One of the suits was filed in a court in Stuttgart where VW’s Porsche unit is based.
The case was brought by half a dozen plaintiffs, including Mitsui OSK Lines, the ship’s operator, and Allianz, one of the insurers of the vessel, according to a spokesman for the tribunal.
The case was filed a year ago but was recently paused because of mediation talks planned for a second lawsuit over the ship’s that is currently before a court in Brunswick.
Both cases will resume if no settlement can be reached. A Brunswick judge plans to hold the talks later this month, according to a tribunal spokesman.
The Panama-flagged Felicity Ace caught fire near the Azores archipelago in the Atlantic Ocean two years ago and was left adrift after the crew was rescued.
An internal email from VW’s U.S. operations at the time revealed there were 3,965 vehicles aboard the ship. The cargo ship’s loss could have cost the automaker at least $155 million, according to a risk-modeling company’s estimate.
The plaintiffs claim that the fire originated from the lithium ion battery of a Porsche model and allege VW failed to inform them of the danger and necessary precautions needed to transport such vehicles, according to the Stuttgart court.
Although the case was filed a year ago, the judges have not yet looked into the merits of the suit as the parties have been quarreling about the amount of collateral that must be posted before it can proceed.
Whatever the verdict, it is bad news for the EV industry, and ultimately buyers. If Volkswagen end up paying the bill, it will put up costs for the whole industry, which will need to specifically insure against such risks.
And is Allianz have to pay, the insurance industry will insist that shipowners either stop carrying EVs, or have to pay much higher premiums, which will be passed on to the car manufacturers.
By Andrew Montford Jeremy Hunt’s budget was symptomatic of the problems with the Conservative Party, giving the impression of a government that is all but directionless because of the division in its parliamentary ranks between, on the one hand, the green blob and, on the other, a rump of old fashioned Conservatives, desperately trying to stop their colleagues from driving the party and the country into oblivion. So on the one hand we had what was claimed to be a dramatic backtracking on the boiler tax and on the other hand a new ocean of subsidies for renewables.
On closer examination, there is rather less to the boiler tax retreat than meets the eye. The policy will remain in place, but the fines on boiler manufacturers, without which it is toothless, will not be introduced in next twelve months. Insiders, we are told, are saying that the necessary secondary legislation will not even be brought before Parliament this year, and thus almost certainly not under the current administration. Whether this amounts to a hill of beans is hard to say. Is it all a ruse to kick the policy into the long grass, while allowing Green Blob ministers Graham Stuart and Lord Callanan to save face? Or is the Green Blob assuming that Labour’s Ed Miliband will simply do the dirty on the British public in 2025? We will have to wait and see. The contrast with the new wave of subsidies is astonishing. With the government having awarded astonishing price increases to the sector last year, a total of £1.4 billion of new subsidies is expected, a total that amounts to around £50 per household. This is another hammer blow aimed at the hard-pressed public. It can’t go on of course, but it is surely beyond doubt that the damage being done to our way of life by such irrational policies will be catastrophic.
There are lots of ways to screw up, delay, distort and blur a medical study
And the Principle Trial did all of them.
So here we are, years too late, getting another nanomole of truth squeezed through the distortion field. The Principle Trial gave people ivermectin far too late, and told them not to take it with food, both of which stop it being useful — yet despite that, ivermectin still saved lives and produced a statistically significant benefit. So the researchers sat on the results for a year and a half, then wrote it up with the opposite conclusion. Welcome to modern industrial medicine where the experiments are just a theatre performance. The government pretends to care and set up a big study, while they design it to fail and then hide and twist the results.
The point of doing experiments is not to find the truth but to kill it. If the crowd is baying for answers, what better way to silence them than to say you are doing a long indepth “glorious” study that takes years to complete?
It was naked sabotage…
Viruses multiply exponentially at the start of an infection, so every hour matters. The sooner an antiviral drug is started, the smaller the total viral load will be, and most likely, the shorter the infection. By the time symptoms start the virus has run amok and 1 little virion may have turned into one million virions per ml — headed for a billion. So the Principle Trial designers made sure to express deliver the artificial patented Molnupiravir drug to the randomly selected patients, while the people selected in the ivermectin arm were signed up in slow motion. Pierre Kory has the whole sordid story. One poor man claimed that after he tested positive, he had to wait 11 days for his enrollment form to come through. Ivermectin could hardly “shorten his illness” if he’s already recovered. And conversely it could hardly save his life if he was already dead.
It was so petty (but thoroughly so) that the information forms for the Molnupiravir test told patients medicine would be delivered the “next day”, and patients were given the option to pick up the medicine from the pharmacy even faster. But in the Ivermectin arm the words “next day” were deleted — the medicine would just be delivered (sometime).
The excellent c19ivm team listed the differences in the trial design, and practically name a hundred different kinds of bias. It’s as if no stone was left unturned to get a “null” result on ivermectin.
As Pierre Kory says so scathingly — the same person designed both trials:
“The reason why the above table is so powerful is that the two trial designs were by the same Principal Investigator at the same “august” institution. Why such discordant designs? Why did Butler (notice my refusal to call him Professor), when studying ivermectin, use such a low dose on an empty stomach for such a short duration (no other anti-viral is ever used for less than 5 days), so late in the disease (up to 14 days?), in more mildly ill patients?”
Despite the sabotage, theEpoch Times reports ivermectin treated patients died at less than half the rate:
People who tested positive for COVID-19 and took ivermectin as a treatment recovered faster than a comparison group…
The time to self-reported recovery was a median of two days faster among the ivermectin recipients, according to the large UK study.
People who received ivermectin were also less likely to be hospitalized or die, with 1.6 percent of ivermectin recipients being hospitalized or dying versus 4 percent of the comparison group, which received typical care, which in the UK is largely focused on managing symptoms.
About 2,000 people were given ivermectin (of a sort) and about 3,000 were given “usual treatment”. 11 people died in the normal treatment arm, but only 2 died when given ivermectin.
The biggest crime was that for three years people were denied the best treatment they could get.
Statistical games
As Pierre Kory points out, the results must have looked so good they couldn’t possibly release them. Apparently they suddenly needed to extend the trial for a whole years followup and create some excuse about how ivermectin didn’t make some arbitrary hazard ratio bar they set post hoc.
Kory remarks that in their results of “time til recovery” the probability ivermectin was superior was found to be >.999. Yet their conclusion was that “Ivermectin is unlikely to provide clinically meaningful treatment” (especially if you want to keep the hospitals full eh?) Furthermore they say, it’s not worth doing more trials. (Big Pharma will be happy about that).
The new “Hazard Ratio Bar” they invented is chicanery:
So the authors concluded that this finding was unlikely to provide a clinically meaningful result? What? I want to be brief here, but this is statistical chicanery – to support this statement they instituted an almost impossible bar to clear, that of a “pre-specified hazard ratio level that must be greater than 2.0.” I have never heard of this. A hazard ratio does not need a pre-specified level. If the HR is > 1.0, and it is statistically significant, it is a robust finding. The HR for ivermectin was a statistically significant 1.15! But it was not 2.0, so .. dismiss the result? Whatever.
Wow. just wow. Another way of saying the above is that they literally designed the statistical threshold for effectiveness in such a way that, even if ivermectin was found to be effective (which they found), if it was not like, am (arbitrary) “super large magnitude” of efficacy, it should not be recommended or thought effective. What? — Pierre Kory
Despite the extraordinary lengths they went too, ivermectin still helped.
Hayward et al (2024) Ivermectin for COVID-19 in adults in the community (PRINCIPLE): an open, randomised, controlled, adaptive platform trial of short- and longer-term outcomes, Journal of Infection on Feb. 29 2024.
I see that the usual gloomy hype about arctic sea ice continues unabated. This has been going on for a while. Here’s the dean of failed serial doomcasting, James Hansen, pontificating on the subject back in 2008.
Figure 1. James Hansen’s 2008 crashed and burned prediction of an arctic ice-free summer by 2018.
The latest entry in the prediction sweepstakes is described in the climate alarmists’ favorite newspaper, the Guardian, with the obligatory tear-jerking polar bear photo:
Ice-free summers in Arctic possible within next decade, scientists say
Home of polar bears, seals and walruses could be mostly water for months as early as 2035 due to fossil fuel emissions
Now, you’ve got to be careful to watch the pea under the walnut shell. Well down in the scientific study they say:
The definition of an ‘ice-free Arctic’ has varied over time. Early on, it referred to the nearly complete disappearance of all sea ice, or zero SIE [sea ice extent]. However, as thick sea ice remains north of Greenland and the Canadian Arctic Archipelago more than a decade after the rest of the Arctic Ocean becomes ice free in September a SIE threshold of 1 million km2 [386,000 square miles] became commonplace.
So we’re not really talking about zero sea ice extent. We’re talking about getting down to a million square kilometers of ice, more than a third of a million square miles. That’s a very different question.
Next, they say:
Statistical methods have also been used to provide predictions of an ice-free Arctic. Most of these predictions are based on observed linear relationships between global or Arctic temperature and sea ice cover.
I saw that claim of a linear relationship between temperature and Arctic sea ice extent and said “Hmmm” … let’s start with what’s actually happened to sea ice since the start of the satellite era in 1979. First, the changes up until 2012.
Now, this is curious. Minimum Arctic sea ice extent decreased slowly from the start of the satellite record up to the year 2000. From there it started dropping faster and faster, up to 2012.
And that’s why the scientific cognoscenti were so sure it was going to crash. I mean, in 2012, any sane person could see the inevitable. After dropping from 6 million to 4 million square kilometers since the turn of the century, 1 million square kilometers (AKA “ice free”) was obviously just around the corner. That’s why even back in 2008 James Hansen was so sure of an ice-free Arctic in the near future.
However, a funny thing happened on the way to Thermageddon™. Here’s the rest of the Arctic ice extent record.
Arctic sea ice extent went flat in 2012 and has stayed relatively stable since. I’m sure this made Jim Hansen tear his hair out. And it’s an excellent example of the limitations of climate models.
As far as I know, not one climate model and not one climate scientist predicted that around 2012, the strong downward trend of Arctic ice extent would go flat, and stay that way for a decade. It’s a problem with iterative climate models of chaotic systems. It’s also a problem with humans. Both humans and models tend to calculate that a trend will continue. Neither humans nor models are very good at predicting U-turns or regime shifts in chaotic systems.
So which way will it go from here? Unknown. For example, one of the oddities is that a warmer world is a wetter world, and a wetter world means more snow. Snow on top of ice insulates the ice, making it last longer. It’s a fine example of what I modestly call Willis’s First Law of Climate, which says:
In the chaotic giant heat engine we call the climate, everything is connected to everything else, which in turn is connected to everything else … … … except when it isn’t.
It’s true. The climate has six main subsystems—atmosphere, hydrosphere, lithosphere, biosphere, cryosphere, and electrosphere. Each of these subsystems is constantly exchanging matter and/or energy with all the other subsystems. Each subsystem contains relevant phenomena at all time scales from nanoseconds to millions of years, and at all spatial scales from nanometers to planetwide.
In addition, each of these subsystems has its own chaotic internal resonances, cycles, and regime shifts, which in turn affect all of the other subsystems. Climate is a system of almost unimaginable complexity that we’re only beginning to understand. As a result, claiming that we can model it with current computers is … well … let me call it hubris of the highest order.
But I digress. I started to test one of their central claims, that Arctic ice extent has a “linear relationship” with temperature. So I took the Arctic ice extent data shown in Figure 4 and compared it to a variety of temperature records. To show things clearly, I used just the smoothed versions of each dataset, and set them all to the same range from maximum to minimum.
Figure 4. A view of what the paper erroneously describes as “observed linear relationships between global or Arctic temperature and sea ice cover”. Temperature datasets are inverted because greater temperatures should yield less Arctic ice.
Not only is there no “linear relationship” between Arctic ice extent and temperature, there is very little relationship at all. Yes, in very general terms, warmer temperatures are correlated with less Arctic sea ice extent.
But none of the temperature datasets show the recent leveling out of the Arctic sea ice extent. The closest, as you might expect, is the Reynolds OI sea surface temperature north of the Arctic Circle … but even that one diverges wildly in the early part of the record and matches poorly in the recent part.
So I’m gonna say that their claim of “observed linear relationships between global or Arctic temperature and sea ice cover” is simply not true.
Finally, to return to the topic of the study, the “projections” of the year when we’ll see the first ice-free Arctic are pretty hilarious. They are so broad that if ice-free Arctic conditions were to occur at any time between now and 2150, someone’s model could claim credit for it. Below I show the nine different models and model averages reported in the study.
The first thing to notice is that contrary to the claims of an imminent ice-free summer, in fact we’re already past the claimed earliest ice-free date of five of the nine models.
Figure 5. Earliest and latest ice-free dates of the nine models and model groups. Horizontal lines connect the names of each model with the boxes whose left and right edges show the earliest and latest ice-free dates according to that model.
The dark blue region around 2035 to 2045 shows what the models say is the most likely time when we’ll see an ice-free Arctic. However, given their accuracy to date, that should be taken, not with a grain of sale, but with a kilo of salt …
Finally, the authors have used only the most extreme climate scenarios. The current general agreement among mainstream climate scientists is that these extreme scenarios (SSP5-8.5, RCP8.5, and A1B) are all highly improbable, and are not recommended for use because they lead to very unlikely projections. Despite that, the authors have selected them, presumable because it jacks up the fear and anxiety in the public … which of course will guarantee that these authors continue to receive funding in the future.
CONCLUSIONS
• There is no simple linear relationship between either global or Arctic temperature and Arctic sea ice extent.
• Models are just a reification of the understandings and misunderstandings of the programmers.
• They are supposed to be “physics based”, but if they truly were, there wouldn’t be such huge disagreements between models.
• The use of the most extreme scenarios is clear evidence of the alarmist views of the authors of this study.
And a final thought. The world of climate science would be well served to declare a moratorium on these endless failed serial doomcasts, and study the climate of the past instead. The models are a joke in that regard. Consider that the models give climate sensitivities that range from about 1.5° C to 6.5° C per doubling of CO2. Despite that, they all do a reasonable job of emulating the historical temperature record … and if they are “physics-based” as the modelers claim, that’s physically not possible. I discuss this in my post Dr. Kiehl’s Paradox That is clear evidence that they are merely tuned to match the past, and thus they have no credibility in predicting the future.
Here, it’s nighttime. I walk outside, and the redwood forest surrounding our house is perfectly silent, not a breath of wind. The constellation Orion burns low in the western sky, and Leo is right overhead. The crisp night air is redolent of springtime, of life bursting forth on all sides.
Ah, dear friends, what a wonderfully mysterious universe, with far more questions than we will ever have answers.
Iowa Climate Science Education 