Sometimes there can be manufacturing faults out the starting gate, but once past that they should be fine. The only CFL I had fail was a daylight temperature. They are relatively expensive so I bought the cheapest one I can find and it lasted a couple of weeks as it probably had a manufacturing fault. The rest I've had were mostly name brands, and some the energy company sent me for free, and were all fine. Whether they have survived being in a box in a cold shed for 5 years I don't know, but I haven't had another one fail to need to replace one to test that, but then the ones lighting the shed are CFLs that have been there as long and are fine and probably more exposed to extremes of temperature. They get used pretty much every day, although not for all that long as I tend to spend time in the house rather than the shed.
Well that's a question on use isn't it? If you use a CFL for 3/hr day as proscribed by the "average lifetime of the CFL" in question, you'll be able to get away with it for 10 years. On the other hand, if it's used say 6 hours a day, it quickly becomes a year or less that the CFL on average will last.
And that's still far longer than a standard incandescent, so your original post was nonsense, with a particular agenda not supported by evidence.
Those aren't weasel words, but because those are the standard language of science since nothing is ever absolutely proved beyond doubt. Even if you think something will happen 99.9999% of the time, you use 'highly likely', specify the probability, and error bars.
if you said it was a trend downwards because the last two numbers are 9 then 8 you would likely be wrong. And of course there are a few places in that sequence where the numbers reduce. When applied to climate some say "cooling", even though the average in some window (say 5 numbers in the above) keeps going up.
And when the quality issues were fully examined by the BEST study and Cowtan and Way it became apparent that it tended to underestimate the rate of warming.
Of course AGW is falsifiable. For example Hansen in 1988 made projections of what would happen over the next 30 years given various CO2 emissions scenarios, and the climate has changed as projected. That looks like science to me. If you think it's a political movement then the climate scientists I know seem not to have got that memo.
Record lows in the USA, perhaps. It's very mild in Europe, record highs in Australia. And the record lows in the USA are due to disturbances in the polar vortex which are a predicted consequence of global warming.
What the hell brand of CFL ae you using that fail so quickly? I have literally had one a CFL fail and I was 100% CFL for a decade. Anyway, why would you buy CFLs now as opposed to LEDs? I now have 75% LEDs apart from a couple of small lamps that are rarely on (halogen), on a dimmer circuit that isn't the right type for dimmable LEDs (using halogens) and in the sheds which are using three of the same CFLs I used to have in the house. I have a stock of old CFLs should I ever need to replace one.
State subsidy is state aid and officially banned within the EU, although there are some workarounds.
I am not sure what you mean by 'the EU' here anyway. The EU Parliament is relatively weak, although the President, elected by it, has some power. The main power lies in the Council of Ministers, so in the collective will of the constituent states.
In general the advice over the last 70 years with regards to diet, exercise and smoking has been pretty consistent. Where there are adjustments to the overall pretty consistent message it gets blown out of all proportion. Plus people tend to suggest that the message is black-and-white (give up butter) when the actual advice was to reduce saturated fat overall and replace with with monounsaturated vegetable fats, not margarine. Sometimes examples like noting that butter contains a lot of saturated fat is mentioned when people are asked for examples, and the actual advice seems to be lost by turning the nuanced advice into the headline 'Butter is now bad!'.
In terms of exaggerated risk that is often due to the misunderstanding between risk, prevalence and lifetime risk. Clinicians probably don't help matters, but again it's mostly the media not understanding the science.
One of the problems is that whilst weather forecasts are done using ensembles, the reported result is normally just the median or mean result, not the range. So the forecast might have been, if you looked at the raw output, encompassing the weather seen, but the weather seen might have been a relative outlier. But media outlets don't tend to say 'likely 0 to 10 inches of snow, most likely an average of 4 inches, lasting from 0 to 6 hours, most likely 3'. The other issue is 4 to 10 inches might be an area-adjusted 4.49 inches, or 4 when rounded and quoted, even if some places got 10.
In the UK the report may say one inch in Yorkshire, but that covers areas barely above sea level to some of the highest points in England. But most people live in the low lying areas, so the figure quoted is biased towards that. If you are from the area you know trying to go across the Pennines to Manchester is a bad idea in general (as you end up in Lancashire) but in particular if it is snowing as even if it's 1mm in Leeds it will be a ton on Saddleworth Moor. Soft southerns don't get it, though.
For completeness, it might mean that the chance of it raining in any given hour of the time period, including the one at the end of the period, might be as low as, say, 5%, even though rain on that day at some point is fairly likely. It's relatively counterintuitive for most people, even when newspapers report it correctly, and they might want to consider changing the system.
E.g. if any hour rain has a totally independent chance of 5%, the chance of rain during 24 hours is 1-(0.95)^24, or 70%. Of course, if it is raining at 3pm, it's often raining at 4pm - i.e. it's not independent. But saying there's a 70% chance of rain over 24 hours is useful if you are a farmer wondering if it's worth running the irrigation system or harvesting what that day.
At a 99.5% chance of no rain (0% of rain when rounded) per hour there's still an 11% of chance it will rain that day.
The issue you may be having is that the forecast is accurate but the news aggregator that is presenting it to you doesn't understand it and misrepresents it. In particular the 'x% probability of rain' element is widely misunderstood. '40% chance of rain' means 40% chance of raining at any point during the given period within the catchment area, and not, as popularly interpreted, including by news papers, as '40% of it raining at the moment the given time period specified in all locations in the catchment area'.
Then doubling the minimum wage for 10 an hour would increase the cost by $1.50.
That's not how the economics of a restaurant work, so that's nonsense given the overall way that a restaurant works.
At $8 an hour, and assuming the ingredients and fixed costs average out at three times this, then the cost to make a burger when 100 an hour are being produced, assuming that it takes 1/100 of a person's effort is 8*4/100, or $0.32. It sells for $1. At $16 wage it costs $0.40.
When the business is 10 per hour (which is really, really bad) then at $8 an wages the cost is now $8+$8+$8+$8/10 (ingredients cost less if you are making 1/10th as many), so the cost per burger is $2.48. At $16 an hour wage it's $16+$8+$8+$8/10, so the cost per burger is $3.28. The difference in cost is not $1.50 but $0.80
Now on the face of it if you are selling at $1 then you are losing at $8/hour anyway. But if you don't have the restaurant open often enough (and enough depends on the type of establishment) people won't come during busy hours. So you end up cross sudsidising the quiet times with the busy ones.
So at $8 per hour then each busy hour generates 100*(1-0.32) in profit, or $68. Each $1 burger during the quiet time at $8 an hour wage loses $1.48, but the total lost is only $14.80. So there is still $53.20 profit assuming equal amounts of busy and quiet times.
At $16 an hour wage the profit from busy times is 100*(1-0.40) or $60. The total loss in the quiet period is $22.80, and total profit is $37.20. Profit is reduced, but there's no increase in burger cost here.
If you increased the burger cost by $0.15 (my original estimate) then profit would be $53.70. Actually a little more than $1 burgers and $8 wage, assuming the same numbers of burgers are sold.
Obviously the numbers are nominal, but hopefully you get the principle involved. And this is assuming the same staffing at all times.
Slashdot Mirror
When the scientific establishment calls for relocation policies that encourage colonization of "flyover country" in the US by the coastal population.
And then people will complain about the scientific establishment interfering in policy, which happens whenever a scientist opines on a policy area.
Indeed there are climate cycles. This should be the cooling part of the cycle.
Saying that there has been the occasional instance I've forgotten about the shed and left them on for days at a time. I try to avoid that, of course.
Sometimes there can be manufacturing faults out the starting gate, but once past that they should be fine. The only CFL I had fail was a daylight temperature. They are relatively expensive so I bought the cheapest one I can find and it lasted a couple of weeks as it probably had a manufacturing fault. The rest I've had were mostly name brands, and some the energy company sent me for free, and were all fine. Whether they have survived being in a box in a cold shed for 5 years I don't know, but I haven't had another one fail to need to replace one to test that, but then the ones lighting the shed are CFLs that have been there as long and are fine and probably more exposed to extremes of temperature. They get used pretty much every day, although not for all that long as I tend to spend time in the house rather than the shed.
Well that's a question on use isn't it? If you use a CFL for 3/hr day as proscribed by the "average lifetime of the CFL" in question, you'll be able to get away with it for 10 years. On the other hand, if it's used say 6 hours a day, it quickly becomes a year or less that the CFL on average will last.
And that's still far longer than a standard incandescent, so your original post was nonsense, with a particular agenda not supported by evidence.
Those aren't weasel words, but because those are the standard language of science since nothing is ever absolutely proved beyond doubt. Even if you think something will happen 99.9999% of the time, you use 'highly likely', specify the probability, and error bars.
People who live on a planet where food production is related to climate? They might care.
That's not how statistics work
In the series 0,1,2,3,4,3,4,5,4,6,5,7,8,9,8
if you said it was a trend downwards because the last two numbers are 9 then 8 you would likely be wrong. And of course there are a few places in that sequence where the numbers reduce. When applied to climate some say "cooling", even though the average in some window (say 5 numbers in the above) keeps going up.
And when the quality issues were fully examined by the BEST study and Cowtan and Way it became apparent that it tended to underestimate the rate of warming.
Of course AGW is falsifiable. For example Hansen in 1988 made projections of what would happen over the next 30 years given various CO2 emissions scenarios, and the climate has changed as projected. That looks like science to me. If you think it's a political movement then the climate scientists I know seem not to have got that memo.
Record lows in the USA, perhaps. It's very mild in Europe, record highs in Australia. And the record lows in the USA are due to disturbances in the polar vortex which are a predicted consequence of global warming.
What the hell brand of CFL ae you using that fail so quickly? I have literally had one a CFL fail and I was 100% CFL for a decade. Anyway, why would you buy CFLs now as opposed to LEDs? I now have 75% LEDs apart from a couple of small lamps that are rarely on (halogen), on a dimmer circuit that isn't the right type for dimmable LEDs (using halogens) and in the sheds which are using three of the same CFLs I used to have in the house. I have a stock of old CFLs should I ever need to replace one.
I don't think Iceland has oil either. Just cod and Bjork.
Ah, yes - Nordic (includes Finland), Scandanavia does not.
State subsidy is state aid and officially banned within the EU, although there are some workarounds.
I am not sure what you mean by 'the EU' here anyway. The EU Parliament is relatively weak, although the President, elected by it, has some power. The main power lies in the Council of Ministers, so in the collective will of the constituent states.
Only Norway has any significant amount of oil of the three Nordic countries.
Seemingly clicking fast is a significant component of winning the game.
Often the issue is not that it is wrong, just not detailed enough. Like running is good for most people. Not those with a broken leg, though.
In general the advice over the last 70 years with regards to diet, exercise and smoking has been pretty consistent. Where there are adjustments to the overall pretty consistent message it gets blown out of all proportion. Plus people tend to suggest that the message is black-and-white (give up butter) when the actual advice was to reduce saturated fat overall and replace with with monounsaturated vegetable fats, not margarine. Sometimes examples like noting that butter contains a lot of saturated fat is mentioned when people are asked for examples, and the actual advice seems to be lost by turning the nuanced advice into the headline 'Butter is now bad!'.
In terms of exaggerated risk that is often due to the misunderstanding between risk, prevalence and lifetime risk. Clinicians probably don't help matters, but again it's mostly the media not understanding the science.
(By 'some' I just wanted to exclude the possibility there's a higher peak in Derbyshire or Lancashire on the edge of Yorkshire).
One of the problems is that whilst weather forecasts are done using ensembles, the reported result is normally just the median or mean result, not the range. So the forecast might have been, if you looked at the raw output, encompassing the weather seen, but the weather seen might have been a relative outlier. But media outlets don't tend to say 'likely 0 to 10 inches of snow, most likely an average of 4 inches, lasting from 0 to 6 hours, most likely 3'. The other issue is 4 to 10 inches might be an area-adjusted 4.49 inches, or 4 when rounded and quoted, even if some places got 10.
In the UK the report may say one inch in Yorkshire, but that covers areas barely above sea level to some of the highest points in England. But most people live in the low lying areas, so the figure quoted is biased towards that. If you are from the area you know trying to go across the Pennines to Manchester is a bad idea in general (as you end up in Lancashire) but in particular if it is snowing as even if it's 1mm in Leeds it will be a ton on Saddleworth Moor. Soft southerns don't get it, though.
For completeness, it might mean that the chance of it raining in any given hour of the time period, including the one at the end of the period, might be as low as, say, 5%, even though rain on that day at some point is fairly likely. It's relatively counterintuitive for most people, even when newspapers report it correctly, and they might want to consider changing the system.
E.g. if any hour rain has a totally independent chance of 5%, the chance of rain during 24 hours is 1-(0.95)^24, or 70%. Of course, if it is raining at 3pm, it's often raining at 4pm - i.e. it's not independent. But saying there's a 70% chance of rain over 24 hours is useful if you are a farmer wondering if it's worth running the irrigation system or harvesting what that day.
At a 99.5% chance of no rain (0% of rain when rounded) per hour there's still an 11% of chance it will rain that day.
At the end of the time period, that should read.
The issue you may be having is that the forecast is accurate but the news aggregator that is presenting it to you doesn't understand it and misrepresents it. In particular the 'x% probability of rain' element is widely misunderstood. '40% chance of rain' means 40% chance of raining at any point during the given period within the catchment area, and not, as popularly interpreted, including by news papers, as '40% of it raining at the moment the given time period specified in all locations in the catchment area'.
Then doubling the minimum wage for 10 an hour would increase the cost by $1.50.
That's not how the economics of a restaurant work, so that's nonsense given the overall way that a restaurant works.
At $8 an hour, and assuming the ingredients and fixed costs average out at three times this, then the cost to make a burger when 100 an hour are being produced, assuming that it takes 1/100 of a person's effort is 8*4/100, or $0.32. It sells for $1. At $16 wage it costs $0.40.
When the business is 10 per hour (which is really, really bad) then at $8 an wages the cost is now $8+$8+$8+$8/10 (ingredients cost less if you are making 1/10th as many), so the cost per burger is $2.48. At $16 an hour wage it's $16+$8+$8+$8/10, so the cost per burger is $3.28. The difference in cost is not $1.50 but $0.80
Now on the face of it if you are selling at $1 then you are losing at $8/hour anyway. But if you don't have the restaurant open often enough (and enough depends on the type of establishment) people won't come during busy hours. So you end up cross sudsidising the quiet times with the busy ones.
So at $8 per hour then each busy hour generates 100*(1-0.32) in profit, or $68. Each $1 burger during the quiet time at $8 an hour wage loses $1.48, but the total lost is only $14.80. So there is still $53.20 profit assuming equal amounts of busy and quiet times.
At $16 an hour wage the profit from busy times is 100*(1-0.40) or $60. The total loss in the quiet period is $22.80, and total profit is $37.20. Profit is reduced, but there's no increase in burger cost here.
If you increased the burger cost by $0.15 (my original estimate) then profit would be $53.70. Actually a little more than $1 burgers and $8 wage, assuming the same numbers of burgers are sold.
Obviously the numbers are nominal, but hopefully you get the principle involved. And this is assuming the same staffing at all times.