by Skylar Tallal Fri, August 23rd 2024 at 10:30 PM
DES MOINES, Iowa — Summit Carbon Solutions is facing a set back in its proposed CO2 pipeline project, as the South Dakota Supreme Court ruled in favor of landowners who sued to keep Summit from surveying their land.
It’s a reversal of a lower court decision, with the state’s high court now claiming it’s premature to categorize Summit as a ‘common carrier’ for public utility. It’s something Summit needs to be able to prove before it can use eminent domain.
“One of our main arguments is that Summit’s not a common carrier,” Jess Mazour the conservation program coordinator with the Sierra Club Iowa Chapter said. “So it really does change the game here in Iowa as well.”
Summit can’t start building its pipelines in Iowa until it gets approval in North and South Dakota.
The Sierra Club Iowa Chapter calls the decision a victory for landowners. Even though the Iowa Utilities Commission isn’t taking up the club’s reconsideration request, the club is moving forward with its plan to take the fight to court.
“We now have precedent on our side and we’re going to have a strong base for when we file our appeal in district court,” Mazour said.
A similar court case is already on the books in Iowa, with Iowa’s highest court set to hear oral arguments October 8 at the state capitol.
“A landowner in Hardin County, Kent, he was sued for denying Summit access to his land and we are fighting that and also challenging Iowa’s survey law,” Mazour said.
Eminent Domain has been a major issue in Iowa over the last few years. Some Iowa lawmakers joined the pipeline opposition but haven’t been successful in their efforts to change state laws.
The topic is also coming up on the campaign trail, specifically in Iowa’s congressional races.
Congressional Rep. Mariannette Miller-Meeks (R) Iowa said carbon capture pipelines make sense for Iowa.
“So the carbon capture pipeline is only meant to lower the carbon intensity score of ethanol which makes it competitive globally,” Rep. Miller-Meeks said.
She said while eminent domain is a state issue, she hopes there will only be a limited number of landowners who don’t sign on voluntarily.
“Farmers and property owners need to look at the why the rationale and then determine if it’s in their best interest,” Rep. Miller-Meeks said. “Companies that are acquiring easements are looking at how do you make the land whole. How do you ensure farmers that you can grow crops in the near future?”
Iowa’s News Now did reach out to Summit for comment didn’t hear back.
A hydrogel has learned to play the 1970s video game “Pong” and improved its ability to hit the ball by 10% with some practice.
Dr Hayashi, a biomedical engineer at the University of Reading in the UK, says: “Our research shows that even very simple materials can exhibit complex, adaptive behaviours typically associated with living systems or sophisticated AI.
“This opens up exciting possibilities for developing new types of ‘smart’ materials that can learn and adapt to their environment.”
The research is described in a paper published in Cell Reports Physical Science.
Video link, an example run of a hydrogel playing Pong.
Credit: Cell Reports Physical Science/Strong et al.
What is a hydrogel?
A hydrogel, like gelatine or agar, is made of a 3D network of polymers that become jelly-like when water is added.
The hydrogel in this study is an “ionic electro-active polymer”, where the media surrounding the polymer matrix contains charged particles, in this case hydrogen ions.
As a result, it can deform when an electric current is applied to it.
Stimulation by an electric field causes the hydrogen ions migrate and, as they move, drag water molecules with them, causing areas to swell.
“The rate at which the hydrogel de-swells takes much longer than the time it takes for it to swell in the first place, meaning that the ions’ next motion is influenced by its previous motion, which is sort of like memory occurring,” says first author and University of Reading robotics engineer, Dr Vincent Strong.
“The continued rearrangement of ions within the hydrogel is based on previous rearrangements within the hydrogel, continuing back to when it was first made and had a homogeneous distribution of ions.”
It’s this property the researchers exploited to teach the hydrogel to play Pong.
How does a hydrogel play Pong? (snip-More on the page)
NASA is about to launch a helium balloon carrying a telescope, to test its ability to see exoplanet atmospheres.
The Exoplanet Climate Infrared Telescope (EXCITE) is eventually destined to fly around the poles, collecting data above much of the Earth’s atmosphere, but its first test flight is due to happen from the USA in the next few months.
It will be launched for the first time from the Columbia Scientific Ballooning Facility in New Mexico.
EXCITE (EXoplanet Climate Infrared TElescope) hangs from a ceiling at the Columbia Scientific Balloon Facility’s location in Fort Sumner, New Mexico. The mission team practiced taking observations ahead of flight by looking out the hanger doors at night. Credit: NASA/Jeanette Kazmierczak
“EXCITE can give us a three-dimensional picture of a planet’s atmosphere and temperature by collecting data the whole time the world orbits its star,” says principal investigator Peter Nagler, from NASA’s Goddard Space Flight Center. (snip-More on the page)
Like many of us, I grew up with the Lost in Space Robot, Hal, and of course, the T1000.
And, as anyone who has ever seen me around a computer can tell you, I am in no danger of ever creating an AI, much less giving any fair representation of the risks that come with AI. What I can tell you is that images, chat, and other electronically produced media does share a risk that can be co-opted and influenced by our current understanding of AI. This does require us to look closely at what we see on the internet, what we believe is going on in and around our environment, and most importantly becoming a better defender of our personal borders. There is no doubt that the impersonation of human creations is going to effect our lives going forward. Further, there is no doubt that beautiful things CAN be created via AI. Not sure about this one: https://www.youtube.com/shorts/glIzD8CVwrQ
As with everything, new technology brings new fears, new opportunities, new joys, and a new way of life. In regards to the T1000, I’m really crossing my fingers on the “new way of life” part.
Hugs!
Randy
-ps: Scottie, this should teach you to not ask me to post on your blog. roflmao! Sorry, I’m easily entertained.
The integration of artificial intelligence into public health could have revolutionary implications for the global south—if only it can get online.
(Whew! It’s a long one. Maybe read it in part, then come back and read some more. Or read it all at once, it’s not insurmountable. I’m interested what people here think about this.)
The transformative potential of digital connectivity became a global game changer more than two decades ago. Mobile phones reshaped telecommunications, enabling connectivity even in homes without landlines. Digital health quickly leveraged these innovations, making remote patient-doctor communication, digital payments, care coordination, and online peer support networks possible.
Artificial intelligence (AI) has undoubtedly sparked another phase of digital innovation. Although the field’s origins date to the mid-twentieth century, recent advancements in large language models (LLMs) have thrust it into the spotlight. Reflecting this growing relevance, the World Health Organization (WHO) dedicated a session at its World Health Assembly (WHA) in early 2024 to AI’s implications for global health, convening regional, national, academic, and international health organizations and actors to examine this matter.
AI Applications in Global Health
The literature generally presents four key use cases for artificial intelligence in health in low- and middle-income countries: disease diagnosis, risk assessment, outbreak preparation and response, and planning and policy-making. As the 2021 WHO report on AI in healthcare indicates, several AI applications are already in use or in development for diagnosis and assessment, such as in India for rapidly creating encephalograms in six minutes; in Rwanda and Pakistan for patient navigation; in Uganda, for malaria diagnosis; and in Nigeria for monitoring vital signs in mothers and children, and detecting infant asphyxia. On a broader scale, the advancement of DeepMind’s AlphaFold system in predicting the three-dimensional shape of proteins holds promise for enhancing our understanding of diseases and accelerating treatments.
Use cases in outbreak surveillance and response are also prominent. Google Flu Trends used search engine queries to predict influenza activity, but its overestimation of flu prevalence demonstrated the need for continuous algorithm updates. Tools like HealthMap have also proven valuable, detecting early signs of vaping-related lung disease and issuing an early bulletin about the novel coronavirus in Wuhan.
AI is also being used in planning and policy making, such as in South Africa where machine-learning (ML) models were used to predict how long recruited health workers’ would commit to their placements in rural communities; and in Brazil where artificial neural networks were used to create a method to geographically optimize resources based on population health needs.
Could AI Represent a Sea-Change in Global Health?
The integration of AI in public health is still evolving and being cautiously assessed in some cases, but it’s poised to transform key health functions. Evidence generation, the foundation of health policies and practices, is undergoing significant change. Traditionally, systematic reviews, a cornerstone of evidence synthesis, may take months or even years to complete. Now tools like Eppi-Reviewer use ML for more efficient screening, while platforms like Open Evidence are able to summarize existing studies rapidly. As AI becomes capable of handling technical aspects such as quality appraisal, meta-analysis, and synthesis with high rigor and fidelity, its role in evidence generation will expand. This advancement will enable more cost-effective and timely production of health guidelines, with leading bodies already creating guidelines for AI use in evidence synthesis.
Data collection and analysis are also experiencing transformative changes. AI-powered tools enable rapid analysis of both structured and unstructured data, marking a significant shift from traditional paper-based methods and conventional fieldwork. This capability has a remarkable impact on public health strategies centered on behavior change. AI can allow for the creation of highly targeted health promotion campaigns with unprecedented speed and precision. Moreover, sentiment analysis tools can assess public perceptions in real-time, enabling agile adjustments to ongoing health campaigns.
The healthcare workforce is also expected to evolve as AI-human partnerships are normalized. For instance, Hippocratic AI’s generative models can perform certain care management functions, while Google’s Med-Gemini provides real-time feedback on medical procedures, including surgeries. As they improve and are adopted by practitioners, these tools will have the potential to enhance the cost-effectiveness and precision of healthcare delivery.
As of May 2024, the FDA had authorized 882 AI- and ML-enabled medical devices. The rising volume of such AI-enabled devices as well as the rise in registered clinical trials related to their use underscores how much the field has embraced such tools.
A Changing Actor Landscape
The integration of AI in healthcare is not only transforming practices but also reshaping the landscape of global health actors. Historically, global health was a multilateral activity, dominated by international non-governmental organizations and national governments alike. The early twenty-first century saw the emergence of influential philanthropic actors like the Gates Foundation. Now, we are entering a phase where private-sector AI companies are poised to become increasingly influential in this arena.
While open-source models and government-developed AI systems exist, the predominance of private-sector AI models, such as OpenAI’s ChatGPT and Google’s Gemini, raises critical questions about data governance in global health. Unlike existing cross-national commercial influences on health such as the fast food or tobacco industries, AI systems present more nuanced concerns. For instance, if private models become integrated into existing multilateral health initiatives, how can we ensure their compliance with global health objectives? How do we address potential conflicts of interest when companies hold influence over health data and decision-making?
Regional and national guidelines are emerging to govern this evolving landscape. The European Health Data Space, discussed at the World Health Assembly, offers one such example. This initiative aims to create a single data space across the twenty-seven EU member states, empowering patients to control their health data while establishing a framework for safe data reuse and AI deployment. It also includes provisions for rigorous evaluation of high-risk AI systems in healthcare.
Similarly, the African Union recently launched its Continental AI Strategy, with a stated aim “to harness artificial intelligence to meet Africa’s development aspirations and the well-being of its people, while promoting ethical use, minimizing potential risks, and leveraging opportunities.” Monitoring measures like this as they develop will be instructive for the future deployment of AI in global health initiatives.
Building Foundational Infrastructure
Another factor to consider is that advances in AI mean little for health systems at an insufficient level of maturity. Progress in AI depends heavily on a strong foundation of digital health architecture, which encompasses secure data management, interoperability between health information systems, and comprehensive digital strategies. While most countries have digital health strategies, their implementation varies widely, with progress in resource-limited settings often lagging. Several countries have neither sufficient health workers to regularly input data nor dependable electricity and Wi-Fi to support a transition from paper to digital records. The lack of foundational infrastructure presents a significant barrier to AI implementation.
Initiatives like the Precision Public Health Initiative, led by the Rockefeller Foundation in collaboration with the WHO, UNICEF, global health funding agencies, ministries of health, and technology companies aim to strengthen AI use in low- and middle-income countries (LMICs). With initial funding of US$100 million, it aims to extend the use of AI and data science in LMICs, providing the latest technology to under-resourced parts of the world. Initiatives like this will need to concentrate resources on foundational health system strengthening functions such as the training and supportive supervision of staff and resource management.
Ethical Implications
As AI advances, ethical considerations must keep pace. These challenges can be broadly categorized into privacy and surveillance concerns, data misuse, algorithmic biases, and issues of transparency and liability. Recent cases highlight the urgency of addressing these matters proactively.
As the research report Ethics and Governance of Artificial Intelligence for Health: WHO Guidance explains, during the COVID-19 pandemic, China’s Alipay introduced a “Health Code” that used collected data to determine exposure risks. This system, which determined individuals’ mobility based on their assigned color codes, raised concerns about privacy, rights, and the potential for mass surveillance. Another case discussed in the WHO guidance report is Dinerstein vs. Google, in which the University of Chicago shared patient records stripped of identifying information with Google to develop machine-learning tools for predicting medical events. A class action complaint was filed, alleging that records could be re-identified, threatening patient privacy.
Several cases other cases in the WHO guidance report highlight the critical issue of bias in AI systems. In Argentina, an AI system designed to predict adolescent pregnancy faced criticism when it was found to have flawed methodology and to violate the privacy of adolescents. Similarly, a study in the US revealed racial biases in an algorithm that resulted in Black patients receiving less medical attention than equally sick white patients.
Additionally, an AI technology designed to detect potentially cancerous skin lesions was trained primarily on data from lighter-toned individuals in Australia, Europe, and the US, highlighting its inadequacy for darker-skinned populations.
The “black box” nature of many AI algorithms also raises critical questions about informed consent and liability. If an AI system recommends a specific drug dosage, but the underlying algorithm is opaque to the physician, who bears responsibility for adverse outcomes?
A Case Study
To illustrate how the various considerations of AI in global health converge, the WHO’s Smart AI Resource Assistant for Health (S.A.R.A.H.) project provides a recent and relevant case study. Launched in April 2024, S.A.R.A.H. is a video-based generative AI assistant designed to address gaps in health information accessibility. Developed in partnership with Soul Machines Biological AI, this initiative represents, in the words of WHO Director-General Dr. Tedros Adhanom Ghebreyesus, “how artificial intelligence could be used in future to improve access to health information in a more interactive way.”
The potential for LLMs in health promotion must be viewed against the backdrop of the burden placed on health systems. For example, Sub-Saharan Africa and South Asia have an estimated 0.2 and 0.8 doctors per 1000 people, respectively, compared to 4.3 in the European Union and 3.4 in North America. A map of travel time to health facilities reveals that it’s not uncommon to spend a day traveling to see a doctor in several regions such as North Africa. Even when they can see a doctor, more than a billion people are driven into poverty each year because of exorbitant health care costs. In such contexts, LLMs can complement the health promotion efforts currently being provided by community health workers. They can also enhance supervision and training.
S.A.R.A.H. stands out for its efforts to tailor recommendations to local contexts. For example, it offers meal recommendations based on regional dietary habits. It also uses visual emotional cues to display empathy. Like its WhatsApp-based chatbot predecessor for sharing COVID-19 information, S.A.R.A.H.’s reach will probably expand through partnerships with telecommunications providers and social networks, supporting its broad dissemination.
However, S.A.R.A.H. faces some challenges that mirror broader issues in AI for global health. Users have noticed errors in the information S.A.R.A.H. has provided; it incorrectly stated, for example, that a drug for Alzheimer’s was still in clinical trials when the drug had been approved in 2023. This highlights the critical need for AI systems to keep pace with rapidly evolving medical knowledge.
While S.A.R.A.H. offers a wider range of languages than many existing tools (including French, Russian, English, Spanish, Hindi, Portuguese, Arabic, and Chinese), this still represents only a fraction of global languages, potentially limiting its reach. Also, the success of video-based tools like S.A.R.A.H. depends on robust digital infrastructure and access to smartphones with video capabilities, which are hardly universally available.
The processing of users’ video data also raises important privacy considerations. While not yet available, the WHO has committed to making the training materials and the evidence base for S.A.R.A.H. publicly accessible, aligning with its principles on LLM use. Transparency in how S.A.R.A.H. processes and uses data will be crucial in maintaining trust and offering insights for this emerging space.
Conclusion
As noted by WHO Director-General Dr. Tedros at the WHA, AI represents a transformative advancement in global health akin to past innovations such as the introduction of vaccines, penicillin, MRI machines, and human genome mapping, all of which revolutionized the field. As reported in the above-linked 2021 WHO report on AI in healthcare, the integration of AI into health systems presents immense potential with projections noting that the top ten AI applications in health could result in an estimated US$150 billion in savings by 2026.
While the potential of AI is undeniable, the critical question remains: can it fulfill the promise of improving health outcomes worldwide? This hinges on several factors, including building foundational infrastructure, addressing ethical considerations, and effectively governing the evolving landscape of actors, which are no small feats.
The Inflation Reduction Act has sparked a manufacturing boom across the U.S., mobilizing tens of billions of dollars of investment, particularly in rural communities in need of economic development.
The future of those investments could hinge on the outcome of the U.S. presidential election. The prospect of a Republican victory has shaken the confidence of some investors who worry the IRA could be weakened or in a worst-case scenario repealed.
Actual manufacturing investment has totaled $89 billion, an increase of 305% compared to the two years prior to the IRA, according to MIT and Rhodium. Overall, the IRA has leveraged half a trillion dollars of investment across the manufacturing, energy and retail sectors, according to the data.
“It is having a transformative effect within the manufacturing sector,” said Trevor Houser, a partner with the Rhodium Group. “The amount of new manufacturing activity that we’re seeing right now is unprecedented in recent history, and is in large part due to new clean energy manufacturing facilities.”
Some 271 manufacturing projects for clean energy tech and electric vehicles have been announced since the IRA passed, which will create more than 100,000 jobs if they are all completed, according to the advocacy group E2, a partner of the National Resources Defense Council. The investments sparked by the IRA have been a boon for rural communities in particular, Houser said.
“Unlike investment in AI and tech and finance, which is clustered in big cities, clean energy investment really is concentrated in rural communities, and is one of the brightest sources of new investment in those areas,” Houser said.
The IRA has also accelerated the deployment of renewable energy, with $108 billion in invested in utility-scale solar and battery storage projects. Investments in solar and battery storage have surged 56% and 130%, respectively, over the past two years, according to the Rhodium data.
“The more mature technologies, so like wind and solar generation, electric vehicles, those have achieved escape velocity,” Houser said. “They will continue to grow no matter what. It’s a question of speed.”
Trump threats to IRA
But the “manufacturing renaissance” is still in its early stages and remains fragile, Houser said. Without the IRA, the resurgence of new factories would not have taken off, said Chris Seiple, vice chairman of Wood Mackenzie’s power and renewables group.
Former President Donald Trump has threatened to dismantle the law as he advocates for more oil, gas and coal production.
“Upon taking office, I will impose an immediate moratorium on all new spending grants and giveaways under the Joe Biden mammoth socialist bills like the so-called Inflation Reduction Act,” Trump told supporters at a May rally in Wisconsin.
“We’re going to terminate his green new scam,” he said. “And we’re going to end this war on American energy — we’re going to drill, baby, drill.”
(And of course you should listen to “Supermassive Black Hole” by Muse while enjoying this article. It’s the real only way. 😉)
August 21, 2024 Evrim Yazgin
Astrophysicists at Melbourne’s Monash University have generated the first simulation which accurately depicts what happens when a star ventures too close to a supermassive black hole.
The research, published in Astrophysical Journal Letters, is a technical milestone in our attempts to understand these mysterious cosmic giants.
First author Daniel Price, a professor at Monash, tells Cosmos that there are about 100 events which have been observed over the past decade-and-a-half which astronomers believe fit the bill to be a star being destroyed by a supermassive black hole, also called a tidal disruption event (TDE).
Not X-ray vision
But these observations have thrown up some odd measurements which haven’t been explained until now.
“If you dump a bunch of material close to black hole and form an accretion disk around that black hole, there’s a prediction for where the material should land,” Price says. “The material at that location should be more than a million degrees in temperature. It should generate X-rays.
“So, if you have unobscured stuff feeding a black hole, you get X-ray emission. For example, the black hole sources in the galaxy, they’re all X-ray emitters.”
Stars falling into supermassive black holes, however, do not result in emission of X-rays. They emit light in the visible, or optical, spectrum.
Current theories can only speculate why such events lead to material being flung toward us at 20,000km per second – about one-fifteenth the speed of light.
An eating analogy – but not in the way you think
Price explains that the simulation illuminates why it is optical light, not X-rays, which we observe when our telescopes pick up stars falling into supermassive black holes.
“The analogy with me eating is that you don’t see my stomach. You’re not seeing the thing that’s generating the energy, you’re seeing it reprocessed through my skin,” Price says. “If you look at my light curve, you see that I’m a constant temperature of 38°C all day.
“My light curve is very much like a disruption event. The temperatures are pretty much constant. Luminosity changes a bit, but you infer that’s because the size of the objects changing, but the temperature evolution is very flat. So, it looks like exactly like me, just a lot warmer and a lot bigger.”
In fact, this size of the photosphere – the object which emits the optical rays – itself is surprising, says Price.
The photosphere in the simulation, which matches observations, is about 100 astronomical units (AU), where 1 AU is the distance from the Earth to the Sun (roughly 150 million kilometres).
Price says the simulations confirm a theoretical explanation for these unexpected observations called the Eddington envelope.
“That’s the concept that you’re stuffing material down towards the black hole faster than it can process it,” Price says. “By process, I mean like the sun processes the energy from its core – it just kind of gently radiates it away. So the black hole can’t radiate away the stuff that you’re trying to feed it. And, so, it has to literally blow it away.”
This material “smothers” the black hole, absorbing the X-rays that the black hole emits and re-emitting it as optical light.
Price extends the eating analogy to an unpleasant place.
“Basically, it’s like stuffing your stomach. You’re going to vomit eventually. That’s pretty much what happens.”
The power of a simulation
“That’s the exciting thing in simulations. People have speculated for a long time and drawn illustrations and this kind of thing, but there’s no physics in that. That’s just what we call phenomenology. That’s how it must be to explain this phenomena. But we don’t know what produces that kind of envelope or layer, or reprocessing layer,” Price says.
The simulation, Price says, just requires the initial conditions – the star – the fluid mechanics governing the star, and the rules of general relativity.
“Then it’s just a technical challenge,” he says.
“In a lot of simulation work, you’re kind of guessing what might have happened,” he adds. “But in this case, we’re pretty sure what happens. It’s really nice to get that connection to the observations of transients from just chucking a star at a computer.”
Price explains that the simulation will set astrophysicists and astronomers up to be able to understand such phenomena much better as more observations are expected to be made soon.
“The first optical transient was only detected in 2010, but what’s coming is the Rubins observatory being built in Chile. That’s expected to boost the population of these things into the thousands.
“Having a good theoretical understanding of what the kind of phenomena is sets us up really well for that future flood of observations. It’s not just some theoretical speculation. There’s really something we can go after and understand by looking at it.”
Scientists have compiled a library of hailstones to help fine-tune hailstorm simulations and make weather forecasts more accurate.
To make calculations more simple, conventional scientific hailstorm modelling assumes all hailstones are perfectly spherical. In reality, they’re a little more complicated than that.
A hailstone, flecked with black paint to assist in 3-D scanning, is weighed as part of processing for the hail library. Credit: UQ
“Hail can be all sorts of weird shapes, from oblong to a flat disc or have spikes coming out – no two pieces of hail are the same,” says Dr Joshua Soderholm, honorary senior research fellow at University of Queensland and research scientist at the Bureau of Meteorology in Australia.
In their new study in the Journal of the Atmospheric Sciences, Soderholm and collaborators explored whether compiling a reference library of non-spherical, natural hail shapes could change the outcomes of hailstorm modelling.
“Our study used data from 217 hail samples, which were 3-D scanned and then sliced in half, to tell us more about how the hailstone formed,” says Soderholm.
“This is effectively a dataset to represent the many and varied shapes of hailstones.”
According to lead researcher Yuzhu Lin, a PhD candidate at Pennsylvania State University in the US, the differences were dramatic.
“Modelling of the more naturally shaped hail showed it took different pathways through the storm, experienced different growth and landed in different places,” she says.
Dr Joshua Soderholm photographing a hailstone. Credit: UQ
“It also affected the speed and impact the hail had on the ground. This way of modelling had never been done before, so it’s exciting science.”
While the modelling is currently only used by scientists studying storms, Soderholm says the end game is to be able to predict how big hail will be and where it will fall in real-time.
“More accurate forecasts would of course warn the public so they can stay safe during hailstorms and mitigate damage,” he says.
“But it could also significantly benefit industries such as insurance, agriculture and solar farming which are all sensitive to hail.”
August 12, 1953 The first Soviet hydrogen (thermonuclear or fusion) bomb, far more potentially damaging than those dropped on Japan, was exploded in the Kazakh desert, then part of the Soviet Union. Igor Vasziljevics Kurcsatov, head of the Soviet Uranium Committee, said to Josef Stalin at the time: “The atomic sword is in our hand. It is time to think about the peaceful use of nuclear energy.” The Soviet Nuclear Weapons Program: https://nuclearweaponarchive.org/Russia/Sovwpnprog.html
August 12, 1982 Open missile tubes on Trident sub Twelve were arrested in an attempted blockade of the first Trident submarine, the USS Ohio, entering the Hood Canal in the state of Washington. In motorboats, sailboats and small handmade wooden vessels, the demonstrators were objecting to the presence of nuclear weapons in Seattle. The Coast Guard overturned some of the vessels with water cannon.
August 12, 1995 Thousands demonstrated in Philadelphia and other cities in support of journalist and former Black Panther Mumia Abu-Jamal (on death row for murder since 1982) in the largest anti-death-penalty demonstrations in the U.S. to date. Who is Mumia Abu-Jamal? https://www.amnesty.org/en/wp-content/uploads/2021/06/amr510012000en.pdf
The Soviet Nuclear Weapons Program: 
Open missile tubes on Trident sub
Scottie's Playtime 