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Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering
Zhiqiong Wang1,
Mo Li1,
Zhen Xu2,
Yanlin Jiang3,
Huizi Gu4,
Ying Yu5,
Haitao Zhu6,
Hao Zhang ORCID: orcid.org/0000-0002-0049-12207,
Ping Lu8,
Junchang Xin9,
Hong Xu7 &
Caigang Liu10
The Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) classification is a key gastric cancer prognosis system. This study aimed to create a new TNM system to provide a reference for the clinical diagnosis and treatment of gastric cancer.
A review of gastric cancer patients' records was conducted in The First Hospital of China Medical University and the Liaoning Cancer Hospital and Institute. Based on patients' prognoses data, computer-aided unsupervised clustering was performed for all possible TNM staging situations to create a new staging division system.
The primary outcome measure was 5-year survival, analyzed according to TNM classifications. Computer-aided unsupervised clustering for all TNM staging situations was used to create TNM division criteria that were more consistent with clinical situations. Furthermore, unsupervised clustering for the number of lymph node metastasis in the N stage led to the formulation of a classification method that differs from the existing N stage criteria, and unsupervised clustering for tumor size provided an additional reference for prognosis estimates.
Finally, we developed a TNM staging system based on the computer-aided unsupervised clustering method; this system was more in line with clinical prognosis data when compared with the 7th edition of UICC gastric cancer TNM classification.
In the past 3 decades, both the Japanese and Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) classification systems for gastric cancer have undergone several major changes [1]. The biggest difference between the 2 systems exists in the N stage division method [2]. However, in 2010, the UICC released the 7th edition of TNM classifications of gastric cancer that used the number of metastatic lymph nodes for N classification. This standard has now been adopted by the Japanese TNM [3]. However, the exact threshold values for division between the different N stages have become a critical issue.
In clinical practice, other independent clinical or pathological features can directly or indirectly predict patient survival [4,5,6,7,8,9]. For example, tumor size, although closely related to the T stage, remains an independent prognosticator in patients with gastric cancer. Therefore, the threshold tumor size and its effect on prognosis need to be evaluated to help clinicians determine patient prognosis more accurately.
Importantly, although TNM staging has been revised several times, in clinical practice, there is often a marked difference in the prognoses of patients with the same TNM stage, which might be owing to heterogeneity between patients of different ethnic backgrounds, the evolution of the biological behavior of gastric cancer, and other factors [10]. Moreover, among patients with a poor prognosis, there are those who achieve long-term survival. Therefore, a more accurate division of the TNM stages is needed to determine patient prognoses, comprehensive treatment planning, and other disease management aspects [11,12,13].
To resolve the problems mentioned above and develop a system for improved prognostic accuracy, we summarized information obtained from patients with gastric cancer who underwent treatment over the past 3 decades [14]. We conducted a precise enumeration of the optimal division points for clinical factors related to gastric cancer (e.g., age, tumor size, the number of lymph node metastases), and selected the optimal cut-off points. Data permutations were performed to obtain the final TNM staging system based on the principle of having smaller differences within groups and greater differences between groups. The postoperative 5-year overall survival rate was used as the comparison standard to account for the extensive duration of the study period. This study provided a reference for determining more scientific and accurate TNM stage division criteria, as well as threshold values for various factors that might influence gastric cancer prognosis.
We enrolled 2414 patients with histologically confirmed gastric cancer who underwent surgery at the Liaoning Cancer Hospital and Institute and China Medical University. All patients had complete medical records available.
All patients were followed-up by postal or telephone interviews. The last follow-up was conducted in December 2015, with a total follow-up rate of 91%. Clinical, surgical, and pathological findings, and all follow-up data were collected and recorded in the database.
The study protocol was approved by the Ethics Committee of The First Hospital of China Medical University and the Liaoning Cancer Hospital and Institute, and informed consent was obtained from all subjects. All methods were performed in accordance with the relevant guidelines and regulations.
Endpoints and follow-up
The primary endpoint was the 5-year survival. Overall survival time was calculated from the date of surgery until the date of death or last follow-up contact. Patient data were censored at the last follow-up when they were alive. Follow-up assessments were conducted every 6 months for the first 5 postoperative years, and every 12 months thereafter until death.
Computer-aided unsupervised clustering method
A precision enumeration was performed to determine the optimal division points for clinical factors related to gastric cancer (e.g., age, tumor size, the number of lymph node metastasis), and all possible division points were calculated to form a cycle. For each cycle, the log-rank test was used to derive the p-value between 2 points. At the end of each cycle, the minimum p-value cut-off point was selected as the optimal cut-off point.
Permutations were carried out for the 5 T stages, 4 N stages, and 2 M stages in TNM gastric cancer staging, i.e., a total of 5 × 4 × 2 = 40 groups. Log-rank test p-values between these groups were calculated; differences within groups were minimized, and those between groups were maximized by combining groups with greater p-values into a single unit, thereby, obtaining the 7 most optimal groups as the final TNM stages.
Kaplan-Meier survival curves were used to estimate 5-year overall survival. For univariate analyses, the prognostic factors of interest and the diagnosis period were covariates in the Cox regression model. Multivariate analyses were conducted using the Cox proportional hazards regression model to assess risk factors associated with survival. Two-sided p-values < 0.05 were considered statistically significant. Analyses were performed using SPSS software, version 23.0.
Patient characteristics are shown in Table 1. The median age of patients at gastric cancer onset was 57 years, and there were significantly more male patients compared with female patients. In most patients, the gastric cancer was located in the lower portion of the stomach and presented at an advanced stage. Almost 50% of the patients underwent radical surgery, with the scope of lymph node resection being based on D2 surgery. The results of the multivariate analyses of factors associated with survival are shown in Table 2. After adjusting for 16 variables, patient survival was significantly associated with tumor size, tumor site, gross appearance, T stage, N stage, TNM stage, hepatic metastasis, and peritoneum metastasis. Factors such as the surgical extent and joint organ removal also affected prognoses. Adjuvant chemotherapy and the diagnosis period affected the 5-year overall survival rates.
Table 1 Characteristics of population from the three periods (n = 2414)
Table 2 HR for death in population (n = 2414) —univariable and multivariable analysis
Computer-aided unsupervised clustering: tumor size
Patient's tumor size and survival time were inputted on a dot plot (Fig. 1). After calculations, 5 cm and 9 cm were chosen as the optimal cut-off points, and tumor size was defined as S1 (< 5 cm), S2 (5–8 cm), S3 (≥9 cm), according to when the differences between the groups were maximized (Fig. 2, p < 0.001).
Scatter distribution of tumor size vs. survival time in patients with gastric cancer
Survival curves according to tumor size in patients with gastric cancer
Computer-aided unsupervised clustering: number of lymph node metastases
Patient number of lymph node metastases and survival time were inputted on a dot plot (Fig. 3). After calculations, 0, 5, and 15 were chosen as the optimal cut-off points and N stages were subdivided as N0 (n = 0), N1 (n = 1–4), N2 (n = 5–14), and N3 (n ≥ 15), according to when the differences between the groups were maximized (Fig. 4, p < 0.001).
Scatter distribution of the number of lymph node metastases vs. survival time in patients with gastric cancer
Comparison of survival curves for the clustered N stage and the UICC N stage
Computer-aided unsupervised clustering: TNM stage
Based on patients' prognoses data, the computer-aided unsupervised clustering method was applied to re-cluster patients with different TNM stages. Clustering results and the number of patients in each group after clustering are shown in Table 3, which is also thought as the new TNM staging criteria. In the original 7th edition of the UICC gastric cancer TNM stages, there was an orderly arrangement of the different T, N, and M stages, which was disrupted after computer-aided unsupervised clustering.
Table 3 Comparison of the 7th UICC and the clustering TNM stage
Effect of TNM stage on prognosis predictions after unsupervised clustering
The significance of the differences between the various stages is shown in Table 4. When comparing each row, there was a significant difference between the classes in the clustered stages, making it superior to the UICC staging criteria. Survival rate curves for the 2 different staging methods are shown in Fig. 5. Compared with the UICC stages, which is the "7th UICC TNM stage", the use of the computerized clustering method, which is the "clustering TNM stage", resulted in a significant decrease in the differences between the groups for each stage, as well as for the different T and N stages (data not shown).
Table 4 Comparison of P values between each stage of UICC and the clustering TNM stage
Comparison of survival curves of the clustered TNM stages and the UICC TNM stages
Because we performed clustering analysis on N stage in this study, the N stage of many patients was changed. We also introduced the clustering N stages of N0 (n = 0), N1 (n = 1–4), N2 (n = 5–14), and N3 (n ≥ 15) into the UICC TNM stage, which is "the UICC TNM stage based on the clustering N stage" in Fig. 6, and re-performed the unsupervised clustering for TNM stage, which is "the clustering TNM stage based on the clustering N stage". Survival rate curves for the 2 different staging methods are shown in Fig. 6.
Comparison of survival curves of the clustered TNM stages based on the clustered N stage and the UICC TNM stages based on the clustered N stage
In the past, when performing confirmation or exploratory TNM staging improvements, differences in survival were always compared between different stages by observer-determined divisions. Such methods could result in selection bias, thereby introducing problems in obtaining accurate staging for a particular patient population. However, in computer-aided unsupervised clustering, which is based on patient survival data, patients are clustered inversely. This ensures the accuracy of the patient population for each stage, produces the least amount of heterogeneity between patients, and maximizes survival differences between each stage. Regarding the degree of difference between the classes, although the UICC and Japanese staging criteria have significantly different p-values that are superior to the cluster staging method, as a whole, there is a greater degree of difference between classes in the cluster staging method. Neither the UICC nor Japanese criteria consider significant differences between groups within the classes. Rather, they take the groups with greater differences and divide them into a separate class. However, by analyzing the degree of difference between groups within classes, the cluster staging method divides the group with the lowest degree of difference into a separate class, thus creating a lesser degree of difference within classes, which is more in line with actual gastric cancer data.
After clustering the TNM stages, we found that there were more pre-IIIA stage patients compared with the UICC staging system, and there was a particularly significant increase in the number of patients with IA stage disease. This shows that in the past, judgments of a good prognosis may have been limited and pessimistic. Therefore, in some patients, prognosis might need to be revisited to formulate a more accurate and rational comprehensive treatment program. After clustering, the T1N1M0 and T1N2M0 patient classes were added to stage IA, which indicates that the invasion depth of gastric cancer might have a greater effect on patient prognosis compared with the extent of lymph node metastases. Furthermore, the adverse effects caused by lymph node metastases in these patients might be more easily controlled through comprehensive treatment.
By contrast, after clustering, there were significantly fewer patients with stage IV gastric cancer. This indicated that, for many patients, the prognosis might be more optimistic than previously considered. However, many of these patients were classified as having stage IIIC disease, which has a 5-year survival rate of < 10%.
Tumor size is directly related to invasion depth and is an independent prognosticator for gastric cancer. Although the existing gastric cancer staging systems do not take tumor size into consideration, we performed cluster analysis on tumor size based on survival data. The results revealed that in our database, 4 cm and 9 cm represented good tumor size threshold values. The adverse effects of a greater tumor size are caused by a greater invasion depth, more extensive lymph node metastases, and a greater possibility of distant metastases, although they might also be related to the need for a greater extent of gastric resection and the possibility of resection of adjacent organs. Furthermore, in the present study, the median tumor size was ~ 5 cm, indicating that significant improvements are needed regarding gastric cancer screening and early diagnosis. The majority of patients with gastric cancer are elderly and from rural areas, and the lack of timely and standardized treatments, in addition to poor compliance, remain significantly severe issues for interventions [15].
In 2010, the UICC and Japanese TNM staging systems came to an agreement on the divisions for N stage according to the number of lymph node metastases. In the present study, a cluster analysis of the number of lymph node metastases (0, 5, and 15 nodes), based on survival data, improved the distinction of patients' prognoses compared with the existing classification systems. However, to maintain consistency with the existing UICC stages, when performing multivariate analysis, we did not use the cluster analysis division criteria for N stage and TNM stage analyses.
For cluster analysis according to age, 55 years was found to be optimum age for distinguishing patients' prognoses. Further subgroup analysis including sex, revealed that in female patients, prognoses could not be divided based on significant differences in critical age values, whereas in male patients, the critical age was 53 years. Therefore, in male patients aged > 53 years, there was a significant difference in diagnosis compared with male patients aged < 53 years. The specific mechanism behind this prognostic difference remains unknown, but this phenomenon might provide clues regarding the pathogenesis of gastric cancer between the sexes.
Because the present study was retrospective, the reliability of the data would be inferior to that obtained in prospective clinical trials; therefore, appropriate TNM classification guidelines for gastric cancer, especially in the Chinese population, need to be studied further. Meanwhile, China is an expansive region where people from different areas have different economic circumstances and lifestyle habits, which has certain effects on the development, progression, and outcome of cancer. In the present study, most of our patients are from northeastern China, which is representative of the characteristics of gastric cancer patients in northeastern China to a certain extent, however, not patients in all of China. In future studies we will increase collaboration with hospitals in other regions to investigate staging methods more appropriate to Chinese patients and behavioral characteristics with respect to gastric cancer biology. Nevertheless, these findings provide a reference for the future improvement of gastric cancer TNM staging, accurate determination of gastric cancer prognoses, and improved implementation of more comprehensive treatments.
Compared with the existing TNM staging classification for gastric cancer, there was a greater difference between stage classes when using the computer-aided unsupervised clustering method. In addition, in the cluster staging method, groups with a lesser degree of difference were divided into separate classes, thereby creating a staging system that is more in line with actual gastric cancer data. In summary, in Chinese patients with gastric cancer, the cluster staging method was preferable over the UICC or Japanese TNM classification for determining prognosis regarding the degree of difference within classes or among groups within the classes.
TNM:
Tumor-node-metastasis
UICC:
The Union for International Cancer Control
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This work was supported in part by China National Natural Science Foundation (61402089, 61472069, 81402384 and 81572609) for the follow-up, data analysis and writing, the Fundamental Research Funds for the Central Universities (N141904001) for the data analysis, the Natural Science Foundation of Liaoning Province (2015020553) for the clinicopathological data collection, the China Postdoctoral Science Foundation (2016 M591447) for the design of the study, and the Postdoctoral Science Foundation of Northeastern university (20160203) for the data analysis and writing.
The datasets analysed during the current study are available from the corresponding author on reasonable request.
Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110169, China
Zhiqiong Wang & Mo Li
Department of General, Visceral and Transplantation Surgery, Section Surgical Research, University Clinic Heidelberg, Im Neuenheimer Feld 365, 69120, Heidelberg, Germany
Zhen Xu
Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China
Yanlin Jiang
Department of Internal Neurology, the Second Hospital of Dalian Medical University, Dalian, 116027, China
Huizi Gu
Liaoning Medical Device Test Institute, Shenyang, 110179, China
Ying Yu
Department of Gastric Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, 110042, China
Haitao Zhu
Department of Breast Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, No. 44, Xiaoheyan Road, Dadong District, Shenyang, 110042, Liaoning Province, China
Hao Zhang & Hong Xu
Department of Surgical Oncology, the first hospital of China Medical University, Shenyang, 110001, China
Ping Lu
School of Computer Science and Engineering, Northeastern University, Shenyang, 110189, China
Junchang Xin
Department of Breast Surgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China
Caigang Liu
Zhiqiong Wang
Mo Li
Hao Zhang
ZW, HX, and HG participated in the design of the study and drafting the article. ZX, YY, and ML participated in the design of the study, the statistical analysis and drafting the article. YJ, HX, and HZ participated in the design of the study and the statistical analysis. CL, HZ, JX, and PL participated in the design of the study, and revising the article. All the authors read and approved the final manuscript.
Correspondence to Hao Zhang, Junchang Xin, Hong Xu or Caigang Liu.
The study was granted ethical approval by the Ethical Committee of China Medical University and the Liaoning Cancer Hospital and Institute, and all the patients provided written informed consent.
Wang, Z., Li, M., Xu, Z. et al. Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering. BMC Cancer 18, 706 (2018). https://doi.org/10.1186/s12885-018-4623-z
Tumor-node-metastasis staging


The weather in New York has taken a turn for the cold and blustery incredibly quickly. It's making me sad. Except for the fact that I can start busting out my tights on a regular basis. What I've realized I'm lacking is an array of black patterned ones. Every night this week, I've seen at least one adorable pair on a girl in a simple outfit that becomes a little less simple with that extra addition. Unfortunately the Louis Vuitton and Chanel versions aren't exactly how I should be spending my paycheck right now. Unless of course I decide to give up Christmas presents for the fam. Last night at the hair salon one of the girls (who also happened to be a dead ringer for Rayanne Graff) told me hers were from Urban Outfitters and that she'd just picked up a whole bunch of them. This Betsey Johnson pair seem to fit my criteria perfectly: black, not so dark as to obscure the pattern, and affordable. Plus they have bows! Even if those aren't your style, there are tons of others to choose from. Friday shopping complete. Now if that wind would just die down.


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redpajama_set_name: RedPajamaCommonCrawl


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Ireland: Haass negotiations reveal the contradictions within the North
Fightback Ireland Editorial Board
American diplomats Richard Haass and Meghan O'Sullivan , were invited to Belfast by Martin McGuinness and Peter Robinson to seek an agreement over the issues of parades, flags and the legacy of the past. After a month long marathon of talks and discussions and brinksmanship over the last few days of December Haass produced a seventh version of the draft agreement for the five largest parties to sign up to. Both the Unionist Parties rejected the proposals, while the SDLP and Sinn Féin accepted them. Since then the SF Ard Comhairle has voted to accept the proposals. The position of the Unionist parties and those of Sinn Féin and the SDLP reveal much about the underlying contradictions and divisions in the North.
There are clearly emotive issues. The flag protests and the stand offs and conflicts around marches and parades both illustrate this, while the history of 30 years of armed conflict has impacted on thousands of people across the six counties and beyond. But the problems in the North run far deeper than the immediate issues on the negotiating table.
Over the last couple of years, however, tensions, particularly within the protestant community have become exacerbated, with claims that restrictions on controversial marches and parades and the decision of Belfast City Council to only fly the union flag on specific days represent a threat to the protestant community. The conflicts have threatened to boil over and escalate onto a higher level, a threat not only to catholic communities but to working class protestants also.
But the North is no longer a "grand wee place"; the economy has been devastated over the last 30 or more years. Many of the big industries have closed and the relative privilege of the skilled protestant workers has been eroded away. Ultimately it is the blind anarchy of capitalist economic laws that have undermined the historic alliance between the protestant workers and the unionist bourgeoisie. The figures speak for themselves. There are more people on sickness and invalidity benefits in the North than there are workers in manufacturing. That is perhaps the biggest factor underlying the threat to the way of life of the protestant workers. The catholic working class has also suffered, but never had so much to lose. That explains why the crisis in the North is most clearly manifested as a crisis of unionism.
For a more detailed analysis see: The emergence of dissident loyalism
Under these conditions it is no longer enough for the DUP to try and out bluster the Ulster Unionists for the majority of the protestant vote, they now have to deliver, and under current economic and social conditions that is far from easy. They have to watch their backs within the protestant community, and their strategy is of course to play on fears within the protestant community and to say NO. Martin McGuinness has accused Peter Robinson and the DUP of bowing to pressure from the Orange order the UVF and the PUP.
Sinn Féin have different issues to deal with, but it is evident that they must appear to be making some headway in the negotiations. After thirty years of armed struggle, years of negotiation and the peace process not one blade of grass has been liberated in the North. As has happened many times in the past, the tensions between moral and physical force republicanism will escalate, especially if there is an impasse. The flag protests and the issue of parades represent a threat to the dominant tendency within republicanism also, as the protests have a direct effect on catholic communities, especially where the communities interface with each other. So for Sinn Féin to retain credibility the negotiations have to succeed or at least show some signs of life.
This Easter marks the 16th anniversary of the Good Friday Agreement. But 2014 has begun with yet another set of failed negotiations to add to a long list. Even today the Assembly remains little more than a glorified County Council with very little power, administering public funds on behalf of the Westminster parliament. The leaders of Unionism and of Sinn Féin wile away the time administering bin collections and car parks, imposing cuts and slashing services in line with Whitehall strategies to balance the budget after the bankers were bailed out. The North remains in a blind alley, with no prospect of a way out on the basis of capitalism.
The extent of the problem is evident from official statistics:
"The seasonally adjusted claimant count rate in NI (6.7%) was higher than the UK average rate (3.8%) and was the highest rate among the twelve UK regions. This is the 44thconsecutive month that NI has had the highest or second highest UK region unemployment rate, on this measure. The monthly decrease in NI claimants (1.1%) was lower than the UK average decrease (2.8%) during the same period. The annual decrease in NI claimants (6.7%) was the lowest decrease of twelve UK regions (the annual decrease in the UK was 19.1%)" Monthly Labour Market report December 2013
Thousands of catholic and protestant youth face an uncertain future, with the return of mass unemployment and very little prospect of a positive change in the economic situation. The North may have escaped the initial impact of the economic crisis when it broke in 2008, but only because of the decisive importance of the state sector in the North. Now that the Assembly is delivering the British Government's cuts the economic situation in the North has deteriorated.
There may well be further negotiations and talks around the Haass document, but the contradictions in the North won't be solved by the stroke of a pen. As James Connolly predicted the partition of Ireland provoked a carnival of reaction. The only solution to the contradiction in the North lies as Wolfe Tome explained in the "men of no property". The problems of the North can only be solved as a part of struggle for a 32 County Socialist United Ireland.
As we explained in The emergence of dissident loyalism
"Alongside the sectarian tradition in the North there is also the tradition of trade union organisation and struggle. There are almost a quarter of a million workers organised in the trade unions in the North. That tradition reaches back to Connolly and Larkin, the Belfast Dock Strike in 1907 and beyond, but it is also present today in the magnificent struggle against the austerity and in defence of public sector pensions.
That is the basis upon which the Marxists and the most active and self sacrificing layers of the workers movement must organise. A Marxist Tendency armed with a socialist programme would tap not only into the revolutionary traditions of the Catholic working class but would also combat the unionist demagogy and reach out to the protestant workers on a class basis. Lenin, Trotsky and the Bolshevik Party fought for the unity of the working class in a country with a far more complex national make up than Ireland."


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The US to require incoming passengers to quarantine upon arrival
Passengers flying to the United States will be tested for COVID-19 before boarding a flight into the country, and they would need to undergo quarantine upon arrival, US President Joe Biden announced on Thursday.
Unveiling his national strategy to tackle the COVID-19 pandemic, Biden, during his remarks at the White House, said this strategy was created in response to address the past administration's failure to act with "the urgency and focus and coordination we needed."
"In light of the new COVID variants that we are learning about we are instituting new measures for individuals flying into the US from other countries. In addition to wearing masks everyone flying to the United States from another country will need to test before they depart and quarantine when they arrive in America," Biden said while announcing a raft of measures aimed at containing the spread of COVID-19.
The US President also signed several executive orders to combat the pandemic, including setting up a pandemic testing board and keeping workers safe.
He reassured Americans that restoring "public trust" is a top priority of his administration to fight the coronavirus pandemic. However, he added that the death toll from COVID-19 in the US is likely to top 5,00,000 next month.
"Things are going to continue to get worse before they get better. The memorial we held two nights ago will not be our last one, unfortunately. The death toll will likely top 500,000 next month. And the cases will continue to mount. We did not get into this mess overnight, and it is going to take months for us to turn things around. But let me be equally clear, we will get through this. We will defeat this pandemic. And to a nation waiting for action, let me be the clearest on this point: help is on the way," he said.
"Above all, our plan is to restore public trust. We will make sure that scientists and public health experts will speak directly to you," Biden said. "That is why you are going to be hearing a lot more from Dr [Anthony] Fauci again, not from the President but from the real genuine experts and scientists."
He called his plan to tackle the coronavirus pandemic "a wartime undertaking."
"Our national plan launches a full-scale wartime effort to address the supply shortages by ramping up production and protective equipment, syringes, needles…you name it," Biden said.
"And when I say wartime, people kind of look at me like 'wartime?' Well, as I said last night, 400,000 Americans have died due to COVID-19. That is more than the number of people who died in World War II. This is a wartime undertaking," he added.
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If you haven't joined our mailing list, please do so, especially if you are taking a telesecope out on May 19th. PLEASE, PLEASE do not send me an email with your email address - I don't have time to manually sign you up.
There are flyers posted, please cut and paste them to add to your own club's information to hand out on the night of May 19th. If anyone has flyers that they would like to share, please send them to me and I'll post them. Unfortunately, I don't know how to do the .pdf stuff yet, so it will be cut/paste also or I can post a link to your site if you have them download-able.
We just ask everyone to add our website address to any information handed out during International Sidewalk Astronomy Night so that the public can learn more about sidewalk astronomy if they wish.
May 19, 2007 will be the 1st International Sidewalk Astronomy Night and we invite all amateur astronomers to join us! We'll have telescopes out on the street corners, in front of movie theaters, in state and national parks, in city centre parks ... anywhere there are crowds of people, from San Francisco to Sao Paulo to Kharkov.
Our goal is to take 1000 scopes to the public on the same night worldwide, reaching hundreds of thousands of people and uniting amateur astronomers on different continents. We also hope many amateurs will try and like this different approach to astronomy outreach and will continue to hold sidewalk observing sessions throughout the year.
The events don't have to be large, one or two scopes at a location will be enough and if your club has more scopes and members, why not set up multiple observing sites around your city? We know that many clubs and organizations have regularly scheduled public events at local observatories and planetariums, so we hope that you can spare one or two members for sidewalk observing.
If you wish to be a part of this exciting event, please send an email to sidewalkastronomynight@earthlink.net with contact information and it will be posted immediately. Exact location isn't needed yet, but any contact information submitted will be posted on the website.
Also, for updates, please join our mailing list and we will notify you of our progress.


EngageReaders, the digital editions analytics tool developed by Twipe, has received the global 'Excellence in Predictive Analytics Award' from the World News Media Network (WNMN).
WNMN has announced last Thursday the winners of its Big Data and AI in Media awards during the BIGGIE Awards Ceremony in New York. Twipe's EngageReaders took the first place for 'Excellence in the Use of Predictive Analytics'. Winners in the other categories include The Washington Post, BBC, and Styria Media.
Annick Deseure (right) from Mediahuis was there to collect the award on Twipe's behalf.
Supported by Google DNI, EngageReaders provides the newsroom and product managers daily insights on content and composition of their digital editions. Through predictive modelling, EngageReaders identifies Overperforming and Underperforming articles and highlights Hidden Gems. Now live in newsrooms across Europe, EngageReaders first emerged as the result of a collaborative research initiative in 2015 between Twipe, KU Leuven, imec, and Mediahuis.
Interested in what predictive analytics can do for your newsroom? Talk to one of our experts now.
This entry was posted in Twipe news and tagged analytics, artificial intelligence, Digital Growth, Digital publishing, EngageReaders, Reader Engagement. Bookmark the permalink.


text:
Nikaia (en grec ancien  / ), morte vers 302 av. J.-C., est l'une des filles d'Antipater, régent de Macédoine, et la première épouse de Lysimaque.

Biographie

Dans le cadre des négociations matrimoniales qui suivent la mort d'Alexandre le Grand, Nikaia est censée épouser Perdiccas mais celui-ci est assassiné en 321 av. J.-C. Les sources historiques sont peu claires au sujet du supposé mariage avec Perdiccas. Certaines indiquent que Perdiccas épouse Nikaia afin de ne pas froisser le régent de Macédoine pour la répudier aussitôt au profit de Cléopâtre, sœur d'Alexandre. Eumène de Cardia aurait eu pour mission d'annoncer à cette dernière l'annulation du mariage avec Nikaia. D'autres mentionnent au contraire qu'Antipater refuse de marier sa fille à Perdiccas.

Elle épouse ensuite Lysimaque, roi de Thrace, dans le cadre de négociations de rapprochement entre ce dernier et son père. À sa mort, Lysimaque se remarie avec Amastris (302), puis avec  (300). Elle est la mère d'Agathocle de Thrace, fils aîné de Lysimaque que ce dernier fait tuer vers 283, d' et d'Eurydice.

En hommage à sa défunte épouse, Lysimaque renomme en 301 la cité d'Antigonie de Bithynie en Nicée (aujourd'hui İznik en Turquie).

Notes et références

Biographie
 .

Nikaia
Nikaia
Personnalité féminine de l'Antiquité
Personnalité féminine du IVe siècle av. J.-C.

redpajama_set_name: RedPajamaWikipedia


text:
What Is MTTR?: The DORA Metric You Need To Know
What Is "Mean Time To Recovery (MTTR)"? — A Complete Overview
Previously Published to Propelo.AI
DORA metrics are cornerstone to the software engineering culture that is DevOps. In fact, DORA is actually an acronym for "DevOps Research and Analytics," a practice that has been widely adopted by engineering organizations all over the world.
It's an excellent tool for improving the performance, productivity and efficiency of the software development lifecycle (SDLC) — but an even better tool for making sure products are safe, secure, reliable and always available to the end-user.
Since its conception, DORA has only consisted of four priority metrics:
Lead time for change
Change failure rate (CFR)
Deployment frequency (DF)
Mean Time To Recovery (MTTR)
It has since added the fifth metric of reliability, as most engineers are moving to the cloud and are pushing out smaller, more frequent deployments to their clients over time.
The DevOps lifecycle strongly advocates for automation and monitoring at all steps of software production, covering all facets of development from integration, testing, releasing to deployment and infrastructure management — but more specifically, it pushes for more reliable programs, an increase in stability and an always-on availability expected from software-as-a-service (SaaS) platforms of today. It also aims at shorter development cycles, increased deployment frequency and more dependable releases — all of which closely align with ongoing business objectives.
To understand the potential impact of risky build iterations and repair procedures, engineers must also pay close attention to operational needs within the production environment.
While their primary focus should always be on the reliability and functionality of a quality product, they must also keep in mind that eyes are on them at all times — and that business clients and executives don't take kindly to delays, losses or even downtime should unexpected troubles arise.
Engineers should always plan ahead — to mitigate risks and fool-proof the system.
By leveraging DevOps-related strategies, they will see a tremendous improvement in deployment frequency, lead time, the detection of cybersecurity vulnerabilities and flaws, the mean time to repair and mean time to recovery.
Mean Time to Recovery (MTTR) Explained
"Mean Time to Recovery" is the amount of time it takes, on average, for a system to rebound, or recover, from a disruption of service or total failure altogether. As an incident management metric, it's essential to quantify and track downtime — whether the interruption is due to a recent deployment or an isolated system failure. The name itself is synonymous with other "mean time" calculations but generally shares the same concept for repair and recovery during the software development lifecycle (SDLC) or related services. Each of these concepts has a similar meaning with a slightly different definition. Most of these will be covered throughout this blog and include:
Mean Time to Fix
Mean Time to Respond
Mean Time to Resolve
Mean Time to Resolution
Mean Time to Remediate
There are other incident metrics used alongside MTTR to assess the performance of DevOps and ITOps processes. They're used to evaluate the effectiveness of determining fixes, to detect the reliability of applicable solutions and to measure how easy it will be to maintain systems both during and after remediation:
Mean Time to Failure (MTTF)
Mean Time to Acknowledge (MTTA)
Mean Time to Detect (MTTD)
Mean Time to Identify (MTTI)
So, what is Mean Time to Recovery?
MTTR is often explained as the time that it takes for engineers to not only find a problem but to realize the problem, decide the best plan of action in remediating that problem, how long it takes to apply the fix and what it takes to get the platform back up and running — at full functionality.
In the incident management process, MTTR serves as a key performance indicator (KPI) that allows engineering teams to improve their response to issues both controlled and undetectable.
Atlassian, the creator of Jira and Trello, provides some clarity on this matter, suggesting that it's a good idea to define which MTTR a team has adopted before tracking successes and failures. The company states that "a team needs to be on the same page about exactly what you're tracking and be sure everyone knows they're talking about the same thing,"
It's just one step in the incident response process and one way engineers can gauge how quickly problems can find remediation and how soon new changes can be shipped out after that. It also provides deeper insight as to how stable a product actually is, primarily when delays have caused teams to work under stricter timelines and scrutiny through to delivery. The faster a system can be recovered, the least likely issues will worsen — and a higher probability for customer satisfaction.
Sometimes that means slowing down a bit.
When faced with a major issue, teams should only focus on this one problem — even if it means putting the entire project on hold to correct these errors. Cutting corners can lead to much bigger problems, and a domino effect can occur if the SDLC continues without resolution.
Controlled testing should immediately take place to decide whether there's a problem. Here are a few questions to ask the engineering team:
Which data was monitored, and did anything stand out?
Did the system fail in a way that would otherwise be expected?
Was the system an easy fix, and was it able to be handled quickly?
How long did it take for the service to be restored once an issue was detected?
Both recovery speeds and response times mirror the team's ability to not only diagnose problems but to correct them.
Engineers should focus on building a more robust system for recovery. This often includes an expanded view of real-time data and increased control over monitoring and analysis. In this same sense, teams will become more careful when preserving quality and even more concerned about improving the product throughout the development process.
What is Mean Time To Restore (MTTR)? Why is it important?
MTTR can also represent the time it takes to restore business-critical services from a failure in production, whether it's an unplanned outage or simply a loss of service. Production issues can significantly impact the customer experience and should be prioritized to avoid displeasure with the system.
For this, engineers will want to know how much time it will take to recover from specific failures during production and how quickly those issues can be resolved on average. Some will go as far as building continuous improvement, continuous delivery systems that report failure and alert the teams as soon as an issue presents itself.
If you've read our whitepaper on DORA Metrics, you probably already know that measuring MTTR can be trickier than it appears because service failures and outages can be of different types or severity. This ultimately causes the reporting of a single MTTR score to be incorrect and of no value.
In some organizations, especially those with smaller teams, minor and low-severity issues are almost never prioritized or fixed. And so it's said that they should not be counted towards the final MTTR calculation.
Service desks and production monitoring systems are necessary in order to accurately track MTTR data, prioritize system recovery and improve deployment times. Flagging particular changes or features within a system will allow engineers to quickly reference timestamps or to toggle between features. This will allow them to better understand what went wrong and to identify which problems are occurring at present while potentially bringing the MTTR down to just seconds on the hour.
What MTTR Is and Isn't
MTTR is one of the most widely used metrics — and one of the most misunderstood metrics — in what's often called the "systems reliability toolbox."
Because so many engineers have a different understanding of what MTTR actually means, it can be, at times, hard for everyone to get on the same page. Since each instance of MTTR has a slightly different meaning, teams that lack clarity on the true definition of what MTTR means to them — or a clear vision for what needs to be done — may see more harm come than good, as the most minute differences can throw the entire repair and production off its course.
There needs to be a unified front among teams on how to use this metric, how to improve it and how to execute it in a sustainable yet consistent manner. There needs to be one set of rules in place — a single set of rules that determines how performance will be tracked, measured and adjusted across any given number of changes.
MTTR allows teams to set standards for reliability, accelerate velocities between sprints and increase the overall quality of the product before it's delivered to the end user.
With continuous improvement at the helm of what DevOps actually represents, metrics should also factor in the lead time for changes, ongoing change failure rate and the deployment frequency thereafter.
MTTR can be a powerful predictor of the impact incidents can and will have on the organization's bottom line. The higher the MTTR, the greater the risk of significant downtime. The lower an organization's MTTR, the lower the risk for downtime — if at all — during the recovery process.
Delaying repair or incident response procedures to issues that have already occurred could mean potentially leading the business to further disruptions, customer dissatisfaction and loss of revenue.
Understanding the mean time to repair helps teams define and optimize DevOps incident management procedures — which is especially critical to the greater picture. If managed properly, minimizing MTTR can fortify the resiliency and stability of a product, add an extra layer of protection against system failure and lead to longer "uptimes" for the end-user. MTTR is also used in DevSecOps to establish cybersecurity measures when measuring a team's ability to neutralize system attacks.
To further address what MTTR is or isn't, we must first understand the differences between the various definitions:
Mean Time to Recovery (Mean Time to Fix)
Mean time to recovery exists as a metric to assess the entire incident management process. It's the time that lapses from the first sign of failure during production or deployment until the complete restoration of production or service-related operations. In other words, the mean time to recovery is how long it takes on average for applications in the production stage of deployment to fully recover from system failure and can be directly applied to:
System and application deployments
Backup and data lifecycle management
Change and patch management
Platform governance
This is the actual time spent during system recovery and fixing the problem when tackling outages. This does not include any delays from the discovery of each incident to the beginning of the recovery process.
This is the average time it takes to fix the issue, test the fix and successfully apply the fix.
This is the average total time spent diagnosing and fixing the problem, restoring the product or service and applying a fix. It also includes the time spent on safeguarding products against future failures.
What is the MTTR Formula?
Although MTTR is essentially the same metric across the board, the incident management process requires decision-makers to decide which instance of MTTR will be used based on situational analysis. Because each iteration is slightly different, choosing the wrong formula could lead to much more significant issues further down the line. So, it's up to leadership to decide which one is most adequate.
Slight changes to the meaning of MTTR will mean slightly different calculations will be used to estimate a mean time or velocity. As an example, here are five different formulas that demonstrate how to calculate MTTR:
Stability of systems = change failure rate + mean time to recovery (MTTR)
Mean time to repair (MTTR) = total time spent repairing in any given time period / # of repairs
Mean time to recovery (MTTR) = total time spent in discovery and repairing systems / # of repairs
Mean time to resolve = total resolution time during any given time period/ # incidences
Mean time to respond = Full response time from alert to fix / # of incidents
Accuracy can be increased by implementing data found using system timestamps. Developers need to know when an incident occurred and when it was effectively resolved. Understanding the root cause for system failure will also allow teams to pinpoint when the system went down and how much time lapsed between discoveries.
By knowing which deployment resolved an incident and the steps taken to mitigate each incident, further calculations will allow us to decide whether the service has been restored effectively and whether the user experience has suffered from such an event.
What is MTTR vs. MTBF?
MTBF is another key performance indicator (KPI) that addresses the average "mean time between failures," as used to track both the availability and reliability of a software-based product or service.
Unlike MTTR, which looks at a lower mean time as an indicator of a healthy system, the higher the mean time is between failures, the more reliable the system is considered. And because of this, most companies aim to keep the MTBF as high as possible — eliminating any and all opportunities for failure, as long as it's in their control.
The MTBF is calculated by finding the mean, or average, between failures over a designated period of time — whether a year or six months. Each stretch of time between failures is added up and then divided by the number of total failures within the selected period of time.
Because the metric is used to track reliability, MTBF does not factor in expected downtime during scheduled maintenance or testing procedures but instead focuses on the unexpected outages and issues faced due to outside sources or influences that dictate service capabilities.
In an enterprise, engineers should aim towards reducing the MTTR while increasing the MTBF to minimize — or completely avoid — unplanned downtime and failure. While an MTBF is generally a metric used when failure occurs within a repairable system, MTTFs typically occur in systems that require replacement.
With that said, this metric also serves as a tool for leadership when making more informed recommendations to their customers on replacing or maintaining particular parts, bug fixes or system upgrades.
If Used Together, MTBF, MTTR, MTTA, and MTTF Can Improve Incident Management While Reducing Downtime and Failure.
Failure metrics allow enterprise-level organizations to track the reliability and security of technical environments. This includes the hardware, software and infrastructure necessary to conduct day-to-day operations. This includes the tools and networks that provide added value to the technical environment — and the ecosystem that connects businesses across continents and territories.
They're used for troubleshooting service requests and pinpointing issues with connectivity. Certain metrics relate to server failures — and others, the replacement of degraded or malfunctioning parts.
Unfortunately, when systems aren't properly functioning, businesses will experience unnecessary downtime. Failure metrics allow us to restore systems before it negatively impacts the business — or the business of our customers.
We need to proactively detect issues before advancing to production. Large data sets need to be collected, processed and then analyzed when gathering both qualitative and quantitative data. This task can become quite tedious, but automating workflow activities, full-scale incident reports and internal management systems can dramatically control response times and lead us to resolve incidents in real time.
Proper visibility can make or break MTTR-related action plans while holding future failures and incidents at bay. Of course, critical incident response procedures should first be established to limit how much time lapses between recovery and the greater number of offenses that normally take place. But knowing how and when to use mean time will improve the organization's response to any given failure, saving the company and its clientele from unnecessary expense, backlash or uncertain delay.
MTTR Performance Benchmarks
A more complete and accurate picture is revealed when MTTR is paired with other metrics during the recovery process. Performance, cost-basis and the impact of downtime can be predicted based on the occurrence of MTTR and how often it arises during production. As the MTTR trends downward, teams will begin seeing a clear indicator of healthier and improved systems for deployment.
The root cause of failure becomes clear when MTTR has been reduced, making it possible to develop strategies toward remediating related instances further down the line. It also signifies a more reliable and stable environment, where bugs become smaller, easier to fix and identifiable during earlier stages of production.
Key Performance Indicators (KPIs) also include:
Instances of dependencies when system fixes become untethered
How often incidents are repeated over a specified period of time
How often new production is halted until past issues have been resolved
The nature and expediency of ongoing feedback loops
The velocity, quality and performance of activities between sprints
A sign of continuous improvement is when issues are either non-existent or are more easily managed over time. Implementing faster feedback loops and mechanisms can improve software builds earlier in the SDLC pipeline. Rapid iterations can mean warding off negative consequences by providing immediate attention to areas where "things just don't seem right."
Smaller packages and quicker fixes allow us to pinpoint the first sign of failure before it becomes a real problem. Planning for failure allows us to reduce MTTR by mitigating failure, rolling back unsuccessful deployments and improving the overall experience — one package at a time.
The Problems and Causes of Poor MTTR
The challenges surrounding MTTR begin with how we define the term.
Businesses — enterprise businesses, in particular — are more heavily and increasingly relying on cloud and software services to operate at their highest efficiency. As a result, any downtime to systems could translate to a disruption in revenue, productivity or dependability.
Disruptions can directly impact the reputation of a business and the ability to effectively conduct operations while the system is in downtime. It could also prevent them from providing a premium customer experience, expected to always stay online.
Generally, MTTR is typically used when talking about unplanned incidents, not service requests, and is only calculated based on business days or hours — which depending on how the team handles this situation, could be a good thing or a bad thing.
If they decide to work through a weekend (or overnight) in the case of extreme failure, they can have a system back up and running by Monday morning, whereas businesses may not even notice that any failures ever took place. However, engineers could face burnout without time off later in the week. MTTR is also not factored in using weekend days or hours. This could add additional complexity when calculating MTTR.
This is where teams need to be transparent and when defining the exact implementation of MTTR is of the utmost importance. The wrong calculation can lead to unrealistic turnarounds or expectations across the incident management process.
Depending on the business model, this could also add a significant cost and risk to the business or its business customer.
Businesses that have implemented a solid MTTR action plan could avoid disruptions by acting quickly, implementing an immediate fix and then testing the system.
In the case of delay or downtime, optimizing MTTR action plans could be the difference between an hour or a few days. Although, anything that takes more than a day could indicate poor alerting or poor monitoring and can result in a larger number of affected systems.
Because the mean time to repair doesn't necessarily equate to the time it takes to repair the system with the actual downtime of the system outage itself, there could be some confusion as to how long it actually took to get the system back up and running. This would be especially true if other projects demanded priority, pushing the repair back even further behind schedule. In such circumstances, it's quite common to see a certain lag between when the issue was first detected and when the repairs initially began.
That said, there are limitations when it comes to certain instances of MTTR. When deciding which iteration best serves the entire recovery process, one must answer the following questions:
Is the issue being handled as quickly as it needs to be?
Does the recovery team have the adequate tools, skills and training to carry out the recovery process?
Is the team taking too long to find and implement fixes?
How costly is downtime to the business or its customers?
How does the company's average downtime compare to its competitors?
Are maintenance teams acting as effectively as they could be?
Is it taking too long for someone to answer or respond to a fix request?
How many issues are actually causing the delay?
Are these delays happening due to an inadequacy among the team — or is there something more sinister at play?
Are teams as effective as they could be? What could make them more effective?
Without the adequate data, it will be hard to arrive at the correct answers. But perhaps another issue could be plaguing the scene:
Are there unnecessary delays taking place between a failure and an alert?
Are alerts taking longer than they should to get to the right person?
Are there other processes that could be improved?
Is there a lack of direction?
Is there a significant amount of data, a need for leadership or visibility?
How much time is the team spending on repairs vs. diagnostics?
While MTTR is most useful when tracking how quickly teams can repair an issue, there's little to factor in when it comes to prepping systems for repair or when faulty system alerts have been causing delays. In this case, the issue is somewhat unrelated to the system itself but necessary to tackle when further trying to close the gap on excessive delays.
The problem could reside within the alert system, or it could be related to automation, incompatibility and diagnostics.
Under these circumstances, any instance of MTTR may just not be enough. While the mean time to recovery is a great starting point for diagnosing unknown problems, other factors will need to be considered when carrying out the recovery process.
Alert fatigue is the byproduct of MTTR-related processes and procedures, unaffected and overlooked by MTTR Itself.
In the case where no particular issue stands out, alert fatigue could be a primary factor. We use alerts when automating our systems for issue discovery. We even become somewhat dependent on them. The phenomenon behind alert fatigue isn't necessarily detectable, as this is a human-related factor as opposed to technical.
Alert fatigue happens when we've become overwhelmed by or desensitized to alerts. Think of it like when someone has slept through an alarm. When engineers are tasked with responding to incidents around the clock, they're so used to hearing these alarms and may not realize an alarm has gone off. When engineers become fatigued by these alarms, they'll often ignore or even miss a few alerts — ultimately delaying the response time for fixes and allowing the problem to worsen before they even realize it.
A few things that could be done to combat alert fatigue include:
Reducing noise so that engineers don't overlook these alerts
Prioritizing alerts to refocus on issues that matter the most
Alerting entire engineering teams of incidents as they occur, escalating failures and routing those incidents to engineers who are both available and equipped to immediately respond in the moment
Establishing a solid incident retrospective, or a thorough plan to follow up, on all incidents for reassurance that repeat incidences will not occur
A troubleshooting process is essential when uncovering non-MTTR, MTTR-related issues. It's equally important to diagnose the incident in its entirety and determine the correct fix without cutting corners on the road to recovery. This isn't a situation where technical debt should be considered, and much larger issues could accumulate further into the future.
How to Improve MTTR through Action, Observation and Engagement Strategies
Create a fool-proof incident response process, ensuring that teams act with a sense of urgency to eliminate issues as soon as they are detected. Assess each dependency and acknowledge ongoing bottlenecks, further documenting everything that sets a precedence for potential failure going forward. Provide context and suggest action items in regard to such resolutions across the entire ecosystem.
Develop a robust plan of action to promote the deployment of more frequent, bite-sized changes across the SDLC, ensuring that any and all future issues will be easier to identify and apply a fix in the event anything should go wrong. An efficient yet effective incident-resolution process should also be developed, with the primary focus on reducing MTTR.
Improve both incident resolution times and workflow strategies to accelerate the process of remediation and establish a clear plan for escalation, including who to call and who will lead should a problem ever arise. Budgets should be allocated and easily accessible for times of incident in order to avoid unnecessary delays in approval when, instead, special tools and resources should be secured and put to use right away.
Commit to long-term service reliability — develop the mindset that once a problem is fixed, it stays fixed no matter how long.
Train interdisciplinary teams for cross-functional collaboration, ensuring that while specialists may be available, they will not become overworked or burnout — especially at times when they're needed most. By developing more efficient teams at the most foundational level, absences won't disrupt the team's overarching ability to tackle each problem.
Among many other reasons, it would be wise to name leads for both technical and communicative aspects of the department or team. These expert voices and opinions would represent the needs of both internal teams and business leaders within the organization — providing very clear information as it relates to the operational and technical nature of the business, especially in the case of an immediate incident, delay or failure.
Hold teams fully accountable for closing the loop on the incident resolution process.
Each lead should serve as a buffer between various departments and make informed decisions on behalf of the engineering department. They should assess how many systems are impacted and present possible solutions in each matter.
Test the system's resiliency by implementing chaos engineering into the recovery process. Uphold all service level agreements (SLAs), and remind everyone that quality is not an option
On the side of automation, leadership should consider alerting engineering teams of certain and identifiable failures. Tools should be thoughtfully calibrated for situations when issues are almost inevitable.
Stay Alerted to Failure with Around-the-Clock Incident Management
Real-time monitoring systems will provide accurate reads and average response times for a variety of complex metrics. These will provide teams with more solid, concrete facts that are devoid of all guesswork associated with incident management.
Many of these dashboards now include systems that will alert on-call team members during times of maintenance, testing and system disruption. Take control of these alerts to minimize alert fatigue by setting thresholds for notification.
Propelo can integrate with many systems, such as Jira, Salesforce service desk, or PagerDuty, to measure the MTTR. Propelo lets you take a scalpel approach to precisely measure certain types of failures across all your teams and gives you a much more standardized view of MTTR across all your teams.
Learn more about Propelo's Engineering Excellence platform and how DORA Metrics can help your engineering organization to succeed!
BusinessCFRChange Failure RateDeployment FrequencyDeveloper HappinessDevelopment Productivity EngineeringDevopsDPEGoogleIssue MangementIssue ResolutionLead Time to ChangeMean Time to RecoverMean Time to RecoveryMean time to repairMean time to ResolutionMTTRProject ManagementPropeloSPACE FrameorkSPACE FrameworkSRETechnologyThe State of DevOps 2023Troubleshooting
Financial Transparency is Key to Any Relationship, Financial Infidelity Being the Ultimate Killer
Avaya and Plantronics Join Forces in the Name of Unified Communications
Delphi360™ to Officially Launch, Improve the Work Environment and Change Indoor Air Quality Forever


text:
Cultural Diversity and Sustainable Development for Peace
Two wings for our world to fly in the sky of Peace
UN: Four Peacekeepers killed in an attack in northern Mali
On April 2, 2021, the United Nations reported a deadly attack against the peacekeepers in Mali which killed 4 and injured 19 peacekeepers from Chad. The United Nations mission in Mali (MINUSIMA) said in their statement that the "peacekeepers valiantly repelled a complex attack carried out by several heavily armed terrorists." They were reportedly attacked in their camp in Aguelhok in Northern Mali which was around 200km from the Algerian border.
The attack follows several others in Mali with over 120 peacekeepers killed since the mission was established in 2013, making Mali the UN's most dangerous peacekeeping operation. The United Nations Multidimensional Integrated Stabilization Mission in Mali (MINUSMA) was deployed in July 2013 to help stabilize Mali and assist the country's return to constitutional order after being overrun by a coalition of Tuaregs and terrorist groups in 2012. This mission was constituted after the unsuccessful attempts by the African Union and France in resolving the conflicts.
Reports of this attack also come after UN investigators concluded that at least 19 civilians were killed in an airstrike by France which discredited France's claims that only rebel fighters were hit. Such civilian casualties and the increasing hostilities from the terror groups further seem to indicate the need to find non-violent solutions to these conflicts. Many experts stress on the importance of actions that focus on climate change and protection of environment along with dealing with the intercommunal tensions, rather than the deployment of more troops into these war torn areas.
Posted in News, PB News and Reports
CD4Peace
Suicide bombing on a cathedral in Indonesia
Mozambique : Violent clashes, raids, and massacres are leading to a humanitarian catastrophe


This can be done by adding an Xpath url element in a KBA set. You can either define a specific sampler name or the parent sampler name of the target.
This can be generalised to get the name of any element that has one, just replace sampler with whatever you need.
For example, we have a KBA Set named "Sampler page". The KBA "Sampler URL" has three url elements. One of which is an xpath using the ancestor function to get the sampler name above the target of the KBA which is the cell of the dataview. The configuration of your KBA set should follow the xml codes below.
For further details regarding ancestor functions on relative paths, please refer to 31.3 Appendix E of the Gateway Technical Reference Guide.


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La rozenita és un mineral sulfat de ferro poc comú, amb fórmula química Fe2+SO₄·4(H₂O). Pertany i dona nom al grup de la rozenita.

Es presenta com mineral secundari, que es forma sota humitat baixa a menys de 21 °C com a alternativa sense coure al mineral melanterita el qual és una alteració post mina de la pirita i la marcassita. També es presenta la rozenita en sediments lacustres i dipòsits de carbó. Els minerals associats inclouen la melanterita, epsomita, jarosita, guix, sofre, pirita, marcassita i la limonita.

Segons la classificació de Nickel-Strunz, la rozenita pertany a "07.CB: Sulfats (selenats, etc.) sense anions addicionals, amb H₂O, amb cations de mida mitjana" juntament amb els següents minerals: dwornikita, gunningita, kieserita, poitevinita, szmikita, szomolnokita, cobaltkieserita, sanderita, bonattita, aplowita, boyleita, ilesita, starkeyita, drobecita, cranswickita, calcantita, jôkokuita, pentahidrita, sideròtil, bianchita, chvaleticeita, ferrohexahidrita, hexahidrita, moorhouseita, nickelhexahidrita, retgersita, bieberita, boothita, mal·lardita, melanterita, zincmelanterita, alpersita, epsomita, goslarita, morenosita, alunògen, meta-alunògen, aluminocoquimbita, coquimbita, paracoquimbita, rhomboclasa, kornelita, quenstedtita, lausenita, lishizhenita, römerita, ransomita, apjohnita, bilinita, dietrichita, halotriquita, pickeringita, redingtonita, wupatkiita i meridianiïta.

Va ser descrita per primera vegada el 1960 a les Munyanyes Ornak, a les Muntanyes Tatra occidentals, Małopolskie, Polònia. Reben el nom del mineralòleg polonès Zygmunt Rozen (1874–1936).

Referències

Minerals de ferro
Grup de la rozenita
Minerals descoberts a Polònia


@motherofpearl1 wrote: I can't help but think Rian made one mistake when he 'moved' the scar.
I think they put themselves in a catch 22 with the scar. Had the current position of the scar been actually where Rey sliced him, he would have lost his eye. At the same time, if they had kept it where it was at in TFA, to use Rian's exact words, he's right it would have looked goofy. Interesting that they want to keep the dark and dangerous dreamboat motiff with Kylo for TLJ so much that they're willing to sacrifice continuity to do so.
Which is possibly the most intriguing thing about TLJ....why do they want him to be attractive?
Totally. If he were to remain "evil" for the entire trilogy they would have made him lost his eye. I think he would look more menacing that way.


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Pending Business: Is Radio Still the Frequency Medium?
TALKERS | August 23, 2021
By Steve Lapa
Lapcom Communications Corp
PALM BEACH GARDENS, Fla. — Do you remember this rule from basic sales training? Radio is a frequency medium. Radio is the more efficient way to deliver a message with high repetition to a qualified audience and for measurable results; your message needs to hit your target audience at least_____times.
How many times should a target consumer hear an audio message to generate response?
Pick a reasonable number that will trigger a purchase cycle, before the message becomes an irritant. Can't find a number? You are not alone. I think the rules have changed faster than you realize.
TALKERS | March 1, 2021
Monday Memo: On the Air, In the Air. Repetition is a powerful radio tactic. As billion-plus-dollar lawsuits and corporate censorship edicts throttle toxic talk post-January 6, consultant Holland Cooke asks, "Should it take that?" In this week's column, he cautions that credibility is on thin ice. Read it here.
Pending Business: Stop Fighting, Start Selling. Sales and marketing pro
Steve Lapa, president of Lapcom Communications Corp, writes in today's column that the natural reaction from sellers who face objections is to fight. "Your overwhelming instinct is to defend the pitch as designed and sidestep the objections. The poise and discipline you've practiced when physically face-to-face with your advertiser is lost in the current fast-moving, rapid-response world of email and text. You push your point instead of 'listening' to the voice behind the words in the email, text, or other digital reply." Read Lapa's six steps for overcoming this urge here.
Round Four of January PPM Ratings Survey Released. The fourth and final round of ratings data from Nielsen Audio's January PPM survey has been released for 12 markets including: Austin, Raleigh, Indianapolis, Milwaukee, Nashville, Providence, Norfolk, Jacksonville, West Palm Beach, Greensboro, Memphis, and Hartford. Nielsen's January 2021 survey covered January 7 – February 3. TALKERS magazine managing editor Mike Kinosian presents his Ratings Takeaways from this group of markets. In Austin, Waterloo Media's news/talk KLBJ-AM rises 1.5 shares to finish with a 5.7 share and the #4 rank in the market. iHeartMedia's news/talk WTKK-FM, Raleigh jumps from #5 to #3 after tacking on 1.6 shares for a 7.0 share finish. In Indianapolis, Emmis Communications' news/talk WIBC-FM jumps to #1 after adding 1.3 shares to finish the survey with an 8.9 share. And in Milwaukee, iHeartMedia's WISN-AM takes over the #1 rank after adding 2.8 shares for an 11.0 share, while Good Karma Brands' crosstown news/talk WTMJ-AM rises a half share to a 6.5 share good for the #3 rank. See Mike Kinosian's complete Ratings Takeaways report for this group of markets here.
John Fredericks Expands Radio Network into Atlanta. In a Local Marketing Agreement deal with WMLB-AM, Avondale Estates, Georgia owner Delmarva Educational Association, the Richmond, Virginia-based John Fredericks Radio Network begins programming the station and launches a conservative talk format. Talk host and CEO John Fredericks says, "News/talk radio is the last bastion of free and
unencumbered speech in America. It's our final frontier of free speech, and it's a community devoid of the cancel culture now stifling and squashing free and open discussion in our country. We are honored to bring our fresh and dynamic brand of news/talk radio and cutting-edge commentary to our Atlanta metro listeners." In conjunction with the launch of the format, John Fredericks Radio Network announces the launch of the daily "Doug Collins Show" hosted by the former Georgia Congressman. It will air from 3:00 pm to 4:00 pm on WMLB-AM. Fredericks adds, "We are very excited to have Doug as part of our radio syndicated network and I believe his show will become immediate must-listen radio not only in Georgia but nationally. Doug has always had his finger on the pulse of America." Collins' show will also air live on Fredericks-owned stations in WJFN-AM/W224EB, Chester, Virginia and WJFN-FM, Goochland, Virginia.
Entercom Makes Lineup Changes at Portland's '1080 The Fan'; Brings AJ McCord Aboard as Midday Co-Host. Portland sports talk outlet KFXX-AM, Portland, "1080 The Fan" announces the addition of KOIN-TV sportscaster AJ McCord to the 12:00
noon to 3:00 pm show alongside Dusty Harrah for the "AJ and Dusty" show. Harrah moves from morning drive as the midday "Dirt and Sprague" show with Andy "Dirt" Johnson and Brandon Sprague shifts to morning drive. FOX Sports Radio's "The Herd with Colin Cowherd" continues in the 9:00 am to 12:00 pm slot and "Primetime with Isaac and Suke" featuring Isaac Ropp and Jason Scukanec continues in the 3:00 pm to 7:00 pm daypart. Entercom Portland SVP and market manager Kim Martinez says, "I'm so excited about this enhanced lineup. With Dirt and Sprague making the well-deserved move to mornings and the addition of AJ McCord in middays, '1080 The Fan' will continue to provide the best content and entertainment for our listeners, and results for our advertisers."
Leverage All Your Past, Present And Future Content For Years To Come
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Morning Radio Host Russ Martin Dead at 60. Dallas morning drive personality Russ Martin – host of the "Russ Martin Show" on iHeartMedia's classic rock KEGL-FM,
Dallas "97.1 The Eagle" – was found unresponsive at his home in Frisco, Texas early Saturday morning after a friend performed a wellness check. Authorities say the cause of death has not been determined but say that at this point, there is no foul play suspected. Martin was a longtime North Texas radio personality. He hosted an eponymous show on then-CBS Radio's "Free FM" hot talk format on then KLLI-FM prior to its flip to sports talk as KRLD-FM "The Fan" in 2008. He joined KEGL in 2010.
Key Networks Launches 'Bloomberg Business of Sports' on 100 SportsMap Radio Affiliates. The radio show "Bloomberg Business of Sports," hosted by Michael Barr, is debuting today on 100 SportsMap Radio affiliate stations across the country. Key Networks is syndicating the program that "takes listeners inside the business end of
the sports world and explains what it means to fans and their pocketbooks. The show follows the money in the world of sports and the decisions that power the multi-billion-dollar industry. From media and technology to finance and real estate, leagues and teams across the globe have matured into far more than just back-page entertainment. The show reports on sports trades, salaries, endorsements, contracts, collective bargaining and more – all from an insider's perspective and explains the money behind the final score." Key Networks chief revenue officer Dennis Green says, "In today's world, sports and business align more than ever. There is no brand better equipped than Bloomberg to report on the news and events that impact the business side of sports. We are delighted to bring this content to the SportsMap network and their affiliates around the country."
iHeartMedia Launches 'FOX Sports 1230 The Gambler' in Toledo. WCWA-AM, Toledo is now "FOX Sports 1230 The Gambler." Station owner iHeartMedia announces the programming lineup will consist of content from FOX Sports Radio and VSiN
(Vegas Stats and Information Network). The company says the lineup will offer listeners betting guides, handicapping and strategies plus signature programming from FOX Sports Radio, including "The Dan Patrick Show" and "The Herd with Colin Cowherd," as well as highly respected Toledo sportscaster Anthony Bellino on weekday mornings. iHeartMedia Ohio and West Virginia SVP of programming Scott Sands says, "'FOX Sports 1230 The Gambler' is the future of sports radio. We are thrilled to bring this hot new format to Northwest Ohio and Southeast Michigan, assisting our growing audience in navigating the ever-growing world of sports wagering."
Trump at CPAC, COVID-19 Stats & Vaccines, Biden's Stimulus Bill/Minimum Wage Issue, Cuomo Allegations, Virginia Legalizes Pot, Myanmar Protests, and Golden Globe Awards Among Top News/Talk Stories Over the Weekend. Former President Donald Trump speaks at the final day of the CPAC in Orlando; the falling number of COVID-19 cases in the U.S., Johnson & Johnson's vaccine is approved, and concerns about variants; President Joe Biden's $1.9 trillion stimulus package passes the House and the battle over the $15/hour minimum wage proposal; the allegations of sexual harassment against New York Governor Andrew Cuomo and increasing calls for his resignation; Virginia becomes the 16th state to legalize marijuana; more violent protests break out in Myanmar; and Sunday night's virtual Golden Globe Awards were some of the most-talked-about stories on news/talk radio over the weekend, according to ongoing research from TALKERS magazine.


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Switching of tasks becomes easy: When you have acquired a right payroll software for your business operations, the switching of multiple tasks becomes easy. The latest software does the tricks for your business in various ways. Using the software one can easily manage the different process of employee pay, leave, attendance, time, rota and document management in the blink of an eye. The management can save hours of data input and duplication by switching over to the latest payroll software.
The Employee can manage their personal data: The management is not always free for the tedious tasks like revising or correcting the employee data as per the requests and emails. Using the updated software helps the management to authorize the employee for updating his personal information without any waste of time.
Unless you ditch the old payroll software, you won't be benefited with the new payroll features. An another advantage of using a highly efficient payroll software is it helps you to get the most out of the system such as automation of the flow of data from the employees. Either it is reporting, leave management or employee rotas, you can beat the clock with the help of the latest payroll software.
Finally, it is the time to convince your boss of a latest and an efficiency payroll software that makes management simple and easy.


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CAT'S RETURN
Cat Deeley says she moved back to the UK after 'terrifying' mall shooting left her husband and son 'shaken'
Nick Ferris
Updated: 16:09, 13 Sep 2020
CAT Deeley has said that she moved back to the UK from California after a "terrifying" mall shooting left her husband and son "shaken".
The 43-year-old TV presenter has revealed that part of the reason why she wanted to leave the golden state was that her husband Patrick Kielty and their eldest son Milo were caught up in a mall shooting.
Cat Deeley has said she moved back to the UK from California after a "terrifying" mall shooting left her husband and son "shaken"Credit: Rex Features
In an interview with You magazine, Cat said Patrick, 49, and Milo, 4, were shopping in the Century City Mall in Los Angeles when FBI agents announced there was a shooter on the loose.
She said: "I got a call from Paddy, saying, 'They're taking us out through the fire exits but nobody can get to their car. If we walk to a junction, can you come and get us?'
"He wanted to keep Milo calm, so I didn't understand the enormity of what was happening.
"As I was driving I began to see helicopters, news vans, firemen and SWAT [armed police response] squads.
Cat's husband Patrick and their son Milo were both caught up in the Century City Mall shooting in Los Angeles, picturedCredit: CBSLA
Mall shootings have become a tragically common occurrence in the US. Pictured: people hug following a shooting in a mall in Indiana on SaturdayCredit: AP:Associated Press
"It makes me go funny now. It was terrifying... Paddy was shaken by it, more than Milo, who was hot and cranky but didn't properly understand."
Cat feels happy to be home after swapping her mansion in Los Angeles for a flat in north London.
The Sun exclusively revealed last month that Cat, Patrick, Milo and youngest son James, 2, had put their 4-bed mansion with a desirable 91210 zip code on the market for a whopping $4,995,000.
A source close to Cat told The Sun: "She still has multiple projects in the works in the US and will be here and there for work, but she will be based in Britain for now."
Cat feels happy to be home after she and her husband swapped her mansion in Los Angeles for a flat in north LondonCredit: Splash News
The family's return home means that Milo and James will now begin school in the UKCredit: Instagram
In her interview with You magazine, Cat added that the risk of a shooting had also unnerved when looking at school for Milo.
She said: "There was a moment when I was with a friend looking at potential schools for Milo and we had to ask the question nobody wants to 'What do you do if there is a live shooter on the premises?'
Most read in Celebrity
"They tell you exactly what would happen, whether the kids would go to a safe room or hide under the desks…
"The danger suddenly becomes a reality."
The family's return home means that Milo will now begin school in the UK, while Cat's parents will now be available to help with childcare.
Cat Deeley reveals Ant and Dec broke down in tears filming SM:TV documentary - and it's out at the end of the year


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Auction clearance rate tops 57 pc in SE Qld
by webmaster 07 March 2012 1 minute read
South East Queensland's auction clearance rate hit 57 per cent last week, with an increasing number of vendors being placed in forced sale positions, new data from independent auctioneering firm Jason Andrew Auctioneers (JAA) revealed.
JAA said the percentage of vendors in a forced sale position has been rising since late last year, hitting a high of 88 per cent last week.
Director Jason Andrew said the vast majority of current vendors are citing a strong motivation to sell, including mortgagee in possession (31 per cent), relocation (31 per cent), purchased elsewhere (10 per cent), financial pressure (seven per cent) and divorce (seven per cent).
"This is the highest percentage of forced sales recorded so far this year, although the number has been steadily rising over the past quarter," Mr Andrew said.
"Buyers are showing they are more than willing to act, with the average shift downwards required for a vendor from their reserve price to achieve a sale under the hammer falling slightly last week to 4.3 per cent."
"Activity numbers so far this year are far higher than during the same period last year, and encouragingly, the overall clearance rate is sitting at just under 50 per cent, up from the 35 per cent recorded across 2011."
The company handled 35 auctions last week, and represents around 18 per cent of the region's auction market. Remaining consistent with the previous two weeks, the number of registered bidders per auction was recorded as 1.43, with the percentage of those registered actually making a bid rising slightly to 60 per cent.
Last Updated: 17 April 2020 Published: 07 March 2012
Rates on Hold - March 2012
Rate decision slammed


What this means is that each assisted living and independent living community is as unique as the residents we serve. Although the physical layout of each community may vary, our mission and our relationship-centered philosophy remains the same. We are committed to taking the time to get to know each resident; their likes and dislikes and their patterns of activity throughout the day. We understand the importance of a successful transition when one moves into one of our communities. We especially understand how difficult it can be for the resident and family to make the decision to move.
Our staff encourages residents to do as much for themselves as they are capable of.
Once you start doing for others that which they can do for themselves, they lose meaning, purpose and motivation to care for and challenge themselves. We strive to find the balance of promoting independence when possible, and provide assistance when needed. We do this by talking with our residents and getting to know them.
Consistent assignment of staff is key to building strong relationships.
When a set group of staff work with individual residents, they get to know how to best care for that resident. UMH employees practice the "New Golden Rule - treat others how THEY want to be treated." Treating others how YOU want to be treated does not respect the individuality of our residents. Not everyone wants to get up at the same time, nor do they want to eat the same foods or participate in the same activities and events. Through our core values of Respect and Collaboration, we create an environment where our residents can thrive.
United Methodist Homes (UMH) was established in 1874 out of the vision of the members of a small church in West Haven, CT who cared deeply about helping the elders in their community and others in need.
Out of their caring, they had the foresight to collaborate in such a way that nearly 140-years later their vision continues to serve those in need.
UMH, as it stands today, is proud to carry on this tradition of caring for people across the continuum; seniors who are independent and those needing assistance, those rehabilitating from illness or surgery, younger adults with disabilities, and those living with dementia.
To sustain meaningful options for living that are built upon a foundation of spirituality.
United Methodist Homes has a 140-year tradition of caring. That caring is based on a mission that we, and those before us, have cultivated since 1872.
What is the UMH difference? Why does our care and support feel so different? What exactly is this special and unique difference so many people feel and experience? Families coming to us express a strong desire for compassionate care for their loved ones. How do we achieve this? This can best be illustrated by taking a closer look at the five core values of United Methodist Homes.
We are responsible for preserving all that has come to us from those who have come before us and we are responsible for those who will come after us.
Not only do we care for those who live in our communities, we care for and about their families and friends, and understand the need to offer them emotional and spiritual support.
Equally important are the ways that we nurture and support our staff, the cornerstone of UMH communities.
The members of the West Haven Methodist Church understood all those years ago the importance of community and relationships. That focus has been the common thread of all that we do at UMH for decades.
Positive relationships are critical to our well-being.
Through simple ways such as asking questions, really listening to what someone has to say, offering a genuine smile and caring touch of the hand we are able to connect with those we serve. We know that by creating caring relationships, we can help those we care for live meaningful lives.
Want to learn more about senior caregiving?
Dowload our eBook "The Essential Caregiver's Guide".
If a mission-based organization is important to you and the care you desire for your loved-one, a UMH community is the place to be. Take a Tour to Learn More!
We take the stress out of making a move by offering the opportunity to tour our UMH communities. Stop by for a visit at a time that's convenient for you and experience our relationship-centered, mission-based care.


When towing isn't a concern, you're free to have fun. And the lightweight Jay Flight SLX Travel Trailer is the perfect place for it. Durable construction, brand-name appliances and comfortable sleeping options make the memories even sweeter. This trailer has bunk for the little ones plus a bed for Mom & Dad. Colors may vary from photos.


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