The Interagency Arctic Research Policy Committee (IARPC) is a committee made up of representatives from 16 US federal agencies that coordinates Arctic research policy and implements the US Arctic Research Plan. IARPC was established by the 1984 Arctic Research Policy Act and develops a 5-year research plan to advance Arctic research priorities. IARPC's current 2017-2021 Arctic Research Plan identifies four policy drivers and nine research goals to guide US Arctic research. IARPC also coordinates collaborations between federal and non-federal Arctic researchers through nine thematic teams to implement the research plan.
Estuaries, long recognized for their local importance, form collectively an important global ecosystem, sensitive to both climate change and local pressures. This has been recognized by a 2013 U.S. workshop, which issued a set of recommendations directed at building worldwide capacity and collaborations to address estuaries as a global ecosystem. The workshop recognized that modern observation and modeling technology is poised to play a key role in advancing the scientific understanding of estuaries, and identified the need to map the resulting understanding of individual estuaries into a common global framework. An international partnership has since emerged, driven by the increasingly recognized need to advance estuarine observation, modeling, science and science translation worldwide. Anchoring the partnership is a belief that there are important commonalities across estuaries that, if explored, will prove synergistic and transformation towards understanding and sustainable management of all estuaries. On behalf of this emerging international partnership, we describe here steps that are being taken to develop Our Global Estuary. Integral to these efforts are: (a) the organization of regular international workshops, to build a common vision and global capacity and collaborative networks—the first of these workshops planned for Chennai, India; (b) the creation of a pilot project, Our Virtual Global Estuary, where a common modeling and analysis framework, supported by and supporting local observations, will be progressively put in place for estuaries across the world—with an initial set identified in Brazil, China, Portugal, Spain, and United States, and additional estuaries under consideration; and (b) exploration of synergies with global organizations (such as the Partnership for Ocean Global Observations) and global-scale programs and initiatives (such as Blue Planet), to further contextualize the role of estuaries in the earth’s sustainability.
The Ocean Watch open data platform delivers science to policy makers developing sustainable ocean economies and operationalizing integrated ocean management.
Learn more: https://oceanwatchdata.org
An Atoll Futures Research Institute? Presentation for CANCCNAP Global Network
Presentation by Professor Jon Barnett, University of Melbourne, at the Coalition Of Low-Lying Atoll Nations on Climate Change (CANCC) peer learning cohort workshop on “National Adaptation Planning With a Focus on Coastal Adaptation” in North Malé Atoll, Maldives, between May 1 - May 3, 2024.
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.
Estuaries, long recognized for their local importance, form collectively an important global ecosystem, sensitive to both climate change and local pressures. This has been recognized by a 2013 U.S. workshop, which issued a set of recommendations directed at building worldwide capacity and collaborations to address estuaries as a global ecosystem. The workshop recognized that modern observation and modeling technology is poised to play a key role in advancing the scientific understanding of estuaries, and identified the need to map the resulting understanding of individual estuaries into a common global framework. An international partnership has since emerged, driven by the increasingly recognized need to advance estuarine observation, modeling, science and science translation worldwide. Anchoring the partnership is a belief that there are important commonalities across estuaries that, if explored, will prove synergistic and transformation towards understanding and sustainable management of all estuaries. On behalf of this emerging international partnership, we describe here steps that are being taken to develop Our Global Estuary. Integral to these efforts are: (a) the organization of regular international workshops, to build a common vision and global capacity and collaborative networks—the first of these workshops planned for Chennai, India; (b) the creation of a pilot project, Our Virtual Global Estuary, where a common modeling and analysis framework, supported by and supporting local observations, will be progressively put in place for estuaries across the world—with an initial set identified in Brazil, China, Portugal, Spain, and United States, and additional estuaries under consideration; and (b) exploration of synergies with global organizations (such as the Partnership for Ocean Global Observations) and global-scale programs and initiatives (such as Blue Planet), to further contextualize the role of estuaries in the earth’s sustainability.
The Ocean Watch open data platform delivers science to policy makers developing sustainable ocean economies and operationalizing integrated ocean management.
Learn more: https://oceanwatchdata.org
An Atoll Futures Research Institute? Presentation for CANCCNAP Global Network
Presentation by Professor Jon Barnett, University of Melbourne, at the Coalition Of Low-Lying Atoll Nations on Climate Change (CANCC) peer learning cohort workshop on “National Adaptation Planning With a Focus on Coastal Adaptation” in North Malé Atoll, Maldives, between May 1 - May 3, 2024.
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.
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.
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.
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.
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.
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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
6. IARPC practices open government.
We consult the research community and Arctic stakeholders
in planning and implementing the Arctic Research Plan.
7. We consult the research community and Arctic stakeholders
in planning and implementing the Arctic Research Plan.
How does it work?
IARPC practices open government.
9. Develops a national
Arctic research policy and
a 5-year plan to
implement the policy
Promotes Arctic research
and recommends an
Arctic research policy
It established the Arctic Research Commission and the IARPC
and required them to:
Congress enacted the ARCTIC RESEARCH POLICY ACT in 1984
10. The Committee is made up of Principals from 16 Federal
agencies and is chaired by the director of the NSF.
11. National Science Foundation
Department of Agriculture
Department of Commerce
Department of Defense
Department of Energy
Department of Health and Human Services
Department of Homeland Security
Department of the Interior
Department of State
Department of Transportation
Environmental Protection Agency
Marine Mammal Commission
National Aeronautics and Space Administration
Office of Management and Budget
Office of Science and Technology Policy
Smithsonian Institution
The Committee is made up of Principals from 16 Federal
agencies and is chaired by the director of the NSF.
12. In 2011 IARPC became part of the Executive Branch
located in the Eisenhower Executive Office Building.
13. IARPC
In 2011 IARPC became part of the Executive Branch
located in the Eisenhower Executive Office Building.
EXECUTIVE BRANCH
OFFICE OF SCIENCE
& TECHNOLOGY POLICY
NATIONAL SCIENCE
& TECHNOLOGY COUNCIL
COMMITTEE ON
ENVIRONMENT, NATURAL
RESOURCES & SUSTAINABILITY
14.
15. In December 2016,
IARPC released
Arctic Research Plan 2017-2021,
published by the
Executive Office of the President
16. The Policy Drivers are:
This policy-driven Plan
identifies critical areas
where the U.S. research
enterprise supports U.S.
policy from community to
global scales.
17. The Policy Drivers are:
This policy-driven Plan
identifies critical areas
where the U.S. research
enterprise supports U.S.
policy from community to
global scales.
1. Enhance the well-being of Arctic residents.
18. The Policy Drivers are:
This policy-driven Plan
identifies critical areas
where the U.S. research
enterprise supports U.S.
policy from community to
global scales.
1. Enhance the well-being of Arctic residents.
2. Advance stewardship of the Arctic environment.
19. The Policy Drivers are:
This policy-driven Plan
identifies critical areas
where the U.S. research
enterprise supports U.S.
policy from community to
global scales.
1. Enhance the well-being of Arctic residents.
2. Advance stewardship of the Arctic environment.
3. Strengthen national and regional security.
20. The Policy Drivers are:
This policy-driven Plan
identifies critical areas
where the U.S. research
enterprise supports U.S.
policy from community to
global scales.
1. Enhance the well-being of Arctic residents.
2. Advance stewardship of the Arctic environment.
3. Strengthen national and regional security.
4. Improve understanding of the Arctic as a component of planet Earth.
21. The Research Goals are:
1. Enhance understanding of health
determinants and improve the
well-being of Arctic residents;
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The Research Goals are:
1. Enhance understanding of health
determinants and improve the
well-being of Arctic residents;
2. Advance process and system
understanding of the changing Arctic
atmospheric composition and
dynamics and the resulting changes
to surface energy budgets;
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The Research Goals are:
1. Enhance understanding of health
determinants and improve the
well-being of Arctic residents;
2. Advance process and system
understanding of the changing Arctic
atmospheric composition and
dynamics and the resulting changes
to surface energy budgets;
3. Enhance understanding and improve
predictions of the changing Arctic
sea ice cover;
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The Research Goals are:
1. Enhance understanding of health
determinants and improve the
well-being of Arctic residents;
2. Advance process and system
understanding of the changing Arctic
atmospheric composition and
dynamics and the resulting changes
to surface energy budgets;
3. Enhance understanding and improve
predictions of the changing Arctic
sea ice cover;
4. Increase understanding of the structure
and function of Arctic marine ecosystems
and their role in the climate system and
advance predictive capabilities;
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The Research Goals are:
1. Enhance understanding of health
determinants and improve the
well-being of Arctic residents;
2. Advance process and system
understanding of the changing Arctic
atmospheric composition and
dynamics and the resulting changes
to surface energy budgets;
3. Enhance understanding and improve
predictions of the changing Arctic
sea ice cover;
4. Increase understanding of the structure
and function of Arctic marine ecosystems
and their role in the climate system and
advance predictive capabilities;
5. Understand and project the mass balance of
glaciers, ice caps, and the Greenland Ice Sheet,
and their consequences for sea level rise;
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6. Advance understanding of processes
controlling permafrost dynamics and the
impacts on ecosystems, infrastructure,
and climate feedbacks;
The Research Goals are:
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6. Advance understanding of processes
controlling permafrost dynamics and the
impacts on ecosystems, infrastructure,
and climate feedbacks;
7. Advance an integrated, landscape-scale
understanding of Arctic terrestrial and
freshwater ecosystems and the
potential for future change;
The Research Goals are:
28. 6. Advance understanding of processes
controlling permafrost dynamics and the
impacts on ecosystems, infrastructure,
and climate feedbacks;
7. Advance an integrated, landscape-scale
understanding of Arctic terrestrial and
freshwater ecosystems and the
potential for future change;
8. Strengthen coastal community
resilience and advance stewardship of
coastal natural and cultural resources by
engaging in research related to the
interconnections of people, natural and
built environments;
The Research Goals are:
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29. 6. Advance understanding of processes
controlling permafrost dynamics and the
impacts on ecosystems, infrastructure,
and climate feedbacks;
7. Advance an integrated, landscape-scale
understanding of Arctic terrestrial and
freshwater ecosystems and the
potential for future change;
8. Strengthen coastal community
resilience and advance stewardship of
coastal natural and cultural resources by
engaging in research related to the
interconnections of people, natural and
built environments;
9. Enhance frameworks for environmental
intelligence gathering, interpretation,
and application toward decision support.
The Research Goals are:
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Environmental
Intelligence
33. Health &
Well-being
Atmosphere
Sea Ice
Glaciers &
Sea Level
Permafrost
Coastal
Resilience
Terrestrial
Ecosystems
Marine
Ecosystems
Federal only
Environmental
Intelligence
Through IARPC Collaborations we open our work to
non-Federal Arctic researchers and stakeholders.
Federal & non-Federal
We welcome you to join one or more
of our nine thematic Collaboration Teams
34. Led by Federal Program Managers and non-Federal partners, our teams
connect researchers and stakeholders from academia, non-profit,
industry, State of Alaska, Indigenous and international organizations.
35. Each team has monthly meetings where they cover a wide range of
topics through webinars and discussions, and they want YOU!
36. There is an opportunity to share your work
built into every meeting agenda
37. There is an opportunity to share your work
built into every meeting agenda
45. …and it will be shared with >1500 members via our email digest.
46. Click here to request an account at iarpccollaborations.org
9 Collaboration Teams led by 32 Federal Program Managers and Arctic research
leaders, working on 122 performance elements, in collaboration with 1500 Arctic
scientists and stakeholders, through a website with over 1500 views per month!