This document provides an overview of Newton's three laws of motion:
1) An object at rest stays at rest and an object in motion stays in motion unless acted upon by an unbalanced force. Friction is given as an example of a force that can slow objects in motion.
2) The acceleration of an object as produced by a net force is directly proportional to the magnitude of the net force, in the same direction as the net force, and inversely proportional to the mass of the object.
3) For every action, there is an equal and opposite reaction. Examples of this law include a bird's wings pushing air down to lift itself up and a rocket expelling gases out the bottom to propel
A powerpoint i used for a STEM Presetation on using Dukane products with STEM( Science , Technology, Engineering and Math).
Bill McIntosh
SchoolVision Inc ( my consulting company)
Authorized Dukane/Convey Consultant
Phone :843-442-8888
Email :WKMcIntosh@Comcast.net
Twitter : @OtisTMcIntosh
SchoolVision Website on Facebook: https://www.facebook.com/WKMIII
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
A powerpoint i used for a STEM Presetation on using Dukane products with STEM( Science , Technology, Engineering and Math).
Bill McIntosh
SchoolVision Inc ( my consulting company)
Authorized Dukane/Convey Consultant
Phone :843-442-8888
Email :WKMcIntosh@Comcast.net
Twitter : @OtisTMcIntosh
SchoolVision Website on Facebook: https://www.facebook.com/WKMIII
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
2. While most people know
what Newton's laws say,
many people do not know
what they mean (or simply do
not believe what they mean).
3. Newton’s Laws of Motion
1st Law – An object at rest will stay at
rest, and an object in motion will stay in
motion at constant velocity, unless acted
upon by an unbalanced force.
2nd Law – Force equals mass times
acceleration.
3rd Law – For every action there is an
equal and opposite reaction.
4. 1st Law of Motion
(Law of Inertia)
An object at rest will stay at
rest, and an object in motion
will stay in motion at
constant velocity, unless acted
upon by an unbalanced force.
5. 1st Law
Inertia is the
tendency of an
object to resist
changes in its
velocity:
whether in
motion or
motionless.
These pumpkins will not move unless acted on
by an unbalanced force.
6. 1st Law
Once airborne,
unless acted on
by an
unbalanced force
(gravity and air
– fluid friction),
it would never
stop!
7. 1st Law
Unless acted
upon by an
unbalanced
force, this golf
ball would sit on
the tee forever.
8. Why then, do we observe every
day objects in motion slowing
down and becoming motionless
seemingly without an outside
force?
It’s a force we sometimes cannot see –
friction.
9. Objects on earth, unlike the
frictionless space the moon
travels through, are under the
influence of friction.
10. There are four main types of friction:
Sliding friction: ice skating
Rolling friction: bowling
Fluid friction (air or liquid): air or water resistance
Static friction: initial friction when moving an
object
What is this unbalanced force that acts on an object in motion?
11. Slide a book
across a table and
watch it slide to a rest
position. The book
comes to a rest
because of the
presence of a force -
that force being the
force of friction -
which brings the book
to a rest position.
12. In the absence of a force of friction, the book
would continue in motion with the same speed
and direction - forever! (Or at least to the end
of the table top.)
13. Newtons’s 1st Law and You
Don’t let this be you. Wear seat belts.
Because of inertia, objects (including you) resist changes
in their motion. When the car going 80 km/hour is stopped
by the brick wall, your body keeps moving at 80 m/hour.
15. 2nd Law
The net force of an object is
equal to the product of its mass
and acceleration, or F=ma.
16. 2nd Law
When mass is in kilograms and acceleration is
in m/s/s, the unit of force is in newtons (N).
One newton is equal to the force required to
accelerate one kilogram of mass at one
meter/second/second.
17. 2nd Law (F = m x a)
How much force is needed to accelerate a 1400
kilogram car 2 meters per second/per second?
Write the formula
F = m x a
Fill in given numbers and units
F = 1400 kg x 2 meters per second/second
Solve for the unknown
2800 kg-meters/second/second or 2800 N
18. If mass remains constant, doubling the acceleration, doubles the force. If force remains
constant, doubling the mass, halves the acceleration.
19. Newton’s 2nd Law proves that different masses
accelerate to the earth at the same rate, but with
different forces.
• We know that objects
with different masses
accelerate to the
ground at the same
rate.
• However, because of
the 2nd Law we know
that they don’t hit the
ground with the same
force.
F = ma
98 N = 10 kg x 9.8 m/s/s
F = ma
9.8 N = 1 kg x 9.8 m/s/s
20.
21. Check Your Understanding
1. What acceleration will result when a 12 N net force applied to a 3 kg
object? A 6 kg object?
2. A net force of 16 N causes a mass to accelerate at a rate of 5 m/s2.
Determine the mass.
3. How much force is needed to accelerate a 66 kg skier 1 m/sec/sec?
4. What is the force on a 1000 kg elevator that is falling freely at 9.8
m/sec/sec?
22. Check Your Understanding
1. What acceleration will result when a 12 N net force applied to a 3 kg object?
12 N = 3 kg x 4 m/s/s
2. A net force of 16 N causes a mass to accelerate at a rate of 5 m/s2. Determine the
mass.
16 N = 3.2 kg x 5 m/s/s
3. How much force is needed to accelerate a 66 kg skier 1 m/sec/sec?
66 kg-m/sec/sec or 66 N
4. What is the force on a 1000 kg elevator that is falling freely at 9.8 m/sec/sec?
9800 kg-m/sec/sec or 9800 N
23.
24. 3rd Law
For every action, there is an
equal and opposite reaction.
25. 3rd Law
According to Newton,
whenever objects A and
B interact with each
other, they exert forces
upon each other. When
you sit in your chair,
your body exerts a
downward force on the
chair and the chair
exerts an upward force
on your body.
26. 3rd Law
There are two forces
resulting from this
interaction - a force on
the chair and a force on
your body. These two
forces are called action
and reaction forces.
27. Newton’s 3rd Law in Nature
Consider the propulsion of a
fish through the water. A
fish uses its fins to push
water backwards. In turn,
the water reacts by pushing
the fish forwards, propelling
the fish through the water.
The size of the force on the
water equals the size of the
force on the fish; the
direction of the force on the
water (backwards) is
opposite the direction of the
force on the fish (forwards).
28. 3rd Law
Flying gracefully
through the air, birds
depend on Newton’s
third law of motion. As
the birds push down on
the air with their wings,
the air pushes their
wings up and gives
them lift.
29. Consider the flying motion of birds. A bird flies by
use of its wings. The wings of a bird push air
downwards. In turn, the air reacts by pushing the bird
upwards.
The size of the force on the air equals the size of the
force on the bird; the direction of the force on the air
(downwards) is opposite the direction of the force on
the bird (upwards).
Action-reaction force pairs make it possible for birds
to fly.
30.
31. Other examples of Newton’s
Third Law
The baseball forces the
bat to the left (an
action); the bat forces
the ball to the right (the
reaction).
32. 3rd Law
Consider the motion of
a car on the way to
school. A car is
equipped with wheels
which spin backwards.
As the wheels spin
backwards, they grip the
road and push the road
backwards.
33. 3rd Law
The reaction of a rocket is
an application of the third
law of motion. Various
fuels are burned in the
engine, producing hot
gases.
The hot gases push against
the inside tube of the rocket
and escape out the bottom
of the tube. As the gases
move downward, the rocket
moves in the opposite
direction.