text:
Member retention often focuses on the member experience, journey, and communications. But a significant contributing factor to the poor member retention in the fitness industry is poor staff retention.
By working on staff pathways, motivation and benefits, we
see more engaged staff, which has a direct positive effect on the member
experience. Put simply, if you improve your staff retention, you will also
improve member retention.
At GGFit, we spend a lot of time defining the member journey with clubs, looking at key contact points and measures to maximise member engagement. We've recently been working with clients on staff pathways to help manage the process of recruiting and retaining good fitness instructors and other key staff.
Your staff pathways need to be clearly defined and available for new recruits to review before their interview. Including references to staff pathway in your job advertisements will even help to get more, and better applicants.
Examples of fitness instructor pathways could include group exercise, exercise referral, personal training, and management. Each will come with a timeline, training plan, skills matrix and support network. Staff could focus on one or more concurrently, depending on aptitude or club requirements. Discussing the staff pathways should be a key part of the interview, and could even help with candidate selection or job acceptance. For example, you might choose not to recruit a candidate if they want to follow the management route when you already have 5 staff members on that pathway.
In summary, define your staff pathways, and get your new and existing staff members onto them. This will enable you and your staff to measure their progress and development, and discuss in performance reviews and appraisals, leading to a more engaged team.


text:
ORM with Metastorage - Printable Version
+- CodeIgniter Forums (https://forum.codeigniter.com)
+-- Forum: Archived Discussions (https://forum.codeigniter.com/forum-20.html)
+--- Forum: Archived Development & Programming (https://forum.codeigniter.com/forum-23.html)
+--- Thread: ORM with Metastorage (/thread-12198.html)
ORM with Metastorage - El Forum - 10-09-2008
[eluser]Colin Williams[/eluser]
I just caught a good article on PHPClasses about ORM, and a new solution called Metastorage, described as an "object persistence API generator." Being a code generation tool, I imagine integration with CI would be fairly simple, since all you need to do is load the proper files that Metastorage generates sometime during execution in your CI app (don't see why they couldn't be models, in fact).
The article serves as a good primer to ORM, and can be found at [url="http://www.phpclasses.org/blog/post/82-PHP-ObjectRelational-Mapping-ORM-or-ROM.html"]http://www.phpclasses.org/blog/post/82-PHP-ObjectRelational-Mapping-ORM-or-ROM.html[/url]
Metastorage is at [url="http://www.meta-language.net/metastorage.html"]http://www.meta-language.net/metastorage.html[/url]
Just wanted to share for those of you looking for ORM solutions.

subset: commoncrawl


text:
White Fence
|Founding location
|Boyle Heights, Los Angeles, California, United States
|Years active
|1910s – Present
|Mexican Mafia, other Sureños subsets
White Fence (also known by the acronym WF[6][7]) is a predominantly Mexican American street gang in the Boyle Heights neighborhood of East Los Angeles.
White Fence is the oldest gang in Los Angeles. The gang itself claims its history goes back as far as 1900,[8] although the gang did not emerge until the 1910s in the form of the all-male sports team associated with the La Purissima Church.[1][2][3][4][5] The group was originally referred to as La Purissima Crowd, but gradually changed its name to White Fence, after the white picket fence that surrounded La Purissima Church. The gang's name has also been interpreted as a "symbolic barrier" between the white residents in the area and the Hispanic residents of the neighborhood, at a time when racism plagued the area. During the 1950s and 1960s, White Fence was considered one of the "most violent and powerful gangs in East Los Angeles."[9][8] The rivalry between the gang and another Hispanic gang, El Hoyo Maravilla, is one of the longest, ongoing feuds in all of Los Angeles, a rivalry going back to the 1930s.[8][10] White Fence was the first gang in East Los Angeles to use firearms, chains and other dangerous weapons.[11]
White Fence is an old established gang territory in Boyle Heights adjoined to East Los Angeles.[3][12][self-published source]
- ^ a b Shelden, Randall G.; Tracy, Sharon K.; Brown, William B. (2001). Youth gangs in American Society (2nd ed.). Belmont, CA: Wadsworth Thomson Learning. pp. 43–44. ISBN 9780534527457.
- ^ a b Hohm, Charles F.; Glynn, James A., eds. (2002). California's Social Problems (2nd ed.). Thousand Oaks, CA: Pine Forge Press. pp. 44–45. ISBN 9780761987130.
- ^ a b c Moore, Joan W. (1991). Going Down to the Barrio: Homeboys and Homegirls in Change. Philadelphia: Temple University Press. pp. 1–181. ISBN 9781439903940.
- ^ a b "White Fence | Street Gangs Resource Center". streetgangs.com. 2012. Retrieved January 26, 2012.
- ^ a b Spergel, Irving A. (1995). The Youth Gang Problem: A Community Approach. New York: Oxford University Press. p. 155. ISBN 9780195092035.
- ^ Bag, Alice (2011). Violence Girl: East L.A. Rage to Hollywood Stage, a Chicana Punk Story. Port Townsend, WA: Feral House. p. 66.
- ^ "U.S. gang acronyms and abbreviations". accuracyproject.org. September 12, 2012.
- ^ a b c Blatchford, Chris (2008). The Black Hand: The Bloody Rise and Redemption of "Boxer" Enriquez, a Mexican Mob Killer. HarperCollins. p. 102.
- ^ Rosen, Fred (2005). Historical Analysis of American Crime. New York, NY: Facts on File Inc. pp. 235–237.
- ^ Vinson, J.; Crame, J.; Von Seeburg, K. "Rocky Mountain Information Network, (2008). Surenos" (PDF).
- ^ Mazón, Mauricio (1984). The Zoot-Suit Riots: The Psychology of Symbolic Annihilation. Austin, TX: University of Texas Press. p. 5.
- ^ Griñie, Gilbert M. (2008). The Way Out: A Historical Perspective on Gangs. Bloomington, IN: Xlibris Corporation. p. 20.


text:
HistoryCaptain Barracuda was a modern day pirate who tried to board a city cuise ship, that had Iceman, the Human Torch and Dorrie Evans as its passengers. He was defeated by the two heroes and arrested after he crashed his ship into an iceberg created by the Iceman[1].
He reappeared later, capturing Namor the Submariner and Karthon the Quester who were fighting for the Serpent Crown. Barracuda took the crown for himself, but was again defeated when he stole a sonic device that attracted a torpedo into his own ship.
He survived and has since clashed with both the Fantastic Four (when he stole the horn which the Sub-Mariner used to control sea monsters and used it to attack New York)[2] and the Hulk. More recently, he was seen again, only to be defeated this time by Hawkeye and Deadpool.[3]
Powers and Abilities
|Power Grid [5]
|Energy Projection
|Fighting Skills
He is a skilled leader, a proficient thief and talented in both conventional and advanced firearms. He is also an expert seaman and commandeered two submarines armed with many high-tech weapons.
Since he can only see with one eye, his depth perception is greatly hindered.
The first submarine he commandeered had an electrified metallic net to ensnare prey, a cannon which fired an inertia-ray strong enough to down an American bomber by instantly ceasing its forward motion, and had one torpedo fitted with an atomic warhead as well as explosive shells. The second submarine, stolen from Captain Omen, could fire explosive shells too. Besides, Barracuda usurped control of Omen's former base complete with its own power plant, laboratory and mini-sub. He had possession of an omni-directional beam also known as the Sonic Magno-Directoid which was a military device that could control the course of underwater weapons, and a machine which was intended to stimulate cell growth using a gamma-ray power source to generate neurogenic rays, making wounds heal faster, but when its power source fused several circuits together, the machine instead rearranged cells, devolving human beings into ape-like beasts. He also possessed legendary relics like the Horn of Proteus which could summon and command sea creatures, and the Glove of Asteria which was able to direct a destructive column of air moving at nearly light speed.
Links and References
- 12 Appearances of Captain Barracuda (Earth-616)
- Minor Appearances of Captain Barracuda (Earth-616)
- Media Captain Barracuda (Earth-616) was Mentioned in
- 2 Images featuring Captain Barracuda (Earth-616)
- Quotations by or about Captain Barracuda (Earth-616)
- Character Gallery: Captain Barracuda (Earth-616)
- http://www.marvunapp.com/Appendix/capbar.htm
Discover and Discuss
- Search this site for: Captain Barracuda · Captain Barracuda (Earth-616)
|Like this? Let us know!


text:
Fly Free Zone Natural Fly Repellent Dog Collar – Flea and Tick Prevention for Cats,Flea Control for Cats-Prevents,Repels Fleas,Ticks And Lice Waterproof and Adjustable Cat Flea and Tick Control for 8 Month Protection(New Version) – Product Information
- Product Dimensions: 25 x 0.4 x 0.2
- Inches: 1.28 ounces
- Shipping Weight: 2.2 ounces
Tick Control
Tick Control – The worms live in the heart just when the pet is significantly infest with the bloodsucker. Lungs. Kidney and liver can additionally damag by heartworm disease. You can picture just how much damages can done by the lengthy thread-like worms liv inside your pet.
Insects spread heartworms from an infect pet to a new host. The insects attracts larva circulat in the blood when he bites an infect dog. The heartworm grows to the larval stage inside the insect in the next two weeks. Now the disease is infectious and the bite of the mosquitoes transfers the problem to various other dogs.
Preferr heartworm mications:
Iverhart and also
This is a prescription micine generally offer as pork liver flavor chewable tablets. The basic dosage of iverhart and also for canines consider around 25 pounds is 68mcg/57mg. For canines in tween 26-50 pounds. The suitable dose is 136mcg/114mg. And for pet dogs evaluat tween 51-100 extra pounds. The dose is 272mcg/227mg. Pets weigh greater than 100 pounds require a mixture of iverhart plus pills.
Usually. Vets ask pet proprietors to give iverhart plus as soon as monthly to prevent the condition of heartworm in canines. This heartworm micine likewise avoids roundworm and also hookworm in dogs. An important point you require to seek advice from vets is a feasible allergic reaction dogs may have. To this drug.
This is a prescription heartworm micine readily available as unflavor pills.The usual dose of heartgard for canines consider around 25 extra pounds is 68mcg and 136 mcg for dogs weigh tween 26-50 extra pounds. As well as finally for dogs weigh in tween 51-100 pounds it is 272 mcg.


text:
Human immunodeficiency virus type 1 (HIV-1) integrase inhibitors are in clinical trials, and raltegravir and elvitegravir are likely to be the first licensed drugs of this novel class of HIV antivirals. Understanding resistance to these inhibitors is important to maximize their efficacy. It has been shown that natural variation and covariation provide valuable insights into the development of resistance for established HIV inhibitors. Therefore, we have undertaken a study to fully characterize natural polymorphisms and amino acid covariation within an inhibitor-naïve sequence set spanning all defined HIV-1 subtypes. Inter- and intrasubtype variation was greatest in a 50-amino-acid segment of HIV-1 integrase incorporating the catalytic aspartic acid codon 116, suggesting that polymorphisms affect inhibitor binding and pathways to resistance. The critical mutations that determine the resistance pathways to raltegravir and elvitegravir (N155H, Q148K/R/H, and E92Q) were either rare or absent from the 1,165-sequence data set. However, 25 out of 41 mutations associated with integrase inhibitor resistance were present. These mutations were not subtype associated and were more prevalent in the subtypes that had been sampled frequently within the database. A novel modification of the Jaccard index was used to analyze amino acid covariation within HIV-1 integrase. A network of 10 covarying resistance-associated mutations was elucidated, along with a further 15 previously undescribed mutations that covaried with at least two of the resistance positions. The validation of covariation as a predictive tool will be dependent on monitoring the evolution of HIV-1 integrase under drug selection pressure.
Antiviral therapy has been highly successful in managing human immunodeficiency virus type 1 (HIV-1) infections in individuals who have access to treatment. Current HIV-1 inhibitors target the reverse transcriptase and protease enzymes, as well as the fusion of virus to host cells. To date, there are 22 inhibitors of HIV-1 licensed for use within the clinical setting (30); however, the high mutation rate of HIV-1 (27) drives extensive natural polymorphism and provides a mechanism that allows resistance to develop to all inhibitors (25, 32). As a consequence of HIV-1 drug resistance, there is an ongoing need to generate new inhibitors of HIV both to existing and novel targets.
One such target, HIV-1 integrase, mediates the integration of the reverse-transcribed HIV-1 DNA into the host cell genome and has long been an attractive target for inhibition, as this process is critical within the retroviral life cycle (17). There is the potential to inhibit a number of steps within the HIV-1 life cycle that involve integrase (18); however, the most intensely studied compounds inhibit the strand transfer of the proviral DNA into the host genome (strand transfer inhibitors [STIs]) (12).
HIV-1 integrase comprises a three-domain monomer (5, 6) and a multimeric quaternary structure. The N-terminal domain (codons 1 to 50) is alpha-helical, binds zinc, and is important for protein stability. The peptide chain that links this domain to the catalytic core may be structurally disordered and has not been resolved by X-ray crystallography. The catalytic core domain (codons 51 to 211) forms a two-layer alpha-beta sandwich and contains the active-site triad of residues (Asp 64, Asp 112, and Glu 152) that coordinates magnesium ion binding and the catalysis of the strand transfer process (16). In silico studies have suggested that STIs prevent integrase activity by binding to the active site via the magnesium ion (29). The C-terminal domain (codons 212 to 288) forms an all-beta-sheet SH3 domain that binds DNA in a nonspecific manner (21). The quaternary structure of HIV-1 integrase has not been resolved; however, crystallography and modeling studies have proposed that integrase forms a tetrameric structure (33). This tetrameric model contains two exposed active-site triads and allows for interactions between the three monomeric domains on different chains.
The development of inhibitors that are active against integrase has been slow due to a lack of effective screening methodologies and suitable lead compounds with low toxicity. Nevertheless, two compounds are in advanced stages of clinical evaluation (raltegravir [MK-0518], phase III, and elvitegravir [GS-9317], phase II). As with all other classes of HIV-1 inhibitors, determining and predicting resistance to these compounds will be critical to their effective use in the clinical setting (3, 9). Data from clinical trials and the in vitro passage of HIV-1 in the presence of both lead inhibitors and related compounds has generated an extensive list of mutations that modulate the sensitivity of HIV-1 to these compounds (Table 1). Resistance data from clinical trials has shown that there are two distinct resistance pathways to raltegravir, which are determined by the presence of either the N155S mutation or the Q148K/R/H mutation (13). Depending on which of these mutations develops initially, the accessory mutations that confer high-level resistance will differ. Both of these resistance pathways also confer high-level resistance to elvitegravir (22), even though clinical trial data and in vitro analysis show that alternative mutations also can cause resistance to this inhibitor.
Because the approval of HIV-1 integrase inhibitors for clinical usage is imminent, we sought to examine the natural polymorphisms within a set of 1,250 integrase inhibitor-naïve sequences (20). We have assessed the extent to which the frequency of integrase inhibitor-associated mutations impact upon the antiviral efficacy and emergence of resistance for this class of compounds. In order to identify mutations potentially associated with resistance, we also have assessed amino acid covariation within HIV-1 integrase sequences.
Sequences.A total of 1,250 full-length HIV-1 genomes were retrieved from the HIV sequence database (20). The HIV-1 protease, reverse transcriptase, and integrase coding regions were extracted from the full-length genome sequences using a local alignment algorithm (Matcher-Emboss [24]) and aligned using ClustalW (31). Protease and reverse transcriptase sequences were used to verify the subtype annotation (using STAR [23]) provided by the database, and integrase sequences were used for subsequent analysis. The 1,250 integrase coding sequences subsequently were filtered for redundancy at 100% sequence identity, resulting in a nonredundant sequence set of 1,165. This sequence set contained 274 ambiguous nucleotides (0.24 per sequence) and 125 ambiguous amino acids (0.11 per sequence). Ambiguous amino acids were assigned (letter X) only when multiple amino acids were possible at the same codon, and these positions were considered mutations from the wild-type sequence. Ambiguous nucleotides were included in the subtype diversity analysis, but ambiguous amino acids were excluded from the analysis of the frequency of amino acids associated with resistance to integrase inhibitors.
Subtype diversity.A multiple alignment of 1,165 HIV-1 integrase sequences (amino acids 1 to 288) was generated, and this alignment was subdivided into smaller alignments representing the defined HIV-1 subtypes and groups (28) (number of sequences per subtype: subtype A, 165; CRF_01, 58; CRF_02, 43; B, 189; C, 391; D, 41; F, 10; G, 14; H, 3; J, 2; K, 1; N, 5; and O, 21). Sequences were assigned to a subtype alignment in which the Los Alamos database subtype assignation (based on the 9-kb HIV genome) agreed with the STAR subtype designation. A total of 222 sequences were not assigned to the subtypes or groups listed above, usually because the subtype predicted along the length of the genome was recombinant. In many cases, the published recombinant architecture and STAR subtype prediction both indicated that a sequence was not recombinant within the integrase coding region. However, it was decided that a conservative assignment of subtype would minimize errors during downstream analysis.
Subtype-specific multiple alignments were converted into simple position-specific scoring matrices (PSSMs), where the frequency of an amino acid at each position within the alignment was scored. Relative subtype diversity was calculated for each subtype relative to the subtype B PSSM using the L1 norm metric. The amino acid residue frequency at each position within the subtype B PSSM was subtracted from the frequency of the equivalent amino acid and position for each of the other HIV-1 subtypes. The absolute values from this subtraction then were summed. Thus, for instances of a position within integrase where the subtype B PSSM and a non-subtype B PSSM contained differing amino acids with no variation at that position, the score returned was maximal (2). Division by two of the summed absolute values and conversion to a percentage represented a measure of the diversity between a position within two subtype PSSMs. These diversity measures were averaged over a sliding window of 20 amino acids with a step interval of 10.
Frequency analysis.Data from in vitro and clinical resistance studies on integrase inhibitors were collated from the scientific literature (Table 1) (1, 4, 7, 8, 11, 13, 19, 22). The frequency of resistance-associated mutations was calculated for each subtype using the subtype PSSMs described above.
Covariation analysis.Covariation analysis was performed on three independent data sets comprised of subtype A (n = 165), subtype B (n = 189), and subtype C (n = 391). Amino acid positions containing greater than 2% variation from subtype consensus sequences were included in the covariation analysis. Covariation analysis was performed using the Jaccard index (J) (equation 1), where NXY is the number of sequences containing mutations at amino acid positions X and Y and NX0 and N0Y are the number of sequences with a mutation at position X or Y alone. The Jaccard index for each mutational pair was converted into a Z score by a comparison of observed data to a random model (equation 2) (26). The random model (RJ) was calculated by simulating 10,000 sequences using the distribution of amino acids observed at each position within the subtype alignments. For each simulated sequence, amino acids at each position were drawn from the multinomial distribution according to the frequencies at which each amino acid was found in the data sets. The standard deviation of the Jaccard index was calculated for each pair of covarying amino acids using a leave-one-out analysis of sequences containing that amino acid pair. (1) (2) To compensate for the phylogenetic relatedness of sequences containing covarying amino acid positions, the Z score was weighted using a sequence distance measure (D) (equation 3). The average pairwise distance between sequences containing a pair of mutations (NXY), calculated using a BLOSUM62 matrix, was used as a measure of phylogenetic relatedness. This value subsequently was scaled between 0 and 1 using the maximal pairwise distance [max(data set)] between all sequences in a data set (subtype A, B, or C). (3) The distance scaling factor (D) was used to modify the Jaccard index and the calculation of Z scores (ZD) for an observed covarying amino acid pair (equation 4). The distance scaling factor used to modify the Jaccard index of the random model (RD) was estimated using the average D of sequences containing covarying amino acids within 10,000 random sequences, generated 30 times. (4) P values were estimated from the Z scores and subsequently corrected for multiple testing using a false discovery rate (FDR) (14) set to P = 0.001.
Amino acid variation within HIV-1 integrase was consistent with that observed within the whole of the HIV-1 pol gene. Group M subtypes contained approximately 5% average intrasubtype variation and 7 to 8% average intersubtype variation. Group M varied by approximately 11% from group N and 18% from group O. Integrase amino acid variation was not homogenous along the length of the coding region and occurred within each of the three domains within HIV-1 integrase (Fig. 1). Subtypes CRF_01, K, and H showed the greatest diversity from the subtype B PSSM within the N-terminal domain (codons 1 to 50). Subtypes CRF_02, F, G, K, and H varied relative to subtype B, in both the alpha-helical linker and the small DNA binding motif within the C-terminal domain (codons 212 to 288). The greatest inter- and intrasubtype variation was found within the catalytic domain of integrase (codons 51 to 211) and specifically was located between amino acids 90 and 150. Subtypes CRF_01, CRF_02, and A diverged from subtype B by as much as 40% around amino acid position 130. The variable region of the catalytic domain encompassed one of the catalytic amino acids (Asp 116) that is required for enzyme activity and targeted by STIs. Variation around the active and inhibitor binding site suggests that the efficacy of STIs or the genetic barrier to resistance is influenced by virus subtype.
An analysis of the frequency of the occurrence of polymorphisms associated with resistance to HIV-1 integrase inhibitors (Table 1) showed that mutations V72I and V201I were extremely prevalent across all subtypes and occur in 80 and 46% of these 1,165 sequences, respectively (Fig. 2a). Other mutations, such as V74I/M, T97A, M154I, V165I, and T206S, occur with a frequency of greater than 12% in certain subtypes. Overall, 25 out of 41 integrase resistance mutations were detected within 1,165 inhibitor-naïve sequences spanning all HIV-1 subtypes. The resistance-associated mutations that occurred as natural polymorphisms within the Los Alamos database tended to occur within the most populated subtypes (CRF_01, CRF_02, A, B, C, D, F, and G). It was impossible to say whether the observed relative absence of resistance mutations in subtypes H, J, K, and N was due to the small numbers of sequences from these subtypes, such that the genetic diversity of these subtypes was not represented, or because of some inherent biological constraint. All of the inhibitors and pathways to resistance described previously include mutations that were present within a broad-spectrum inhibitor-naïve population (Fig. 2b). However, the key mutations ascribed to resistance (where these are known) were rare; thus, key mutations specific for resistance to raltegravir were found only in the subtype B sequence set, which contained one N155H and three G140S/A polymorphisms. Similarly, the key mutations specific for resistance to elvitegravir were either not detected or detected at very low frequency: H51Y, one subtype A sequence; S147G, three subtype CRF_01 and C sequences; and E157Q, eight subtype CRF_02, A, B, C, and D sequences.
In order to utilize HIV-1 sequence data prospectively rather than purely retrospectively, amino acid covariation analysis was performed to determine whether resistance-associated mutations covaried within inhibitor-naïve sequence sets. Covariation analysis has been used extensively to determine sequence-based interactions between HIV-1 drug resistance mutations in the protease and reverse transcriptase enzymes (2, 14, 34) and to infer mechanistic interactions between amino acids in the V3 loop region of gp120 (15). The absence of drug selection pressure on the integrase sequences used within this study conferred an established problem with the determination of amino acid covariation (10); namely, that covariation could be observed as a function of mechanistic interactions between specific amino acids or as a function of the evolutionary relationships between sequences. Without drug selection pressure, some of the observed polymorphisms may confer a selective advantage, but it is unclear what generates that selection pressure. It is conceivable that there are natural inhibitors of integrase or that the inhibition of HIV by inhibitors targeted to other enzymes indirectly alter the selection pressure applied to the integrase coding region. We hypothesize that pairs of mutations in sequences that cluster within a phylogeny are more likely to be mutations that have been fixed within specific clusters by chance. Conversely, pairs of mutations that are present in sequences distributed across a phylogeny may represent multiple mutation and selection events at these positions. In the latter case, amino acid covariation is more likely to represent functional interactions between these residues rather than evolutionary patterns. For this reason, the detection of covariation was weighted toward sequences that did not cluster within a phylogeny.
Covarying mutations at codons 72 and 201 were present in 27 subtype B sequences, and those sequences had an average overall distance (D) of 0.39 (Fig. 3a). Mutations at codons 154 and 201 co-occurred in 23 sequences, with an overall distance of 0.15, which was lower because all except three of the sequences containing these mutations were present within a single cluster (Fig. 3b). The distribution of the 154 and 201 mutations within a sample of the random sequence phylogeny (1,000 sequences from a total random population of 10,000) did not show any clustering (Fig. 3c). To improve the stability of the prediction model, the distance between sequences containing covarying amino acids within the random model (RD; see Materials and Methods) was estimated using 10 iterations of 10,000 random sequences per subtype. On the basis of this analysis, the RD was fixed at 0.43 for all covarying pairs of amino acids using sequences from subtypes A, B, and C (average RD for subtype A, 0.44 [standard deviation, 0.034]; average RD for subtype B, 0.43 [standard deviation, 0.041]; and average RD for subtype C, 0.42 [standard deviation, 0.042]).
As the distance between sequences within the data model (D) usually was lower than the random model distance (RD), Z scores calculated with the incorporation of the distance model (ZD) were lower than those where this model was not used (Z) (Fig. 4a). The incorporation of the distance correction factor resulted in the exclusion of 75.3% of the amino acid pairs predicted as covarying significantly using the FDR and a P value of less than 0.001. A comparison between the weighted (ZD) and unweighted (Z) scores suggested that the weighted score was more sensitive to convergence between sequences and that HIV-1 integrase showed evidence of convergence. Simulations of six sets of 1,000 sequences, constrained such that the distance scaling factor D was fixed within the ranges of 0.1 to 0.3 (most similar, least convergent) to 0.6 to 0.8 (most dissimilar, more convergent), with each bin range increasing by 0.1, were generated, and the relationships between ZD and Z were plotted. A binomial curve was fitted to each of the scatterplot series, with correlation values ranging between 0.51 (D, 0.1 to 0.3) and 0.84 (D, 0.3 to 0.5). The lowest correlation coefficients were obtained where D was constrained at the highest and lowest ends of the constraint scale. The data from the simulated data was limited to the range of Z and ZD values observed using the subtype B integrase sequences, and these data and a fitted curve also were presented (r2 = 0.63) (Fig. 4b). As expected, the analysis of weighted and unweighted Z scores, where the distance scaling factor was constrained to a score similar to that used within the random model (D, 0.43), produced a linear relationship. Covariation between sequences constrained to have a high distance scaling factor, indicative of convergence, produced shallow curves that reached a Z score plateau with an increasing ZD score. While the line generated by observed subtype B data is elevated from the highly convergent simulated sequences, the shape of the curve suggests that the observed data shows a level of sequence convergence at high ZD scores. The minimum ZD scores required to give a significant estimated FDR-corrected probability across a range of P values were calculated for each of the six simulated data sets (Fig. 4c). The data set for which D was constrained between 0.1 and 0.3 resulted in the highest ZD scores across the range of P values, and the data set for which D was constrained between 0.6 and 0.8 required the lowest ZD scores to achieve significance. The P value cutoff used to analyze the HIV-1 subtype data sets was 0.001. In all cases, the minimum ZD score used to assign significance to an instance of covariation in the observed data sets was higher than the minimum ZD scores generated by the simulations.
The detection of covarying amino acid pairs within HIV-1 integrase was performed independently on sequences from subtypes A (n = 165), B (n = 189), and C (n = 391). Collectively, 108 amino acid positions were detected as covarying; however, only 16 positions (14.8%) covaried in all three subtypes. There was extensive overlap in covariation between subtypes A/B and A/C (20 and 12 positions, respectively), while subtypes B and C shared only two positions that covaried. In addition, each subtype contained a number of unique covarying amino acid positions (A, 24; B, 31; and C, 3). Position 201 exhibited the most covarying partners, though many other positions were detected frequently. Thirteen out of the 29 resistance-associated amino acid positions (Table 1) were shown to covary, with positions 72, 74, 125, 156, 167, and 206 detected most frequently. Ten of the 13 resistance-associated amino acid positions that were detected as covarying could be linked to form an ad hoc network of positions that varied together (Fig. 5). This ad hoc network was further expanded to include amino acid positions that linked multiple resistance-associated nodes. The addition of amino acid positions that had not previously been implicated in HIV integrase resistance enabled the inclusion of position 203 within the network.
Subtype-dependent sequence variation was observed in all three structural domains of HIV-1 integrase. The alpha-helical N-terminal domain showed the greatest variation on the side of the bundle that interacts with the N-terminal domain from an adjacent integrase chain rather than the side that interacts with the catalytic core (Fig. 6). The C-terminal SH3-like domain (21) was more conserved than the extended alpha-helical strand linking it to the catalytic domain. The catalytic domain was highly variable between amino acids 110 and 145, with additional variation in subtype J between positions 90 and 110. Structurally, this region encompasses a strand of alpha-helix and a poorly resolved or disordered fragment that leads into the active-site residue at glutamine 152. Sequence variation within HIV-1 integrase may be constrained by the maintenance of both the active site and its macromolecular structure. It has been proposed that integrase forms a dimer structure that in turn dimerizes to form a tetramer comprised of four chains of HIV-1 integrase (Fig. 6) (33). This tetrameric structure allows direct interactions between N-terminal, C-terminal, and catalytic domains on different chains. The conserved regions of the catalytic domain form an alpha-helix loop alpha-helix (residues 145 to 185) between the N-terminal domain and another conserved antiparallel beta-sheet region (residues 50 to 90). These regions crucially contain two of the active-site amino acids that coordinate magnesium ion binding and many of the integrase inhibitor resistance mutations. Changes in these regions consequently may affect both the activity of the enzyme and interactions with the zinc ion binding N-terminal domain.
Notably, the major mutations associated with pathways to resistance for either raltegravir or elvitegravir (N155H, Q148K/R/H, and E92Q [Table 1]) were not present in the inhibitor-naïve sequence population. However, many of the other mutations associated with these resistance pathways were present, suggesting that the rate at which resistance develops is affected by the baseline genotype. There was no obvious relationship between the subtype and the frequency of occurrence of polymorphisms, other than a slight increase for the more frequently sampled subtypes.
An analysis of pairwise amino acid covariation was performed in an attempt to use sequence analysis prospectively to determine whether resistance-associated polymorphisms covaried and whether there were any previously unidentified positions that covaried with these resistance positions. In order to prevent bias toward the detection of phylogenetically related amino acid pairs, a novel modification of the Jaccard index (26) was implemented. The software generated to perform the covariation analysis takes a multiple-sequence alignment and an optional mutation list as its input and therefore is applicable to a wide range of HIV or other protein sequence data sets. The program was written in Perl and is available on request from the authors.
The covariation analysis performed in this work is a prediction; therefore, in principal, it would have been beneficial to perform a receiver operating characteristic (ROC) curve analysis of the sensitivity and specificity of the modified Jaccard index algorithm. While simulating sequences that encompass a range of Jaccard indices and variable distance values is trivial, defining a set of true-positive and true-negative covarying pairs of amino acids from such a simulated data set is either arbitrary or circular. The frequency with which a pair of simulated covarying amino acids occur together within sequences or the Jaccard index (which is simply derived from the initial frequency) will lead to an arbitrary assignment of true-positive or true-negative covariation for that pair. Any derivation of the ROC using this arbitrary assignment method would be meaningless, especially when the error model was incorporated. The inherent error model within this covariation analysis method (26) compares the Jaccard index derived from a real data set to that derived from a simulated random data set and estimates a probability that a pair of observed amino acids covary to a greater extent than would be expected based on a random model. Using the estimated probability of pairs derived from a simulated data set to assign true-positive or true-negative status to a pair of covarying amino acids would be circular, in that both assignment and ROC curve analyses would be performed using the same score and, consequently, the method would appear to perform perfectly. For these reasons, ROC curve validation was omitted from this analysis and is not generally performed during analyses of covariation. Simulations of the effect of varying the distance score that was incorporated into the probability estimated from the Jaccard index were included, and these suggested that the evolution of the HIV integrase coding region showed signs of convergence due to the repeated observation of pairs of covarying amino acids within separate branches of each subtype phylogeny.
An ad hoc network of covarying resistance-associated mutations was elucidated along with 15 novel mutations that covaried with these sites. The results are presented collectively for three subtypes (A, B, and C) (Fig. 5); however, many of these interactions were subtype specific, and it remains to be seen whether there will be differential patterns of compensatory mutations when the inhibitors are used in patients infected with non-subtype B HIV-1. Both the resistance-associated mutations and the 15 highlighted polymorphisms occurred within the catalytic core domain of integrase. However, the proposed tetrameric structure of HIV-1 integrase also provides a mechanism whereby mutations in the N- and C-terminal domains can covary both with each other and directly with the catalytic domain itself (Fig. 6) (33). Interactions of this type were detected using covariation analysis but are difficult to rationalize until the macromolecular structure of integrase is confirmed. The use of covariation analysis as a tool to predict positions within HIV-1 integrase that may be associated with resistance to such inhibitors will be validated by monitoring the evolution of the enzyme under drug selection pressure in a clinical setting.
This work was funded by the Health Protection Agency and the NIHR UCLH/UCL Comprehensive Biomedical Research Centre.
- Received 13 July 2007.
- Accepted 25 June 2008.
- ↵*Corresponding author. Mailing address: Virus Reference Department, Centre for Infections, Health Protection Agency, 61 Colindale Avenue, London NW9 5EQ, United Kingdom. Phone: 2083276071. Fax: 2082001569. E-mail: Richard.Myers{at}hpa.org.uk
↵▿ Published ahead of print on 2 July 2008.
- American Society for Microbiology


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Washington Watch
Medicare for All, abortion, marijuana's long-term effects trigger discussion
Healthcare came up again during the fifth Democratic primary debate on Wednesday night, with discussions of healthcare reform, abortion, and marijuana legalization.
Mostly agree on abortion rights; pointed questions about septuagenarians' own health
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Minnesota senator and Democratic presidential candidate outlines her health priorities
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After the Sales Pitch: Post-Sales Call Practices to Help You Close the Deal
Every sales rep knows it's important to follow up with prospects — but what's the best way to do so? Here are 7 tips for turning your follow-ups into sales.
Every sales rep knows it's important to follow up with prospects — but what's the best way to do so? Here are 7 tips for turning your follow-ups into sales.
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The stronger your business plan, the better your chances of building a successful business. Here's what you need to know to stand out from the crowd.
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The Method:CRM team is reporting live from Scaling New Heights 2019 (Jun 16-19). Follow our blog for up-to-the-minute coverage of the conference!
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The Sheik (Paramount, 1921). Very Fine. Lobby Card (11" X 14").. ...Click the image to load the highest resolution version.
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DescriptionThe Sheik (Paramount, 1921). Very Fine. Lobby Card (11" X 14").
In one of Rudolph Valentino's most famous roles, Sheik Ahmed Ben Hassan (Valentino) rescues Lady Diana Mayo (Agnes Ayers) from the desert, only to have her reject his advances. Set free, Mayo is kidnapped by the villainous Omair (Walter Long), and is condemned to a fate worse than death. In the end, much to the delight of Valentino's thousands of swooning fans, the dashing Sheik rescues the helpless heroine who now pledges her undying love. This wonderful hand-tinted scene card captures an endearing moment between the two in lovely vibrant color. Signs of light usage include slight edge wear, small corner bends, and very faint stains in the bottom border.
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Cooking Up Some Trade Talk
In a few days, we will be entering July. This means Major League Baseball's trade season will soon be getting hot. Like a hot stove…hmm…As the heat turns up, our fantasy teams will be put in now or never situations. Buy or sell? Stand pat or take a chance? Trade him or him? Deciding how, who, and what to trade can be as laboring as preparing for your fantasy draft. Let this article start up what is indeed a labor of love. And if we can get a discussion going in the comments section filled with ideas, opinions, and questions, that will be even better.
Targeting What Matters:
But before I start indulging in fantasy baseball trade tactics, keep in mind that some of this comes down to what is relative to your team and league. If this write-up doesn't fully apply (or enlighten) to you, hopefully it will at least open up some ideas and get those wheels turning. And for the sake of keeping things simple, we will keep this a roto-based column, since points leagues are relative to a custom scoring system.
In general, I feel catching up in categories such as steals, saves, or even homers is a lot more doable than catching up in ratios such as batting average and WHIP. In order to catch up in these categories, it seems like you would need to acquire at least a couple of impact players, and at the same time replacing the players who are hurting you. It seems like a very steep hill to climb. It is much easier to breakdown a category such as saves. If you are behind in this category and add two closers, from this point of the season, you should now be able to add about 40 or saves (give or take) to your projected total.
When it comes to adding the pieces you need to win, you are going to have to make some educated guesses.
For a category such as saves, I would wait until after the MLB trade deadline (if you can). You don't want to trade for a closer who then happen to get traded away in real life and ends up as a holds guy. And as the weeks draw closer to that MLB deadline, picking up any possible closer handcuffs is a good idea.
Adding home runs to your team may be a little trickier than saves or steals, but adding players who traditionally hit for power is the obvious way to go. Even if a hitter who traditionally hits for power is off to a slow start, he could still deliver on the homers. Of course this is assuming he is healthy and is showing that his skills are still intact. At the end of April, Jay Bruce had one homer. Through two months of the season, he had eight. In June alone, he has hit 10.
Some of the players I am about to list could be available to you at a lower price than usual. These guys should provide you with a power boost going forward: Freddie Freeman, Pablo Sandoval, Carlos Santana, Matt Holliday, Giancarlo Stanton, and Jason Heyward. There are others of course. And you shouldn't expect this bunch to hit you 30 bombs the rest of the way. However, their past/pedigree indicates they should start hitting homers at a better rate than what they are doing currently. And for certain players, such as Freeman, you have to sometimes gamble on them tapping more into their power potential.
If you are loaded up on infielders and need an outfielder, you should probably trade an infielder for an outfielder. This seems pretty self-explanatory. If you have great pitching, but need a big bat, this too is self-explanatory. Dealing from a big strength to fix a weakness makes sense. Make sure you don't create one hole to fill another, however. Your replacements need to be strong enough to avoid a significant drop in production. And it obviously doesn't make any sense to weaken your team in a category to fill a position of need. At the end of the day, you are playing to fill categories. If you lack power, but need an outfielder, trading Paul Goldschmidt for Justin Upton isn't the right move in most circumstances. It is a lateral move at best. Trading Goldschmidt for someone like Jacoby Ellsbury makes even less sense.
Looking at the details in the standings of your league is very helpful. Try to project the point system. See what points you can realistically catch up in and see what leads you can realistically hold. Maybe with a couple of trades, you can potentially jump 10 points in the standings. There is also no bonus for a big lead in each category. In roto, your points get maxed out. In a 12 team league, you can't get more than 12 points per category. Eventually, you may have a comfortable lead in a category such as saves or steals. Even if you are a bit concerned you may lose a point or two, trade from that strength. It is more important to gain those points in the other categories you are lacking. Many teams are scared to let go of their big category leads. But unless the categories are bunched up, and are considered swing categories, this is a mistake. Take a deep look into the details of your leagues standings, and make smart decisions.
Is Buying Low a Myth And How to Make a Deal:
Wise fantasy players aren't going to give great players away. Even the guys I listed earlier may not be available at a low price. But perhaps an owner is giving up on Freeman reaching his 25-30 homer potential. Maybe there is an owner tired of Heyward or worried about Matt Holliday's production falling off a cliff. The truth is smart fantasy owners rarely sell low. Or at least to the point of making a deal an obvious win. You sometimes have to dig deeper, and in tougher leagues, that means taking shots on players such as Josh Willingham, Aramis Ramirez, Ryan Howard, and Paul Konerko. And when it comes to something like steals, taking chances on guys like Jose Reyes, Brett Gardner, Ben Revere, and Michael Bourn makes sense. It may be too tough to pry away steals leaders such as Jacoby Ellsbury, Everth Cabrera, or Jean Segura.
In saying this, everyone has their breaking point. So definitely pepper your league mates with offers. Even the best owners make mistakes, and at the end of the day, self-evaluation and player evaluation are some of the big ways to win this game.
Part of finding a buy low deal or simply completing a trade is by knowing the pulse of your league and competition. The game of poker, like fantasy baseball, is near and dear to my heart. And I believe having a feel for the pulse of your table and the poker players at it, is one of the most important things to get a hold of if you want to win. Knowing who is doing what and when and why they are doing it. As well as knowing how one will react when presented with a certain situation.
Fantasy baseball is similar. But instead of watching the way hands are played and figuring out the hand ranges and betting styles of your opponents, watch the transactions page and trading block, keep in contact with owners (through text/e-mail or website trade offers), and make sure you know the rosters and needs of every team. Look back at the draft results. Remember conversations. All these things add up to a story that could define what an owner likes in a player.
And while looking at the standings, transactions list, and trading block helps identify trade partners, also look for teams that have players coming off the disabled list. If their replacement (i.e. Jean Segura replacing Jose Reyes) is doing well enough, perhaps they are willing to now trade one of the two. It is a nice way to find trade opportunities.
Also, if you have high upside players coming off the disabled list such as Brandon Beachy or Adam Eaton, that may also help you create a trade opportunity. In all likelihood, these specific players involve a more long-term outlook for players, but someone may be in love with these guys and it could help you piece together a trade.
When you are on the verge of a deal, don't get too greedy. I used to lose a lot of the fish I had on the hook because of my greed. I try to avoid that now, and I also try to be a lot more forward about what I want in a trade. When trade talks begin, it is common for teams to ask for more than what they are willing to settle for. After some discussion, compromise then occurs. Be satisfied with the result if it is what you were looking to achieve.
Keeper/Dynasty Leagues:
I find keeper/dynasty leagues to be more fun than any sort of redraft league. In a redraft league, there are no worries about next season. You're only goal is to win that season. Plain and simple. In a keeper/dynasty league, however, you feel more like a GM, having to keep an eye on the future, as well as the present.
Let's break it down into three types. First, leagues which allow you to keep players (usually with limits) with no penalties. Second, round value keepers (usually with limits). This is determined by where you draft a player or if that player was a waiver wire add. And third, dynasty leagues based on salary (limits or no limits). Out of these, type three will be discussed with the most detail. There are other types of leagues out there, but let's keep it simple.
1. Keepers with No Penalties
This type of league seems to be fading. It just isn't fun when one guy has Miguel Cabrera, Ryan Braun, Clayton Kershaw, and Mike Trout for what feels like an eternity. In these leagues, noticing small breakdowns, and looking to ship players a year early rather than a year late is key. Keep your best players no matter (unless a devastating injury) what during their primes. Because there are no penalties, you usually can only keep a certain number of players. This is all the more reason to keep the best of the best.
The strategy in this league is relatively simple. If you are a contender, sell your excess keepers to a team in need of one, acquire lots of talent, and you win your league. If you need keepers and your team isn't going to win, well then you sell your assets in hopes to add a top keeper or two.
Really, these leagues just aren't that fun anymore.
2. Round Value Keepers
This type of league involves snake drafting. Usually, you have a limited number of keepers (i.e. five) and their values are based on where they are drafted. Normally, there is inflation involved. Each year you keep a player, his round value gets higher up in the draft. So if he was a 20th round pick. In say 3 seasons, he will be a 5th round pick. Eventually the day will come where this player can't be kept and is forced back into the draft pool.
Snake drafts have a special place in my heart, so I happen to like this system.
Unlike the keepers with no penalty league, many of the top echelon players are selected in the first couple of rounds and can't even be kept. Each year a team has a chance at a lot of the top players. Since that is the case, the real value comes in the later rounds. Jose Fernandez, Jean Segura, Man Bear Puig…all these players have big value because of where they were likely drafted (or as a waiver add). No one is saying you should trade these players. But depending on how many keepers your league is allowing, you could really obtain big time value if you did.
But should you? Well, what if you could deal one of these players for a big haul, while not hurting your future outlook?
There is no doubt it would be great to keep Jean Segura in the 20th round next season. But, if you could ship him off for a few pieces that give you a title, do it. Under normal circumstances, you should have a few players on your team that you took in the mid-teen to late-teen rounds that would make worthy keepers for 2014. Guys like Mike Minor, Homer Bailey, and Chris Davis all will have a significantly higher ADP next season, which gives you a nice profit on your investment. If you could lock up a title, while keeping a strong core intact, you do it. If that means dealing away Jose Fernandez and his late round keeper tag, so be it.
3. Dynasty Auction Leagues
Auction dynasty leagues usually have deep rosters. A roster of 40 players, including minor leaguers that is based on a salary structure are just good times. And I don't mean than sarcastically. They really are great. And that's all there is to it. Inflation is usually tied to each player, so their salaries go up each season. Once a player hits a certain amount, they aren't worth to keep, so back into the draft pool they go. In many instances, you can cut a player from your team in the offseason (sometimes with a penalty).
If you are looking to rebuild, you have to decide on a strategy and target players with certain salaries. Acquiring cheap prospects on the verge or cheap young MLB talent is usually the way to go. I would target 2-4 prospects depending on their value. Keep in mind; you only have so many tradable pieces, and not many potential trade partners, so you can't afford to get it wrong. Prospects do end up being busts, so try to get as many as you can if you are in true rebuild mode. You can also acquire current MLB players with low salaries such as Alex Cobb and Manny Machado.
If you are a team on the brink of winning a championship, trade Christian Yelich, Kevin Gausman, and Rubby De La Rosa. Sure, you may end up cutting newly acquired Adrian Beltre and C.C. Sabathia after the season, but flags fly forever, and you can't pass on the opportunity to win. We play for championships.
In fantasy baseball, many owners would rather have the young hitter than the young pitcher. And that is totally understandable. Hitters play every day, have a lesser chance for injury, and if saves are in your league, usually contribute to more categories than a pitcher. But under certain circumstances, it make sense to keep the pitcher in an auction league.
Because pitchers are so vulnerable, we should be happy to keep cheap pitchers with big upside. Trading those pitchers away would only lead us into bidding on a high priced starting pitcher in next year's auction. And that is the sort of risk we want to avoid.
Isn't a $2 Shelby Miller more valuable than a $15 Anthony Rizzo? Both of these players have a high upside. Sure, maybe Rizzo is safer. Maybe he has less of a chance for injury. Maybe he even has a better chance to fulfill his potential down the road. But why trade away a perfect situation? You have a high risk commodity paying off at a low price. Why spend $22 on C.C. Sabathia or a $33 David Price when I can hang onto my $2 Shelby Miller, pass on this trade offer, and use the savings to spend on a $27 Edwin Encarnacion. Use your saved funds on acquiring hitters in the draft.
Trade Talk Conclusion:
Winning a fantasy baseball league takes work. Making a trade takes effort. Think about your league and what is needed to succeed. It is truly a labor of love. Get what you desire before someone else swoops in and takes it from you.
Go ahead and feel free to post questions or comments below.


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VERDUN, October 27, 2011 – Ville de Montréal – Verdun Borough is organizing a two-phase architectural competition in order to set up a cultural venue within Édifice Guy-Gagnon (at 5190, boulevard LaSalle, corner Desmarchais in Verdun). This former arena will be reconfigured and expanded to house— in the part of the building commonly called "Studio B"—a performing arts and circus arts venue, including an auditorium with seating for 368 to 414 spectators and an exhibition hall. The other part, where Studio A is located and which is being used by École de cirque de Verdun at the present time, will also be renovated.
Claude Trudel, Verdun Borough Mayor responsible for public safety and security on Ville de Montréal's Executive Committee, made the following announcement today: "The architectural competition is one step further in the process eventually leading us up to the construction of this much-awaited venue that Verdun greatly needs—an auditorium in keeping with the professional standards of the entertainment world."
The architectural competition of Centre de diffusion culturel / Édifice Guy-Gagnon comes within efforts to promote the quality of the built environment, in accordance with the City's orientations, as described in the program. This process is intended to be transparent as well as promote equality and accessibility within its rules and regulations. Through concern for a quality architectural structure, translucency, materiality and inventiveness will have to be among the features of this project. Such requalification of the building requires redeveloping the building envelope in harmony with its site along the St. Lawrence River. The project aims at creating a performing arts and circus arts hub in this area.
This will be a two-phase competition with the objective of selecting a distinctive project and engaging professional architectural services to design the cultural venue and ensure site supervision while construction is under way. On the basis of pre-determined criteria, a seven (7)-member panel of judges will be called upon to recommend to Ville de Montréal – Verdun Borough four (4) finalists upon completion of Phase 1, and subsequently, the successful team and project upon completion of Phase 2.
The competition documents (rules and regulations as well as the summary plan) are available through SÉAO (Service électronique d'appels d'offres). These documents may be obtained by contacting one of the representatives by phone at 1-866-669-7326 or 514-856-6600. Or they may be downloaded from SÉAO's website (www.seao.ca). The documents may be obtained at a cost set by SÉAO.
For the purpose of the architectural competitions, the cost of the project, has been estimated at a total of $11,473,758 ($8,361,255 for the cultural venue and $3,112,503 to redevelop the premises of École de cirque de Verdun). Added to these amounts are the costs related to landscaping, parking facilities, stage equipment and the art piece and estimated at a total of $3 964 002. The financing package for the Borough's cultural venue is assured. As for the École de cirque de Verdun project, those in charge are waiting for a reply from the Ministère de la Culture, des Communications et de la Condition féminine du Québec.
As it may be recalled, Verdun has no professional auditorium, but does have six locations used for professional performing arts shows that are very well attended by residents.
- 30 -
Source: Verdun Borough
For further information:Francine MorinResponsable du protocole et des relations publiquesVerdun firstname.lastname@example.com@ville.montreal.qc.ca


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Remembering Altamont, the Day the Sixties DiedHistorians/History
tags: 1960s, counterculture, Altamont
James Thornton Harris is an independent historian and a regular contributor to the History News Network. For more information see www.JamesThorntonHarris.com
Fifty years ago this month, on December 6, 1969, the 1960s died. On a sunny Saturday in the dusty hills east of San Francisco, the Altamont Rock Concert dissolved into chaos, leaving four dead and dozens injured. Like so many events of the 1960s, an idea conceived with good intentions went terribly wrong and ended in tragedy.
The day-long free concert, attended by 300,000 people, was held at a run-down race car track, a choice made at the last-minute after negotiations to hold it closer to the city fell through. The event was sponsored by the Rolling Stones, who initially envisioned a "Woodstock West," a free music festival featuring the biggest California bands including Crosby, Still, Nash and Young, the Jefferson Airplane and the Grateful Dead.
In what was to become, quite literally, a fatal mistake, the event organizers hired the Hells Angels motorcycle gang to serve as security guards. As noted in Joel Selvin's book, Altamont, the biker group was hired (for $500 worth of beer) on the recommendation of Rock Scully, the Grateful Dead's manager.
Today, the event is remembered by the shocking images of violence that occurred at the climax of the concert, as the Rolling Stones took the stage surrounded by Hells Angels. As the drug-fueled young men and women in the crowd surged forward, the leather-jacketed gang members beat many senseless with pool cues and motorcycle chains. Dozens were taken to the hospital and one young black man was stabbed to death.
The most complete visual account of the violence was captured in Gimme Shelter, the concert documentary film made by the Maysles brothers. When the film appeared in theaters in 1970, its scenes of swaggering gang members and bloody concertgoers provided a shocking counterpoint to the cheerful atmosphere of brotherhood and sharing associated with Woodstock.
Altamont's significance came from its timing, just four months after Woodstock. Four deaths at a rock concert was a tragedy, but other contemporary events had produced higher body counts. The members of the Manson gang had killed seven people in August and despite President Nixon's pledge to de-escalate, the Vietnam War clamed 12,000 Americans in 1969.
I attended the Altamont concert along with two college friends. For many of us, the disaster was particularly demoralizing because the event had been billed as California's answer to Woodstock. Although I was safely ensconced at a suburban junior college, like many Bay Area young people I felt a sense of belonging to the hippie, flower-power movement. After all, we had seen it first-hand in San Francisco's Haight Ashbury district; we had attended the free concerts in Golden Gate Park, heard Allen Ginsberg chant and seen the Diggers hand out free food.
The Concert
On that fateful December 6, we headed out on the freeway for the remote Altamont Pass. We turned off onto the narrow, road leading to the Speedway and were excited by a scene that reminded us of the photos of Woodstock. Thousands of cars were parked head-first on the roadside and a huge stream of young men and women walked towards the concert, toting blankets, wine bottles and backpacks. Guitar music, casual laughter and clouds of marijuana smoke filled the air.
The first sign of trouble appeared as we entered the gates of the race track. Inside, a dozen Hells Angels roared up and down along the edge of the crowd. Revving their engines and spinning their wheels, they sprayed the concertgoers with mud and gravel. Some of the bikers cruised slowly by making obscene comments about the young women. I saw a large bearded gang member with oil-stained jeans grab a wine bottle out of the hands of a startled attendee and speed off.
My friends and I glanced nervously at each other. What could we do? There weren't any cops in sight. No one wanted to pick a fight with a Hells Angel.
The event stage was set at one end of the oval speedway. A series of gently sloping, grass-covered hills ringed the track. By 10 am, a massive throng of white, suburban youths were spread across the bumpy landscape.
We wedged ourselves into a space about a thousand feet from the performers. With our view obscured by two metal scaffolds bristling with movie equipment and an old school bus, we could only see part of the stage.
The primitive sound system might have sufficed for a small auditorium, but much of the music was dispersed in the afternoon breeze. For us, the sound quality was akin to what you'd hear standing in a parking lot and listening a radio playing inside a car.
We could see and hear the different bands come and go, but we had no idea of the beatings taking place near the stage. This was a sixties outdoor concert experience. It is hard to imagine today, when pop performances use giant video screens to project the singers' faces and the audience focuses on the event through their cell phones.
At Altamont, we endured a long wait as evening fell and temperatures dropped. Our patience was rewarded when the Rolling Stones finally took the stage around 8 pm. The sound system was turned up and the band cranked through a dozen of their hits including "Honky Tonk Women," "Jumpin Jack Flash," "Satisfaction" and "Sympathy for the Devil."
After the last song, the band hurried off the stage. We stumbled through the darkness, tripping over blankets and wine bottles, guided to our cars by the glow of distant headlights.
It wasn't until the next day we learned of the casualty count: one man drowned in a drainage canal, two campers crushed by a runaway car and one young African American man, Meredith Hunter, stabbed to death in front of the stage.
In this pre-Internet era, our main source of news about the event was KSAN-FM, the Bay Area's most popular rock station. Their news director hosted a six-hour call-in program. Beating victims and eyewitnesses recalled their experiences, often in tears. As we struggled to understand what happened, it became clear that it was one thing to question authority, another to abolish it altogether.
A week later, Rolling Stone covered the disaster and described it as "rock and roll's all-time worst day."
On December 31, the sixties officially ended and the new era of the 1970s began. Following the assassinations, urban riots and massive causalities of Vietnam, we hoped for a fresh beginning. Through TV ads and newspaper commentaries, the media suggested the seventies would be sleeker, smoother; society would be restyled after the head-on crash of the 1960s.
Instead, we endured four more years of the Vietnam war, the Kent State shootings, gasoline rationing, Watergate and the Iran hostage crisis. In November 1980, the electorate turned decisively conservative and elected Ronald Reagan.
Today, the Woodstock festival is commemorated by a large concrete memorial placed in front of the grassy hillside where the concert was held. Nearby, the Museum at Bethel Woods displays artifacts celebrating the festival and the counterculture it embodied.
In contrast, the Altamont Speedway sits empty, having ceased operations a decade ago. The concrete oval remains, in a small valley hidden from the nearby interstate. The only sound is the whirring of hundreds of wind turbines, sending electricity to the wealth engines of Silicon Valley.
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Thrifty Lesley - 1 person, 1 day, £1or How To Feed Yourself For £1 A Day
Fed up with plain cheese sandwiches? How about flavoured potted cheese?
Do you have cheese sandwiches for lunch? Are you a little tired of them, or maybe wanting to ring the changes a little?
How about making a potted cheese.
Home made ice cream for a baking hot day, no machinery required
Home made ice cream for a baking hot day, no machinery required, simply stir and freeze
Panzanella with lovely sun ripened tomatoes.
The perfect way to use full flavoured summer ripened tomatoes
Celery, Swede & Chickpea Bake. Vegan
Homely vegetables, given a twist and used as a main course
Home made honey smoked walnut butter. Easy, cheap, versatile and super delicious
All nut butters are easy to make, and this walnut version is no exception.
UK Money Bloggers Summer Giveaway
This summer, some of the UK Money Bloggers have come together to offer you the chance to win one of five fabulous M&S Afternoon Tea hampers, plus a runner up prize of a Bees Knees hamper.
A gorgeous Chickpea, Mango and Coconut Curry
This gorgeous Chickpea, Mango and Coconut Curry couldn't be easier to make!
The garden in July
pictures of my garden in July
Quick Banana Bread
I usually use up soft bananas in smoothies, with an unpeeled apple and a splash of orange juice. But if I want cake, this recipe for a homemade banana bread is super quick to mix up and very tasty.
Competition – copy of Tin Can Cook
4 copies of Jack Monroe's latest book Tin Can Cook up for grabs. Seventy Five recipes using mainly, yes, cans. Some new recipes, some older, favourite ones.
Home made apricot jam. Fresh and wonderful, and better than even the poshest versions you can buy!
home made apricot jam that tastes better than Bonne Maman! Fresh and zingy with lemon juice. Very easy to make
Progress on the loft and on the blog
Where we've got to with the loft extension, and some much needed blogmin


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The UK Ministry of Defence (MoD) has announced an investment of GBP1 million (USD1.3 million) in Oxford Space Systems' (OSS's) development of a new generation of deployable satellite antennas.
This funding will allow OSS to increase the size of the wrapped rib antenna and improve the antenna's performance to enable it to be used in support of defence applications.
The system is lighter than other available systems so is more easily deployed into space, while greater cost efficiency makes it appealing in what the MoD deems to be a costly industry.
The development is being funded under the UK government's Defence and Security Accelerator (DASA) innovation support body, in collaboration with the Defence Science and Technology Laboratory and the Defence Innovation Fund.
Want to read more? For analysis on this article and access to all our insight content, please enquire about our subscription options at ihsmarkit.com/janes


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Musi - Simple Music Streaming
by: Musi Inc. • 864.4K
All iPhone applications categories
by: Musi Inc. • 864.4K
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text: Im randomly experiencing a big slowdown in my code.. but I fail see where and what is causing this slowdown. Advices on how to move on are appreciated. Im writing a text editor which can do syntax colorering of Ruby code. recomputing all 50 lines takes about 0.09 - 0.15 seconds. However when inserting one letter.. so that only one line is recomputed, then it takes between 0.03 - 0.43 seconds! Im interested in hunting down why it often spends so long time computing just a single line. I have 1) profiled the recomputing of all 50 lines and 2) profiled the recomputing of a single line when speed is bad and 3) profiled the recomputing of a single line when speed is good. when I compare the profiler output, I fail to see where the slowdown are. You may see the output here: http://aeditor.rubyforge.org/wiki/wiki.pl?ProfilingLexerNew The place where I recompute is in the method #sync_lcache in this file http://rubyforge.org/cgi-bin/viewcvs/cgi/viewcvs.cgi/projects/experimental/buffer/source/buffer.rb?rev=184.108.40.206&cvsroot=aeditor&only_with_tag=b20040707&content-type=text/vnd.viewcvs-markup I have inserted the following code around the place where I recompute Profiler__.start_profile # code to profile Profiler__.stop_profile Profiler__.print_profile(STDOUT) If you have any ideas why the recomputation of a single line takes unnecessary long time.. then please contact me. How can I identify what sometimes is causing this slowdown? -- Simon Strandgaard


text:
Pottsgrove is located in Pennsylvania.
Pottsgrove, Pennsylvania has population of 3,265.
Pottsgrove is less family-centric than the surrounding county with 27% of the households with children.
The median household income in Pottsgrove, Pennsylvania is $79,219.
The median household income for the surrounding county is $70,788 compared to the national median of $49,877.
The median age of people living in Pottsgrove is 45.9 years.
The average high temperature in July is 85.34 degrees, with an average low temperature in January of 19.14 degrees.
The annual precipitation is 47.34.
Loralea Hartle
1070 Bloom Rd.,
Danville, PA 17821 | Phone: (570) 452-0500 |
Email: email@example.com
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Prime Minister Narendra Modi kick starts Bihar's election campaign with NDA'S "Sankalp" rally in Patna, along with ally Janta Dal (United) chief and state Chief Minister Nitish Kumar from the historic Gandhi Maidan in Patna, for the first time since 2009.
The three tall leaders of the NDA, PM Modi, Nitish Kumar and Ram Vilas Paswan would look to woo the voters in Bihar that have a total of 40 Parliamentary seats. Soon the rally kick-started, Chief Minister Nitish Kumar at Sankalp rally said, "We should respect all religions."
Nitish Kumar further added, "Assure PM Modi that we will win all 40 seats for him in Bihar." When PM Modi came to the addressSankalp rally in Patna, Crowd chants "Bharat Mata ki Jai" along with PM Modi.
"I salute the martyrs of Pulwama, the whole nation is standing with the families of the jawans," PM Narendra Modi said.
PM Narendra Modi in Patna: I salute the martyrs of #Pulwama, the whole nation is standing with the families of the jawans pic.twitter.com/p8wDSGtPUx— ANI (@ANI) March 3, 2019
This is PM Modi's second visit to the state within a fortnight, the first being on February 17 in Begusarai, from where he inaugurated and launched projects.
"We welcome his return and want to thank and congratulate the PM over the manner in which he raised the matter at world forum. The world has united against terrorism," Bhupendra Yadav, BJP MP and the party's in-charge of Bihar said on Saturday.
After Sankalp rally, PM Modi will head towards Congress chief Rahul Gandhi at his bastion - Amethi - in Uttar Pradesh.
Also read: Read Wing Commander Abhinandan's last radio message before landing in Pakistan