About Us:
Sage Donnelly has a doctorate of the arts from North Kenwood university. She uses her talents to help launch small businesses. Some of her past successes include Microsoft, Standard Oil, The North Atlantic Railroad, and Google.
Raymond Grady is a self-sealing stembolt mogul with a passion for amazing coffee. He’s put his vast stem-bolt fortune toward opening Beandust espresso. His dedication knows no bounds.


"x"
"1" "AWOGI,T, ITOH,T, SHIBAHARA,T, KANEKO,E AND TSUSHIMOTO,G, GENOTOXICITYSTUDIES OF(+/-)-9-FLUORO-6,7-DIHYDRO-8-(4-HYDROXY-1-PIPERIDYL)-5-METHYL-1-OXO-1H,5H-BENZO[I,J]QUINOLIZINE-2-CARBOXYLIC ACID (OPC-72 __ 51), A SYNTHETIC ANTIBACTERIALAGENT, IYAKUHIN KENKYU 21(4):626-635, 1990"


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Viewers moved as Ant and Dec talk about friendship being tested
Viewers said they went though a “rollercoaster of emotions” as Ant McPartlin and Declan Donnelly told how their friendship was tested in the wake of McPartlin’s drink-driving arrest.
Many fans said they were sobbing as the pair opened up in ITV’s Ant And Dec’s DNA Journey, which saw them investigating their ancestry together.
Filming for the programme began in 2017, but was halted after McPartlin crashed his car in March 2018 while more than twice the alcohol limit, before entering rehab.
The star struggled with a two-year addiction to super-strength painkillers following a knee operation in 2015.
In emotional scenes in the programme, Donnelly said at times he thought their decades-long relationship would not “survive”.
The 44-year-old also admitted that he was “incredibly angry” that his friend did not confide in him.
He said: “I was incredibly angry at the start. So angry, disappointed in him that he didn’t ever come to me and say, ‘I’m struggling and I need you’.”
“He never came to me and that hurt me a lot,” he said.
However, the friendship did survive the turbulent time, and Donnelly noted: “We are much stronger together now.”
Viewers said they were moved to tears by some of the scenes.
One fan posted on Twitter: “That last ten minutes had me sobbing so much. They’ve been a part of my life for 20 odd years, ever since the SMTV days!
“I’m so proud of Ant for taking control of his priorities and taking a break to focus on himself.”
“Oh my god!! Best bit of telly EVER!!! Bloody sobbing here!!!” said another.
“Ah lads you’ve me in tears now, so so happy to see you back together stronger than ever. What an incredible friendship you have,” another person posted.
Another person said: “This @antanddec #DNAjourney has everything – fun, laughter, tears. A emotional rollercoaster. It’s brilliant to watch and very poignant. It emphasises the bond you both have.”
One fan tweeted: “i’m sobbing… they’re talking about what happened to ant and how it affected their friendship. i’m so glad they came out of the other side. i love them so much and i couldn’t imagine a life without them both working together and just being friends.”
“Dec said he’s never cried so much on the telly, while I have never cried so much WATCHING the telly!!!” said another viewer.
“My heart @antanddec such a rollercoaster of emotions,” tweeted another fan.
Ant And Dec’s DNA Journey continues on Monday.


In Rochestown Park Hotel I was being taught on how to do stuff such as; Take a ph reading of the pool water to ensure the correct chlorine levels were present at all times.
I was also placed on duty of power washing the sauna and steam room. On top of this they temporarily placed me on duty of lifeguarding on certain occassions. This taught me
Great independence skills which have stuck with me since. Aswell, they often instructed me to clean the gym i.e clean the mirrors and put back loose weights on the gym floor.
In Citco I was introduced to the many aspects both (1) Phyical and (2) Internal compenents of a computer. At the beggining of my time here it was mainly physical which I did
really enjoyed. After , I was allowed to sit in on some specialist employees and see what they were working on. I found this experience far more entertaining and enjoyable.
This experience is where my love and interest for computers and their endless possibilities was birthed.
In Wistek I was put in to role of drive strip. This role was very important in the process of the overall aims that had to be met on a weekly basis. This work included stripping
down hard drives and retrieving the paddle sticks from them. We then proceeded to scan the paddle sticks to see if they were recyclable or not. I personally enjoyed this work as
it gave me a real sense of meaning and need within the company.
In Mcdonalds, I work in the service area of the restaurant. This work includes; Making McFlurry's, Pouring drinks, Order taking, Order Presenting, Order assembly etc...
I personally enjoy my work in McDonalds as I enjoy working with Customers and helping make people have a more enjoyable experience. I also enjoy this work due to my fellow
collegues as they are very kind and are always willing to help me whenever I require assistance.


{% extends "../layout/base.html" %} {% include "style/bootstrap.html" %} {% block content %}
We've emailed you instructions for setting your password. If they haven't arrived in a few minutes, check your spam folder.
Since the app is under development process, sent email is under "discussion_board/sent_emails" folder
{% endblock %}


I'm Carlos! Nice to meet you! I have varying interests, I love to learn new things. Currently, I am learning to code, but I am also learning french and game theory in classes much like this one. Granted, not as hard. I love to laugh, enjoy cinema, and adore spending time outdoors.
I was born in Ecuador, so my native language is Spanish. My favorite beer is called Ghost in the Machine, it's drafted in Louisiana. I have played soccer all my life, but also enjoy tennis and baseball. I love videogames, sometimes I give them too much of my free time.


[gecode-users] pdb files
Filip Konvička
filip.konvicka at logis.cz
Thu Sep 20 21:24:37 CEST 2007
Hi,
today I encountered a problem which I have not solved yet, and I'm not
sure if the problem is in Gecode or in my code. In disassembly code, I
saw what seemed as a quite tight infinite loop somewhere in
GecodeKernel.dll. What I would like is to get a pdb file so that the
Visual C++ debugger correctly sees the call stack. Is there a
recommended way of obtaining the pdb files? I think that it's necessary
to pass "/DEBUG /PDB:"GecodeKernel.pdb" to link.exe for the release
build. (This IMHO does not change the dll files themselves, it just
creates appropriate pdbs and thus enables debugging.)
Thanks,
Filip
More information about the gecode-users
mailing list


Hua L, Challa GS, Subramanian S, Gu X, Li W. 2018. Genome-wide identification of drought response genes in soybean seedlings and development of biomarkers for early diagnoses. Plant Mol Biol Rep. 2018 May 13. doi: 10.1007/s11105-018-1085-z.
Li W, Yang B. 2017. Translational genomics of grain size regulation in wheat. Theor Appl Genet. 130(9), 1765-1771
Li W, Challa GS, Zhu H, Wei W. 2016. Recurrence of Chromosome Rearrangements and Reuse of DNA Breakpoints in the Evolution of the Triticeae Genomes. G3: Genes, Genomes, Genetics 6 (12), 3837-3847.
Zhang ZZ, Wei W, Challa GS, Bi C, Trick HN, Li W. 2015. W3 is a new wax locus that is essential for biosynthesis of β-diketone, development of glaucousness, and reduction of cuticle permeability in common wheat. PLoS One 10(10): e0140524.
Zhang Z, Zhu H, Gill BS, Li W. 2015. Fine mapping and haplotyping of Br2 interval revealed genomic and population structure variation in Aegilops tauschii Coss. Theor Appl Genet 128:745–755.
Gornicki P, Zhu H, Wang J, Challa GS, Gill BS, Li W. 2014. The Chloroplast view of the evolution of polyploid wheats. New Phytologist 204:704-714.
Wang J, Li W, Wang W. 2014. Fine mapping and metabolic and physiological characterization of the glume glaucousness inhibitor locus Iw3 derived from wild wheat. Theor Appl Genet 127:831-841.
 A 4-gigabase physical map unlocks the structure and evolution of the complex genome of Aegilops tauschii, the wheat D-genome progenitor. Proc Natl Acad Sci USA. 110: 7940-7945.
Li W, Zhu H, Challa GS, Zhang ZZ. 2013. Non-additive interaction in a single locus causes a very short root phenotype in wheat. Theor Appl Genet. 126:1189-1200.
Zhang Z, Wang W, Li W. 2013. Genetic Interactions Underlying the Biosynthesis and Inhibition of β-Diketones in Wheat and Their Impact on Glaucousness and Cuticle Permeability. PLoS ONE 8(1): e54129. doi:10.1371/journal.pone.0054129.
Rawat N, Sehgal SK, Joshi A, Rothe N, Wilson DL, McGraw N, Vadlani PV, Li W, Gill BS. 2012. A diploid wheat TILLING resource for wheat functional genomics. BMC Plant Biology 2012, 12: 205 doi:10.1186/1471-2229-12-205.
Akhunov E, Sehgal S, Liang H, Wang S, Akhunova A, Kaur G, Li W, Forrest K, See D, Simkova H, Hayden M, Luo M, Farris J, Dolezel J, Gill BS. 2012. Comparative analysis of syntenic genes in grass genomes reveals accelerated rates of gene structure and coding sequence evolution in polyploid wheat. Plant Physiol. 161: 252-265.
Sehgal SK, Li W, Rabinowicz PD, Šimková H, Doležel J, Gill BS. 2012. Chromosome arm specific BAC end sequences permit comparative analysis of homoeologous chromosomes and genome of polyploid wheat. BMC Plant Biol. DOI: 10.1186/1471-2229-12-6422559868
Bi C, Chen F, Jackson L, Gill BS, Li W. 2010. Expression of lignin biosynthetic genes in wheat during development and upon infection by fungal pathogens. Plant Mol Biol Rep DOI 10.1007/s11105-010-0219-8.
Huang L, Brooks S, Li W, Fellers J, Nelson JC, and Gill BS. 2009. Evolution of new disease specificity at a simple resistance locus in a crop–weed complex: Reconstitution of Lr21 gene in wheat. Genetics 182: 595-602.
Zhang P, Li W, Friebe B, Gill B. 2008. The origin of the ‘zebra’ chromosome consisting of segments from nonhomologous chromosomes of Triticum aestivum and Elymus trachycaulus and its implications in chromosome evolution. Genetics 179: 1169–1177.
Perumal A, Li W, Rudd JC, Gill BS, Michels Jr. GJ, Weng Y. 2008. Aphid pest feeding responses and microsatellite-based genetic diversity among six diploid Brachypodium distachyon accessions. Plant Genetic Resources doi: 10.1017/S1479262108994235.
Li W, Huang L, Gill BS. 2008. Recurrent deletions of puroindoline genes at the grain hardness locus in four independent lineages of polyploid wheat. Plant Physiol 146: 200-212.
Gill BS, Li W, Sood S, Kuraparthy V, Friebe B, Simons KJ, Zhang Z,Faris JD. 2007. Genetics and genomics of wheat domestication-driven evolution. Israeli Journal of Plant Science. 55: 223-229.
Li W, Gill BS. 2006. Multiple genetic pathways for seed shattering in grasses. Functional and Integrative Genomics 6: 300-309.
Lamoureux D, Peterson DG, Li W, Fellers JP, Gill BS. 2005. The efficacy of Cotbased gene enrichment in wheat. Genome 48: 1120-1126.
Weng Y, Li W, Devkota R, Rudd J. 2004. Microsatellite markers associated with two Aegilops tauschii-derived greenbug resistance loci in wheat. Theor Appl Genet 110: 462–469.
Li W, Zhang P, Fellers JP, Friebe B, Gill BS. 2004. Sequence composition, organization and evolution of the core Triticeae genome. Plant Journal 40: 500-511.
Yu JK, Dake TM, Singh S, Benscher D, Li W, Gill BS, Sorrells ME. 2004. Development and mapping of EST-derived simple sequence repeat markers for hexaploid wheat. Genome 47:805-818.
Zhang P, Li W, Fellers J, Friebe B, Gill BS. 2004. BAC-FISH in wheat identifies chromosome landmarks consisting of different types of transposable elements. Chromosoma 112: 288-299.
Zhang P, Li W, Friebe B, Gill BS. 2004. Simultaneous painting of three genomes in hexaploid wheat by BAC-FISH. Genome 47: 979-987.
Huang, L, SA Brooks, W Li, JP Fellers, HN Trick and BS Gill. 2003. Map-based cloning of leaf rust resistance gene Lr21 from the large and polyploid genome of bread wheat. Genetics 164: 655-664.
Luo MC, Thomas C, Deal KR, You FM, Anderson OD, Gu YQ, Li W, Kuraparthy V, Gill BS, McGuire PE, Dvorak J. 2003 Construction of contigs of Ae. tauschii genomic DNA fragments cloned in BAC and BiBAC vectors. Proc. 10th Internl. Wheat Genet. Sym., Sept. 1-6, Paestum, Italy, pp. 293-296.
Li W, Nelson CJ, Chu CY, Shi LH, Huang SH, Liu DJ. 2002. Chromosomal locations and genetic relationships of tiller and spike characters in wheat. Euphytica 125: 357-366.
Li W, Gill BS. 2002. The colinearity of the Sh2/A1 orthologous region in rice, sorghum and maize is interrupted and accompanied by genome expansion in the triticeae. Genetics 160: 1153-1162.
Li W, Faris JD, Muthukrishnan S, Liu DJ, Chen PD, Gill BS. 2001. Isolation and characterization of novel cDNA clones encoding chitinases and -1,3-glucanases from wheat spikelets infected by Fusarium graminearum. Theor. Appl. Genet. 102: 353-362.
Anand A, Li W, Sathivel N, Krishnaveni S, Muthukrishnan S, Gill BS, Essig JS, Adams RE, Janakiraman V, Trick HN. 2000. Characterization of wheat PR-protein cDNAs for transformation of wheat to enhance resistance to scab. National Fusarium Head Blight Forum, Dec. 10-12, Erlanger, KT, USA, pp. 5-12.
Gill BS, Li W, Anand A, Fellers JP, Trick HN, Muthukrishnan S, Liu DJ, Chen PD. 2000. Analysis of genes induced in wheat spikes upon infection with Fusarium graminearum and their manipulation to improve wheat plant resistance to Fusarium head scab disease. Proc. Internl. Symp. Wheat Improvement for Scab Resistance, May 5-11, Suzhou and Nanjing, China, pp. 136-139.
Liu, JY, DJ Liu, WJ Tao, W Li, SL Wang, PD Chen, SH Cheng, and DR Gao. 2000. Molecular marker-facilitated pyramiding of different genes for powdery mildew resistance in wheat. Plant Breeding 119: 21-24.
Singh, S, W Li, QJ Song, P Cregan, GL Brown-Guedira and BS Gill. 2000. Development and physical mapping of microsatellite markers in wheat. 2000 National Fusarium Head Blight Forum, Dec. 10-12, Erlanger, KT, USA, pp. 52-53.
Li, W, JD Faris, J Chittoor, JE Leach, DJ Liu, PD, Chen, BS Gill. 1999. Genomic mapping of defense response genes in wheat. Theor. Appl. Genet. 98: 226-233.
Qi LL, Cao MS, Chen PD, Li W, Liu DJ. 1996. Identification, mapping and application of polymorphic DNA associated with the resistance gene Pm21 of wheat. Genome 39: 191-197.
Li W, Chen PD, Qi LL, Liu DJ. 1995. Isolation, characterization and application of a species-specific repeated sequence from Haynaldia villosa. Theor. Appl. Genet. 90: 526-533.
Li W, Liu DJ, Chen PD, Qi LL. 1993. Cloning of repeated sequences of Haynaldia villosa DNA to detect its chromatin in wheat. Proc. 8th Internl. Wheat Genet. Symp. July 20-25, Beijing, China, pp. 817-82.
Li W, Li ZS, Mu SM. 1992. Chromosomal location of genes for erect flag leaves of common wheat variety Xiaoyan No. 6. English version: Chinese Journal of Genetics 19: 21-25.
Li W, Li ZS, Huang SS. 1990. Chromosomal location of gene for auricle development in common wheat. Wheat Information Service 71: 27-28.


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Army recovers gun trucks, anti-Air craft Guns, ammunition from Boko Haram in a failed ambush
by Lukman ABOLADETHE Nigerian Army said it has recovered gun trucks, anti-aircraft guns, ammunitions among other items from Boko Haram fighters in a failed ambush by the insurgents.
In a statement by the army authorities signed by Aminu Iliyasu, the Nigerian Army Operations Media Coordinator, the troops of 153 Task Force Battalion during a fighting patrol on Monday were ambushed by Boko Haram insurgents along Ala Village, in Dikwa local government of Borno State.
He said the patrolling army troop were able to turn the ambush around as they engaged in a firefight with the terrorist who eventually flee abandoning their weapons and food supplies.
The troops embarked on a pursuit of the fleeing insurgents who abandoned two gun trucks, two anti-aircraft guns, 2,080 Rounds of 7.62mm NATO ammunition, 26 Rounds of 12.7 mm armour-piercing incendiary ammunition, he said.
According to him, the troop was also able to recover three AK 47 Rifles, six rounds of 12.7 mm (Belted), one AOJOE motorcycle including some clothes, food supplies and mechanical tools.
He said most of the Boko Haram members were believed to have escaped with varying degrees of gunshot wounds.
“The Chief of Army Staff, Lieutenant General Tukur Yusufu Buratai commends the troops for their gallantry, and equally wishes to reiterate the commitment of the Nigerian Army to accomplish its constitutional mandate professionally and responsively for a secured Nigeria,” he wrote.
He expressed the appreciation of COAS to well-meaning Nigerians for their unalloyed support, goodwill and understanding towards officers and men of the Nigerian Army as they tackle multiple security challenges confronting the nation.
He added that less than two weeks ago, Boko Haram suffered a tactical boomerang when some of them were neutralised and maimed as they mistakenly stepped on the same improvised explosive device that they had earlier planted.


Catalog of Products
Product Code
Product Description
Price
0001
Boots
$56.00
0002
Shoes
$47.00
0003
Hat
$25.00
0004
Bag
$108.00


The New York attorney general is investigating WeWork amid layoffs
by Ellen Cranley, Business Insider US- Reuters reports that New York’s attorney general is investigating the embattled workspace giant WeWork.
- The company confirmed it had been contacted by Attorney General Letitia James’ office, which will reportedly focus on activities by WeWork’s cofounder and former CEO, Adam Neumann.
- The company has faced trouble since it shelved its initial public offering and turned to its largest shareholder for a rescue deal. Massive layoffs are expected at the company in the coming weeks.
- Visit Business Insider’s homepage for more stories.
New York’s attorney general is investigating the embattled workspace giant WeWork, Reuters reported Tuesday.
The outlet cited two people familiar with the matter and said the company confirmed it had been contacted by Attorney General Letitia James’ office.
“We received an inquiry from the office of the New York state attorney general and are cooperating in the matter,” a WeWork spokeswoman told Reuters.
One point of investigation is whether WeWork’s cofounder and former CEO, Adam Neumann, indulged in self-dealing. He was widely reported to have bought properties to lease back to WeWork and to have charged the company almost $6 million to use his trademark of the word “We” for the rebranded The We Company.
The company has faced trouble since it shelved its initial public offering and took a rescue deal from its largest shareholder, the Japanese technology investment company SoftBank. Neumann stepped down as CEO in September, and the company has laid off a large portion of staff.
The company is expected to lay off thousands of employees “in earnest” beginning this week.
Reuters noted that this wasn’t the first time the company had caught the attention of the New York attorney general, as WeWork scrapped its policy of requiring employees to sign noncompete agreements after reaching a settlement with the attorney general last year.
Read more of our WeWork coverage:
SoftBank CEO Masayoshi Son told WeWork executives he wanted the company to turn a profit by 2021
Investors are more skeptical than ever that WeWork will be able to pay back its debt


The username and password above correspond to the Natural Language Classifier service instance you are connecting to. In order to find these, you can open your service instance on Bluemix and navigate to the "Service Credentials" tab on the side panel. This will display a page that contains your username and password, which you can use to log in to the tooling.


The Crime Victim Assistance Program will collect your personal information for the purpose of providing you with victim services and determine your eligibility for benefits in accordance with sections 26(a) and (c) of the Freedom of Information and Protection of Privacy Act (FoIPPA), and the Crime Victim Assistance Act. Your personal information may also be collected as per section 26(e) of FoIPPA in order to evaluate the program to better serve you.
Should you have any questions about the collection, use, or disclosure of personal information, please contact the Crime Victim Assistance Program at {{cvapEmail}} or by phone at<PHONE_NUMBER> and toll free at 1-800-660-3888 or at PO Box 5550, Stn Terminal, Vancouver, BC, V6B1H1.
By signing this section you declare that the information you have provided on this application is true and correct.
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| PVI irrigation |
Off-label use for EKC; reduces risk of disease transmission |
Dry eye symptoms, corneal epithelial damage/toxicity with repeated use.
104
|
| Cidofovir |
Antiviral activity against HAdV5 exhibited in animal models.
105
Cidofovir 1% lowered the frequency of severe corneal opacities in patients with adenoviral keratoconjunctivitis.
64,
106
|
Narrow therapeutic index when used topically; high doses for greater than one week associated with rare cases of lacrimal canalicular
blockade in rabbit models.
107
|
| Ganciclovir |
3% ganciclovir reduced HAdV 5 replication and pathogenesis in animal models.
108 Ganciclovir is efficacious against HAdV types that cause EKC.
46 Ganciclovir ophthalmic gel treatment prevents complications in adenoviral ocular infection.
109
|
Transient blur following instillation, eye irritation, punctate keratitis, conjunctival hyperemia.
108
|
| Brincidofovir |
Brincidofovir has antiviral activity against adenoviruses.
55,
105,
110–
113
|
Mild gastrointestinal tract upset, asymptomatic and elevated levels of serum transaminases
114 diarrhea, acute graft versus host disease, abdominal pain, nausea/vomiting, decreased appetite, peripheral edema, hyperglycemia, hypokalemia, rash, fatigue, fever.
115
|
| Topical corticosteroids |
Relief of EKC symptoms and Persistent adenoviral SEIs.
2,
63
|
Glaucoma and cataracts.
116
|
| Topical cyclosporine |
Effective against persistent adenoviral SEIs.
66,
69,
117–
119
|
Transient or long-lasting burning sensation;
120 ocular pain/irritation, redness; eyelid swelling in Steven Johnsons patients.
121
|
| Topical tacrolimus |
Superior to dexamethasone in reducing symptomology and SEIs
70 as well as a safe and effective treatment of adenoviral SEIs.
87,
122,
123
|
Transient burning sensation.
124
|


Athens County had 37 cases on July 1. By August 1, the county had 342 cases. James Gaskell, health commissioner at the Athens City-County Health Department described this as a “small surge.”
About 75% of cases in the county are from people under the age of 30. Of these 256 people, four have been hospitalized and there have been no deaths. The only death in the county as of August 1 was a person in their 60s, according to the Ohio Department of Health.
Statewide, people under the age of 30 accounted for about 29% of all cases. They only count for 0.3% of deaths and 6% of hospitalizations.
Mary Berger | Art Director
The number was as high as 88% in July, Gaskell said.
In mid-July, Ohio Gov. Mike DeWine increased Athens’ coronavirus safety level to three with a watch for level four, the highest level. This was during the surge of cases in the county. Athens County has since been reduced to level two.
DeWine said there were at least three outbreaks at bars. Most of the cases were linked to bars and restaurants, according to a previous Post report.
On top of restaurants and bars, small group gatherings and parties were also causes of spread, DeWine said.
Gaskell said he thinks Athens will likely “have a surge in diseases” when students return on campus.
Ohio University announced on July 31 that most students will return to campus in late September, rather than August 24.
Students who have to be in-person for their classes, such as students who are required to be in science and medical labs, should be on-campus, while OU limits other students who are online, Gaskell said.
Gaskell, who has talked with university officials about bringing students back, said bringing a limited number of students, who are required to wear masks, would help.
Gaskell said the type of masks people wear also makes a difference. He recommends people wear the N95 mask, a kind of mask often used by health professionals, because that prevents the spread of disease by nearly 100%.
Homemade masks are still effective, providing about 60% of protection, he said.
When students return, contact tracing could overwhelm the health department, Gaskell said.
Nurses from the health department do contact tracing after a person tests positive, Gaskell said. He said if a person spends 15 minutes talking with someone in close proximity who tested positive, then they would likely have to quarantine for two weeks.
“At a certain point, there will be enough cases that it will spread to the community,” he said. “We’ll have community-wide spread.”
While almost all people under 30 who have gotten the virus in Athens County have not been hospitalized, older members of the community are at a much higher risk. The mortality rate for people over 80 is about 16%, Gaskell said.
On August 1, the state of Ohio reported having 92,807 cases. The leading age range are people in their 20s. Over 18,700 people in their 20s have contracted the virus. There were also 8,092 people aged 0-19 who contracted the virus.
As July came to a close, cases began to decrease, Gaskell said.
COVID-19 is contagious two days before people become symptomatic, Gaskell said.
Masking up and social distancing are some of the few mitigating factors that people can control, Gaskell said.
“It’s worked in South Korea, it’s worked in Japan, it’s worked in Italy and they’ve decreased the infection rate considerably,” Gaskell said.


# An Introduction to Deep Metric Learning Matthew Nokleby, Lead AI Scientist @ Target
## About me ### Work on machine learning + computer vision at Target ### Previously: Asst. Professor of Electrical Engineering at Wayne State University, Detroit, MI ### Research interests: ML/CV, information theory, distributed learning, stochastic optimization ### Papers/etc. at: http://docnok.github.io
# A brief history of deep learning
## Deep learning pre-history
### Convolutional neural networks go back (at least) to the 1980s! ### **LeNet**: CNN for handwritten digit recognition, 1989 ### Elements familiar to modern DL: - Convolutional filters extract features - Trained via backpropagation + SGD
## Deep learning pre-history ### LeNet-5: updated CNN from 1998 ### Similar ideas, more "modern" terminology
## Modern DL: AlexNet ### Image classification network announced in 2012 ### Five convolutional + three fully-connected layers ### Rectified linear unit (ReLU) activations between layers
## Modern DL: AlexNet ### Won 2012 ImageNet challenge by a 10+% margin: - Learn 1000 object classes - Training set of 1.2M+ images
[ImageNet dataset]
## How AlexNet works ### Convolutional + FC layers extract high-level features ### 1000-way softmax layer performs logistic regression
## Why AlexNet works
### Stacked convolutions extract good visual features ### ImageNet has enough data to train a "deep" network ### GPUs accelerate prototyping
## Image classification pipeline
### Parameterize CNN by `$g_\theta(\mathbf{x}) = \hat{y}$`: - `$\mathbf{x}$`: input image - `$\theta$`: CNN weights + biases - `$\hat{y}$`: estimate of class probabilities
## Image classification pipeline ### Large labeled dataset: `$$ T = \{(\mathbf{x}_1, y_1), \cdots, (\mathbf{x}_k, y_k)\}$$` ### Train via mini-batch SGD: `$$ \theta_{t+1} = \theta_{t+1} - \gamma_t \frac{1}{|B|}\sum_{i \in B} \nabla L(y_i, g(\mathbf{x}_i))$$`
## Deep learning since AlexNet ### "Better" network architectures: - Deeper: VGG, ResNet, Inception - More lightweight: SqueezeNet, MobileNet ### Substantial accuracy improvements
[InceptionV1 architecture]
## Deep learning since AlexNet ### Expanded problem domains: - Object detection, segmentation: SSD, Mask R-CNN - Text processing: RNNs/LSTMs
[SSD and Mask R-CNN]
## Deep learning since AlexNet ### Heuristic tips and tricks: - Transfer learning via pre-trained networks - New optimizers: AdaGrad, Adam, RMSProp - Adversarial training / GaNs
# Closed vs. open set problems
## Closed-set problems ### Static, unambiguous object classes ### Plenty of training data for each class ### Objective is simple: classify, localize, etc. ### ### **Many** real-world problems do not fit this paradigm!
## Open set problems ### Extreme + fine-grained classification: - Thousands or millions of (time-varying) image classes - Classes are variations of similar objects
[Stanford Online Products dataset]
## Open set problems ### Particular object retrieval: - Search image catalog for a query image - Handle never-before-seen queries
[Google Landmarks dataset]
## Open set problems ### Visual complementarity: - Search image catalog for **complementary** items - Fashion, style recommendations
[Polyvore dataset]
## Open set problems ### Why can't we use the standard pipeline? - Tough to retrain model when catalog changes - Often don't even know the object classes - We aren't always classifying
## Metric learning! ### Reminder: standard DL learns features + classifier: - Convolutional + FC layers => high-level features - Softmax layer does logistic regression on features
## Metric learning! ### Query against catalog of image: - Compute CNN features of query image - Inference via k-nearest neighbors
### Only works if we have trained a "good" metric
## Rest of this talk 1. How do we train a deep metric? 2. How does DML work on real data? 3. Where to go for more information?
# Deep metric learning
## Formal definition ### Supervised metric learning: - Input images: `$\mathbf{x} \in \mathbb{R}^n$` - Pairwise labeling: `$y(\mathbf{x}_i, \mathbf{x}_j) \in\{ 0, 1\}$` ### Classification / retrieval: Are `$\mathbf{x}_i$`, `$\mathbf{x}_y$` of the same "thing"? ### Compatibility: Are `$\mathbf{x}_i$`, `$\mathbf{x}_y$` images of compatible things?
## Formal definition ### Deep feature embedding: - `$g_\theta: \mathbb{R}^n \to \mathbb{R}^m$` maps images to features - Network weights `$\theta \in \Theta$` determine embedding
## Formal definition ### Embedding defines a metric over images: `$$d(\mathbf{x}_i, \mathbf{x}_j) = || g(\mathbf{x}_i) - g(\mathbf{x}_j)||$$`, ### where `$|| \cdot ||$` is usually the Euclidean distance
## DML Architecture ### Mapping `$g_\theta(\cdot)$` is usually a CNN ### Usually use last convolutional layer + FC layers
[VGG19 architecture]
## Learning a deep metric
### Training set: `$ T = \{\mathbf{x}_1, \dots, \mathbf{x}_k\} $` - Labeling `$y(\cdot, \cdot)$` for all pairs ### Want a `$g_\theta(\cdot)$` such that: - `$y(\mathbf{x}_i, \mathbf{x}_j) = 1$` implies small `$d(\mathbf{x}_i,\mathbf{x}_j)$` - `$y(\mathbf{x}_i, \mathbf{x}_j) = 0$` implies large `$d(\mathbf{x}_i,\mathbf{x}_j)$` ### What is a good loss function?
## Triplet loss
### Draw **triplets** from the training set: `$(\mathbf{x}^a, \mathbf{x}^p, \mathbf{x}^n)$` - Anchor point `$\mathbf{x}^a$` - Positive example `$\mathbf{x}^p$` with `$y(\mathbf{x}^a, \mathbf{x}^p) = 1$` - Negative example `$\mathbf{x}^n$` with `$y(\mathbf{x}^a, \mathbf{x}^n) = 0$`
### Define the **triplet loss** with margin `$\alpha$`: `$$ L_t(\mathbf{x}^a, \mathbf{x}^p, \mathbf{x}^n) = \max( d(\mathbf{x}^a, \mathbf{x}^p) - d(\mathbf{x}^a, \mathbf{x}^n) + \alpha, 0)$$`
## Triplet loss `$$ L_t(\mathbf{x}^a, \mathbf{x}^p, \mathbf{x}^n) = \max( d(\mathbf{x}^a, \mathbf{x}^p) - d(\mathbf{x}^a, \mathbf{x}^n) + \alpha, 0)$$`
### "Hard" triplet: `$d(\mathbf{x}^a, \mathbf{x}^n) < d(\mathbf{x}^a, \mathbf{x}^p) $`, loss big
## Triplet loss `$$ L_t(\mathbf{x}^a, \mathbf{x}^p, \mathbf{x}^n) = \max( d(\mathbf{x}^a, \mathbf{x}^p) - d(\mathbf{x}^a, \mathbf{x}^n) + \alpha, 0)$$`
### "Semi-hard": `$0 < d(\mathbf{x}^a, \mathbf{x}^p) - d(\mathbf{x}^a, \mathbf{x}^n) < \alpha$`, loss small
## Triplet loss `$$ L_t(\mathbf{x}^a, \mathbf{x}^p, \mathbf{x}^n) = \max( d(\mathbf{x}^a, \mathbf{x}^p) - d(\mathbf{x}^a, \mathbf{x}^n) + \alpha, 0)$$`
### "Easy" triplet: `$ d(\mathbf{x}^a, \mathbf{x}^p) - d(\mathbf{x}^a, \mathbf{x}^n) > \alpha$`, loss zero
## Training for DML ### Organize training set into batches of triples: `$$ B = \{ (\mathbf{x}_1^a, \mathbf{x}_1^p, \mathbf{x}_1^n), \cdots, (\mathbf{x}_b^a, \mathbf{x}_b^p, \mathbf{x}_b^n) \}$$` ### For each batch, take a gradient step w.r.t. the triplet loss: `$$ \theta_{t+1} = \theta_t - \gamma_t\frac{1}{b}\sum_{i=1}^b \nabla_\theta L_t(\mathbf{x}_i^a, \mathbf{x}_i^p, \mathbf{x}_i^n)$$` ### Goal is to make all triplets "easy"
## Convergence challenges ### Randomly generated triplets tend to be "easy" ### Triplet loss is zero, so convergence is slow
## Hard triplet mining ### Idea: find triplets that are **difficult** ### **Offline mining**: when constructing batches, choose triplets `$(\mathbf{x}_i, \mathbf{x}_i^p, \mathbf{x}_i^n)$` with - `$ \mathbf{x}_i^p = \arg\max_{\mathbf{x} \in T} d(\mathbf{x}_i, \mathbf{x}), \quad y = y_i $` - `$ \mathbf{x}_i^n = \arg\min_{\mathbf{x} \in T} d(\mathbf{x}_i, \mathbf{x}), \quad y \neq y_i $` ### Speeds up convergence, but: - Time consuming - Sensitive to label noise
## Semi-hard mining ### Draw random batches of samples, choose any positive example ### Choose a negative example with `$$ 0 < d(\mathbf{x}^a, \mathbf{x}^p) - d(\mathbf{x}^a, \mathbf{x}^n) < \alpha $$` ### Can construct triplets online
# Deep Metric Learning in Action
## Simple example: MNIST
### 28x28 images of handwritten digits ### 60,000 training samples ### Train a deep metric on digits 0-4 - MobileNet backbone - Triplet loss w/ semi-hard mining
## Simple example: MNIST ### Pre-trained features, digits 0-4
## Simple example: MNIST ### Features after one training epoch
## Simple example: MNIST ### Features after five training epochs
## Simple example: MNIST ### Feature embeddings for digits 5-9 ### "Overfits" to the training classes
## Stanford Online Products ### 120k images scraped from eBay listings - 23k unique products ### Split into training/test sets, no overlapping products
## Stanford Online Products ### Partial embeddings trained on InceptionV1:
## Stanford Online Products ### Classification accuracy: - Using triplet loss: ~67% - Advanced DML techniques: 73% ### ### All without having seen any of the test products!
# What else do you need to know?
## What this talk left out ### New + improved loss functions: - Lifted structured loss - n-pairs loss - Angular loss - Proxy neighborhood components ### Consider bigger training tuples, faster convergence
## What this talk left out
### Specalized pooling layers: - Regional maximum of activations (R-MAC), generalized mean (GeM) ### Attention-based local features: - Extract only features relevant to the query
## Want to try it out? ### Full-featured implementation (Target TMs): https://git.target.com/AIComputerVision/deep-metric-learning ### Open source implementation: https://github.com/filipradenovic/cnnimageretrieval-pytorch (PyTorch)
## References 1. LeCun et al., "Backpropagation Applied to Handwritten Zip Code Recognition", 1989 2. LeCun et al., "Gradient-based Learning Applied to Document Recognition", 1998 3. Dalal and Triggs, "Histograms of Oriented Gradients for Human Detection", 2005 4. Krizhevsky et al., "ImageNet Classification with Deep Convolutional Neural Networks", 2012 5. Szegedy et al., "Going Deeper with Convolutions", 2014
6. Simonyan and Zisserman, "Very Deep Convolutional Networks for Large-scale Image Recognition", 2015 7. He et al., "Deep Residual Learning for Image Recognition", 2015 8. Szegedy et al. "Rethinking the Inception Architecture for Computer Vision", 2015 9. Iandola et al. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and 0.5MB model size", 2016 10. Howard et al. "MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications", 2017
11. Liu et al., "SSD: Single Shot MultiBox Detector", 2015 12. He et al., "Mask R-CNN", 2017 13. Duchi et al., "Adaptive Subgradient Methods for Online Learning and Stochastic Optimization" 2011 14. Kingma and Ba, "Adam: A Method for Stochastic Optimization", 2014 15. Goodfellow et al., "Generative Adversarial Networks", 2014
16. Song et al., "Deep Metric Learning via Lifted Structured Feature Embedding", 2015 17. Noh et al., "Large-Scale Image Retrieval with Attentive Deep Local Features", 2018 18. Vasileva et al., "Learning Type-Aware Embeddings for Fashion Compatibility", 2018 19. Schroff et al., "FaceNet: A Unified Embedding for Face Recognition and Clustering", 2015 20. Hermans et al., "In Defense of the Triplet Loss for Person Re-Identification", 2017
21. Sohn, "Improved Deep Metric Learning with Multi-class N-pair Loss Objective", 2016 22. Wang et al., "Deep Metric Learning with Angular Loss", 2017 23. Movshovitz-Attias et al., "No Fuss Distance Metric Learning using Proxies", 2017 24. Tolias el al., "Particular object retrieval with integral max-pooling of CNN activations", 2016 25. Radenovic et al., "Fine-tuning CNN image retrieval with no human annotation", 2018


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The Logger class may be used to instrument an object with logging functionality. Application logging is handled by the Hemi.message.service.sendMessage function, which supports multiple levels of message levels and message scoping.
Utility for instrumenting a logging API into an object. Logging facilities use the Message Service message block format of: ###.#.###.### where the first set identifies the global scope, the second is the level, the third is the inner scope, and the fourth is the fine scope.
See Example Log for an example of implementating the script on a page.
Demonstrate how to use the Logger with an existing object.
// Some JavaScript Objectvar oMyObject = ...;// The '900' block is an arbitrary value of 1 - 999Hemi.util.logger.addLogger(oMyObject, "MyLog","Actions for my object", 900);// Define a function to receive all log messagesoMyObject.HandleMessages = function(sType, oMessage){ var iLevel = oMessage.level; // iLevel == 900 var sMessage = oMessage.message;}// Listen for log messages on the same objectHemi.message.service.subscribe("onsendmessage", oMyObject.HandleMessages);// Test it out, optionally supply a numeric code pair (###.###) to identify message origination.// The entire code for the message would be: 9<IP_ADDRESS>oMyObject.logWarning("Something happened!","100.1");
Instruments the specified logger with a context sensitive logging facility.
void addLogger( oObject, sLogName, sLogDescription, iContextId )
Sends a message in the ###.3 message block. Method is virtual and can be overridden.
void log( sMessage )
Sends a message in the ###.2 message block. Method is virtual and can be overridden.
void logAdvisory( sMessage )
Sends a message in the ###.1 message block. Method is virtual and can be overridden.
void logDebug( sMessage )
Sends a message in the #100.5 message block. Method is virtual and can be overridden.
void logError( sMessage )
Sends a message in the ###.7 message block. Method is virtual and can be overridden.
void logFatal( sMessage )
Sends a message in the ###.4 message block. Method is virtual and can be overridden.
void logWarning( sMessage )
[ Hemi JavaScript Framework - Stephen W. Cote, 2002 - 2013. ]


<EMAIL_ADDRESS><EMAIL_ADDRESS>BrObjectProfiler is a great tool for making code profiling and call time measurements.
There is one global config object (singleton) accessible via br()->profiler()
. You can still create own profiler by $profiler = new BrProfiler();
| Method/property | Description |
|---|---|
If you are using global profiler, please prepend below methods with br()->profiler()-> |
|
| start(operationName) | Start time measurement |
| finish(operationName) | Finish time measurement and return microseconds since operation started $microsconds = br()->profiler()->finish('operation1'); echo('Operation1 took ' . $microseconds . ' msecs')); |
| logStart(operationName) | Same as start() but with writing operation start timestamp into log file. Check BrLog section for details about logging. |
| logFinish(operationName) | Same as finish() but with writing operation duration into log file. Check BrLog section for details about logging. |


Implemented interface member:
property
Runspace
System.Management.Automation.Host.IHostSupportsInteractiveSession.Runspace
2 writes to Runspace
System.Management.Automation (2)
engine\remoting\server\ServerRemoteHost.cs (1)
82
Runspace
= runspace;
engine\remoting\server\ServerRunspacePoolDriver.cs (1)
589
this.ServerRemoteHost.
Runspace
= args.Runspace;
5 references to Runspace
System.Management.Automation (5)
engine\remoting\server\ServerRemoteHost.cs (4)
337
PSEventManager localEventManager =
Runspace
?.Events;
459
if ((
Runspace
== null) || (
Runspace
.Events == null)) { return; }
464
Runspace
.Events.GenerateEvent(
engine\remoting\server\ServerRemotingProtocol2.cs (1)
715
_transportManager, runspaceServerRemoteHost.
Runspace
, runspaceServerRemoteHost as ServerDriverRemoteHost);


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com.pg.bigdata
Object which helps to determine change in file tree and synchronize one with another, if needed


Make sure to check the 'Dictionary' link on the top for the API documentation!
Version 1.0 of cl-gserver
library comes with quite a few new features. One of the major new features is that an actor is not bound to it's own message dispatcher thread. Instead, when an actor-system
is set-up, actors can use a shared pool of message dispatchers which effectively allows to create millions of actors.
It is now possible to create actor hierarchies. An actor can have child actors. An actor now can also 'watch' another actor to get notified about it's termination.
It is also possible to specify timeouts for the ask
and async-ask
functionality.
This new version is closer to Akka (the actor model framework on the JVM) than to GenServer on Erlang. This is because Common Lisp from a runtime perspective is closer to JVM than to Erlang/OTP. Threads in Common Lisp are heavy weight OS threads rather than user-space low weight 'Erlang' threads (I'd like to avoid 'green threads', because threads in Erlang are not really green threads). While on Erlang it is easily possible to spawn millions of processes/threads and so each actor (GenServer) has its own process, this model is not possible when the threads are OS threads, because of OS resource limits. This is the main reason for working with the message dispatcher pool instead.
But let's jump right into it. I'll explain more later.
To use the shared dispatcher pool we have to create an actor-system
first.
(defvar *system* (asys:make-actor-system))
When we eval *system*
in the repl we see a bit of the structure:
#<ACTOR-SYSTEM shared-workers: 4, user actors: 0, internal actors: 0>
So the actor-system
has by default four shared message dispatcher workers. Depending on how busy the system tends to be this default can of course be increased.
Shutting down an actor system may be necessary depending on how it's used. It can be done by:
(ac:shutdown *system*)
This will stop all dispatcher workers and all other actors that have been spawed in the system.
Actors kind of live within an actor-context
. An actor-context
is in fact a Common Lisp protocol that spawns a set of generic functions.
There are two 'things' that host an actor-context
. This is:
actor-system
. Creating actors on the actor-system
will create root actors.actor
. Creating actors on the context of an actor will create a child actor.
Here we now use the actor-context
protocol/api nicknamed ac
.
(ac:actor-of *system* (lambda () (act:make-actor (lambda (self msg state) (let ((output (format nil "Hello ~a" msg))) (format t "~a~%" output) (cons output state))) :name "answerer")))
This creates a root actor on the *system*
. Notice that the actor is not assigned to a variable. It is now registered in the system. The main argument to the actor-of
function is a 'creator-function' which when evaluated returns an actor created with the main actor constructor make-actor
.
make-actor
requires as main parameter a 'behavior' function which should look familiar if you know the previous version of cl-gserver. The parameters to the 'behavior' function are still the tuple of:
self
- the instance of the actormsg
- the received message of when this 'behavior function is calledstate
- the current state of the actor
The return value of the 'behavior' function should also be familiar. It is the cons
with car
being sent back to sender (in case of ask/async-ask) and cdr
that is set as the new current state of the actor.
The function actor-of
still returns the actor as can be seen on the repl when this is executed. So it is of course possible to store the actor in a dynamic or lexical context. However, when the lexical context ends, the actor will still live as part of the actor context.
Here we see a few details of the actor. Among which is the name and also the type of message-box it uses. By default it is a message-box/dp
which is the type of a shared message dispatcher message-box.
#<ACTOR answerer, running: T, state: NIL, message-box: #<MESSAGE-BOX/DP mesgb-9541, processed messages: 0, max-queue-size: 0, queue: #<QUEUE-UNBOUNDED #x3020029918FD>>>
Had we stored the actor to a variable, say *answerer*
we can create a child actor of that by doing:
(ac:actor-of (act:context *answerer*) (lambda () (act:make-actor (lambda (self msg state) (let ((output (format nil "~a" "Hello-child ~a" msg))) (format t "~a~%" output) (cons output state))) :name "child-answerer")))
This will create a new actor on the context of the parent actor. The context is retrieved with (act:context *answerer*)
.
:pinned
vs. :shared
By default an actor, created using actor-of
, uses a :shared
dispatcher type which uses the shared message dispatchers that are setup in the system. It is also possible to create actors with their own dispatcher thread, those are called :pinned
actors. Just provide the :pinned
value to the dispatcher-type
key parameter.
If actors are not directly stored in a dynamic or lexical context they can still be looked up and used. The actor-context
protocol contains a function find-actors
which works like this:
(first (ac:find-actors *system* (lambda (actor) (string= "answerer" (act-cell:name actor)))))
find-actors
takes as first parameter the actor context. This can be either the actor system, or the context of an actor. The second parameter is a test function. This example makes a string comparison on the actor name. So the above function will output:
#<ACTOR answerer, running: T, state: NIL, message-box: #<MESSAGE-BOX/DP mesgb-9687, processed messages: 0, max-queue-size: 0, queue: #<QUEUE-UNBOUNDED #x30200263C95D>>>
This function only does a simple flat search. The functionality of looking up an actor in the system generally will be expanded upon.
Let's send some messages.
tell
is a fire-and-forget kind of send type. It doesn't expect a result in return.
And because of that, and in order to demonstrate it does something, it has to have a side-effect. So it dumps some string to the console using format
, because we couldn't otherwise tell
if the message was received and processed (see the *answerer*
actor definitions above).
CL-USER> (act:tell *answerer* "Foo") T CL-USER> Hello Foo
So we see that tell
returns immediately with T
. But to see the 'Hello Foo' it takes another hit on the return key, because the REPL is not asynchronous.
tell
accepts a 'sender', which has to be an actor. So we can do like this:
CL-USER> (act:tell *child-answerer* "Foo" *answerer*) T CL-USER> Hello-child Foo Hello Hello-child Foo
This sends "Foo" to *child-answerer*
, but *child-answerer*
sends the response to *answerer*
. So we see outputs of both actors.
ask
blocks until the message was processed by the actor. This call returns the car
part of the cons
return of the behavior function.
Insofar an ask
call is more resource intensive than just a tell
.
(act:ask *answerer* "Bar")
Will respond with: 'Hello Bar'
async-ask
combines both ask
and tell
. From ask
it 'inherits' returning a result, even though it's a future result.
Internally it is implemented using tell
. In order to wait for a result a temporary actor is spawned that waits until it receives the result from the actor where the message was sent to. With this received result the future is fulfilled.
So async-ask
is async, it returns immediately with a future
. That future
can be queried until it is fulfilled. Better is though to setup an on-completed
handler function on it.
So we can do:
(future:on-completed (act:async-ask *answerer* "Buzz") (lambda (result) (format t "Received result: ~a~%" result)))
Well, one step at a time:
(act:async-ask *answerer* "Buzz")
Returns with:
#<FUTURE promise: #<PROMISE finished: NIL errored: NIL forward: NIL #x302002EAD6FD>>
Then we can setup a completion handler on the future:
(future:on-completed * (lambda (result) (format t "Received result: ~a~%" result)))
Remember '*' is the last result in the REPL which is the future here.
This will print after a bit:
Hello Buzz Received result: Hello Buzz
A timeout (in seconds) can be specified for both ask
and async-ask
and is done like so:
To demonstrate this we could setup an example 'sleeper' actor:
(ac:actor-of *system* (lambda () (act:make-actor (lambda (self msg state) (sleep 5)))))
If we store this to *sleeper*
and do the following, the ask
will return a handler-error
with an ask-timeout
condition.
(act:ask *sleeper* "Foo" :time-out 2)
(:HANDLER-ERROR . #<CL-GSERVER.UTILS:ASK-TIMEOUT #x30200319F97D>)
This works similar with the async-ask
only that the future will be fulfilled with the handler-error
cons
.
To get a readable error message of the condition we can do:
CL-USER> (format t "~a" (cdr *)) A timeout set to 2 seconds occurred. Cause: #<BORDEAUX-THREADS:TIMEOUT #x302002FAB73D>
An actor can change behavior. The behavior is just a lambda that has to take three parameters:
self
msg
?The behavior then can pattern match (or do some matching by other means) on the received message alone, or in combination with the current state.
The default behavior of the actor is given on actor construction using the default constructor make-actor
.
During the lifetime of an actor the behavior can be changed using become
.
So we remember the *answerer*
which responds with 'Hello Foo' when we send (act:ask *answerer* "Foo")
. We can now change the behavior with:
(act:become *answerer* (lambda (self msg state) (cons (format nil "my new behavior for: ~a" msg) state)))
When we now send (act:ask *answerer* "Foo")
we will get the response: 'my new behavior for: Foo'.
It is still possible to create actors without a system. This is how you do it:
;; make an actor (defvar *my-actor* (act:make-actor (lambda (self msg state) (cons "Foo" state)) :name "Lone-actor")) ;; setup a thread based message box (setf (act-cell:msgbox *my-actor*) (make-instance 'mesgb:message-box/bt))
You have to take care yourself about stopping the actor and freeing resources.
TODO


CAT scans and advanced computing used by Stanford researchers to fight wildfires
CAT scanners, instruments usually used in medicine to get a detailed image of a person's body, have recently been used by Stanford researchers to gain a better understanding on the process of how exactly smoldering works (the state of burning without flame that often leads to fire). They then folded this deeper understanding of burning into computer models to predict where wildfires might strike next. These models could help firefighters allocate precious resources, reduce the loss of property and help save lives, the researchers say.
Seeing inside the material
To the untrained eye, smoldering may appear benign, but it’s
responsible for consuming more than half of the plant matter
burned in wildfires. Smoldering logs can seethe for days and
ignite anew, while glowing embers, carried aloft by hot updrafts,
can transport wildfires to untouched areas in a flash.
“It’s hard to get an accurate understanding of the smoldering
process by looking at the exterior of a log,” said Emeric Boigné,
a graduate student in Ihme’s lab, who developed a new analysis
method using advanced X-ray Computed Tomography (XCT) to study the
smoldering process. XCT is able to penetrate inside dense
materials – just as it does with the human body – to provide
three-dimensional images of wood structures less than a millimeter
in scale as they smolder and eventually catch fire.


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accessed that allows you to decline the use of cookies. To learn more about cookies, please visit http://www.allaboutcookies.org/. If you choose to decline cookies, then some or all of the features,
functionality and promotions available through the Property that may not be available to you.
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If your device stores Flash LSOs, and if you do not want Flash LSOs stored on your device through which you access the Property, you can adjust the
settings of your Flash player to block Flash LSO storage using the tools contained using the Website Storage Settings Panel. You can also
control Flash LSOs by going to the Global Storage Settings Panel and following the
instructions (which may include instructions that explain, for example, how to delete existing Flash LSOs (referred to as “information” on the Macromedia
site), how to prevent Flash LSOs from being placed on your device without you being asked, and (for Flash Player 8 and later) how to block Flash LSOs that
are not being delivered by the operator of the page you are on at the time). Please note that setting the Flash Player to restrict or limit acceptance of
Flash LSOs may reduce or impede the functionality of some Flash applications, including, potentially, Flash applications used in connection with the
Property or our content. We expect our service providers and technology suppliers to honor any decision by you to restrict or limit Flash LSOs, but we
cannot guarantee that they will do so.
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The use of these technologies allows our third-party vendors to deliver advertisements about our products and services, and the products and services of
third parties, when you use the Property or other applications or visit websites or web properties across the Internet. These vendors may place so-called
“pixel tags,” “web beacons,” “clear GIFs” or similar technologies on the device through which you access the Property, and other applications or websites
across the Internet, and also place or recognize third-party cookies when you use the Property, or other applications, websites or web properties. These
vendors may use information about your visits to the Property, and other applications, websites or web properties (excluding your name, address, email
address and telephone number) to provide advertisements for us and others about goods and services that may be of interest to you. If you would like more
information about this practice and to know your choices about not having this information used by these companies, please visit the Network Advertising
Initiative at www.networkadvertising.org or the Digital Advertising Alliance at www.aboutads.info.
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Geographic location information:
If you use any location-enabled products or services, you may be sending us location information. When you use a location-enabled service, we may
collect and process information about your precise geographical location, such as GPS signals sent by a mobile device. We and our third party service
providers and partners may use your device’s physical location to provide you with personalized location-based services, content and advertisements. In
some instances, you may be permitted to allow or deny such uses of your device’s location, but if you choose to deny such uses, we may not be able to
provide you with the applicable personalized services and content.
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From you:
We may collect demographic information, such as your zip code or gender, as well as other information, such as your preferred means of communication,
when you voluntarily provide this information to us. Unless combined with Personal Information, this information does not personally identify you or
any other user of the Properties.
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Information about how you interact on the Properties:
We may collect information about how you interact on the Properties. For example, some Properties may utilize analytic tools to help us better serve
you through improved products, services, and revisions to the Properties. This collected information may let us know which services and features you
are using the most within a Property, as well as device type and hardware features, country and language of download, etc.
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By aggregating information:
We may aggregate Personal Information so that the end-product does not personally identify you or any other user of the Property, for example, by using
Personal Information to calculate the percentage of our users who like a particular artist.
How We May Use and Disclose Other Information
Please note that we may use and disclose Other Information for any purpose, except where we are required to do otherwise under applicable law. If we are
required to treat Other Information as Personal Information under applicable law, then we may use it as described in “How We May Collect Other Information”
section above, as well as for all the purposes for which we use and disclose Personal Information. In some instances, we may combine Other Information with
Personal Information (such as combining your name with your geographical location). If we combine any Other Information with Personal Information, the
combined information will be treated by us as Personal Information as long as it is combined.
SECURITY
We seek to use reasonable physical, technical and administrative measures to protect Personal Information under our control. Unfortunately, no data
transmission over the Internet or data security system can be guaranteed to be 100% secure.
CHOICES AND ACCESS
Your choices regarding our use and disclosure of your Personal Information
We give you many choices regarding our use and disclosure of your Personal Information for marketing purposes. You may opt-out from:
Receiving marketing-related emails from us and our affiliates: If you do not want to receive marketing-related emails from us and our
affiliates on a going-forward basis, you may opt-out from receiving such emails either by using the unsubscribe mechanism provided in the email or by
emailing us at
<EMAIL_ADDRESS>Receiving marketing-related SMS text messages from us and our affiliates: If you do not want to receive marketing-related SMS text
messages from us and our affiliates on a going-forward basis, you may opt-out from receiving such messages by texting back “STOP” or by emailing us at
<EMAIL_ADDRESS>Our sharing of your Personal Information with artists or unaffiliated third parties for their marketing purposes: If you prefer that we
not share your Personal Information on a going-forward basis with artists or unaffiliated third parties for their marketing purposes, you may opt-out from
such sharing by emailing us at
<EMAIL_ADDRESS>In each case, please make clear in your email what you are opting-out from. We will try to comply with your request(s) as soon as reasonably practicable.
Please note that, if you opt-out as described above, we will not be able to remove your Personal Information from the databases of our artists or
unaffiliated third parties with which we have already shared your Personal Information as of the date that we implement your opt-out request. Please also
note that, if you do opt-out from receiving marketing-related messages from us, we may still send administrative messages to you; you cannot opt-out from
receiving administrative messages.
How you can access, change or suppress your Personal Information
If you would like to review, correct, update, suppress, delete or otherwise limit our use of your Personal Information that you have previously provided to
us, you may contact us by emailing us at
<EMAIL_ADDRESS>In your request, please make clear what Personal Information you would like to have changed and what limitations (if any) you would like to place on our
use of your Personal Information. We will try to comply with your request as soon as reasonably practicable. We may need to retain certain information for
recordkeeping purposes, and there may also be residual information that will remain within our databases and other records which will not be removed. We
are not responsible for changing, removing or suppressing information from the databases of artists or unaffiliated third parties with which we have
already shared your Personal Information.
CONTACTING US
If you have any questions about this Privacy Policy, please contact us by email at
<EMAIL_ADDRESS>or
please write to the following address:
Warner Music UK Limited
Legal Department
The Warner Building
27 Wrights Lane
London
W8 5SW
Attn: Privacy Coordinator
Please note that email communications are not always secure, so please do not include credit card information or other sensitive information in your email
messages to us.


Popular Areas in dane county clean swep
Dane County opens new, green recycling center | Madison Commons
Dec 14, 2012 . One part of the new center is occupied by the Dane County Clean Sweep program, which for years has helped residents safely dispose of .
http://www.madisoncommons.org/?q=content/dane-county-opens-new-green-recycling-center
Clean Sweep - Madison / Dane County
Clean Sweep is a recycling and trash disposal alliance between Madison and Dane County. Find information on safe product alternatives, household disposal .
http://www.danecountycleansweep.com/
Dane County Clean Sweep Information - Town of Westport
Clean Sweep Hours: Tuesday, Wednesday, Friday, Saturday 7:30 am - 2:00 pm. May 3 - October 29. Clean Sweep Location: Dane County Highway Garage .
http://www.townofwestport.org/clean_sweep.htm
Clean Sweep closes for year Oct. 31; permanent site coming in 2013 ...
Oct 5, 2012 . Dane County residents only have another 17 days to bring hazardous household waste to the Clean Sweep recycling program, with the site on .
http://host.madison.com/news/local/environment/clean-sweep-closes-for-year-oct-permanent-site-coming-in/article_6895295c-0efd-11e2-9a42-001a4bcf887a.html
2012 Clean Sweep Fact Sheet - Shorewood Hills
2012 Clean Sweep Fact Sheet. Hours: Tuesday through Saturday. 7:00 a.m. 2: 00 p.m.. May 1st through October 31st. Location: Dane County Highway Garage .
http://www.shorewood-hills.org/recycle/clean_sweep_fact_sheet.pdf
Business - Clean Sweep - Madison / Dane County
Business information for Clean Sweep. Find what can be collected, when, and how to transport the waste.
http://www.danecountycleansweep.com/business.aspx
Clean Sweep Household Hazardous Waste Site 2012 Summer
Apr 20, 2012 . The Clean Sweep Program provides an opportunity for residents of Dane County to safely dispose of household hazardous materials, free of .
http://www.cityofmadison.com/news/view.cfm?news_id=3170


Planter
How to plant a tree?
Info on how to do it
- Rules & Code of Conduct
- Regulations
- Where to get the seedlings
- Crash course on how to plant a tree (e.g. youtube video)
- Where to get (professional) help
Planting Locations
Locations where you can plant trees
- Location
- Type of allowed trees
- Max. tree dimensions
- Planting hours
- Number of spots left
- Hotspots / where other members are planning to plant
Planting Events
The next events where I can participate


Lindsey & Rodrigo
Mr. and Mrs. Richard Luedtke
are proud to announce
the Nuptial Mass uniting their daughter
Dr. Lindsey Kristine
and
Mr. Rodrigo José Múnera
son of Mr. and Mrs. Diego Múnera
in the sacrament of Holy Matrimony
Saturday, the twenty-ninth of October
two thousand and eleven
In the fall of 2009, Rodrigo and Lindsey met through Match.com and had their first date at Ella's Wood-Fired Pizza. Rodrigo often comments on the way Lindsey hugged him at the end of that night - shoulder scrunched in a tight embrace. She recalls how attentive, charming, and communicative he was. It wasn't but a few days until the next date and the rest of their lives together.
It is easiest to fly into Regan International (DCA) in Washington DC, the airport is connected to DC's Metrorail. Other options are Dulles International airport (IAD) and Baltimore Washington International (BWI). Taxi service from these other airports to DC will cost around $50
20 rooms available at the JW Marriott Washington, DC at $199 at night. The bride and groom will stay at this hotel before the wedding.
Phone: 1-800-393-2503
Website: JW Marriott Washington, DC
10 rooms available at the Embassy Suites Washington DC at $179 at night for a standard king and $199 a night for two double beds.
Phone: 1-800-HILTONS
Website: Embassy Suites Washington DC
To receive these special room rates, please let the reservations specialist know you are with the Luedtke/Munera Wedding Party. The special rate is for Oct. 28-30 but if you wish to stay longer ask the reservations specialist and they may extend the rate past the set days.
A bus tour of Washington DC will be offered to all guests after the wedding ceremony at St. Patrick's church. Guests are welcome to join the tour for free. The tour concludes at the historic Hay-Adams Hotel. Cocktails begin at 5 p.m. at The Hay-Adams Hotel on the first floor. The reception dinner will follow on the Top of The Hay at the Hay-Adams Hotel.