to study Classical music, all the while ingesting the Punk, R&B and Rap that surrounded her. A particularly significant discovery was that of free and avant jazz, and in particular the music of Alice and John Coltrane, in whom Kidambi found clear echoes and parallels with those Bhajans and Ragas of her earliest musical awakenings.
All these influences collide on 'Holy Science', at times as explosive blasts of sky-opening thunder, at others as moments of soothing, meditative bliss. These holy bursts are enacted by Kidambi's assembled musicians and are given permission to explore the science of spiritual alchemy, plundering their individual and collective soul for the sake of musical expression, and all of the unpredictable and profound revelations such an approach might yield.
'Holy Science' is a work underpinned by traditions, be they the Bhajan spirituals, or the Jazz and Classical avant gardes, that are in their own manner, archetypal. But perhaps most importantly, all of these forms contain an inbuilt capacity for discovery and progression. Amirtha Kidambi's musical pathway has been defined by a studied determination to occupy this specific space, the unbounded realm of improvisation and exploration, summoning the acquired instruments of experience, knowledge, culture and tradition to unlock secrets of the past, present and future. The most cherished music is often remarked upon as having a timeless quality – ancient, modern and futuristic, all at once. And so it is with 'Holy Science'.
Can You See What I'm Trying To Say
I'll Remember
Spiritual Jazz 12: Impulse!
The Storyteller - A Musical Tribute to Yusef Lateef
Build Bridges
Copyright Jazzman Records © 2019 - All rights reserved.


For a discussion of callback with computer modems, see Callback (telecommunications).
In computer programming, a callback, also known as a "call-after" function, is any executable code that is passed as an argument to other code that is expected to call back (execute) the argument at a given time. This execution may be immediate as in a synchronous callback, or it might happen at a later time as in an asynchronous callback. In all cases, the intention is to specify a function or subroutine as an entity[clarification needed] that is, depending on the language, more or less similar to a variable (see first-class functions).
Programming languages support callbacks in different ways, often implementing them with subroutines, lambda expressions, blocks, or function pointers.
There are two types of callbacks, differing in how they control data flow at runtime: blocking callbacks (also known as synchronous callbacks or just callbacks) and deferred callbacks (also known as asynchronous callbacks). While blocking callbacks are invoked before a function returns (in the C example below, which illustrates a blocking callback, it is function main), deferred callbacks may be invoked after a function returns. Deferred callbacks are often used in the context of I/O operations or event handling, and are called by interrupts or by a different thread in case of multiple threads. Due to their nature, blocking callbacks can work without interrupts or multiple threads, meaning that blocking callbacks are not commonly used for synchronization or delegating work to another thread.
Callbacks are used to program applications in windowing systems. In this case, the application supplies (a reference to) a specific custom callback function for the operating system to call, which then calls this application-specific function in response to events like mouse clicks or key presses. A major concern here is the management of privilege and security: whilst the function is called from the operating system, it should not run with the same privilege as the system. A solution to this problem is using rings of protection.
In assembly, C, C++, Pascal, Modula2 and similar languages, a machine-level pointer to a function may be passed as an argument to another (internal or external) function. This is supported by most compilers and provides the advantage of using different languages together without special wrapper libraries or classes. One example may be the Windows API that is directly (more or less) accessible by many different languages, compilers and assemblers.
C++ allows objects to provide their own implementation of the function call operation. The Standard Template Library accepts these objects (called functors), as well as function pointers, as parameters to various polymorphic algorithms.
CLI languages such as C# and VB.NET provide a type-safe encapsulating reference, a "delegate", to define well-typed function pointers. These can be used as callbacks.
Events and event handlers, as used in .NET languages, provide generalized syntax for callbacks.
Functional languages generally support first-class functions, which can be passed as callbacks to other functions, stored as data or returned from functions.
Some languages, such as Algol 68, Perl, Python, Ruby, Smalltalk, C++11 and later, newer versions of C# and VB.NET as well as most functional languages, allow unnamed blocks of code (lambda expressions) to be supplied instead of references to functions defined elsewhere.
In object-oriented programming languages without function-valued arguments, such as in Java before its 8 version, callbacks can be simulated by passing an instance of an abstract class or interface, of which the receiver will call one or more methods, while the calling end provides a concrete implementation. Such objects are effectively a bundle of callbacks, plus the data they need to manipulate[clarification needed]. They are useful in implementing various design patterns such as Visitor, Observer, and Strategy.
Callbacks have a wide variety of uses, for example in error signaling: a Unix program might not want to terminate immediately when it receives SIGTERM, so to make sure that its termination is handled properly, it would register the cleanup function as a callback. Callbacks may also be used to control whether a function acts or not: Xlib allows custom predicates to be specified to determine whether a program wishes to handle an event.
The following C code demonstrates the use of callbacks to display two numbers.
Note how this is different from simply passing the output of the callback function to the calling function, PrintTwoNumbers() - rather than printing the same value twice, the PrintTwoNumbers calls the callback as many times as it requires. This is one of the two main advantages of callbacks.
* The callback function is in the same file as the calling code.
* e.g. a shared object to increase flexibility.
First a function someEvent is defined with a parameter intended for callback: callbackFunction. Then a function that can be used as a callback to someEvent is defined, calcProduct. Other functions may be used for callbackFunction, like calcSum. In this example, someEvent() is invoked twice, once with calcProduct as a callback and once with calcSum. The functions return the product and sum, respectively, and then the alert will display them to the screen.
A classic use of callbacks in Python (and other languages) is to assign events to UI elements.
Here is a very trivial example of the use of a callback in Python. First define two functions, the callback and the calling code, then pass the callback function into the calling code.
...     """ the callback """
^ "What is a callback function?". Stack Overflow. Retrieved 2018-05-16.
^ "Perl Cookbook - 11.4. Taking References to Functions". Retrieved 2008-03-03.
^ "Advanced Perl Programming - 4.2 Using Subroutine References". Retrieved 2008-03-03.
^ "PHP Language Reference - Anonymous functions". Retrieved 2011-06-08.
^ "What's New in JDK 8". oracle.com.
^ "Callbacks". Mozilla Developer Network. Retrieved 13 December 2012.
This page was last edited on 15 March 2019, at 21:07 (UTC).