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Lightning talk from F#nctional Londoners user group meeting 04/06/2015. Briefly discusses the instrument control software we have written in F# to control a custom experiment at the University of Warwick.
EXHIBIT A
V A C C I N E - A N A L Y S I S - B Y - D R . R O B E R T - Y O U NG
Graphene Oxide; also known as G.O. is a compound of magnetic nanoparticles.
Atomic level manipulation of matter using Scanning Transmission Electron Micr...Ondrej Dyck
Discussion of developments surrounding the transformation of the scanning transmission electron microscope from an imaging platform into a manipulation platform.
CZECH NANO SHOW - Marketa Borovcova - CEITEC Jan Fried
CEITEC is a scientific center in Brno, Czech Republic focused on life sciences, advanced materials, and technologies. Its aim is to establish itself as a recognized European center of science through collaboration. It has over 110 researchers across 9 groups studying advanced nanotechnologies and microtechnologies and 78 researchers across 4 groups studying advanced materials. CEITEC collaborates with universities, research institutes, and companies both within the Czech Republic and internationally. It produces scientific publications, receives research grants, and has launched its first startup company based on a patented interferometric imaging system.
Employing Electrophysiology and Optogenetics to Measure and Manipulate Neuron...InsideScientific
In this webinar, Dr. Tahl Holtzman, Founder of Cambridge NeuroTech, describes a new generation of silicon neural probes offering dozens of recording channels in precisely spaced, high-resolution arrays, built using sophisticated fabrication techniques borrowed from the electronics industry, along with simple-to-follow surgical implantation schemes for both acute and chronic animals.
Watch to learn how to take advantage of ultra-small chronic drives to open up scalability to span multiple brain areas in parallel and to achieve excellent chronic stability. In addition, Dr. Holtzman demonstrates integration of novel probes and drives offered by Cambridge NeuroTech with optogenetics that thereby enable your experiments to have the combined capability for measurement AND manipulation of neuronal activity in both acute and freely behaving settings.
This webinar will benefit both established electrophysiologists who wish to increase their data yield and experimental reach as well as those investigators whose expertise is centred in and around the animal behavioural, neuropharmacological, and optogenetics arenas. Viewers will learn what silicon neural probes are and how to use them in both acute and chronic experiments, best-practice techniques for surgical implantation in species ranging from mice to monkeys and how to integrate fibre optic cannulas with your probes to enable simultaneous opto-electrophysiology.
This document provides an overview of particle-induced x-ray emission (PIXE), an analytical technique for elemental analysis. It begins with a brief history, noting early work in the 1910s and key developments in the 1950s and 1960s that established PIXE as a method. The basic principle, instrumentation including particle accelerators and silicon drift detectors, and analytical process involving qualitative and quantitative analysis are described. PIXE is highlighted as a powerful nondestructive method useful for applications like environmental monitoring and tracing toxic elements.
The document discusses PIXE (particle-induced X-ray emission), an analytical technique used to determine the elemental composition of materials. It begins with the basic principle of using charged particles like protons to induce X-ray emission from samples. It then provides a brief history of the development of the technique from early experiments in the 1910s to its establishment as a powerful multi-element analytical method by the 1970s. The rest of the document covers the instrumentation, analytical process, applications, and new developments of PIXE.
This document discusses various natural language processing (NLP) tools that can be used from .NET, including SharpNLP, Stanford NLP for .NET, IKVM.NET, OpenNLP for .NET, and MaltParser for .NET. It provides links to pages with code samples and tutorials for tools like Stanford NLP.NET, which implements popular NLP libraries like the Stanford Named Entity Recognizer and Part-of-Speech Tagger for .NET. It also demonstrates how NLP can be used to find related questions on Stack Overflow before a user posts a new question.
Lightning talk from F#nctional Londoners user group meeting 04/06/2015. Briefly discusses the instrument control software we have written in F# to control a custom experiment at the University of Warwick.
EXHIBIT A
V A C C I N E - A N A L Y S I S - B Y - D R . R O B E R T - Y O U NG
Graphene Oxide; also known as G.O. is a compound of magnetic nanoparticles.
Atomic level manipulation of matter using Scanning Transmission Electron Micr...Ondrej Dyck
Discussion of developments surrounding the transformation of the scanning transmission electron microscope from an imaging platform into a manipulation platform.
CZECH NANO SHOW - Marketa Borovcova - CEITEC Jan Fried
CEITEC is a scientific center in Brno, Czech Republic focused on life sciences, advanced materials, and technologies. Its aim is to establish itself as a recognized European center of science through collaboration. It has over 110 researchers across 9 groups studying advanced nanotechnologies and microtechnologies and 78 researchers across 4 groups studying advanced materials. CEITEC collaborates with universities, research institutes, and companies both within the Czech Republic and internationally. It produces scientific publications, receives research grants, and has launched its first startup company based on a patented interferometric imaging system.
Employing Electrophysiology and Optogenetics to Measure and Manipulate Neuron...InsideScientific
In this webinar, Dr. Tahl Holtzman, Founder of Cambridge NeuroTech, describes a new generation of silicon neural probes offering dozens of recording channels in precisely spaced, high-resolution arrays, built using sophisticated fabrication techniques borrowed from the electronics industry, along with simple-to-follow surgical implantation schemes for both acute and chronic animals.
Watch to learn how to take advantage of ultra-small chronic drives to open up scalability to span multiple brain areas in parallel and to achieve excellent chronic stability. In addition, Dr. Holtzman demonstrates integration of novel probes and drives offered by Cambridge NeuroTech with optogenetics that thereby enable your experiments to have the combined capability for measurement AND manipulation of neuronal activity in both acute and freely behaving settings.
This webinar will benefit both established electrophysiologists who wish to increase their data yield and experimental reach as well as those investigators whose expertise is centred in and around the animal behavioural, neuropharmacological, and optogenetics arenas. Viewers will learn what silicon neural probes are and how to use them in both acute and chronic experiments, best-practice techniques for surgical implantation in species ranging from mice to monkeys and how to integrate fibre optic cannulas with your probes to enable simultaneous opto-electrophysiology.
This document provides an overview of particle-induced x-ray emission (PIXE), an analytical technique for elemental analysis. It begins with a brief history, noting early work in the 1910s and key developments in the 1950s and 1960s that established PIXE as a method. The basic principle, instrumentation including particle accelerators and silicon drift detectors, and analytical process involving qualitative and quantitative analysis are described. PIXE is highlighted as a powerful nondestructive method useful for applications like environmental monitoring and tracing toxic elements.
The document discusses PIXE (particle-induced X-ray emission), an analytical technique used to determine the elemental composition of materials. It begins with the basic principle of using charged particles like protons to induce X-ray emission from samples. It then provides a brief history of the development of the technique from early experiments in the 1910s to its establishment as a powerful multi-element analytical method by the 1970s. The rest of the document covers the instrumentation, analytical process, applications, and new developments of PIXE.
Computational materials design with high-throughput and machine learning methodsAnubhav Jain
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Power point presentation for science researchSatish Bhat
The document discusses a research study investigating whether polycaprolactone can be used in tissue engineering. The study tested polycaprolactone through NMR, thermal analysis, and mechanical tests and compared the results to polylactic acid, which is currently used successfully in tissue engineering. The NMR and thermal analysis results showed that polycaprolactone has similar characteristics to polylactic acid. Therefore, the study suggests that polycaprolactone is a viable potential material that could possibly be used for tissue scaffolding.
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This study investigated whether polycaprolactone could be used in tissue engineering as a scaffolding material. The hypothesis was that polycaprolactone would have similar properties to polylactic acid, which is currently used successfully in tissue engineering. Nuclear magnetic resonance testing showed that polycaprolactone had resonance peaks in the same locations as polylactic acid. Thermal analysis also demonstrated that polycaprolactone has properties very similar to polylactic acid. The results suggest that polycaprolactone is a viable potential material for use in tissue scaffolding.
Bradley B. Barth is a PhD candidate in biomedical engineering at Duke University. His research focuses on developing implantable devices to record and stimulate the enteric nervous system using flexible electronics, with the goal of creating diagnostic and therapeutic tools for digestive diseases. He has experience in animal studies, electrophysiology, microfabrication, and collaborating on projects involving the peripheral nervous system.
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Ions in channels and solutions control most living functions. Analysis in atomic detail is needed, but so is prediction of functions on the macroscopic scale. Computational electronics has solved similar issues and we all benefit from the computational devices it provides us. These slides show how a similar approach can be used, and is necessary in my view, for ions solutions and biological systems, most notably in ion channels
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Kelvin J. A. Ooi presented a document summarizing research on the interaction of nanostructures with optical fields. The document covered topics such as plasmonic waveguides, optical antennas and cavities, graphene plasmonics, plasmon excitation through scattering and tunneling, and nonlinear plasmonics. For each topic, several key publications were referenced with brief descriptions. The overall document aimed to provide an overview of recent work relating nanostructures to optical phenomena.
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We describe and demonstrate here how we are realizing such capabilities at the Argonne Leadership Computing Facility. In our demonstration, we use large quantities of time-dependent density functional theory (TDDFT) data on proton stopping power in various materials maintained in the Materials Data Facility (MDF) to build machine learning models, ranging from simple linear models to complex artificial neural networks, that are then employed to manage computations, improving their accuracy and reducing their cost. We highlight the use of new services being prototyped at Argonne to organize and assemble large data collections (MDF in this case), associate ML models with data collections, discover available data and models, work with these data and models in an interactive Jupyter environment, and launch new computations on ALCF resources.
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The document summarizes research on neural engineering related to cochlear implants and intracortical microelectrodes. It discusses:
1) Cochlear implant research involving developing a method to fit implants using stapedius electromyography recordings in rats.
2) Chronic neural interfacing research using intracortical microelectrodes to record brain activity, the challenges of long-term recordings due to tissue encapsulation, and methods explored to address this like enzyme-aided electrode insertion.
3) The quantification of recording performance over time and correlations with electrode impedance.
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I gave this talk at a conference for young scientists in New Zealand, "Running Hot": www.runninghot.org.nz. It was a great meeting. My slides are mostly images, so may not make too much sense.
Abstract follows: Impressed with the telephone, Arthur Mee predicted in 1898 that if videoconferencing could be developed, ‘earth will be in truth a paradise.’ Since his time, rapid technological change, in particular in telecommunications, has transformed the scientific playing field in ways that while not entirely paradisical, certainly have profound implications for New Zealand scientists. The Internet has abolished distance, as Mee also predicted–a New Zealand scientist can participate as fully in online discussions as anyone else, and their blog can be every bit as influential. Exponential improvements in networks, computing, sensors, and data storage are also profoundly transforming the practice of science in many disciplines. But those seeking to leverage these advances become painfully familiar with the ‘dirty underbelly’ of exponentials: if you don’t constantly innovate, you can fall behind exponentially fast. Such considerations pose big challenges for the individual scientist and for institutions, for researchers and educators, and for research funders. Some of the old ways of researching and educating need to be preserved, others need to be replaced to take advantage of new methods. But what should we preserve? What should we seek to change?
Fu-Kang Wang has extensive research experience in radar systems, including 9 journal papers, 11 conference papers, and 9 patents. His research focuses on developing self-injection locked radar techniques for applications such as vital sign monitoring, see-through-wall imaging, and indoor positioning. He has a Ph.D. from National Sun Yat-Sen University and has held research positions in Taiwan and Belgium, developing radar systems to detect vital signs, gestures, and indoor positioning using retransmitted wireless signals.
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Microservice Teams - How the cloud changes the way we workSven Peters
A lot of technical challenges and complexity come with building a cloud-native and distributed architecture. The way we develop backend software has fundamentally changed in the last ten years. Managing a microservices architecture demands a lot of us to ensure observability and operational resiliency. But did you also change the way you run your development teams?
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This study investigated whether polycaprolactone could be used in tissue engineering as a scaffolding material. The hypothesis was that polycaprolactone would have similar properties to polylactic acid, which is currently used successfully in tissue engineering. Nuclear magnetic resonance testing showed that polycaprolactone had resonance peaks in the same locations as polylactic acid. Thermal analysis also demonstrated that polycaprolactone has properties very similar to polylactic acid. The results suggest that polycaprolactone is a viable potential material for use in tissue scaffolding.
Bradley B. Barth is a PhD candidate in biomedical engineering at Duke University. His research focuses on developing implantable devices to record and stimulate the enteric nervous system using flexible electronics, with the goal of creating diagnostic and therapeutic tools for digestive diseases. He has experience in animal studies, electrophysiology, microfabrication, and collaborating on projects involving the peripheral nervous system.
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Ions in channels and solutions control most living functions. Analysis in atomic detail is needed, but so is prediction of functions on the macroscopic scale. Computational electronics has solved similar issues and we all benefit from the computational devices it provides us. These slides show how a similar approach can be used, and is necessary in my view, for ions solutions and biological systems, most notably in ion channels
The document discusses several areas of progress and potential in nanotechnology, as well as some pitfalls. It describes advances in zirconium isotope separation that could improve nuclear reactor components. It highlights the development of institutes studying nanoscience, like the National Institute for Nanotechnology and Institute for Quantum Computing. It also outlines potential applications of nanotechnology in areas like molecular electronics, quantum computing, biomedical imaging, and targeted drug delivery.
Kelvin J. A. Ooi presented a document summarizing research on the interaction of nanostructures with optical fields. The document covered topics such as plasmonic waveguides, optical antennas and cavities, graphene plasmonics, plasmon excitation through scattering and tunneling, and nonlinear plasmonics. For each topic, several key publications were referenced with brief descriptions. The overall document aimed to provide an overview of recent work relating nanostructures to optical phenomena.
Going Smart and Deep on Materials at ALCFIan Foster
As we acquire large quantities of science data from experiment and simulation, it becomes possible to apply machine learning (ML) to those data to build predictive models and to guide future simulations and experiments. Leadership Computing Facilities need to make it easy to assemble such data collections and to develop, deploy, and run associated ML models.
We describe and demonstrate here how we are realizing such capabilities at the Argonne Leadership Computing Facility. In our demonstration, we use large quantities of time-dependent density functional theory (TDDFT) data on proton stopping power in various materials maintained in the Materials Data Facility (MDF) to build machine learning models, ranging from simple linear models to complex artificial neural networks, that are then employed to manage computations, improving their accuracy and reducing their cost. We highlight the use of new services being prototyped at Argonne to organize and assemble large data collections (MDF in this case), associate ML models with data collections, discover available data and models, work with these data and models in an interactive Jupyter environment, and launch new computations on ALCF resources.
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The document summarizes research on neural engineering related to cochlear implants and intracortical microelectrodes. It discusses:
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2) Chronic neural interfacing research using intracortical microelectrodes to record brain activity, the challenges of long-term recordings due to tissue encapsulation, and methods explored to address this like enzyme-aided electrode insertion.
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GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
GraphSummit Paris - The art of the possible with Graph Technology
Building scientific experiments with F#
1. Building scientific
experiments with F#
A. Tcholakov, B. L. Green, A. C. Frangeskou, C. J. Stephen, P. Diggle,
J. Lishman, T. Wheeler, M. E. Newton, and G. W. Morley
2. A. Tcholakov, B. L. Green, A. C. Frangeskou, C. J. Stephen, P. Diggle,
J. Lishman, T. Wheeler, M. E. Newton, and G. W. Morley
Building scientific
experiments with F#
3. A. Tcholakov, B. L. Green, A. C. Frangeskou, C. J. Stephen, P. Diggle,
J. Lishman, T. Wheeler, M. E. Newton, and G. W. Morley
Building scientific
experiments with F#
4. A. Tcholakov, B. L. Green, A. C. Frangeskou, C. J. Stephen, P. Diggle,
J. Lishman, T. Wheeler, M. E. Newton, and G. W. Morley
Building scientific
experiments with F#
5. A. Tcholakov, B. L. Green, A. C. Frangeskou, C. J. Stephen, P. Diggle,
J. Lishman, T. Wheeler, M. E. Newton, and G. W. Morley
Building scientific
experiments with F#
6. Anatomy of an experiment
PC
Output
device
Input
device
Science!
@ant_pt
7. • Concurrent control of multiple devices
• Cancellation
• Reporting of partial progress
• Signal processing
• Robust error handling
• Good performance
Requirements
@ant_pt
8. • Concurrent control of multiple devices
• Cancellation
• Reporting of partial progress
• Signal processing
• Robust error handling
• Good performance
Requirements… and solutions
Async<'T>
IObservable<'T>
Choice<'T1,'T2> or exn?
}
}
@ant_pt
9. • Software isn’t actually the key output
• Experiments start as prototypes
• Need path to fully-fledged application
Requirements (process)
@ant_pt
10. • National Instruments VISA
• C API + DLL import
• Typically very imperative and stateful
• Inherently Async, MailboxProcessor-like
Instrument I/O
@ant_pt
11. Command-request agent
• Module for creating MailboxProcessor agents
which process Command or Request messages
• Instrument APIs often have large surface area
• Propagates errors to caller without stopping the
agent
@ant_pt
13. Oscilloscope
• Essential tool in a
physics lab
• Records voltages
against time
• Has settings for
triggering, input
range, offset, etc.
Source: “Oscilloscope.” Wikipedia: The Free Encyclopaedia.
Wikimedia Foundation, Inc. 20 Mar 2016. Web. 13 Apr 2016.
@ant_pt
15. PicoScope agent: review
• Async but still imperative
• Device is typically used in one of several modes:
streaming, block acquisition, etc.
• Functional approach:
- model acquisition configuration
- define workflow to run a general acquisition
- push sample blocks via IObservable<'T>
@ant_pt
26. N-V-
spectrometer: review
• Declarative streaming API makes code
straightforward to read, write, and modify
• IObservable<'T> + FSharp.Control.Reactive
offer a powerful way to implement DSP
• FSharp.Charting is great for prototyping
• Async provides robust cancellation support
• MailboxProcessor ensures sequential I/O
@ant_pt
28. 397 GHz spectrometer
• Irradiate sample with
397 GHz mm-waves
• Sweep field on
superconducting
magnet system
• Measure what comes
back and stream
data with PicoScope
@ant_pt
32. Confocal microscope
Pulse length
(1ns resolution)
Integrated
photon counts
Acquisition
parameters
System development time: ~9 months
Oscillations represent
manipulation of a qubit!
@ant_pt
33. Performance
• Hasn’t really been a problem
• PicoScope streaming acquisition copes with 32ns
sample interval (fastest available) in .fsx
• Time tagging acquisition copes with several
million photon counts per second
@ant_pt
34. Towards open source…
• Aim to publish the code under Apache 2.0
• Wrappers for several common lab instruments
• First need to:
- migrate to Paket, FAKE
- make namespaces consistent
- consolidate git branches
- write some unit tests (?)
@ant_pt
35. Conclusions
• F# is a great fit for instrument control thanks to
powerful Async, Reactive programming features
• Functional paradigm + .fsx aids prototyping
• Units of measure are the cherry on top
• Working towards open source instrument
libraries
@ant_pt