The Fordow Fuel Enrichment Plant (FFEP) is an underground facility located near the city of Qom in Iran. It was built by Iran to enrich uranium and is considered one of the key sites in the country’s nuclear program. The plant became known to the international community in 2009 when its existence was revealed by Western intelligence agencies, raising concerns about Iran's intentions regarding nuclear weapons development.
"Manufactured Crisis: The Untold Story of the Iran Nuclear Scare" is a book written by diplomat and scholar, Gareth Porter. Published in 2014, the book critiques the narrative surrounding Iran's nuclear program and the alleged threats it poses to global security. Porter argues that much of the fear and concern about Iran's nuclear ambitions have been exaggerated or misrepresented, serving the political agendas of certain interests in the U.S. and Israel.
Nuclear power reactors come in various designs, each with its unique features, advantages, and disadvantages. Here are some of the main types of nuclear reactors: 1. **Pressurized Water Reactor (PWR)**: - **Description**: The most common type of nuclear reactor worldwide. In a PWR, water is heated under high pressure to prevent it from boiling. This pressurized water transfers heat to a secondary loop that produces steam to drive a turbine.
"KS 150" can refer to different things depending on the context. For instance: 1. **KS 150 (Air Conditioner)**: It may refer to a specific model of an air conditioning unit, possibly from a manufacturer that produces HVAC systems. 2. **KS 150 in Engineering/Manufacturing**: It could denote a specific equipment model or a part number used in particular industries.
The Neely Nuclear Research Center (NNRC) is a facility associated with the Department of Nuclear Engineering at Texas A&M University. The center focuses on research and education in nuclear engineering and related fields. It provides advanced resources for students and researchers to conduct experiments, simulations, and analyses related to nuclear science and engineering. The NNRC features a research reactor, which is a critical asset for hands-on learning and experimentation in areas such as nuclear reactor design, radiation detection, and nuclear safety.
Nuclear accidents and incidents in the United States refer to events that involve the release of radioactive materials, operational failures, or other significant issues related to the use of nuclear power. While the United States has a relatively good safety record, there have been notable incidents that have raised concerns about nuclear safety. Some of the most significant nuclear accidents and incidents include: 1. **Three Mile Island (1979)**: This is the most significant accident in U.S. commercial nuclear power plant history.
Siemens is a global technology company headquartered in Munich, Germany. It is one of the largest industrial manufacturing companies in Europe and operates in various sectors, including: 1. **Automation and Digitalization:** Siemens provides solutions for manufacturing and processing industries to enhance efficiency and productivity through automation and digital services. 2. **Smart Infrastructure:** The company offers products and services that focus on intelligent infrastructure for buildings and grids, enhancing energy efficiency and sustainability.
Japan has a well-established nuclear technology sector, which includes a number of companies specializing in various aspects of nuclear power generation, fuel production, and related technologies. Here are some of the key players in Japan's nuclear technology industry: 1. **Tokyo Electric Power Company Holdings, Inc. (TEPCO)**: One of the largest electric power companies in Japan, TEPCO operates numerous nuclear power plants and has been a significant player in the nuclear energy sector.
GE Hitachi Nuclear Energy (GEH) is a global leader in nuclear technology and services. It is a joint venture between General Electric (GE) and Hitachi, Ltd., which focuses on the development, design, and manufacturing of nuclear reactors and related technologies.
A Nuclear Weapons Convention (NWC) is a proposed international treaty aimed at the comprehensive prohibition and elimination of nuclear weapons. The concept of an NWC is rooted in the idea of a legally binding agreement that would establish a framework for the complete disarmament of nuclear arsenals globally.
The list of nuclear weapons tests refers to the documented instances in which nuclear weapons have been detonated, either for experimental purposes or military testing. These tests have been conducted by various countries since the inception of nuclear weapons in the 20th century. The first such test was the Trinity Test by the United States on July 16, 1945.
The term "nuclear whistleblowers" refers to individuals who expose illegal or unethical practices related to nuclear safety, security, and environmental issues, often within governmental or corporate contexts. These whistleblowers can come from various sectors, including government agencies, private companies, and research institutions. Some notable nuclear whistleblowers include: 1. **Karen Silkwood**: A worker at a plutonium processing plant, Silkwood raised concerns about unsafe working conditions and contamination.
Treaties establishing nuclear-weapon-free zones (NWFZs) are international agreements that create specific regions where the development, testing, deployment, and possession of nuclear weapons are prohibited. These treaties serve to promote global peace, security, and non-proliferation of nuclear arms by creating designated areas where states collectively agree not to acquire nuclear weapons. The establishment of NWFZs is seen as a way to enhance regional security, prevent the spread of nuclear weapons, and promote disarmament.
Emu Field is a locality in South Australia, situated in the north-western part of the state. It is primarily known for its proximity to the Emu Field Nuclear Research Facility, which has been used for various scientific and defense-related purposes, including nuclear testing in the past. The area is characterized by its arid environment and is part of the larger region of the Anangu Pitjantjatjara Yankunytjatjara (APY) Lands, known for its Indigenous cultural heritage.
CNN convolution kernels are not hardcoded. They are learnt and optimized via backpropagation. You just specify their size! Example in PyTorch you'd do just:
nn.Conv2d(1, 6, kernel_size=(5, 5))
as used for example at: activatedgeek/LeNet-5.
This can also be inferred from: stackoverflow.com/questions/55594969/how-to-visualise-filters-in-a-cnn-with-pytorch where we see that the kernels are not perfectly regular as you'd expected from something hand coded.
Ciro Santilli believes that there is a close link between the ability to create disruptive technology, and the desire to find bugs/exploits in systems.
Both of them destabilize society and enterprises.
Some examples:
And yes, this sometimes leads into a fine line between legality and illegality:
MLperf v2.1 ResNet by Ciro Santilli 40 Updated 2025-07-16
Ubuntu 22.10 setup with tiny dummy manually generated ImageNet and run on ONNX:
sudo apt install pybind11-dev

git clone https://github.com/mlcommons/inference
cd inference
git checkout v2.1

virtualenv -p python3 .venv
. .venv/bin/activate
pip install numpy==1.24.2 pycocotools==2.0.6 onnxruntime==1.14.1 opencv-python==4.7.0.72 torch==1.13.1

cd loadgen
CFLAGS="-std=c++14" python setup.py develop
cd -

cd vision/classification_and_detection
python setup.py develop
wget -q https://zenodo.org/record/3157894/files/mobilenet_v1_1.0_224.onnx
export MODEL_DIR="$(pwd)"
export EXTRA_OPS='--time 10 --max-latency 0.2'

tools/make_fake_imagenet.sh
DATA_DIR="$(pwd)/fake_imagenet" ./run_local.sh onnxruntime mobilenet cpu --accuracy
Last line of output on P51, which appears to contain the benchmark results
TestScenario.SingleStream qps=58.85, mean=0.0138, time=0.136, acc=62.500%, queries=8, tiles=50.0:0.0129,80.0:0.0137,90.0:0.0155,95.0:0.0171,99.0:0.0184,99.9:0.0187
where presumably qps means queries per second, and is the main results we are interested in, the more the better.
Running:
tools/make_fake_imagenet.sh
produces a tiny ImageNet subset with 8 images under fake_imagenet/.
fake_imagenet/val_map.txt contains:
val/800px-Porsche_991_silver_IAA.jpg 817
val/512px-Cacatua_moluccensis_-Cincinnati_Zoo-8a.jpg 89
val/800px-Sardinian_Warbler.jpg 13
val/800px-7weeks_old.JPG 207
val/800px-20180630_Tesla_Model_S_70D_2015_midnight_blue_left_front.jpg 817
val/800px-Welsh_Springer_Spaniel.jpg 156
val/800px-Jammlich_crop.jpg 233
val/782px-Pumiforme.JPG 285
where the numbers are the category indices from ImageNet1k. At gist.github.com/yrevar/942d3a0ac09ec9e5eb3a see e.g.:
  • 817: 'sports car, sport car',
  • 89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita',
and so on, so they are coherent with the image names. By quickly looking at the script we see that it just downloads from Wikimedia and manually creates the file.
TODO prepare and test on the actual ImageNet validation set, README says:
Prepare the imagenet dataset to come.
Since that one is undocumented, let's try the COCO dataset instead, which uses COCO 2017 and is also a bit smaller. Note that his is not part of MLperf anymore since v2.1, only ImageNet and open images are used. But still:
wget https://zenodo.org/record/4735652/files/ssd_mobilenet_v1_coco_2018_01_28.onnx
DATA_DIR_BASE=/mnt/data/coco
export DATA_DIR="${DATADIR_BASE}/val2017-300"
mkdir -p "$DATA_DIR_BASE"
cd "$DATA_DIR_BASE"
wget http://images.cocodataset.org/zips/val2017.zip
wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip
unzip val2017.zip
unzip annotations_trainval2017.zip
mv annotations val2017
cd -
cd "$(git-toplevel)"
python tools/upscale_coco/upscale_coco.py --inputs "$DATA_DIR_BASE" --outputs "$DATA_DIR" --size 300 300 --format png
cd -
Now:
./run_local.sh onnxruntime mobilenet cpu --accuracy
fails immediately with:
No such file or directory: '/path/to/coco/val2017-300/val_map.txt
The more plausible looking:
./run_local.sh onnxruntime mobilenet cpu --accuracy --dataset coco-300
first takes a while to preprocess something most likely, which it does only one, and then fails:
Traceback (most recent call last):
  File "/home/ciro/git/inference/vision/classification_and_detection/python/main.py", line 596, in <module>
    main()
  File "/home/ciro/git/inference/vision/classification_and_detection/python/main.py", line 468, in main
    ds = wanted_dataset(data_path=args.dataset_path,
  File "/home/ciro/git/inference/vision/classification_and_detection/python/coco.py", line 115, in __init__
    self.label_list = np.array(self.label_list)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (5000, 2) + inhomogeneous part.
A strangelet is a hypothetical type of exotic matter that is composed of strange quarks. In particle physics, quarks are elementary particles and fundamental constituents of matter. There are six flavors of quarks: up, down, charm, strange, top, and bottom. Normally, matter is made up of up and down quarks (e.g., protons and neutrons).

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 2.
    You can publish local OurBigBook lightweight markup files to either https://OurBigBook.com or as a static website
    .
    Figure 3.
    Visual Studio Code extension installation
    .
    Figure 4.
    Visual Studio Code extension tree navigation
    .
    Figure 5.
    Web editor
    . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
    Video 4.
    OurBigBook Visual Studio Code extension editing and navigation demo
    . Source.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact