Massively Scalable Real-time Geospatial Data Processing with Apache Kafka and...Paul Brebner
This presentation will explore how we added location data to a scalable real-time anomaly detection application, built around Apache Kafka, and Cassandra. Kafka and Cassandra are designed for time-series data, however, it’s not so obvious how they can process geospatial data. In order to find location-specific anomalies, we need a way to represent locations, index locations, and query locations. We explore alternative geospatial representations including: Latitude/Longitude points, Bounding Boxes, Geohashes, and go vertical with 3D representations, including 3D Geohashes. To conclude we measure and compare the query throughput of some of the solutions, and summarise the results in terms of accuracy vs. performance to answer the question “Which geospatial data representation and Cassandra implementation is best?”
This version is a slightly shorter version of previous ones.
Google Cloud Special Edition, Sydney Data Engineering Meetup
https://www.meetup.com/Sydney-Data-Engineering-Meetup/events/269146076/
Grid middleware is easy to install, configure, secure, debug and manage acros...Paul Brebner
A presentation made while I was managing the UK OGSA Evaluation Project in 2004, while I was on leave from CSIRO, at UCL Computer Science department, working with Wolfgang Emmerich: in which we "believe 6 impossible things before breakfast". This project encountered and partially solved many of the problems that Cloud computing finally solved.
Paul Brebner, Oxford University Computing Laboratory invited talk: "Grid middleware is easy to install, configure, debug and manage - across multiple sites (One can't believe impossible things)", 15 October 2004.
The project web site is still here (2020): http://sse.cs.ucl.ac.uk/UK-OGSA/
Massively Scalable Real-time Geospatial Data Processing with Apache Kafka and...Paul Brebner
This presentation will explore how we added location data to a scalable real-time anomaly detection application, built around Apache Kafka, and Cassandra. Kafka and Cassandra are designed for time-series data, however, it’s not so obvious how they can process geospatial data. In order to find location-specific anomalies, we need a way to represent locations, index locations, and query locations. We explore alternative geospatial representations including: Latitude/Longitude points, Bounding Boxes, Geohashes, and go vertical with 3D representations, including 3D Geohashes. To conclude we measure and compare the query throughput of some of the solutions, and summarise the results in terms of accuracy vs. performance to answer the question “Which geospatial data representation and Cassandra implementation is best?”
This version is a slightly shorter version of previous ones.
Google Cloud Special Edition, Sydney Data Engineering Meetup
https://www.meetup.com/Sydney-Data-Engineering-Meetup/events/269146076/
Grid middleware is easy to install, configure, secure, debug and manage acros...Paul Brebner
A presentation made while I was managing the UK OGSA Evaluation Project in 2004, while I was on leave from CSIRO, at UCL Computer Science department, working with Wolfgang Emmerich: in which we "believe 6 impossible things before breakfast". This project encountered and partially solved many of the problems that Cloud computing finally solved.
Paul Brebner, Oxford University Computing Laboratory invited talk: "Grid middleware is easy to install, configure, debug and manage - across multiple sites (One can't believe impossible things)", 15 October 2004.
The project web site is still here (2020): http://sse.cs.ucl.ac.uk/UK-OGSA/
Grid Middleware – Principles, Practice and PotentialPaul Brebner
A presentation I gave at UCL, while I was managing the UK OGSA Evaluation Project in 2004, while I was on leave from CSIRO, at UCL Computer Science department, working with Wolfgang Emmerich.
Paul Brebner, University College London, Computer Science Department Seminar: "Grid Middleware - Principles, Practice, and Potential", 1 November 2004.
The project page was still here (2020): http://sse.cs.ucl.ac.uk/UK-OGSA/
task scheduling in cloud datacentre using genetic algorithmSwathi Rampur
Task scheduling and resource provisioning is the core and challenging issues in cloud environment. Processes running in the cloud environment will race for available resources in order to complete their tasks with the minimum execution time; it is clear that we need an efficient scheduling technique for mapping between processes running and available resources. In this research paper, we are presented a non-traditional optimization technique, which mimics the process of evolution and based on the mechanics of natural selection and natural genetics called Genetic algorithm (GA), which minimizes the execution time and in turn reduces computation cost. We had done comparison with Round Robin algorithm and used CloudSim toolkit for our tests, results shows that Meta heuristic GA gives better performance than other scheduling algorithm.
Blue Waters and Resource Management - Now and in the Futureinside-BigData.com
In this presentation from Moabcon 2013, Bill Kramer from NCSA presents: Blue Waters and Resource Management - Now and in the Future.
Watch the video of this presentation: http://insidehpc.com/?p=36343
How HPC and large-scale data analytics are transforming experimental scienceinside-BigData.com
In this deck from DataTech19, Debbie Bard from NERSC presents: Supercomputing and the scientist: How HPC and large-scale data analytics are transforming experimental science.
"Debbie Bard leads the Data Science Engagement Group NERSC. NERSC is the mission supercomputing center for the USA Department of Energy, and supports over 7000 scientists and 700 projects with supercomputing needs. A native of the UK, her career spans research in particle physics, cosmology and computing on both sides of the Atlantic. She obtained her PhD at Edinburgh University, and has worked at Imperial College London as well as the Stanford Linear Accelerator Center (SLAC) in the USA, before joining the Data Department at NERSC, where she focuses on data-intensive computing and research, including supercomputing for experimental science and machine learning at scale."
Watch the video: https://wp.me/p3RLHQ-kLV
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
There are various efforts underway to build quantum computers using a range of technologies. These include cold atoms, trapped ions, superconducting circuits, photonics, atom vacancies, spin qubits, quantum dots and topological methods. Each approach has its own strengths and challenges when it comes to engineering a complete system that can offer commercial speedup over classical computers. In this talk we will look at the various challenges that will need to be overcome in order to build a fully functional and commercially viable quantum computer along with the associated timelines.
Strengths and limitations of quantum computingVinayak Sharma
Quantum computing as a research field has been around for about 30 years. It seems like a way to overcome the challenges that classical (boolean based) computers are facing due to “quantum tunneling” effect. Although, there are various theoretical and practical challenges that are needed to be dealt with if we want quantum computes to perform better that classical computers (i.e achieving “quantum supremacy”). This seminar will aim to shed light on basics of quantum computing and its strengths and weaknesses.
Video Links
Part 1: https://www.youtube.com/watch?v=-WLD_HnUvy0
Part 2: https://www.youtube.com/watch?v=xXzUmpk8ztU
Quantum Computing: The next new technology in computingData Con LA
Data Con LA 2020
Description
Quantum computing is rapidly becoming commercially feasible. Many tech giants - Google, IBM, Honeywell, and Microsoft - are spending billions to far outpace Moore's Law. Last year achieved the major milestone of Quantum Supremacy where it was shown that a quantum computer could greatly outperform a classical computer. Quantum computing offers the promise of solving problems which would be impossible for a classical computer including optimization, anomaly detection, and material design. It also allows unhackable communication.
In this presentation I will summarize what quantum computing is and why it is so important. I will sketch the landscape of the field including the hardware, software, and major customers at present. The tool most critical for data analysis - quantum machine learning - will be explained, along with the type of applications it is best suited for. Finally I will explain how you can take the first steps into leveraging quantum computing for your enterprise's benefit.
* What is quantum computing
* Who are the major players in the field
* What is quantum machine learning and what types of problems can it address
* How your company can take advantage of this
Speaker
Mark Jackson, Cambridge Quantum Computing, Scientific Lead of Business Development
Bhadale Group of Companies -Universal Quantum Computer System Design catalogueVijayananda Mohire
Quantum systems and constituent elements design engineering:
We offer a wide range of universal quantum development services for the convenience of our clients based on their business needs, and startup mission :
• Design of various planes , their subsystems, modules, elements that are to be integrated in a phased manner
• Optics and lasers related opto-photonics, laser, microwaves, MOTs, and related setup for experiments in lab and production environments based on AMO physics, and mesoscopic principles
• Operating systems for classical hosting, quantum co-hosting, kernels, host process managers, virtualization , real-time schedulers etc
• Design the required redundancy in the circuits enabling meeting a long term operations and coherence of the logical qubits
• Stabilizer codes, Topological codes
• Reservoir based design of QC system
• Key design upgrades to scale from say 100 qubits to 1000 qubits and more
• Upgrade design , transform designs from NISQ based various paradigms to a truly multi-body system design using highly precise, highly reliable, logical qubits based out of the high quality physical qubits derived from the closed loop real time NN based polar molecules accurately trapped, arranged , and measured with precision using lasers, MOT and various technologies
Bhadale Group of Companies -Universal Quantum Computer System Services catalogueVijayananda Mohire
Migration/upgrade services from NISQ to FTQC paradigm. Quantum safe, quantum cryptography, quantum information management and algorithms , primitive services. Offers enable use of latest redesigned computer components, hardware, software and various control planes, improvised trial standards, etc
From R&D to Market: the industrialization challengeQCB-Conference
From R&D to Market: the industrialization challenge
Maud VINET - Quantum hardware program manager, CEA Leti, France
Explore the multiple challenges of the industrialization path (reliability, scaling, design, value chain) and how to overcome them. See how collective intelligence a key element for success is. Discover QuCube framework, which main objective is to demonstrate a quantum processor for simulation applications.
Quantum technology, a burgeoning field at the intersection of physics, engineering, and computer science, holds immense promise for revolutionizing various industries and transforming our understanding of the universe. This document serves as a comprehensive exploration of quantum technology, delving into its underlying principles, current advancements, potential applications, and societal implications.
At the heart of quantum technology lies the enigmatic realm of quantum mechanics, a branch of physics that describes the behavior of particles at the smallest scales. Unlike classical physics, which operates on deterministic principles, quantum mechanics introduces probabilistic phenomena such as superposition and entanglement. Superposition allows particles to exist in multiple states simultaneously, while entanglement links the properties of particles regardless of the distance between them. These fundamental principles form the foundation upon which quantum technologies are built.
One of the most promising applications of quantum technology is quantum computing. Traditional computers rely on bits, units of information represented as either 0 or 1, to perform computations. In contrast, quantum computers employ quantum bits, or qubits, which can exist in a superposition of 0 and 1 simultaneously. This enables quantum computers to perform complex calculations exponentially faster than classical computers for certain tasks. Quantum algorithms, such as Shor's algorithm for integer factorization and Grover's algorithm for unstructured search, showcase the potential of quantum computing to revolutionize fields such as cryptography, optimization, and machine learning.
Quantum communication offers another compelling application of quantum technology. Quantum key distribution (QKD) protocols leverage the principles of quantum mechanics to enable secure communication between parties. By encoding information in quantum states, such as the polarization of photons, QKD ensures that any attempt to intercept the communication will be immediately detected. This promises unprecedented levels of security for sensitive information, with applications ranging from financial transactions to government communications.
Quantum sensing and metrology harness the delicate quantum states of particles to achieve unparalleled levels of precision and sensitivity in measuring physical quantities. Quantum sensors, such as atomic clocks and magnetometers, offer applications in navigation, geology, and medical imaging. These sensors have the potential to revolutionize fields such as GPS technology, mineral exploration, and early disease detection, where traditional sensors fall short in terms of accuracy or resolution.
Quantum simulation represents yet another frontier of quantum technology, offering the ability to simulate complex quantum systems that are computationally intractable for classical computers. Quantum simulators, whether digital or analog, mimic the behavior o
Quantum computers are designed to perform tasks much more accurately and efficiently than conventional computers, providing developers with a new tool for specific applications.
It is clear in the short-term that quantum computers will not replace their traditional counterparts; instead, they will require classical computers to support their specialized abilities, such as systems optimization.
The slides of the first Meetup of the Quantum Technology community in Paris ! Hosted on 10/16/2018 at WeWork Lafayette
Contribtutors
- Chris Erven CEO of KETS Quantum Security
- Michael Marthaler CEO of Heisenberg Quantum Simulations
- Wojciech Burkot CPO of Beit, on quantum optimization
- Christophe Jurczak CEO of Quantonation, on VC funding
Grid Middleware – Principles, Practice and PotentialPaul Brebner
A presentation I gave at UCL, while I was managing the UK OGSA Evaluation Project in 2004, while I was on leave from CSIRO, at UCL Computer Science department, working with Wolfgang Emmerich.
Paul Brebner, University College London, Computer Science Department Seminar: "Grid Middleware - Principles, Practice, and Potential", 1 November 2004.
The project page was still here (2020): http://sse.cs.ucl.ac.uk/UK-OGSA/
task scheduling in cloud datacentre using genetic algorithmSwathi Rampur
Task scheduling and resource provisioning is the core and challenging issues in cloud environment. Processes running in the cloud environment will race for available resources in order to complete their tasks with the minimum execution time; it is clear that we need an efficient scheduling technique for mapping between processes running and available resources. In this research paper, we are presented a non-traditional optimization technique, which mimics the process of evolution and based on the mechanics of natural selection and natural genetics called Genetic algorithm (GA), which minimizes the execution time and in turn reduces computation cost. We had done comparison with Round Robin algorithm and used CloudSim toolkit for our tests, results shows that Meta heuristic GA gives better performance than other scheduling algorithm.
Blue Waters and Resource Management - Now and in the Futureinside-BigData.com
In this presentation from Moabcon 2013, Bill Kramer from NCSA presents: Blue Waters and Resource Management - Now and in the Future.
Watch the video of this presentation: http://insidehpc.com/?p=36343
How HPC and large-scale data analytics are transforming experimental scienceinside-BigData.com
In this deck from DataTech19, Debbie Bard from NERSC presents: Supercomputing and the scientist: How HPC and large-scale data analytics are transforming experimental science.
"Debbie Bard leads the Data Science Engagement Group NERSC. NERSC is the mission supercomputing center for the USA Department of Energy, and supports over 7000 scientists and 700 projects with supercomputing needs. A native of the UK, her career spans research in particle physics, cosmology and computing on both sides of the Atlantic. She obtained her PhD at Edinburgh University, and has worked at Imperial College London as well as the Stanford Linear Accelerator Center (SLAC) in the USA, before joining the Data Department at NERSC, where she focuses on data-intensive computing and research, including supercomputing for experimental science and machine learning at scale."
Watch the video: https://wp.me/p3RLHQ-kLV
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
There are various efforts underway to build quantum computers using a range of technologies. These include cold atoms, trapped ions, superconducting circuits, photonics, atom vacancies, spin qubits, quantum dots and topological methods. Each approach has its own strengths and challenges when it comes to engineering a complete system that can offer commercial speedup over classical computers. In this talk we will look at the various challenges that will need to be overcome in order to build a fully functional and commercially viable quantum computer along with the associated timelines.
Strengths and limitations of quantum computingVinayak Sharma
Quantum computing as a research field has been around for about 30 years. It seems like a way to overcome the challenges that classical (boolean based) computers are facing due to “quantum tunneling” effect. Although, there are various theoretical and practical challenges that are needed to be dealt with if we want quantum computes to perform better that classical computers (i.e achieving “quantum supremacy”). This seminar will aim to shed light on basics of quantum computing and its strengths and weaknesses.
Video Links
Part 1: https://www.youtube.com/watch?v=-WLD_HnUvy0
Part 2: https://www.youtube.com/watch?v=xXzUmpk8ztU
Quantum Computing: The next new technology in computingData Con LA
Data Con LA 2020
Description
Quantum computing is rapidly becoming commercially feasible. Many tech giants - Google, IBM, Honeywell, and Microsoft - are spending billions to far outpace Moore's Law. Last year achieved the major milestone of Quantum Supremacy where it was shown that a quantum computer could greatly outperform a classical computer. Quantum computing offers the promise of solving problems which would be impossible for a classical computer including optimization, anomaly detection, and material design. It also allows unhackable communication.
In this presentation I will summarize what quantum computing is and why it is so important. I will sketch the landscape of the field including the hardware, software, and major customers at present. The tool most critical for data analysis - quantum machine learning - will be explained, along with the type of applications it is best suited for. Finally I will explain how you can take the first steps into leveraging quantum computing for your enterprise's benefit.
* What is quantum computing
* Who are the major players in the field
* What is quantum machine learning and what types of problems can it address
* How your company can take advantage of this
Speaker
Mark Jackson, Cambridge Quantum Computing, Scientific Lead of Business Development
Bhadale Group of Companies -Universal Quantum Computer System Design catalogueVijayananda Mohire
Quantum systems and constituent elements design engineering:
We offer a wide range of universal quantum development services for the convenience of our clients based on their business needs, and startup mission :
• Design of various planes , their subsystems, modules, elements that are to be integrated in a phased manner
• Optics and lasers related opto-photonics, laser, microwaves, MOTs, and related setup for experiments in lab and production environments based on AMO physics, and mesoscopic principles
• Operating systems for classical hosting, quantum co-hosting, kernels, host process managers, virtualization , real-time schedulers etc
• Design the required redundancy in the circuits enabling meeting a long term operations and coherence of the logical qubits
• Stabilizer codes, Topological codes
• Reservoir based design of QC system
• Key design upgrades to scale from say 100 qubits to 1000 qubits and more
• Upgrade design , transform designs from NISQ based various paradigms to a truly multi-body system design using highly precise, highly reliable, logical qubits based out of the high quality physical qubits derived from the closed loop real time NN based polar molecules accurately trapped, arranged , and measured with precision using lasers, MOT and various technologies
Bhadale Group of Companies -Universal Quantum Computer System Services catalogueVijayananda Mohire
Migration/upgrade services from NISQ to FTQC paradigm. Quantum safe, quantum cryptography, quantum information management and algorithms , primitive services. Offers enable use of latest redesigned computer components, hardware, software and various control planes, improvised trial standards, etc
From R&D to Market: the industrialization challengeQCB-Conference
From R&D to Market: the industrialization challenge
Maud VINET - Quantum hardware program manager, CEA Leti, France
Explore the multiple challenges of the industrialization path (reliability, scaling, design, value chain) and how to overcome them. See how collective intelligence a key element for success is. Discover QuCube framework, which main objective is to demonstrate a quantum processor for simulation applications.
Quantum technology, a burgeoning field at the intersection of physics, engineering, and computer science, holds immense promise for revolutionizing various industries and transforming our understanding of the universe. This document serves as a comprehensive exploration of quantum technology, delving into its underlying principles, current advancements, potential applications, and societal implications.
At the heart of quantum technology lies the enigmatic realm of quantum mechanics, a branch of physics that describes the behavior of particles at the smallest scales. Unlike classical physics, which operates on deterministic principles, quantum mechanics introduces probabilistic phenomena such as superposition and entanglement. Superposition allows particles to exist in multiple states simultaneously, while entanglement links the properties of particles regardless of the distance between them. These fundamental principles form the foundation upon which quantum technologies are built.
One of the most promising applications of quantum technology is quantum computing. Traditional computers rely on bits, units of information represented as either 0 or 1, to perform computations. In contrast, quantum computers employ quantum bits, or qubits, which can exist in a superposition of 0 and 1 simultaneously. This enables quantum computers to perform complex calculations exponentially faster than classical computers for certain tasks. Quantum algorithms, such as Shor's algorithm for integer factorization and Grover's algorithm for unstructured search, showcase the potential of quantum computing to revolutionize fields such as cryptography, optimization, and machine learning.
Quantum communication offers another compelling application of quantum technology. Quantum key distribution (QKD) protocols leverage the principles of quantum mechanics to enable secure communication between parties. By encoding information in quantum states, such as the polarization of photons, QKD ensures that any attempt to intercept the communication will be immediately detected. This promises unprecedented levels of security for sensitive information, with applications ranging from financial transactions to government communications.
Quantum sensing and metrology harness the delicate quantum states of particles to achieve unparalleled levels of precision and sensitivity in measuring physical quantities. Quantum sensors, such as atomic clocks and magnetometers, offer applications in navigation, geology, and medical imaging. These sensors have the potential to revolutionize fields such as GPS technology, mineral exploration, and early disease detection, where traditional sensors fall short in terms of accuracy or resolution.
Quantum simulation represents yet another frontier of quantum technology, offering the ability to simulate complex quantum systems that are computationally intractable for classical computers. Quantum simulators, whether digital or analog, mimic the behavior o
Quantum computers are designed to perform tasks much more accurately and efficiently than conventional computers, providing developers with a new tool for specific applications.
It is clear in the short-term that quantum computers will not replace their traditional counterparts; instead, they will require classical computers to support their specialized abilities, such as systems optimization.
The slides of the first Meetup of the Quantum Technology community in Paris ! Hosted on 10/16/2018 at WeWork Lafayette
Contribtutors
- Chris Erven CEO of KETS Quantum Security
- Michael Marthaler CEO of Heisenberg Quantum Simulations
- Wojciech Burkot CPO of Beit, on quantum optimization
- Christophe Jurczak CEO of Quantonation, on VC funding
Call for Chapters- Edited Book: Real World Challenges in Quantum Electronics ...Christo Ananth
Most experts would consider this the biggest challenge. Quantum computers are extremely sensitive to noise and errors caused by interactions with their environment. This can cause errors to accumulate and degrade the quality of computation. Developing reliable error correction techniques is therefore essential for building practical quantum computers. While quantum computers have shown impressive performance for some tasks, they are still relatively small compared to classical computers. Scaling up quantum computers to hundreds or thousands of qubits while maintaining high levels of coherence and low error rates remains a major challenge. Developing high-quality quantum hardware, such as qubits and control electronics, is a major challenge. There are many different qubit technologies, each with its own strengths and weaknesses, and developing a scalable, fault-tolerant qubit technology is a major focus of research. Funding agencies, such as government agencies, are rising to the occasion to invest in tackling these quantum computing challenges. Researchers — almost daily — are making advances in the engineering and scientific challenges to create practical quantum computers
B Kindilien-Does Manufacturing Have a Future?jgIpotiwon
Presentation to students and educators at Eastern Connecticut State University in 2008 on the challenges, and opportunities, facing people in manufacturing.
Concept of edge computing is to leverage new generation technologies, processes, services, and applications that are built to take an advantage of new infrastructure.
Put processing closer to the edge of the network pre-process data and send to the cloud.
Bhadale Group of Companies -Modernization of Electronic era systems using Qua...Vijayananda Mohire
Nanoscale, atomic level design, fabrication and production of quantum chip.We offer co-design facility and tie-ups with various national and international institutes like IEEE, NIST, ISO and partners who make it possible to develop blue prints and manufacture atomic scale chips ,ASIC, FPGA, Different quantum storage memory chips, Digital Analog Chips, Adiabatic and Digital technology, Firmware, Data Control, memory addressing schemes, error correction at chip level, security in the chip at hardware level, Space, time, gravity dimensions using various second quantization and theories like string theory, M-theory, Lorentz transformation, de sitter space etc ,faster than light transmission( FTL), entanglement based far off remote operations, dark energy, use of axions, tachyons, singulatrons, warp features
Bhadale Group of Companies -Quantum Systems Manufacturing catalogueVijayananda Mohire
We offer collaborative services with various partners, universities and institutes to progress towards achieving better design, manufacturing and production of various units, assemblies and parts for the supply chain for various quantum clusters manufacturing hubs across the globe.
Nanoscale, atomic level design, fabrication and production of quantum chip are indeed a very big challenge and are limited by the available stat-of-the art technologies. There is a need to make design level changes to accommodate the various limitations. We offer co-design facility and tie-ups with various national and international institutes like IEEE, NIST, ISO and partners who make it possible to develop blue prints and manufacture atomic scale chips
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
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.
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 .
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.
1. Dr Marcus Doherty
Co-founder and Chief Scientific Officer www.quantumbrilliance.com
CSPA presentation August 2020
Quantum Computing:
Demystifying the seemingly impenetrable, improbable
and impractical
2. “We are not prepared for the end of Moore's
Law”
Moore’s Law is ending
Source: J. Shalf, Phil. Trans. Roy. Soc. A, https://doi.org/10.1098/rsta.2019.0061
4. • Classical computers are
inefficient at solving particular
computational problems
• Classical computers must expand
and consume more resources to
solve those problems
• Limits to expansion and
consumption mean that some
problems will remain intractable
Why is this a problem?
[1] https://www.microsoft.com/en-us/research/blog/problems-will-solve-quantum-computer/
[2] N Jones, Nature 561, 163-166 (2018)
A classically intractable problem: Engineering chemical reactions
for efficient fertiliser production
[1]
[2]
Computing is
projected to
consume a
significant portion
of the world’s
energy
5. Quantum is a solution
to take us beyond the limits of the transistor
30 thousand
Classical processors
faster than
ONE
Quantum processor
Does so by exploiting additional physical properties that are
available at the microscopic scale to increase efficiency
Google quantum supremacy demonstration: F Arute, Nature 574, 505 (2019).
6. What can they do?
Source: https://www.quantum-bits.org/?p=2059
Computational complexity classes
Quantum computing applications
7. Where are the
opportunities
for Software
Professionals?
What are its
applications?
How does
Quantum
Computing
work?
Some
important
Quantum
Physics
Why Quantum
Computing?
8. Some important quantum physics
Source: MW Doherty, https://researchcentre.army.gov.au/library/land-power-forum/quantum-technology-introduction
9. Some important quantum physics
N
S
Detection
screen
Stern-Gerlach experiment
Electron spin
Magnetic field
gradient
10. Some important quantum physics
N
S
Detection
screen
Quantum
observation
Classical
prediction
Stern-Gerlach experiment
Magnetic field
gradient
Superposition
state
11. Some important quantum physics
Source: MW Doherty, https://researchcentre.army.gov.au/library/land-power-forum/quantum-technology-introduction
12. Some important quantum physics
General operating principle
Random qubit
state
Measurement
1
0
or
Initialisation Control
Basic components
Qubit
Measurement
system
Computer
interface
Control system
Initialisation
system
Source: MW Doherty, https://researchcentre.army.gov.au/library/land-power-forum/quantum-technology-introduction
13. Where are the
opportunities
for Software
Professionals?
What are its
applications?
How does
Quantum
Computing
work?
Some
important
Quantum
Physics
Why Quantum
Computing?
14. • DiVincenzo's criteria:
• A scalable physical system with well
characterized qubits
• The ability to initialize the state of the
qubits to a simple fiducial state
• Long relevant decoherence times
• A "universal" set of quantum gates
• A qubit-specific measurement capability
Ingredients of a quantum computer
Quantum Brilliance’s diamond quantum
computing architecture
16. • Approaches to universal quantum
computing
• Circuit-based (gate array)
• Measurement-based (one-way)
• Adiabatic
• Topological
Types of quantum computing
Adiabatic quantum computing
Circuit-based quantum computing
Measurement-based quantum
computing
[1] M Fingerhuth et al PLoS ONE https://doi.org/10.1371/journal.pone.0208561. [2] https://medium.com/@jonathan_hui/qc-programming-with-quantum-gates-
8996b667d256 [3] https://medium.com/@quantum_wa/quantum-annealing-cdb129e96601
[1]
[2] [3]
17. Operating principles of circuit-based
quantum computing
1
0
0
0
𝑎0
𝑎1
𝑎2
𝑎3
| ۧ00
| ۧ01
| ۧ10
| ۧ11
:
𝑐00 𝑐01
𝑐10 𝑐11
𝑐02 𝑐03
𝑐12 𝑐13
𝑐20 𝑐21
𝑐30 𝑐31
𝑐22 𝑐23
𝑐32 𝑐33
𝑏0
𝑏1
𝑏2
𝑏3
:
|𝑏0|2
|𝑏1|2
|𝑏2|2
|𝑏3|2
1
0
0
0
,
0
1
0
0
,
0
1
0
0
…
Initialisation Input/
Encoding
Algorithm operation Readout Output/
decoding
Probability
Repeat
0
1
0
0
• 5 steps:
• Initialisation of the qubit register
• Data encoded as a 2n vector of continuous complex numbers
• Algorithms implemented via a 2n x 2n unitary transformation
• Register state readout and processes repeated to build
statistics of a 2n vector of real probabilities
• Data decoding by a chosen operation on probabilities
o Unitary transformation
constructed from a product of
unitary operators acting on one or
two qubits
o These unitary operators are
selected from a universal set (eg S,
H, T, CNOT)
18. • Comparison of classical and quantum operation
Origins of quantum advantage
1
0
0
0
0
1
0
0
| ۧ00
| ۧ01
| ۧ10
| ۧ11
:
1 0
0 0
0 0
1 0
0 1
0 0
0 0
0 1
0
0
1
0
Initialisation Input/
Encoding
Algorithm operation Readout Output/
decoding
0
0
1
0
1
0
0
0
𝑎0
𝑎1
𝑎2
𝑎3
| ۧ00
| ۧ01
| ۧ10
| ۧ11
:
𝑐00 𝑐01
𝑐10 𝑐11
𝑐02 𝑐03
𝑐12 𝑐13
𝑐20 𝑐21
𝑐30 𝑐31
𝑐22 𝑐23
𝑐32 𝑐33
𝑏0
𝑏1
𝑏2
𝑏3
:
|𝑏0|2
|𝑏1|2
|𝑏2|2
|𝑏3|2
1
0
0
0
,
0
1
0
0
,
0
1
0
0
…
Initialisation Input/
Encoding
Algorithm operation Readout Output/
decoding
Probability
Repeat
0
1
0
0
Denser encoding:
2n more information
Denser operations:
2n higher dimensionality
of operations
Non-determinism:
2n more repetitions
before output
• To gain speed up,
quantum algorithms
must exploit denser
encoding and
dimensionality, whilst
minimising the cost of
non-determinism
• Achieved by
engineering a narrow
readout probability
distribution
19. • Physical constraints
• Operation (initialisation, gate and
readout) errors
• Operation speeds
• Decoherence
• Conflicts between gates
• Limited qubit connectivity
• Finite set of primitive gates
(owing to costs in time and
memory)
• No QRAM (encoding is part of
operation)
The reality of quantum computing
hardware
Optimal control & error
correction protocols
Optimal scheduling &
routing
Optimal gate
decomposition
Mitigation approach
Cluster of 5 diamond spin-qubits
Efficient encoding
methods
Quantum compiling
[1]
[1] https://www.ibm.com/blogs/research/2019/09/quantum-computation-center/
20. Where are the
opportunities
for Software
Professionals?
What are its
applications?
How does
Quantum
Computing
work?
Some
important
Quantum
Physics
Why Quantum
Computing?
21. QRAM not required
• Shor’s Algorithm
• Quantum Support
Vector Machine
• Quantum Semi-
definite Programming
+ more
QRAM required
• Quantum Fourier
Transform
• Phase estimation
• Grover’s Algorithm
• Quantum Principal
Component Analysis +
more
Variational
• Variational Quantum
Eigensolver
• Quantum Approximate
Optimisation
Algorithm
• Variational Quantum
Factoring + more
Quantum algorithms
Clear quantum
advantage
Clear quantum
advantage
Implementable on NISQ
devices
Lots of qubits and large
circuit depth required
Without QRAM, state
preparation routines kill
speed-up
Quantum advantage
often unprovable/
unknown
Taxonomy Applications
• Quantum chemistry for
pharmacology, materials science
and chemical engineering
• Optimisation in finance,
engineering, manufacturing and
routing/ process design
• Statistical analysis and sampling
• Quantum Machine Learning
• Image and signal processing
• Searching unstructured
databases + more
22. Application demonstrations
Understanding the chemical processes in
fertiliser production [1]
Simulation of protein folding [2] Simulation for battery design for cars [3]
Investment portfolio optimisation [4]
Financial risk analysis [5]
[1] https://www.microsoft.com/en-us/research/blog/problems-will-solve-quantum-computer/
[2] A Robert et al arXiv:1908.02163v1 (2019). [3] JE Rice et al arXiv:2001.01120v1 (2020)
[4] M Hodson et al arXiv:1911.05296v1 (2019). [5] S Woerner and DJ Egger npj Quantum Information 5, 15 (2019).
23. • Quantum computing will become increasing
hybridised with classical computing
The advent of the QPU accelerator
• Near-term specialist applications will
demand
• integration of classical and quantum
hardware
• hardware-software co-development
• New hardware will enable massively
parallelised, distributed and mobile
applications
Future vision
[1] https://ai.googleblog.com/2018/03/a-preview-of-bristlecone-googles-new.html
[1]
26. 2020.04.10_LMV
Size, weight and power: the keys to quantum advantage
Size/ Weight/ Power (“SWaP”) + Cost
Performance
Outperform
x1 CPU
Outperform
x1 Supercomputer
Low SWaP → Accelerated Pathway to Quantum Applications
27. Where are the
opportunities
for Software
Professionals?
What are its
applications?
How does
Quantum
Computing
work?
Some
important
Quantum
Physics
Why Quantum
Computing?
28. The quantum software stack
Parallelisation & co-processing
Low-level quantum compiling
High-level quantum compiling
Quantum machine control
Distribution and synchronization of
tasks between classical and quantum
processors
Error correction protocols
Optimal quantum control techniques
Efficient encoding/decoding
Operation decomposition, scheduling
and routing
Fast and precise implementation of
machine operations
Real-time feedback control
Applications & interface
Full use case demonstration and
validation
Development required at all levels of the stack
Demands the skills and knowledge of all types of Software Professionals
29. • Partnering in the development and use case
demonstration of massively-parallelised, distributed
and mobile applications
• Partnering to demonstrate early quantum advantage
by beating a low SWaP CPUs/GPUs
• Solving your problems in finance, logistics, machine
learning, image processing or signal processing
• Helping you integrate quantum computers into High-
Performance Computing systems
Opportunities at Quantum Brilliance
We can provide priority
access to our
• Quantum emulator
• Quantum hardware
• Applications team
30. Where are the
opportunities
for Software
Professionals?
What are its
applications?
How does
Quantum
Computing
work?
Some
important
Quantum
Physics
Why Quantum
Computing?
