The document discusses systems thinking and key concepts about systems. It defines a system as (1) created by nature or humans, (2) physical, abstract, or composed of humans, (3) separated from its environment by a border, and (4) either open or closed. Systems are hierarchical and composed of subsystems. Open systems receive inputs from their environment, transform those inputs, produce outputs, and self-regulate to maintain homeostasis. Feedback loops are important for self-regulation and development. Learning systems can change over time based on experiences, while non-learning systems lack this ability.
These are the slides which I used is a 3 day workshop which I gave to university students in Brazil. Any feedback, and additional material that I could use (text, pictures, cartoons or videos), very gratefully received.
These are the slides which I used is a 3 day workshop which I gave to university students in Brazil. Any feedback, and additional material that I could use (text, pictures, cartoons or videos), very gratefully received.
Futura 02/2015: Koulun tulevaisuus 2030Hannu Linturi
Tulevaisuuden tutkimuksen seuran Futura-lehden julkistamistilaisuus 22.5.2015. Lehden teema on Koulun tulevaisuus ja se on jatkos numerolle 3/2014: Oppimisen tulevaisuus.
Futura 02/2015: Koulun tulevaisuus 2030Hannu Linturi
Tulevaisuuden tutkimuksen seuran Futura-lehden julkistamistilaisuus 22.5.2015. Lehden teema on Koulun tulevaisuus ja se on jatkos numerolle 3/2014: Oppimisen tulevaisuus.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
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.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
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.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Multi-source connectivity as the driver of solar wind variability in the heli...
Systems thinking 1
1. SYSTEMS THINKING
Master’s Degree Programme, FutuS2 Futures Research Methods
Otavan Opisto 15 February, 2012
Anita Rubin
2. Systems Thinking is ...
…a way to understand phenomena and events,
their characteristics and the relationships
between them as one entity;
…a family of methods/methodology which
creates a flexible and manifold tool to help
human problem-solving in practice.
4. The principles of systems thinking
A system is
• created by the Nature or human beings,
• physical, abstract, or human,
• a whole separated from its environment by a border (eg.
skin, cell membrane, water pipes, Declaration of
Independence…)
• open or closed.
A system is built on a hierarchical way. It is composed of different
levels which have their own laws. Those laws cannot be directly
derived from the laws of a higher level, but the laws of a certain
level affect the functions of the levels below them.
Peter Checkland 1985
5. Systemic world view
• Universal principles of organisation apply to all systems
5
(physical, chemical, biological, social)
• Mechanistic world view: Full understading of any
phenomenon can be achieved by reducing it to its basic
components and analysing those parts. Universal
anwers can be achieved this way.
• Systemic world view: Phenomena are more than their
parts. Universal answers can only be achieved by
exceeding the material basis and concentrating on the
abstract characteristics of the system.
6. Definitions of a System
A System is…
… a limited number of factors (actors, actions, interactions)
between which there are continuous tensions and
connections to distinguish them as separate wholes;
…an organism which functions according to laws and rules
of its own. The organism is composed of smaller organisms,
but it cannot be directly understood by merely analysing its
sub-organisms.
… a group of characteristics which form a whole and the
parts of which are related with each other in a definable
way.
8. The Hierarchy of a System
• To be eligible for being defined as a system, a being has to
have at least two parts which are interconnected.
• The parts of a system form sub-systems (i.e. a human being
blood circulation blood cells genes human being, etc.)
The top system is called super-system. The super-system is
always more abstract and more general by nature than its sub-systems
• As such, a system is always more than a mere sum of its parts,
or sub-systems.
• The higher in hierarchy a system functions, the more abstract
and general it is by nature (i.e. a human being family
community municipality state, etc.)
10. 10
Critical information
Inflowing information which grows in amount or quality and for
which the system is not properly prepared is called critical
information.
The more critical information is flowing into the system, the more
unstable it becomes and the closer it approximates to a chaotic
state.
The system’s ability to self-regulation determines the level of its
order.
i.e. The Universe is not merely a combination of phenomena acting
on their own, separate laws, but a whole of intermediating complex
systems.
(Checkland 1985)
11. Natural and Human Systems
1. Natural systems form the Nature as we
know it.
2. Human systems have either been consciously built, or they
have emerged as a result of human actions.
• Rational material systems (= planned by people)
(i.e. the distribution network of electricity in a city)
• Planned abstract systems (= human-made conceptual wholes)
(i.e. mathematics, philosophy, education system, etc.)
• Operational human systems (= the systems which have been
created in order to carry out some purpose or to reach a goal
(i.e. a choir, or political parties)
3. Transcendental systems (of which we cannot know anything)
12. 12
Self-regulation and fluctuation
New energy or information into human systems causes
fluctuation in its internal processes.
At the same time, the system pursues development (=
fluctuation) with the help of cumulative and positive
feedback.
Tendency to self-regulation
(to achieve balance by
using amendatory or
negative feedback.)
Tendency towards
more and more specific
and diverse state.
Dissonance?
13. • receives matter, energy and/or information from its
environment (=input);
• changes that energy, matter and/or information to some
other form, and
• produces that matter, energy and/or information back to
its environment in a changed form (= output);
• while it simultaneously maintains its own inner condition
(=homeostasis) by eliminating extra fluctuation (of matter,
energy and/or information) and by disturbing the influence
of external factors;
…/…
Open system
14. Open system (cont.)
• Aims at negative entropy, i.e. strives for survival and
maintaining its opertion;
• is hierarchically composed of sub- and super-systems;
• aims at separation and specialisation.
In the feedback process, the system utilises energy which it
takes from its outer environment. The feedback process is
important as the conveyor of information transportation
and the success and development of the system are
dependent on the functionality of the feedback.
Therefore regulation is crucial in maintaining the system’s
economy.
15. The Emergent Nature of a System
The third law of thermodynamics
Specialised energy
The law of entropy
16. 16
To understand a system…
…focus has to be turned on
• the technical form of information output (i.e., how it is
transmitted and what symbols are used);
• the accuracy of information (i.e. how well the symbols
describe the acitivities of the system);
• how effective the information is (i.e., how that information
influences the environment of the system and how the
output process is necessary for the survival and
managing of the system).
17. The Role of Feedback
in Open Systems
Negative feedback
• necessary for the self-direction and learning ability
of the system;
• guides the system to keep on the right track.
Positive feedback
• result, product, i.e. output
• the sum of avoided negative alternatives.
.../...
18. Homeostacy
• the ability of a system to
maintain its inner condition;
• takes place by eliminating
redundant fluctuation and
the disturbing influence of
external stimulae or noise.
In keeping up the economy of the open
system, the crucial process is regulation.
19. Human-made systems
The systems which have been created by human activity can be
divided into three wholes:
1. Planned material systems which are formed as the result of
purposeful planning (eg. the heating system of a building).
2. Planned abstract systems are large, human-made wholes which
may also include conceptual and deliberately-designed parts
(eg. school).
3. Planned functional systems which are composed as a result of
people fulfillling some mission or carrying out an assignment.
They form systems in order to create something, or to act
together, or to achieve a goal, etc. (eg. The Finnish learning
system).
20. Learning beings and learning systems
Open systems are”learning beings” (Kuusi 1999; de Jouvenel
1967) which
• are controlled by deterministic natural laws and their own
will;
• are less predictable than non-learning beings and systems,
and,
• their characteristics, abilities and needs can be observed.
The aim of a learning being is its survival, development and
reproduction. These processes call for processes which can be
passive (eg, registering perceptions in memory) or active
(retrieving them back to conscious consideration and changing
them into activity).
21. Learning beings and learning systems (cont.)
• Learning organisation is a special case of learning
beings.
• The essential feature of an organisation as a learning
system is its self-understanding (its conception that its
function has a direction and meaning).
22. Non-learning beings
• are open systems but in a different way than the learning
beings (closer to closed systems);
• are predictable when their history (previous stages, states
etc.) is recorded and can be established eg. by time series,
and their present state is known;
• may seem like non-predictable, if their origins or state of the
beginning cannot be stated on sufficient accuracy (eg.
machines, thermostats, gases);
• are not able of self-regulation, and
• therefore are on the way to decomposition
of their parts, i.e. entropy.