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text:
Ironmaking in Western Europe
Dr.-Ing. Hans Bodo Luengen
Steel Institute VDEh,
Dr.-Ing. Michael Peters
ThyssenKrupp Steel Europe AG,
Dr.-Ing. Peter Schmöle
ThyssenKrupp Steel Europe AG,
Today there are remaining 26 integrated works with blast furnaces in the member works of the European Blast Furnace Committee (EBFC: Austria, Belgium, Finland, France, Germany, Italy, Netherlands, Spain, Sweden, United Kingdom) as to be seen in Figure 1. The Redcar plant located in the North of Great Britain is currently stopped.
In the year 1990, there were still 45 integrated works operated. Since then blast furnace works have been shut down in Europe and partly been replaced by electric arc furnaces. Some of these had also a long history of iron and steelmaking.
Evolution of blast furnace hot metal production from 1990 on
Figure 2 demonstrates the dramatic reduction in the number of operated blast furnaces in the EBFC since 1990. In 1990 approximately 94 million t of basic hot metal were produced in 92 blast furnaces and 90 million t by only 58 blast furnaces in 2008. Whilst the average working volume of the furnaces increased only by 26.6 % from 1630 m3 to 2063 m the average production per blast furnace and year increased by 48% from 1.04 to 1.54 million t hot metal. This demonstrates that apart the enlargement of the furnaces also the measures to increase furnace productivity enabled the required hot metal production with fewer furnaces. In the crisis year 2009, production dropped to 60 million t hot metal produced in 49 blast furnaces. In 2010 hot metal production was raised to approximately 80 million t.
The changes in hot metal production for the EBFC member countries compared to 1990 shows Figure 3.
The drop-in total hot metal production from 1990 to 2010 was due to the partly compensation of oxygen steel by electric steel making and an effect of the crisis year 2009. The largest basic hot metal producing locations in 2010 are outlined in Figure 4.
The highest production capacity is reached in Duisburg by ThyssenKrupp Steel Europe and HKM with in total 18.2 million t hot metal in seven blast furnaces, followed by Taranto with 11.4 million t and ArcelorMittal Dunkerque with 6.8 million t.
Evolution of reductant structure
Figure 5 shows the evolution of the reductant rates as a weighted average for operated EBFC blast furnaces since 1990. Whilst the total reductant consumption slightly increased the coke rate was decreased from 408 kg/t HM in 1990 to 383 kg/t HM in 2009 through increased coal injection rates from 50 to 103 kg/t HM. Oil plus others dropped slightly in the same period from 23 to 13 kg/t HM. The increase in total reductants comes from the replacement ratio of coke to coal which is in the range of 0.8 to 0.85 due to the lower carbon content of coal compared to coke and especially for 2009 by the crisis operation mode.
At individual furnaces extraordinary operation modes regarding coke rate and injectants were achieved in 2008, Figure 6.
(TKS is today TKSE-ThyssenKrupp Steel Europe; Corus is today Tata Steel Europe)
Highest coal rate was realized at blast furnace 6 in IJmuiden with 235.1 kg/t HM as yearly average. The lowest coke rate with 289.9 kg/t HM with a resulting total reductant rate of 516.9 kg/t HM was achieved at this furnace. The lowest total reductant rate
was achieved at Ruukki blast furnace 1 (458.5 kg/t HM) in oil injecting operation mode.
Today certain amounts of nut coke are charged with the ferrous burden. At TKSE Hamborn Nr. 9 furnace 70.9 kg/t HM nut coke were charged with a grain size of 7 to 35 mm, the remaining bell coke rate being only 262.6 kg/t HM. In former times, nut coke rates of 120 kg/t hot metal have been achieved at bell coke rates down to 220 kg/t hot metal /1/.
Blast furnace ferrous burden
The increase of the gas throughput in the blast furnace necessitates excellent charge material properties. These are related to ferrous burden materials and coke.
Regarding ferrous burden materials, compared to 1990 sinter production dropped more than hot metal production did. The sinter to hot metal ratio changed from 1.23 in 1990 over 1.17 in 1995 to 1.10 in 2008. As a consequence the ratio of pellets and more price favorable lump ores increased. In 1990, Figure 7, many of the furnaces were charged with sinter ratios of over 80% at low lump ore charges using the available sinter capacities. A change over is seen for 2008 with less operated furnaces to a wider range of lump ore use.
With respect to this point it has to be kept in mind that sinter is not a traded material but lump ores and pellets are sold by iron ore suppliers. In Western Europe only Corus IJmuiden possesses an own pelletizing plant which enables a ferrous burden composition of the blast furnaces 6 and 7 with 44 % sinter, 52 % pellets and 4 % lump ores.
As to be seen in Figure 7 there is for 2008 at some furnaces a burden of over 90 % sinter and 100% pellets. SSAB for example use nearly 100% pellet charge with some amounts of briquetted waste materials, Figure 8. High sinter rates are used in Belgium, France, Spain and United Kingdom.
Sintering plants were over the years a welcome possibility to process in-plant waste materials. With the upcoming discussion on dioxin emissions this needed to be proved. There was a limitation to process these byproducts via the sinterplant and suitable solutions have been developed, like cupola furnace route, rotary hearth furnace or the Primus furnace. Nevertheless, sinter plants supply a ferrous product carrying the necessary slag components for the total blast furnace charge materials.
Coke supply
The situation with coke supply for European integrated works is quite different. The range is from 100% own coke availability to a 100% external coke supply. Figure 9 shows the cokemaking within the EBFC countries and the coke demand by the steel industry. The coke production was 31.2 million t, the demand for sinter plants and blast furnaces amounts to 34.5 million t. This was a coke shortage of 3.3 million t to be met by imports.
Coke surplus was only available in The Netherlands, Italy and Spain. Largest shortage of coke supply is to be seen especially for Germany. 3.3 million t coke were imported from the European and world market. With this the German steel industry is the biggest coke importer in Europe.
In Germany the coke plant Schwelgern with an annual blast furnace coke production of 2.7 million t in Duisburg, was commissioned in March 2003 as replacement for an old coke plant. This plant is designed for using the world's largest horizontal slot ovens with a useful volume of 93 m3, in total 140 ovens.
Blast furnace constructional features and equipment
The distribution of blast furnace sizes, taking the hearth diameter as a relevant measure, is shown in Figure 10.
The majority of the furnaces are medium-sized with hearth diameters between 10.0 and 11.9 m. The large units of 12.0 m and more are listed in Figure 11.
These seven blast furnaces have a hot metal capacity of 26.6 million t.
Regarding the installed equipment of the 58 operated blast furnaces in 2008, 49 furnaces are equipped with full casthouse dedusting system and 45 furnaces or over 90 % of total hot metal production with a bell-less top device. At 49 blast furnaces slag is granulated. 20 furnaces use the elevated top pressure for power production by a top gas recovery turbine (TRT). As these are all large furnaces 50% share of hot metal production is equipped with a TRT. The operation of only a few large furnaces at high annual output rates requires a long campaign life. Today it is expected that a blast furnace campaign must last 15 to 20 years between two complete relinings. It is always difficult to define the length of a campaign as furnaces are different in size and design.
Especially the 10.2 m hearth diameter blast furnace Hamborn 9 reached excellence performance with a specific production of 20,900 t hot metal per m3 working volume. This furnace possesses only one taphole and has produced since blow-in after a reconstruction in December 1987 proximately 36 million t HM. The 14.9 m blast furnace Schwelgern 2 of TKSE has meanwhile produced over 66 mill t in the running campaign.
The design of a blast furnace influences the duration of its campaign. The main determining factor is the durability of the furnace hearth. The most problematic zone is the transition area between the hearth bottom and hearth wall. When comparing wear patterns of different blast furnaces it is noticeable that there is a pronounced typical wear in this area which is called "mushroom formation or the elephant foot".
Furnaces without mushroom formation had an even wear in the upper bottom refractory blocks. It appears that, for preventing mushroom formation, the hearth should have refractory qualities at the bottom which enables the hot metal to create a concave flow area over the hearth bottom, Figure 12.
As an example, Figure 13 shows two typical European hearth constructions. On the left side a hearth is shown with walls made of microporous blocks, and in the upper part amorphous carbon bricks.
Towards the shell, highly conducting graphite bricks are used. The hearth bottom consists of horizontally installed amorphous carbon blocks with graphite underneath.
The right side shows a hearth with a wall made of micro porous blocks, graphite bonded. The hearth bottom has three insulating chamotte layers in the upper part and carbon blocks at the bottom. The hearth is protected right through with a ceramic cup. The shell has a very large inclination angle of 12 degree to make possible thicker refractory lining in the critical transition region.
Another prerequisite for long campaign life is an effective furnace shell cooling. Typical cooling systems are copper cooling boxes, cast-iron staves as well as spray cooling or double jacket cooling for the hearth walls. The latest development for the cooling of a blast furnace is copper staves.
The most highly stressed zones of a blast furnace are the belly and lower stack. The highest heat removal takes place here via the cooling system. The cooling system can be constructed in different ways. Compact plate coolers or plate coolers with intermediate flat coolers, cast-iron staves with integrated refractory material or the newly developed copper staves are used. Copper staves are a European development which had been tested in joint work between SMS and TKSE at two blast furnaces of TKSE from 1983 on and first time installed in industrial scale at the new construction of TKSE blast furnace Schwelgern 2 and blast furnace Salzgitter B /2/.
There is a significant difference between the consistency of heat dispersion of modular cast-iron staves and copper staves. Compared with cast-iron staves, copper staves permit significantly more intensive heat removal thus forming a stable protective layer by the burden materials. The use of expensive refractory materials to increase the service-life of the copper staves can be dispersed with. These protective layers reduce the heat throughput and the wear of the staves to more or less zero. Due to the low thermal expansion coefficient of the copper staves, these can be built longer than cast-iron staves. They are also considerably thinner, so they make an increased furnace volume with unchanged shell size possible. As the first furnace in the world, ArcelorMittal Bremen No. 2 received copper staves for hearth wall cooling during its relining in 1999.
Figure 14 shows the cooling construction of this furnace with cast-iron staves in the tuyere zone and copper staves above and below /3/. Also the blast furnaces HKM B and ArcelorMittal Gent B had been equipped with copper staves in the hearth during their relining in 2000 and 2001. At the blast furnaces A and B of ArcelorMittal Gent problems with wear of copper staves and water leakages happened in summer 2006 and 2007 respectively /4/. Here the protecting skull was missing in front of the damaged staves. One reason could have been the abrasive behavior of the descending burden. New copper staves were designed with noses to support skull formation and relined with silacon-bonded SiC bricks.
For optimizing blast furnace operation especially the measuring and process monitoring at the blast furnace has reached a high standard, especially to control the process in the inner part of the furnace, Figure 15. Of special importance are the optimization and control of the gas composition and gas distribution inside the furnace, the material charge distribution at the top, the pressure losses inside the furnace, the evolution of the temperature inside the refractory as well as all tuyere parameters.
A hierarchically organized computer network for receiving, evaluating and saving all data enable the use of process models for furnace control in all areas. The steadily correlation of the burden and blast furnace condition data enable the steady optimization of reductant rate efficiency.
Figure 16 shows the modern control room of the blast furnaces Hamborn 8 and 9 of TKSE with the installation of a large screen for the demonstration of different process conditions. The development of process control and instrumentation has largely contributed to an optimized blast furnace operation. It makes the effects of changes in operation more predictable and the distance to the optimum operating point determinable.
Ironmaking in rough times
From September 2008 till May 2009 crude steel production dropped by 40 % and hot metal production by 47 %, Figure 17. A hot metal production of 4.34 million t in May 2009 corresponds to a capacity utilization of 48.5 %. This was achieved by a temporarily stoppage of blast furnaces and a reduction of productivity at the operated blast furnaces.
The number of operated blast furnaces was reduced from 58 in March 2008 to only 33 in May 2009, Figure 18. Generally most of the large furnaces continued production at levels of 50 to 80 % of the capacity. Only 3 furnaces out of the 33 blowing ones produced on a 100 % productivity level just to supply the hot metal demand without restart a second furnace.
At many stopped furnaces the salamander was tapped to prepare the furnace for a longer standstill time. Two furnaces were not blown in after a complete new relining; another furnace was stopped for an earlier relining than initially planned. At the furnaces which were temporarily stopped it has to be decided whether to keep the stoves hot, which is costly, or to cool them down, which needs extra time for heating them up before blowing in the furnace and can be problematic regarding the brickwork lifetime.
Generally speaking the blast furnace operators came from an economical situation where they operated their blast furnaces at such high productivity levels which were before rated to be nearly impossible and later on the productivity level is down to a level which was as well been rated to not being achievable. This also demonstrates the flexibility of a blast furnace and also of the operators, but such operating conditions are not healthy for a blast furnace and its campaign length.
Basically there are two ways to reduce the production. On the one hand a continuously very low operation level and on the other hand a production at a higher level combined with block stoppages to limit output rate. Block stoppages enable short time working of the staff and the carrying through of maintenance work with own staff only. Many block stoppages can lead to the problem that the blast furnace hearth cools down which needs time to achieve a smooth temperature level during operation. To reduce production at stand-alone blast furnaces with only one blower machine and without an integrated blast generation with numerous blowers for several blast furnaces can be the limiting factor as this stand-alone blower can only be reduced to a certain level. Big blast furnaces which possess two blowers are much more comfortable regarding reduced production. The largest West European blast furnace Schwelgern No. 2 of ThyssenKrupp Steel AG, which has a hearth diameter of 14.9 m, was reduced from a production of 12,800 t hot metal per day down to 5,500 t hot metal per day in a more or less continuous operation.
The typical way to reduce blast furnace production is to decrease the blast volume, to reduce the elevated top pressure, to inject less auxiliary reducing agents in combination with reduced oxygen addition to the blast, lower blast temperatures and higher blast moistures. The reductant structure of the blast furnaces has to be adjusted to the coke surplus availability. Coke plants should not be stopped and if they are stopped they have to be hot idled which is very costly. Otherwise they can be destroyed. As a general experience the production of a coke plant can be reduced to a level of 70 to 80% capacity only. Therefore, the reductant structure of the German blast furnaces has changed with decreasing hot metal production, Figure 19. Auxiliary reducing agents injection was reduced at all furnaces, at some furnaces the operation mode was changed to 100 % coke operation as reductant. In April 2009 the total average reductant consumption of the German blast furnaces exceeded the 500 kg/t hot metal level for the first time since the second oil crisis beginning to middle of the 1980s. The coke rate increased from 354 kg/t hot metal in 2008 to 458 kg/t hot metal in April 2009.
There was just a minor effect on the ferrous burden composition of the German blast furnaces, Figure 20. As all German integrated iron and steel works operate their own sinterplants there was a slight increase on the use of sinter in the ferrous burden from 60.7 % in 2008 to 69 % in May 2009. As a general result of the experience gained by the blast furnace operators in Germany it can be highlighted, that even with a dramatic reduction in the productivity level a smooth furnace operation was achieved.
Figure 21 shows a map of Germany with all blast furnaces for basic hot metal production, in which the white ones are identified as temporary stopped furnaces. These are ArcelorMittal Bremen blast furnace No. 3 (newly relined in 2008), ArcelorMittal Eisenhüttenstadt blast furnace No. 1, Hüttenwerke Krupp Mannesmann blast furnace A (under relining from January to April 2008), Rogesa (AG der Dillinger Hüttenwerke) blast furnace No. 4, Salzgitter Flachstahl blast furnace No. C and ThyssenKrupp Steel blast furnace Hamborn No. 9.
For this reason, two general groups of alternatives for reducing the production in blast furnace plants will be dealt with, which have ultimately also been applied worldwide in a variety of ways:
Operation on a reduced productivity level by
changing specific influencing parameters and/or by
reducing the absolute operating parameters
as well as
reducing the production by
short downtimes of the plants for one to two days or
shutting down plants over extended periods of time.
Operation on low productivity level:
The adjustment of outputs by changing the specific process parameters exemplified by the blast furnace process, has often been analyzed. In the past, the main question was, however, how to enhance the output of blast furnaces /5/. The "normal operation" of blast furnaces in the past few years, namely the high-output operation at a maximum injection rate of coal dust, for instance, is – for the sake of the flame temperature – coupled with high blast temperatures and high amounts of additional oxygen. In order to abandon this high-output operation, the amount of additional oxygen is reduced to zero in a first step while the injection rate is reduced, in a second step the blast temperature is reduced while the coal rate is further reduced, and finally the blast moisture is increased when the switch-over to 100 % coke operation takes place, in order to keep the flame gas temperature on a constant level, Figure 22, which would be the ideal case.
After the theoretical study of the specific influencing parameters the results in the plants, for instance at the blast furnace of ArcelorMittal Bremen, point to further possibilities. As from mid-October 2008, the output of blast furnace 2 was reduced by decreasing the volume of oxygen added, along with in part lower specific quantities of injection coals, as well as considerably less absolute blast rates. The blast rate of normally about 300,000 m³/h was temporarily reduced to about 150,000 m³/h. These changes both of specific and absolute process parameters led to a reduction of the blast furnace 2 output by up to 70%, starting from the initial normal productivity level of 70 down to a level of 25 t HM/m² of hearth surface and 24h, especially in the period from beginning of March through mid-May, 2009, Figure 23.
Reducing coke plant productivity, Figure 24 /6/:
There is practically no prior experience with production cuts on present-generation coke oven batteries since cokemaking has always been run at full capacity in iron and steelmaking facilities during the last 20 to 30 years. Only Prosper as an "isolated" coking plant had any historical experience to draw on.
To resolve this issue, the operators of the five coking plants started to meet regularly with experts from the plant supplier and refractory industries to share experience and know-how that would enable them to cut back production safely and without causing damage to the oven structures.
In a first approach, the cokemaking experts all agreed that a cut in production to 80 % of full capacity would be feasible without major problems from a coking plant technology viewpoint. On the other hand, to preserve the full operability of each battery, strict compliance with certain boundary conditions was mandatory since the cutback represented a deliberate departure from the rating data underlying the design of the battery. The optimum operating point of a battery or coking plant combines numerous parameters such as coking time, charge volume, underfire gas quantity, stack draught, heating flue temperature, offgas temperature, collecting main pressure, gas generation, gas temperatures, gas qualities, gas composition, etc. To cut back output, all of the above-mentioned parameters must necessarily be adapted to the altered conditions.
As a general rule, changes in battery operating regime must always be made slowly to allow the complex brick structure to adapt to the new conditions.
The most critical aspect of the entire project lies in the temperature drop associated with the output reduction. It is necessary to preserve the temperature distribution over the height and length of the chamber heating walls, to keep up minimum temperatures at the head heating flues (i.e., the first and last two heating flues of each heating wall) so as to prevent pre-head failures in the refractory brickwork, and to ensure adequate temperatures in the regenerators and offgas system.
On a battery with circulation flow combination ovens, meeting these conditions calls for an adjustment of the gas-air distribution on no less than 2414 burners – i.e., 71 heating walls with 34 heating flues each.
Taking into account the above requirements, the output reduction proceeded in essentially the same manner in all coking plants:
The coking time was stepped up by approx. 15 minutes per day. The number of ovens pushed each day was thus decreased gradually, and coking times were lengthened by 35 to 50%. Given these longer coking times, the energy supply to the batteries had to be adapted to altered conditions. A change in gas flows, gas pressures, calorific values, etc., was implemented on the heating systems originally set for full-load operation. Such far-reaching interventions in the complex coking plant system were feasible only by continuous monitoring of all temperature profiles in the battery structure and by taking appropriate countermeasures, e.g., changing nozzle cross-sections in the heating flues, adapting calorific values, inspecting and adjusting the oven bracing system, and adapting the coal byproducts system to the altered gas situation, which included adjustments to the entire energy network linking the cokemaking operation to the iron and steelmaking plant and external customers.
Besides the reduced number of ovens pushed per day, bulk weight was decreased by grinding the coal to a finer grade and by discontinuing the admixture of oil to the charge. These measures brought down the production rate by another 5% approximately.
CO2 Benchmarking for ironmaking plants in Europe
For the CO2 trading period in Europe from 2013 on the steel industry made the proposal to realize this on the basis of plant benchmarking. The main idea behind this was to leave the cap and trade system in favor of a system with driving character to reduce specific CO2 emissions. The European Commission first required that the benchmark value should be the average of the best 10%, listed in Figures 25, 26 and 27 /7/ for coke, sinter and hot metal benchmarking. In addition it was required, that 25% of the coupling export gas used for power production only gets allocation on the basis natural gas CO2 load. End of October 2010 the European Commission published a draft decision determining transitional Union-wide rules for the harmonized free allocation of emission allowances under the EU emissions trading directive starting in 2013, which dispensed the gas regulation but decreased the benchmark values by another 10 to 14%. The sinter benchmark also includes one pellet plant. It is clearly to be seen, that none of participating plants in the EU 27 reach the required benchmark values set by the European Commission.
This draft makes free CO2 allocation for operating plants and also for new capacities impossible and loads the production plants in Europe with additional costs. This increases the danger for carbon leakage. Carbon leakage is assumed if trade intensity with regions outside EU is over 10 % and cost increases through CO2 burden including electricity in comparison to gross value added is over 5 % or trade intensity is over 30 % or cost increase is over 30 %. Then companies may transfer of production capacities to locations outside Europe.
Europe is currently the only region of the world which tries to reduce CO2 emissions by an emission trading system, Figure 28. Generally speaking the driving character of such a system to reduce specific CO2 emissions remains questionable, because money used for buying CO2 certificates is not available for technological and process developments. These scenarios do not exist outside Europe. The CO2 emission trading restricted to Europe covers only 11% of world crude steel production in 2009.
Blast furnace – further outlook
In the EU (15) the share of oxygen steelmaking remains dominant. A steady increase of electric steel share is seen for the past years but further growth rate may be limited by scrap availability.
Therefore the blast furnace will remain the dominant pre-product supplier especially for high-grade steel production. The costs for hot metal to a great extent determine the economic result of an integrated iron and steelworks working with the BF/BOF route. The trend to a change over from some smaller to remaining economical large-sized furnaces may continue. The operating time factor of a blast furnace is very important. Frequent unscheduled stoppages are not only unhealthy for the life of the furnace, but also negatively influence hot metal costs.
The situation with extreme bad economics has led to drastic decreases in steel and hot metal production. 28 blast furnaces out of 58 were stopped in May 2009, the others operated at reduced production in the rage of 55 to 80 %. Only three furnaces operated at full capacity to supply the demand as other furnaces of the plants were stopped. Hot metal production dropped by 50 %. As too much coke was available in many works the auxiliary reductant injection rate was reduced or partly stopped and the furnaces operated with 100 % coke as reductant. Fortunately the situation has become better in 2010. uncertainties for the location Europe remain by the draft of the European Commission for the CO2 emission trading period from 2013 on. This increases the danger for carbon leakage.
This presentation focuses on the evolution of ironmaking in Western Europe and highlights some aspects, like: Introduction into the development in hot metal production, progress of the structure of reductants and ore burden materials, evaluation of constructional features and equipment of the blast furnaces and further outlook for the European ironmaking scenario. The integrated steel works in Western Europe operate modern plants for the production of a wide variety of high grade steel products. The blast furnace/converter route will remain dominant. With respect to the international finance crisis which also affected the steel industry the question is answered "How flexibly can metallurgical plants be operated". The plunge in order intakes in late 2008 called for decisions which produce immediate effect, in order to adapt the entire chain to the requirements, beginning with logistics and warehousing of raw materials down to the linked production units of integrated works. Suitable measures realized at coke oven batteries and blast furnaces are described. One main focus is set on the future CO2 trading system based on benchmarks with non reachable values as set by the European Commission.
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4. van Campe, Stefan: Stave concerns at ArcelorMittal Gent BF A; Meeting of the General Managers of Blast Furnace Works of VEDh member companies, Lulea, Sweden, 21 March 2007
5. Schmöle, P.: From high productivity operation to reduced output: How flexibly can metallurgical plants be operated?, stahl und eisen 130 (2010), no. 8
6. Beckmann, H.-B.; Dombrowski, G.; Jager, H.-W.; Liszio, P.; Lüngen, H.B.; Masuth, M.; Nelles, L.; Schulte, H.: Possibilities and limits of cutting back coking plant output; stahl und eisen 130 (2010), no. 8
7. Source of curves: Phillip Townsend Associates Inc.; report on Eurofer CO2 intensity data 2010

subset: commoncrawl


text: The Exo-Chasis is the base component of all armor of the Exo-Suit. To make an Exo-Chasis, you need 8 Iron ingots, surrounding 1 gold nugget. Crafting Retrieved from "http://feed-the-beast.wikia.com/wiki/Exo-Chasis?oldid=70962" Ad blocker interference detected! Wikia is a free-to-use site that makes money from advertising. We have a modified experience for viewers using ad blockers Wikia is not accessible if you've made further modifications. Remove the custom ad blocker rule(s) and the page will load as expected. Categories: Add category Cancel Save


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Suspended phones leave people hanging
New violence prevention measure puts lives on hold
November 27, 2012
With just two weeks to go before Kiran Raja's wedding, guests were expected to start gathering at her house for traditional dholki nights of singing and dancing.
Preparations were being finalized when the government suspended mobile phone services across the country over the weekend.
Saturday was Ashura, the Shiite day of mourning, and the television in the Raja family home was showing disturbing images of the day's violence, during which six children died in a remote-controlled blast targeting a procession in the north.
Phones were suspended for the two-day holiday for fear of additional attacks. So far this year, which began November 15, 52 Shias have been killed in six sectarian attacks. Last year, 29 were killed during the first month of the Muslim calendar. Muharram is the second holiest month, after Ramadan, and it is considered unlawful to fight during this time. In 2012, Muharram ends on December 13.
Raja's wedding festivities have been stifled by the extraordinary security measures.
"My siblings are out distributing wedding cards, and we are worried for their safety," she said. "Many routes are blocked, and we cannot reach them on the phone."
Riding two to a motorbike, a common means of transportation, was also suspended for the weekend. Raja says many of her guests said they couldn't make it because of this.
According to Interior Minister Rehman Malik, phone services and wireless telephone network services in 48 cities were partially and fully suspended.
Mobile phone suspension also led to a major drop in emergency calls received at Rescue 1122 headquarters in Lahore.
"Normally we receive 2,500 calls regarding road and fire accidents per day; only 92 calls were received this Saturday," said Ruqaia Bano, public relations officer at Punjab Emergency Service.
"The difference in figures speaks out for itself. Many rushed to telephone booths to contact us. We were helpless since our assignment starts only when we receive calls," she said.
Despite the inconvenience, experts say the security measures are essential for combating terrorism.
"Terrorists use a 9-volt battery with bombs which can be triggered after matching the frequency with a pulse from a mobile phone. They apply the same technique to blow up gas cylinders in cars," said Samson Simon Sharaf, a defense and political analyst.
According to Sharaf, the spread of unregistered SIM cards has contributed to the rise in violence.
"Illegal SIMs are readily available and the cell phone companies cannot monitor all the data. Only post-paid billing and dispatching the SIM to a postal address can help in containing this threat", he said.
China, Myanmar, Vietnam fare poorly in US religion report
State Department takes swipe at jailing, harrassment of believers in annual assessment
Sri Lankans pressure govt. to abolish all-powerful presidency
Protesters identified sweeping presidential powers as an on-going threat to democracy
More areas devastated in Bangladesh floods
Dinajpur district is among the worst affected area, where 23 people died
US highlights cow vigilantism, atrocities against minorities in India
International Religious Freedom Report 2016 criticized various Hindu nationalist groups and their militant sympathizers
New terror plots, US moves worsen Mindanao conflict
Marawi bishop warns of terrorist plan to use hostages as suicide bombers, rejects US offer of air strikes


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Buying & Selling
Buying and Selling Hill Special cycle frames and complete bikes
There are buyers and sellers for both Hill Special frames and complete cycles.
The earlier Padiham built Hill Special frames from the late 1940s and 1950s appeal more to the Classic Lightweight cycle collectors who will use them on classic lightweight rides. Unfortunately these purchasers are very demanding and like the bike to be equipped with correct contemporary equipment from the 1950s and also to be finished in either its original paintwork or to have been re-enamelled with correct transfers. Thus a 1950s frame with its original finish in good condition will command a better price than a 1970s or 1980s frame in similar condition.
A 1940s or 1950s frame could realise £50 to £75 if in good condition. A frame still in its original paintwork in good condition could fetch £70 to £100 (also track frames will always sell for more than equivalent road frames)
A complete bike equipped with good quality 1950s components could fetch £100 to £150
A lot of 1950s frames had some chrome plating on and, unless this chrome is in exceptionally good condition, it will be difficult to get the frame restored to its original condition without considerable expenditure, either on having the areas re-plated or by having the chromium plate professionally removed and the surface prepared for painting.
For Hill Special frames built at Blackpool in the 1980s there is still a good market from cyclists wishing to own a craftsman built steel frame to ride in Audax events or for long distance touring. Frames could fetch £50 to £70 and complete bikes £120 to £150 with some racing bikes with a full groupset of contemporary Campagnolo components fetching considerably more.
There are various ways of selling and buying Hill Special frames and bikes.
To realise the highest price you should sell on Ebay however it may be easier to sell and despatch a frame than a complete bike.
Although you can sell a complete bike on ebay the only realistic way is on the basis that the buyer collects from your house – this will only get good responses if you live in or near a large city or motorway - it is too expensive and too prone to damage to ship complete bikes
If you wish to ensure that the frame or bike stays in the UK and continues to be used Cycling Weekly has a classified section called Collectors Items and for £15 your advertisement will appear for two weeks. You can quote a price but negotiate with prospective buyers who you meet face to face.
Finally if there are cycle jumbles near you, you can usually arrange to take and display complete bikes there as well as just frames.


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Let Us Think Of Ways To Motivate One Another To Acts of Love and Good Works
// Hebrews 10:24
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Nearly half of cancer metastases become clinically evident five or more years after primary tumor treatment; thus metastatic cells survived without emerging for extended periods. This dormancy has been explained by at least two countervailing scenarios: cellular quiescence and balanced proliferation; these entail dichotomous mechanistic etiologies. To examine the boundary parameters for balanced proliferation, we performed in silico modeling.
To illuminate the balanced proliferation hypothesis, we explored the specific boundary probabilities under which proliferating micrometastases would remain dormant. A two-state Markov chain Monte Carlo model simulated micrometastatic proliferation and death according to stochastic survival probabilities. We varied these probabilities across 100 simulated patients each with 1,000 metastatic deposits and documented whether the micrometastases exceeded one million cells, died out, or remained dormant (survived 1,218 generations).
The simulations revealed a narrow survival probability window (49.7 – 50.8 percent) that allowed for dormancy across a range of starting cell numbers, and even then for only a small fraction of micrometastases. The majority of micrometastases died out quickly even at survival probabilities that led to rapid emergence of a subset of micrometastases. Within dormant metastases, cell populations depended sensitively on small survival probability increments.
Metastatic dormancy as explained solely by balanced proliferation is bounded by very tight survival probabilities. Considering the far larger survival variability thought to attend fluxing microenvironments, it is more probable that these micrometastatic nodules undergo at least periods of quiescence rather than exclusively being controlled by balanced proliferation.
The dormancy dilemma impacts millions of cancer patients worldwide. Certain epithelial carcinomas such as from breast or prostate tissues can recur years or decades after primary tumor ablation (1). This late recurrence afflicts nearly 50% of breast cancer patients that develop metastases; other carcinomas exhibit similar late recurrence rates (2). This recurrence is most problematic within metastatic organs such as the liver, lung, and brain where tumor resection may not be possible and chemotherapeutic agents appear to be ineffective in most cases (3, 4). For instance, aggressive treatment (e.g. adjuvant chemotherapy) of breast cancer after surgical removal of the evident primary tumor may reduce 10-year recurrence by less than one-third. Consequently, ostensibly cured cancer patients harbor unseen metastases for decades that eventually emerge into untreatable, lethal tumors. This long period between primary tumor treatment and metastatic appearance is referred to as metastatic latency though the tumor cell behavior during this period is unknown.
Metastatic latency allows disseminated tumor cells to avoid clinical detection and withstand aggressive and toxic neoadjuvant treatment (5). How the disseminated carcinoma cells maintained a long-term, clinically undetectable state in an ectopic site such as the liver is unknown (6). Although extravasation of carcinoma cells from the primary tumor is common, but most of these cells seem not to establish metastases (7, 8), it is likely that the pre-metastatic microenvironment contributes to whether carcinoma cells will seed, survive, and either proliferate to prompt tumor formation or exhibit a dormant phenotype.
Because in vitro and in vivo experimental systems are not sufficiently malleable to consistently and reliably recapitulate the metastatic latency phenotype, in silico models have evolved to explore the mechanisms of metastatic competency, dormancy and emergence (9–11). Many of these in silico models predominately simulate metastatic latency according to the theory of balanced proliferation among micrometastases of greater than one million cells. Therefore they introduce various biological factors such as angiogenesis, immune response, hypoxia, and growth factor availability and deduce through partial differential equations what impact these have on the ability for the micrometastases to emerge or maintain a dormant state. A major limitation to this approach is that little empirical biological data are available to make these models translatable to the in vivo response. Moreover, such studies often assume that latent metastases experience balanced proliferation, meaning additional biological data, even if available, would not resolve latency as being due to balanced proliferation, cellular quiescence or a combination of both.
Notwithstanding these limitations, in silico models are becoming increasingly important to offering insights in prioritizing the landscape of contributing metastatic factors. By using an Approximate Bayesian Computation model applied to empirical patient data Willis et al inferred that metastatic breast cancer late relapse evolved from just 1 to 6 micrometastases that escape from dormancy (12). Other approaches used the Gompertzian growth function to calculate periods of metastatic growth and growth arrest to fit clinical data as presented in the Munich Cancer Registry (13). These results predicted that metastatic seeding occurred before the clinical detectability of the primary tumors. Computational models have also been used to predict the metastatic response according to primary tumor removal and front line chemotherapy (14).
Biologically, the issue of metastatic dormancy has been approached as balanced proliferation and death, quiescence, or a combination of both. In arguing for balanced proliferation and death, investigators invoke various constraints, such as the 'angiogenic switch', prior to which the metastatic nodule is constrained to a certain mass in the absence of a vascular supply (2, 15). In other considerations, multiple feedback mechanisms are invoked to maintain a small, but cycling cell population (16). The cellular and/or molecular mechanisms behind tumor dormancy present with an absence of solid clinical data, though emerging evidence of phenotypic plasticity suggests some other possible routes to dormancy and may suggest quiescence of the disseminated tumor cells.
Thus, the situation remains unsettled as to which behavior predominates during these latent periods. To take an unbiased approach, we modeled metastatic growth dynamics by invoking a two state, Markov chain Monte Carlo (MCMC) simulation where only cell-survival probability and starting metastasis populations were varied. As depicted in Figure 1, the MCMC method assigns a survival probability for each cell in each metastasis during each replication cycle. Cells will then either proliferate or die as statistically influenced by the survival probabilities allowing for metastases to exhibit a range of outcomes not predetermined. If metastatic dormancy can emerge across a wide spectrum of survival probabilities then balanced proliferation may be the dominant contributor. However, if the latent phenotype via balanced proliferation is only manifest within a narrow probability window we propose that cellular quiescence would likely participate nontrivially in protracted metastatic survival.
Markov chain Monte Carlo simulation is a computational method that samples from a probability distribution in order to assign system outcomes commensurate with the underlying distribution (17). This model is described as a branching process whereby each cell in cell cycle k will randomly give rise to zero or two cells in the k + 1 cell cycle. We applied MCMC simulation as a means to model the fate of extravasated circulating tumor cells into the metastatic site. We developed two Markov chain Monte Carlo approaches to assign cell fates. The first, a fixed probability model, assigned static survival probabilities to every cell in each metastatic nodule; the probability of survival for each individual cell was not dependent on the other cells in that metastatic nodule.
The second approach incorporated a stochastic element where the survival probability for any given cell was sampled randomly between +/− 10 percentage points around the specified mean survival probability for the group. We refer to this variable probability as p~ where appropriate to distinguish it from the assigned probability p. All results herein were developed from the second, stochastic model, diagrammed in Figure 1A. Both formulations, however, are examples of branching processes, which allow for convenient analytic expressions for some aspects of tumor behavior. In our two-state MCMC system, every cell in each metastasis could either divide or die per cell cycle, thus mimicking the balanced proliferation phenotype. Notably, cells were individually assigned a new survival probability at each cycle with the stochastically assigned probability adjustment within 10 percentage points above or below the initially assigned survival probability. For example, simulations at a fixed 60 percent survival probability will allow for random fluctuations between 50 and 70 percent survival. Although these survival probabilities coalesced to the expected means, this additional percentage point adjustment further imitated the dynamic survival conditions of the metastatic niche.
These simulated micrometastases could devolve to zero cells (died out), exceed one million cells (clinical metastasis) or exceed 1,218 cycles with fewer than one million cells (dormant). Our data represent one hundred compiled patient trials (100,000 micrometastases) for each combination of cell survival rate and starting cell number. For the progressive clinical metastases, we capture the range of cycles at which this occurred. For the dormant metastases we document the mean cell numbers at the time of dormancy. Although this model does not achieve pseudo-equilibrium given all simulated metastases terminate under one of 3 conditions, dormancy is nonetheless modeled by means of achieving neither the zero or 1 million cell boundary before reaching 1,218 cycles; though it is likely that should there be no cycle limit, the cell boundaries will be reached.
We simulated patients in groups of one hundred person cohorts across a matrix of cell survival probabilities (0.3 to 0.7, given as percentages) and number of initially extravasated cells. For each patient we modeled one thousand carcinoma deposits to the liver at the time of primary tumor resection. The probability of an outgrowth is based on individual micrometastasis and not on patient load of total micrometastases. Each deposit started with one, two, four, or eight cells (later at 1000 and 4000 cells for boundary validation) so as to separate initial extravasation and seeding from subsequent metastatic behavior. We also assumed a one-and-one-half to three-day cell cycle so that 1,218 cell cycles represented five to ten person years (dormancy) at a cycle time of 1.5–3 days per mitosis. Micrometastases that grew beyond one million cells were classified as approaching clinically evident and were not simulated further. Finally, we assumed that the initial one thousand micrometastatic deposits did not give rise to additional deposits and were free to either die out, grow out to greater than one million cells, or become dormant. Representative traces of micrometastatic-tumor growth for four survival probabilities (50.0, 50.2, 50.4, and 50.6) are shown in Figure 1B.
The metastatic fate across all simulated patient trials for 1, 2, 4, and 8 cell starting metastases revealed that the majority of metastases died out until the survival probability exceeded 60% (Figure 2). Sampled time courses of metastatic tumor growth illustrate this phenomenon, even for probabilities above 50% (Figure 1B). Eight-cell starting metastases conferred a grow-out advantage particularly above the 60% survival probability whereas one-cell starting metastases still exhibited metastatic abatement in that range. Of those metastases that die out, they do so quickly in fewer than 60 cycles (Figure 3). Dormant metastases represented a small fraction and were tightly bounded by a small survival probability.
Metastatic dormancy was a rare outcome that manifested only between 49.7 and 50.8 percent survival probability (Figure 4, top panel). Starting with one versus eight cells in the micrometastases did not impact this survival probability range. However, the mean number of dormant metastases increased as the starting cell number increased, up to a maximum of 80 mean dormant metastases per patient (still less than 10 percent) for eight-cell simulations (Figure 4, bottom panel). In a small series of 1000- or 4000-cell micrometastases the boundary percentages were within the same narrow range.
Although dormancy was tightly bounded proximal to the 50 percent survival probability, a dramatic variance of the mean dormant metastatic size was highly sensitive to small changes in survival probability (Figure 5). Half of the survival range (between 49.7 and 50.2 percent) yielded dormant metastases comprised of fewer than a few thousand cells. Interestingly, between 50.3 and 50.7 percent survival probabilities the populations peaked at around 500,000 cells. Not until the 50.8 percent survival probability did the dormant metastases (a single metastasis for 2-cell initialization, 3 metastases for the 8-cell case) approach the outgrowth condition – reaching nearly one million cells.
The cumulative density function in Figure 6 compares 1-cell versus 8-cell starting metastases to the outgrowth condition. At the 70 percent survival probability, all of the metastases that grew out did so in less than 50 cycles. In contrast, half the metastases grew out in approximately 400 cycles for the 51.5 percent survival probability. Interestingly, at just above the 50 percent survival probability, a one-percentage point increase in survival probability resulted in the required number of cycles for the surviving metastases to achieve outgrowth being reduced by two-thirds.
Research into metastatic latency has rapidly evolved over the past decade given the high prevalence of this condition and the lack of effective clinical interventions. Unfortunately, this phenomenon is difficult to recapitulate across in vitro and in vivo experimental systems. Moreover, it is not certain whether metastatic latency results from small deposits of quiescent carcinoma cells that had recently extravasated into the metastatic site or whether small- to mid-sized micrometastases maintain clinically undetectable sizes based on balanced proliferation and cell death (or a combination of explanations). This distinction is critical as therapeutic approaches would be different for either condition: that of targeting proliferating or quiescent cells.
Because of the metastatic latency prevalence, patients are confronted with the dilemma of undergoing extensive and toxic systemic treatments for putative metastases based on the characteristics of the primary nodule and statistical considerations of similar patients that experienced metastatic latency. While the ability to predict which patients will suffer metastatic recurrence has improved (18), the current approach to these dreaded sequelae only reduces the rate by a third, while evoking untoward toxicity including hair loss, neurological impairments, opportunistic infections, bleeding, and death. As most of the therapy is ineffective, we need to characterize the status of the disseminated tumor cells prior to their frank metastatic emergence so as to more effectively target them. What is not known is whether these few surviving cells exist in cellular quiescence or undergo balanced proliferation to engage the dormant phenomenon. This distinction has immense implications, as predominantly only cycling cells are susceptible to chemotherapy, and is therefore the focus of this paper.
Given these limitations, many in silico models have been developed that may help prioritize or frame the metastatic etiology (19, 20). For example, Michor et al computed the probability of metastatic dissemination from primary tumors based on oncogenic mutations in RAS, ERBB2/NEU or MYC (21). Implementing a stochastic Moran process the authors simulated a single genetic mutation that gave rise to neutral, advantageous or disadvantageous metastatic potential. These simulations computed the temporal accumulation of metastases as a function of primary tumor size. Further model development eventually may help clinicians validate whether to treat more aggressively with adjuvant therapy. Another study implemented a Voronoi tessellation approach to model the impact heterogeneous or homogenous extracellular matrix (ECM) stiffness had on metastatic and primary tumor growth kinetics (9). Whereas non-rigid, homogenous ECM gave rise to isotropic tumors and rigid homogenous ECM invoked anisotropic morphologies, a heterogeneous ECM stiffness exhibited both properties, but in a predicable manner. Consequently this modeling if matured may assist clinicians in determining which metastatic tumor-adjacent tissue (in critical metastatic organs such as the brain) may likely harbor disseminated tumor cells – leading to either more or less aggressive tissue resection. Although these models have promise to improve clinical treatments there is a dearth of modeling within the very early stages of metastatic extravasation.
The model presented here invokes explicit representation of each cell and leverages repeated computed trials to sample the distributions of die out, grow out, and dormancy phenotypes exactly. However, analytic formulations called branching processes can also be applied to derive convenient predictions for this type of growth (22). These models exploit the fact that daughter cells are independent from one another and thus behave as if individual metastases (branching processes) themselves, lending to a compact, recursive formulation: hn(t) = [fn(t)]N. Here, h(t) is the 'probability generating function' (pgf) at cell-cycle n, and is computed as the product of N identical pgf's (for N starting cells in the micrometastatic tumor) (23). The pgf allows us to quickly compute the expected cell population after n cell cycles , the expected variance , and the probability of eventual extinction . In all expressions, the inputs are the number of starting cells, N, the survival probability, p, and the number of cell cycles, n, just as in our stochastic simulation model. The recursive formula above cannot yield the exact population distribution for any large n (23), such as our cell cycle limit of 1,218. That is, while we can predict dying out and survival, we cannot exactly predict dormancy with the model, for which simulations are required.
Metastatic lesions are visible through imaging modalities such as MRI when they approach 0.1 cubic centimeter. A tumor of this small size actually consists of approximately 100 million cells (24). Therefore, disseminated tumor cell deposits of less than this cannot be detected without invasive biopsy and subsequent analyses such as immunohistochemistry. Because metastatic latency can be explained by two very different mechanisms – that of cellular quiescence or proliferation offset by cell death (or a combination of both), we sought to model the second hypothesis and determine what survival probability range would give rise to the dormant phenotype. We simulated 100 patients each with 1000 metastatic deposits (1, 2, 4, and 8-cell starting sizes) across stochastic survival probabilities discontinuous between 30 and 70 percent. The modeling revealed a very narrow survival probability range between 49.7 and 50.8 percent that gave rise to dormant metastases. The reason why this dormancy probability window is so small is based upon how sensitive simulated metastases are to small changes in survival probability. If the probability of survival is less than 50 percent, the metastases all die out with the exception of the few dormant clusters because the probability favors the boundary condition of dying out. Only a rare escape from this tendency will therefore evoke a dormant metastasis. Once the probability of survival exceeds 50.8 percent, the grow-out condition of reaching 1 million cells begins to dominate. Thus, we conclude that it is unlikely that metastatic dormancy is governed predominantly by internally balanced proliferation and cell death. As shown in Figure 3, it may seem unexpected that micrometastases will die out even at survival probabilities exceeding 70 percent. The reason for this phenomenon is closely related to the number of starting cells in the metastases. It is difficult for a simulated metastasis to live through its first few generations especially when it has two starting cells; because when a cell dies the metastasis evolves closer to the boundary of dying out. As Figure 2 demonstrates, the chance of a metastasis dying out is reduced when there are eight starting cells versus two starting cells. Of the metastases that die out, they do so in a short time (Figure 3) as this relates to the fact that the metastases start near the null boundary and thus are easy to involute early before attaining a greater cell number. An often suggested model involves micrometastases growing and then being constrained at a subclinical size by the need for external supports; this is the basis of the postulated 'angiogenic switch' (25). However, even here the constraints must be tightly controlled; in an initial series of examining metastases of 1000 or 4000 starting cells, the range for staying dormant remained constrained similarly to the smaller micrometastases at between 49.5% and 51% survival probabilities; if the survival percentage drops below this, the metastatic nodules quickly die out (data not shown). Thus, even this tumor extrinsic constraint would need to be tightly controlled or frequently vacillate between outgrowth and involution. In the spirit of Occam's razor, we propose that extended periods of cellular quiescence most likely accounts for this dormant period.
While there are numerous models for dormancy these suffer from significant differences in the animal hosts, such as life-span and time-scale to development, and a lack of information about the micrometastatic state in actual cancer patients. This approach does not account for the richness of interactions and signals that may constrain or support micrometastatic nodules. For instance, it is possible that an 'angiogenic switch' is required for outgrowth once these nodules reach a certain size. However, the experimental data are lacking currently to build models incorporating such inputs. Rather, such models would presuppose these constraints and be built to account for the limitations and interventions (26). Herein, we chose an a priori unbiased calculation to simply define the boundary conditions of metastatic outgrowth regardless of the actual biological and physiological networks.
The value of mathematical models lies in their ability to suggest avenues for investigation. Recent findings of tumor cells in circulation or bone marrow despite no evidence of metastases may provide some insights into the behavior of the early metastatic cells. Interestingly, ongoing proliferation is evident only in few of these cells (27) consistent with quiescence of these cells. If these cells were truly quiescent then therapies targeted to killing growing cells would not be effective and may even cause outgrowth if the dormant microenvironment is perturbed. Still such findings are only suggestive, and highlight the need to examine human micrometastases with innovative technologies to determine the actual proliferative rates in these hidden metastases. As our currently available chemotherapy mainly attacks cycling cells, the mode of quiescence would make this treatment less effective and necessitate new approaches to the problem of metastatic dormancy.
Dormancy of metastases constitutes an ominous unknown for cancer patients – should there be adjuvant treatment or not. The call for therapy and selection of type of therapy should rationally depend on the biological properties of metastatic cells. If the cells in these clinically silent micrometastases are in a state of balanced proliferation and death, then agents targeting cycling cells are appropriate. However, if the cells are quiescent, then other approaches, or none, are appropriate. As clinical data are scarce, and experimental systems are not established to study this directly, we used an unbiased in silico model to identify the boundary condition probabilities that would allow for micrometastases to remain dormant for 5–10 years even while undergoing regular cell cycling. The resultant tight one percentage point range suggests that the metastatic cells likely undergo at least periods of quiescence. This would suggest that for longer-term dormancy, novel approaches need to be developed.
We thank members of the Wells and Bahar laboratories for helpful discussions.
This work was supported by grants from the VA Merit Award program and NIH (UH2TR000496) to A. Wells.
The authors have no conflicts of interest in regards to this work.
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Science's Sexual Assault Problem - NY Times, 18 September 2014
By: A. Hope Jahren
I am a scientist who studies plants. I like plants. I think about plants almost every hour of the day, and several hours of the night as well. I respect plants and I know there's more to them than meets the eye, because I've been measuring their responses for 20 years. But it is rocks that were my first love and that continue to hold my heart captive. I love rocks with the unconditional love that you lavish upon a newborn baby.
Read more here.