MASS SPECTROSCOPY ( Molecular ion, Base peak, Isotopic abundance, Metastable ...Sachin Kale
CONTENT:
Molecular Ion Peak
Significance of Molecular ion & Graphically Method
Base Peak
Isotopic Abundance
Metastable Ion
Significance of Metastable ion
Nitrogen Rule & graphs
Formulation of Rule
MASS SPECTROSCOPY ( Molecular ion, Base peak, Isotopic abundance, Metastable ...Sachin Kale
CONTENT:
Molecular Ion Peak
Significance of Molecular ion & Graphically Method
Base Peak
Isotopic Abundance
Metastable Ion
Significance of Metastable ion
Nitrogen Rule & graphs
Formulation of Rule
Spin-lattice & spin-spin relaxation, signal splitting & signal multiplicity concepts briefly explained relevant to Nuclear Magnetic Resonance Spectroscopy.
PRINCIPLES of FT-NMR & 13C NMR
Fourier Transform
FOURIER TRANSFORM NMR SPECTROSCOPY
THEORY OF FT-NMR
13C NMR SPECTROSCOPY
Principle
Why C13-NMR is required though we have H1-NMR?
CHARACTERISTIC FEATURES OF 13 C NMR
Chemical Shifts
NUCLEAR OVERHAUSER ENHANCEMENT
Short-Comings of 13C-NMR Spectra
Coupling vibration in IR(Infra Red) spectroscopy and their significance.D.R. Chandravanshi
Introduction, Coupling vibration, Requirements for effective coupling, References.
coupling occurs in IR by stretching and bending vibration, symmetrical and asymmetrical stretching vibration.
Spin-lattice & spin-spin relaxation, signal splitting & signal multiplicity concepts briefly explained relevant to Nuclear Magnetic Resonance Spectroscopy.
PRINCIPLES of FT-NMR & 13C NMR
Fourier Transform
FOURIER TRANSFORM NMR SPECTROSCOPY
THEORY OF FT-NMR
13C NMR SPECTROSCOPY
Principle
Why C13-NMR is required though we have H1-NMR?
CHARACTERISTIC FEATURES OF 13 C NMR
Chemical Shifts
NUCLEAR OVERHAUSER ENHANCEMENT
Short-Comings of 13C-NMR Spectra
Coupling vibration in IR(Infra Red) spectroscopy and their significance.D.R. Chandravanshi
Introduction, Coupling vibration, Requirements for effective coupling, References.
coupling occurs in IR by stretching and bending vibration, symmetrical and asymmetrical stretching vibration.
Core-cladding mode resonances of long period fiber grating in concentration s...IOSR Journals
Long period fiber grating (LPFG) is photoinduced fiber device that facilitates the coupling of core
mode to different cladding modes resulting into series of transmission dips in the transmission spectrum. Here
we present LPFG chemical sensor to determine the concentration of Manganese in water at ppm level. We
fabricated LPFG of period 600μm in single mode communication fiber using 12W carbon dioxide laser
applying point by point method. The fabricated LPFG is directly used as chemical sensor since cladding modes
coupled to core mode directly come in contact with surrounding chemicals. Concentration of manganese in our
collected sample is found to be 0.0329ppm. The result is verified with sophisticated Atomic Absorption
Spectrometer (AAS).
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
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.
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.
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.
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
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.
1. COUPLING CONSTANT
G u i d e d B y
D r . V . S r i d h a r a n
A s s o c i a t e P r o f e s s o r ( H . O . D . )
P r e p a r e d B y
S h a k t i R a n j a n S a m a l
R o l l N o : - 2 4 4 1 6 1 6
Department Of Chemistry And Chemical Sciences
Central University Of Jammu, j&k
3. INTRODUCTION
The distance between the peaks in given multiplet is a measure of
splitting effect known as coupling constant
It is denoted by symbol J and expressed in Hz.
Coupling constant are a measure of the effective ness of spin–spin
coupling and very useful in 1H NMR of complex structures.
4. J = Difference of chemical shift value in ppm
1 ppm = 60 Hz
1 ppm = 300 Hz
5. TYPES
There are three type of coupling constant
1. Geminal Coupling
2. Vicinal Coupling
3. Long Range Coupling