This document discusses key concepts in kinematics including:
- Kinematics is the study of motion without considering causes. It focuses on rectilinear or straight-line motion.
- Displacement is a vector quantity that describes the shortest distance between initial and final positions, while distance is a scalar quantity describing the actual path traveled.
- Uniform motion occurs when equal displacements happen in equal time intervals, resulting in a straight line on a position-time graph. Non-uniform motion has acceleration.
This PPT is based on Physics on Chapter Motion. In this you will find every thing of that chapter with great images. in this PPT their are many animation and images .
thank you
Physics Project On Physical World, Units and MeasurementSamiran Ghosh
This PowerPoint is Physical World, Units and Measurement. This is basically the first chapter of 11th class/grade. This power point explains the basic or fundamental physics with some information about SI units and fundamental forces.
This PPT is based on Physics on Chapter Motion. In this you will find every thing of that chapter with great images. in this PPT their are many animation and images .
thank you
Physics Project On Physical World, Units and MeasurementSamiran Ghosh
This PowerPoint is Physical World, Units and Measurement. This is basically the first chapter of 11th class/grade. This power point explains the basic or fundamental physics with some information about SI units and fundamental forces.
Koleksi soalan percubaan add math kertas 1
1. peperiksaan percubaan sekolah asrama penuh dan jawapan
2. pepriksaan percubaan negeri perak dan jawapan
3. peperiksaan percubaan negeri selangor dan jawapan
4. peperiksaan percubaan negeri terengganu dan jawapan
Lab 2/Lab 2- Kinematics.pdf
1/4/2017 Lab 2: Kinematics
https://moodle.straighterline.com/pluginfile.php/72219/mod_resource/content/17/CourseRoot/html/lab004s001.html 1/20
Learning Objec뙕ves
Disᣊ�nguish between scalar and vector quanᣊ�ᣊ�es
Apply kinemaᣊ�c equaᣊ�ons to 1‐D and projecᣊ�le moᣊ�on
Predict posiᣊ�on, velocity, and acceleraᣊ�on vs. ᣊ�me graphs
Calculate average and instantaneous velocity or acceleraᣊ�on
Determine that x and y components are independent of each other
Relate velocity, radius, and ᣊ�me period to uniform circular moᣊ�on.
Explain the direcᣊ�on of acceleraᣊ�on during uniform circular moᣊ�on
1‐D Kinema뙕cs
1‐D kinemaᣊ�cs occurs when an object travels in
one dimension and can be described using words,
equaᣊ�ons and graphs. Linear mo뙕on describes
how an object will move horizontally or verᣊ�cally
with constant acceleraᣊ�on, how an object will
1/4/2017 Lab 2: Kinematics
https://moodle.straighterline.com/pluginfile.php/72219/mod_resource/content/17/CourseRoot/html/lab004s001.html 2/20
Figure 1: Pool balls in moᾷon demonstrate
1‐D kinemaᾷcs.
Figure 2: Line secant to the path of the
object.
travel if dropped from the side of a cliff, and the
path it will follow if thrown straight up into the air.
Keep in mind the moᣊ�on of an object is relaᣊ�ve to
the viewer. Even though you do not feel like you
are in moᣊ�on right now, you are on planet earth
that has rotaᣊ�onal moᣊ�on in addiᣊ�on to orbital
moᣊ�on around the sun. In almost all cases here
moᣊ�on will be relaᣊ�ve to the Earth.
Scalar and Vector Quan뙕뙕es
In physics, quanᣊ�ᣊ�es can be scalar or vector. The
difference between the two lies in direcᣊ�on.
Scalar quanᣊ�ᣊ�es include magnitudes, which are numerical measurements. The distance an
object has traveled or the speed of an object is a scalar quanᣊ�ty. Scalars do not take direcᣊ�on
into consideraᣊ�on and can be described with only a number and a unit. For example,
somebody might say the temperature outside is 70°F. Seventy is the magnitude, and
Fahrenheit is the unit; there is no direcᣊ�on associated with the quanᣊ�ty. Vector quanᣊ�ᣊ�es, on
the other hand, include magnitude and direcᣊ�on. The displacement from an object's iniᣊ�al
posiᣊ�on, velocity, and acceleraᣊ�on are vector quanᣊ�ᣊ�es. The direcᣊ�on of vectors can be
described as being in the posiᣊ�ve direcᣊ�on, in the negaᣊ�ve direcᣊ�on, north, south, east, west,
leĀ, right, up, down, etc. One might describe an airplane's velocity as 450 miles per hour due
west where both magnitude and direcᣊ�on are given. It is important to disᣊ�nguish between
scalar and vector quanᣊ�ᣊ�es when trying to understand kinemaᣊ�cs.
Speed, Velocity, and Accelera뙕on
You may be familiar with speed outside of the physics classroom. When you drive in a car you
are traveling a distance over a certain amount of ᣊ�me: a speed. How then is velocity different
from speed? Velocity (v) is a vector quanᣊ�ty described as the rate at which an object's
posiᣊ�on changes divided by the ᣊ�me the ...
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.
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.
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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
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.
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 .
2. Kinematics is the study of motion
without going into its causes.
This chapter deals with motion
along a straight line, i.e.
rectilinear motion.
The motion is the change in position
of an object with respect to time.
Slide 2-3