The validation of performance of NMR chemical shift prediction algorithms is a challenging problem for a number of reasons. These will be discussed only at a general level in this technical evaluation since they have been discussed elsewhere. The central challenge associated with the validation of NMR shift prediction algorithms is obtaining a quality data set for validation of the prediction accuracy.
If the validation data set is mainly simple structures, or structures that are well represented in the database used as the basis of the prediction algorithms then the validation exercise will not truly represent the challenges of prediction. The most valid test would be conducted on a validation set containing chemical structures which are very different from these contained within the training dataset. Ideally, an independent party without knowledge of the structures in the training set should choose the validation set, so as to avoid any bias.
Improved Sensitivity and Dynamic Range Using the Clarus SQ8 GC/MS for EPA Met...PerkinElmer, Inc.
U.S. Environmental Protection Agency (EPA) Method 8270D - Semi-Volatile Orgranic Compounds by Gas Chromatography/Mass Spectrometry (GC/MS) - is a common and wide ranging method employed in nearly all commercial environmental laboratories. The analysis focuses on the detection of trace level semi-volatile organic compounds in extracts from solid waste matrices, soils, air sampling media and water samples. The method lists over 200 compounds however a majority of laboratories target between 60 and 90 for most analyses. The study presented here demonstrates the PerkinElmer Clarus SQ 8 GC/MS, not only meets the method requirements but provides users flexibility to satisfy their individual productivity demands. An extended calibration range is presented as are the advantages of the Clarifi detector.
Improved Sensitivity and Dynamic Range Using the Clarus SQ8 GC/MS for EPA Met...PerkinElmer, Inc.
U.S. Environmental Protection Agency (EPA) Method 8270D - Semi-Volatile Orgranic Compounds by Gas Chromatography/Mass Spectrometry (GC/MS) - is a common and wide ranging method employed in nearly all commercial environmental laboratories. The analysis focuses on the detection of trace level semi-volatile organic compounds in extracts from solid waste matrices, soils, air sampling media and water samples. The method lists over 200 compounds however a majority of laboratories target between 60 and 90 for most analyses. The study presented here demonstrates the PerkinElmer Clarus SQ 8 GC/MS, not only meets the method requirements but provides users flexibility to satisfy their individual productivity demands. An extended calibration range is presented as are the advantages of the Clarifi detector.
Deformulating Complex Polymer Mixtures By GPC-IR Technologymzhou45
GPC-IR to de-formulate complex polymer mixtures such as adhesives, coatingg, inks, additives to identify polymer components and find their specific raw material suppliers by IR database search. The presentation was given at American Coating Conference 2012 on May 7 in Indy.
This poster describes a GCMS purge-and-trap (P&T) method validation study conducted to evaluate operating conditions for the existing US EPA Method 624 VOC list, using updated technology and advanced GCMS instrumentation.
For more information, go to www.ssi.shimadzu.com and follow Shimadzu on Twitter at @ShimadzuSSI. Thanks for viewing.
Webinar - Pharmacopeial Modernization: How Will Your Chromatography Workflow ...Waters Corporation
In this webinar, Dr. Leonel Santos and Dr. Horacio Pappa from the United States Pharmacopeia (USP) will provide an overview of its pharmacopeial harmonization and modernization efforts. The pair will also review changes described in the pending USP General Chapter <621> on liquid chromatography (LC), which will provide increased flexibility for gradient methods.
Amanda Dlugasch, from Waters Corporation, will follow with an illuminating case study, which leverages USP <621> allowable adjustments to illustrate the benefits of modernizing methods, including migrating HPLC methods to UHPLC or UPLC, without the need to revalidate.
Topics covered in this webinar will include:
- Pharmacopeial monograph modernization prioritization scheme
- Review of USP General Chapter <621> current allowable adjustments to validated chromatographic methods and forthcoming updates
- Case study on the migration of isocratic and gradient pharmacopeial methods to modern chromatography column technology, highlighting improved method performance and throughput
Replay the webinar, hosted by SelectScience:
https://www.selectscience.net/webinars/pharmacopeial-modernization-how-will-your-chromatography-workflow-benefit/?webinarID=1228
LC-IR Applications In Polymer Related Industriesmzhou45
LC-IR Application Overview for Polymer Related Industries with Many Case Studies: characterize copolymer compositions across MWD and de-formulate complex polymer mixtures
Learn about Waters technologies for analyzing oligonucleotides with LC-MS. We offer solutions for both oligo characterization and QC monitoring. Learn more: http://www.waters.com/oligos
New LC-IR Technique To Characterize Polymeric Excipients In Pharmaceutical Fo...mzhou45
GPC-IR combined technique to characterize polymeric excipients for lot-to-lot variations and degradation/stability from thermal processing in drug formulations
The webinar is all about Ultra High Pressure Liquid Chromatography (UHPLC) performance and how new column technology can deliver the best separation power and be married with the best UHPLC system to ensure an outstanding result. It covers how chromatographers can ensure that even very complex and unfamiliar samples are assayed with the highest scrutiny possible? The webinar discusses how to get the most out of solid core column technology with the right UHPLC system. It covers the use of an extremely long column approach for ultra-high resolution assays and the outlines the importance of robustness and retention time stability.
The ACQUITY Advanced Polymer Chromatography (APC™) System is a breakthrough technology that defines the ultimate in size-based chromatographic separations, delivering more information about your polymers faster than ever before. This means better characterization, improved asset utilization and a superior solution for achieving corporate innovation and sustainability goals.
Passive Soil Gas Testing - Standard for Site CharacterizationHarryONeill
Passive soil gas surveys provide high resolution site characterization data to identify source areas, vapor intrusion pathways, and delineate groundwater plumes. Beacon is known for providing the highest quality soil gas data in the industry by following strict QA/QC procedures in the design of the PSG Samplers and analysis of the samples. Beacon is the only laboratory to have achieved DoD ELAP accreditation for the analysis of soil gas samples by US EPA Method 8260C and US EPA Method TO-17. In addition, Beacon is the first company to receive accreditation for the collection of soil gas samples under the TNI NEFAP program. The experience offered by Beacon coupled with the strict attention to quality control makes Beacon's PSG Surveys the best method in the industry for targeting organic compounds (e.g., chlorinated and petroleum hydrocarbons) in the vapor phase.
There is an increasing availability of free and open access resources for scientists to use on the internet. Coupled with the increasing availability of Open Source software tools we are in the middle of a revolution in data availability and tools to manipulate these data. ChemSpider is a free access website for chemists built with the intention of providing a structure centric community for chemists. As an aggregator of chemistry related information from many sources, at present over 21.5 million unique chemical entities from over 200 separate data sources, ChemSpider has taken on the task of both robotically and manually curating publicly available data sources. This presentation will provide an overview of the ChemSpider platform and how it is fast becoming the centralized hub for resourcing information about chemical entities.
Deformulating Complex Polymer Mixtures By GPC-IR Technologymzhou45
GPC-IR to de-formulate complex polymer mixtures such as adhesives, coatingg, inks, additives to identify polymer components and find their specific raw material suppliers by IR database search. The presentation was given at American Coating Conference 2012 on May 7 in Indy.
This poster describes a GCMS purge-and-trap (P&T) method validation study conducted to evaluate operating conditions for the existing US EPA Method 624 VOC list, using updated technology and advanced GCMS instrumentation.
For more information, go to www.ssi.shimadzu.com and follow Shimadzu on Twitter at @ShimadzuSSI. Thanks for viewing.
Webinar - Pharmacopeial Modernization: How Will Your Chromatography Workflow ...Waters Corporation
In this webinar, Dr. Leonel Santos and Dr. Horacio Pappa from the United States Pharmacopeia (USP) will provide an overview of its pharmacopeial harmonization and modernization efforts. The pair will also review changes described in the pending USP General Chapter <621> on liquid chromatography (LC), which will provide increased flexibility for gradient methods.
Amanda Dlugasch, from Waters Corporation, will follow with an illuminating case study, which leverages USP <621> allowable adjustments to illustrate the benefits of modernizing methods, including migrating HPLC methods to UHPLC or UPLC, without the need to revalidate.
Topics covered in this webinar will include:
- Pharmacopeial monograph modernization prioritization scheme
- Review of USP General Chapter <621> current allowable adjustments to validated chromatographic methods and forthcoming updates
- Case study on the migration of isocratic and gradient pharmacopeial methods to modern chromatography column technology, highlighting improved method performance and throughput
Replay the webinar, hosted by SelectScience:
https://www.selectscience.net/webinars/pharmacopeial-modernization-how-will-your-chromatography-workflow-benefit/?webinarID=1228
LC-IR Applications In Polymer Related Industriesmzhou45
LC-IR Application Overview for Polymer Related Industries with Many Case Studies: characterize copolymer compositions across MWD and de-formulate complex polymer mixtures
Learn about Waters technologies for analyzing oligonucleotides with LC-MS. We offer solutions for both oligo characterization and QC monitoring. Learn more: http://www.waters.com/oligos
New LC-IR Technique To Characterize Polymeric Excipients In Pharmaceutical Fo...mzhou45
GPC-IR combined technique to characterize polymeric excipients for lot-to-lot variations and degradation/stability from thermal processing in drug formulations
The webinar is all about Ultra High Pressure Liquid Chromatography (UHPLC) performance and how new column technology can deliver the best separation power and be married with the best UHPLC system to ensure an outstanding result. It covers how chromatographers can ensure that even very complex and unfamiliar samples are assayed with the highest scrutiny possible? The webinar discusses how to get the most out of solid core column technology with the right UHPLC system. It covers the use of an extremely long column approach for ultra-high resolution assays and the outlines the importance of robustness and retention time stability.
The ACQUITY Advanced Polymer Chromatography (APC™) System is a breakthrough technology that defines the ultimate in size-based chromatographic separations, delivering more information about your polymers faster than ever before. This means better characterization, improved asset utilization and a superior solution for achieving corporate innovation and sustainability goals.
Passive Soil Gas Testing - Standard for Site CharacterizationHarryONeill
Passive soil gas surveys provide high resolution site characterization data to identify source areas, vapor intrusion pathways, and delineate groundwater plumes. Beacon is known for providing the highest quality soil gas data in the industry by following strict QA/QC procedures in the design of the PSG Samplers and analysis of the samples. Beacon is the only laboratory to have achieved DoD ELAP accreditation for the analysis of soil gas samples by US EPA Method 8260C and US EPA Method TO-17. In addition, Beacon is the first company to receive accreditation for the collection of soil gas samples under the TNI NEFAP program. The experience offered by Beacon coupled with the strict attention to quality control makes Beacon's PSG Surveys the best method in the industry for targeting organic compounds (e.g., chlorinated and petroleum hydrocarbons) in the vapor phase.
There is an increasing availability of free and open access resources for scientists to use on the internet. Coupled with the increasing availability of Open Source software tools we are in the middle of a revolution in data availability and tools to manipulate these data. ChemSpider is a free access website for chemists built with the intention of providing a structure centric community for chemists. As an aggregator of chemistry related information from many sources, at present over 21.5 million unique chemical entities from over 200 separate data sources, ChemSpider has taken on the task of both robotically and manually curating publicly available data sources. This presentation will provide an overview of the ChemSpider platform and how it is fast becoming the centralized hub for resourcing information about chemical entities.
There is an increasing availability of free and open access resources for chemists to use on the internet. Coupled with the increasing availability of Open Source software tools we are in the middle of a revolution in data availability and tools to manipulate these data. ChemSpider is a free access website for chemists built with the intention of providing a structure centric community for chemists. It was developed with the intention of aggregating and indexing available sources of chemical structures and their associated information into a single searchable repository and making it available to everybody, at no charge.
There are tens if not hundreds of chemical structure databases such as literature data, chemical vendor catalogs, molecular properties, environmental data, toxicity data, analytical data etc. and no single way to search across them. Despite the fact that there were a large number of databases containing chemical compounds and data available online their inherent quality, accuracy and completeness was lacking in many regards. The intention with ChemSpider was to provide a platform whereby the chemistry community could contribute to cleaning up the data, improving the quality of data online and expanding the information available to include data such as reaction syntheses, analytical data, experimental properties and linking to other valuable resources. It has grown into a resource containing over 21 million unique chemical structures from over 200 data sources.
ChemSpider has enabled real time curation of the data, association of analytical data with chemical structures, real-time deposition of single or batch chemical structures (including with activity data) and transaction-based predictions of physicochemical data. The social community aspects of the system demonstrate the potential of this approach. Curation of the data continues daily and thousands of edits and depositions by members of the community have dramatically improved the quality of the data relative to other public resources for chemistry.
This presentation will provide an overview of the history of ChemSpider, the present capabilities of the platform and how it can become one of the primary foundations of the semantic web for chemistry. It will also discuss some of the present projects underway since the acquisition of ChemSpider by the Royal Society of Chemistry.
The authors of this technical note recently authored a chapter entitled “Applications of 15N NMR in Alkaloid Chemistry” for publication in Modern Alkaloids (Editors E. Fattorusso and O. Taglialatela-Scafati) to be published by Wiley in 2007. During the preparation of this article we took advantage of the opportunity to validate the performance of the ACD/NNMR predictor by applying it to the prediction of nitrogen chemical shifts associated with the diverse and challenging structures found in alkaloids. The results of this study are reported here.
The validation of the performance of a neural network based 13C NMR prediction algorithm using a test set available from an open source publicly available database, NMRShiftDB, is described. The validation was performed using a version of the database containing ca. 214,000 chemical shifts as well as for two subsets of the database to compare performance when overlap with the training set is taken into account. The first subset contained ca. 93,000 chemical shifts that were absent from the ACD\CNMR DB, the “excluded shift set” used for training of the neural network and the ACD\CNMR prediction algorithm, while the second contained ca. 121,000 shifts that were present in the ACD\CNMR DB training set, the “included shift set”. This work has shown that the mean error between experimental and predicted shifts for the entire database is 1.59 ppm, while the mean deviation for the subset with included shifts is 1.47 ppm and 1.74 ppm for excluded shifts. Since similar work has been reported online for another algorithm we compared the results with the errors determined using Robien’s CNMR Neural Network Predictor using the entire NMRShiftDB for program validation.
ChemSpider is a free access online database of over 26 million chemical compounds sourced from over 400 different sources including government laboratories, chemical vendors, public resources and publications. ChemSpider allows its users to deposit data including structures, properties, links to external resources and various forms of spectral data. ChemSpider has aggregated over 3000 high quality NMR spectra and continues to expand as the community deposits additional data. The majority of spectral data is licensed as Open Data allowing it to be downloaded and reused. The validation of the data can be performed by members of the community but an automated validation of the data was undertaken using ACD/Labs software using NMR prediction and verification routines. The dataset is a “real world” dataset containing the contributions of a number of laboratories around the world supplying data of varying quality including S/N issues, misreferencing, impurities etc. This work will report on the batch analysis of the ChemSpider spectral data including the identification of multiple errors in the spectra.
In previous work, we have presented several findings on the automated evaluation of chemical structures using 1H, 13C, and 2D NMR verification algorithms.These studies have shown that these systems have performed extremely well through numerous challenges.
The current study focuses not only on the performance of the verification algorithms but also on the automated preparation of experimental data through a blind test. This study was designed to prove that such a system would hold up in an industrial environment without any human intervention.
Fault detection of feed water treatment process using PCA-WD with parameter o...ISA Interchange
Feed water treatment process (FWTP) is an essential part of utility boilers; and fault detection is expected for its reliability improvement. Classical principal component analysis (PCA) has been applied to FWTPs in our previous work; however, the noises of T2 and SPE statistics result in false detections and missed detections. In this paper, Wavelet denoise (WD) is combined with PCA to form a new algorithm, (PCA- WD), where WD is intentionally employed to deal with the noises. The parameter selection of PCA-WD is further formulated as an optimization problem; and PSO is employed for optimization solution. A FWTP, sustaining two 1000 MW generation units in a coal-fired power plant, is taken as a study case. Its operation data is collected for following verification study. The results show that the optimized WD is effective to restrain the noises of T2 and SPE statistics, so as to improve the performance of PCA-WD algorithm. And, the parameter optimization enables PCA-WD to get its optimal parameters in an auto- matic way rather than on individual experience. The optimized PCA-WD is further compared with classical PCA and sliding window PCA (SWPCA), in terms of four cases as bias fault, drift fault, broken line fault and normal condition, respectively. The advantages of the optimized PCA-WD, against classical PCA and SWPCA, is finally convinced with the results.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
"Optimizing Drug Discovery (ADMET) using Machine Learning" involves leveraging advanced algorithms to enhance the drug development process. By analyzing Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) data with ML models, researchers can predict a drug candidate's properties, safety, and efficacy. This approach accelerates the identification of potential drugs, reduces costs, and minimizes the likelihood of late-stage failures. Machine learning aids in the selection of promising compounds, ultimately improving the efficiency and success of drug discovery, benefiting both pharmaceutical companies and patients by delivering safer and more effective medications.
The influence of data curation on QSAR Modeling – Presented at American Chemi...Kamel Mansouri
This presentation examined the impact of data quality on the construction of QSAR models being developed within the EPA‘s National Center for Computational Toxicology. We have developed a public-facing platform to provide access to predictive models. As part of the work we have attempted to disentangle the influence of the quality versus quantity of data available to develop and validate QSAR models. This abstract does not reflect U.S. EPA policy.
PerkinElmer: Whole Tablet Measurements Using the Frontier Tablet Autosampler ...PerkinElmer, Inc.
Recent advances in NIR technology have changed the ways in which both the pharmaceutical industry and the regulators view the current approaches to tablet testing in manufacturing.
Similar to NMR Prediction Accuracy Validation (20)
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
1. Technical Evaluation
NMR Prediction Accuracy Validation
ACD/CNMR Predictor
Version 10.05
Kirill Blinov, Mikhail Kvasha, Brent Lefebvre, Ryan Sasaki and Antony Williams
Advanced Chemistry Development, Inc.
Toronto, ON, Canada
www.acdlabs.com
Introduction
The validation of performance of NMR chemical shift prediction algorithms is a challenging problem for a
number of reasons. These will be discussed only at a general level in this technical evaluation since they
1
have been discussed elsewhere. The central challenge associated with the validation of NMR shift
prediction algorithms is obtaining a quality data set for validation of the prediction accuracy.
If the validation data set is mainly simple structures, or structures that are well represented in the database
used as the basis of the prediction algorithms then the validation exercise will not truly represent the
challenges of prediction. The most valid test would be conducted on a validation set containing chemical
structures which are very different from these contained within the training dataset. Ideally, an independent
party without knowledge of the structures in the training set should choose the validation set, so as to avoid
any bias.
The quality of a validation database is important but difficult to prove in most cases. The ideal validation set
does not contain any errors in assignment and covers the whole range of structural diversity available in
present chemistry and in all future diversity possibilities. While this is clearly impossible to attain, large
diverse datasets do exist and, while not ideal, can be used for the purpose of validation. Every large dataset
contains errors but for comparisons of prediction between different algorithms this is actually irrelevant since
any errors remain challenging for all algorithms.
A resource is available on the Internet that has met the above criteria of size and quality to serve as a fair
and reliable validation set to evaluate the performance of ACD/CNMR Predictor in terms of accuracy of NMR
2
prediction. This resource is a database called NMRShiftDB and is created as a collaborative effort by
chemists and spectroscopists submitting data to the database. This document is an analysis of the
performance of the ACD/CNMR predictor using the NMRSHIFTDB database as the validation set. Due to
the availability of a comparison test issued by Wolfgang Robien we also have an opportunity to compare
performance with another commercial product, NMR Predict provided by Modgraph Consultants, Ltd.
NMRShiftDB
The NMRShiftDB is an open source collection of chemical structures and their associated NMR shift
assignments. The database is generated as a result of contributions by the public and has been described
3,4 5
in detail elsewhere . Currently , the database contains 19,958 structures with 214,136 assigned carbon
chemical shifts. Based on a cursory examination of the structural diversity within the database these data
represent a statistically relevant set to use in an evaluation of predictive accuracy and is the first large
dataset available from an independent source which we could use for this purpose.
6
Robien has already published an analysis of performance of his neural network predictions . This review
provides an evaluation of the NMR prediction algorithms he has developed over many years. These
algorithms have been the basis of a number of software products including a commercially available
6
product, NMRPredict , offered by Modgraph Consultants, Ltd. Robien focused his analysis on the presence
of a number of outliers but gave no specific review of the quality of the dataset focusing only on the problem
assignments.
2. Technical Note
NMR Prediction Validation
The NMRShiftDB website offers visitors the opportunity to download a file in SDF format containing all of the
5
structures and chemical shifts that compose the NMRShiftDB database . This file was downloaded and the
structures and shifts were imported into an ACD/Labs’ format.
As a first step, an analysis of the degree of overlap between the structures in the training set within the
ACD/CNMR Predictor and the validation set of NMRShiftDB was undertaken. It was found that 57% of the
carbon chemical shifts in the NMRShiftDB were already in the ACD/Labs database. Using this information
the NMRShiftDB database was then stripped of these chemical shifts, since they have been used as the
basis of the prediction algorithms in ACD/CNMR Predictor. The statistics comparing the full dataset and the
validation subset are shown below.
Results Summary
As mentioned above, 2 sets of results were obtained. The average deviation of the predicted vs.
experimental values based on the entire data set, and the same statistics for the subset of chemical shifts
that were unique. ACD/CNMR Predictor significantly outperforms Robien’s program by a significant margin.
The average deviation obtained by CNMR Predictor was 40% lower than that obtained by Robien.
Validation on Entire Dataset
Average Standard Outliers (ppm Difference)
Entire Dataset Shift
Deviation Deviation
Comparison Count
(ppm)5 (ppm)5 >10 ppm >25 ppm >50 ppm
ACD/CNMR 1,040 141 31
214,136 1.59 2.76
v10.05 (0.5%) (0.07%) (0.01%)
CSEARCH 194 56
209,412 2.22 N/A N/A
(Modgraph) (0.09%) (0.03%)
Only 203,284 unique carbon centers were represented in the database but some had multiple assignments.
All redundancy was included in case there was disagreement between the assignments. And therefore over
214,000 assignments were considered. This is more than the number used by Robien and we assume this
to be due to the fact that we downloaded the data file later than Robien and new data had been added.
Robien used 209,412 chemical shifts. Consultation with Steinbeck indicates that some of the errors
identified by Robien in his analysis have been corrected. At present the original source file utilized by Robien
in his analysis is being sourced in order to allow a direct comparison of performance using the exact dataset
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and we will report on that comparison in a separate publication. The web posting of Robien did not provide
a measure of Standard Deviation or the number of chemical shift predictions that were more than 10 ppm
from their experimental value and this is the reason for the absence of this parameter in the table.
Note Robien quoted an Average Deviation of 2.19 PPM after correction of some errors, but for
comparison purposes, we have used the 2.22 PPM value with no corrections since no
corrections were made to dataset that was run through the CNMR Predictor.
Validation on Completely Novel Chemical Shifts
Obtaining a good result with the full dataset was a useful exercise yet a more rigorous comparison was
conducted. The data used to train ACD/Labs NMR prediction algorithms include those collected from recent
literature articles and an overlap with a significant number of structures in the NMRShiftDB was expected.
In order to compare the predictive accuracy of the algorithm and provide an estimate of the performance of
the predictors on novel structures, the NMRShiftDB was cross-referenced with the internal database of
ACD/CNMR Predictor to remove duplicate structures. This exercise revealed that 57% of the compounds in
the NMRShiftDB were also found in the ACD/Labs database. This left 43% of the compounds, a total of
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3. Technical Note
92,927 chemical shifts in NMRShiftDB to use as the dataset for the second validation study. The results are
shown below.
Average Standard Outliers (ppm Difference)
Dataset Shift
Deviation Deviation
Comparison Count
(ppm)5 (ppm)5 >10 ppm >25 ppm >50 ppm
695 89 24
Data Subset 92,927 1.74 3.22
(0.7%) (0.1%) (0.03%)
1,040 141 31
Entire Dataset 214,136 1.59 2.76
(0.5%) (0.07%) (0.01%)
The average deviation associated with the data subset has increased only slightly. The question as to
whether the comparison of different datasets leads to significant differences in performance has been
examined. The expectation would be that the correction of a few data points in a dataset of over 200,000
shifts would have a very small impact on the statistics presented in the table above. In fact, ignoring all data
points with an error of >25ppm reduces the average deviation to a value of 1.56ppm, a difference of
0.03ppm. Clearly the removal of a few points in error only makes a small difference to the overall statistics.
Conclusion
The NMRShiftDB is an excellent resource for the purpose of evaluating chemical shift prediction accuracy as
evidenced by this work and the previous work of Robien. As identified by Robien initially, and later in this
work, there are certainly outliers in the dataset requiring review and correction. Our previous work has
shown that the literature itself contains about 8% errors in the form of mis-assignments, transcription errors
and incorrect structures. The obvious errors in NMRShiftDB are certainly below this level and this is a
testament to the value of this resource. The NMRShiftDB dataset is large and structurally diverse and
continues to grow as scientists contribute.
Despite a large overlap between the NMRShiftDB and the ACD/Labs carbon NMR database, a statistically
relevant validation set of over 92,000 chemicals shifts was extracted from the NMRShiftDB and used to test
the algorithms. The data presented here shows that the ACD/Labs prediction algorithms have an average
deviation of less than 1.8 ppm on the validation set and significantly outperforms the algorithms of Robien
presented in his review. This work will be discussed in further detail in a future publication and validation is
presently being performed on the proton NMR shift data.
Acknowledgements
We thank Christoph Steinbeck and the members of his team for the provision of the NMRShiftDB service
and dataset. This has provided and invaluable resource for the testing of NMR prediction algorithms.
References
1. Jens Meiler et al, J. Magn. Res., 157, 242–252 (2002).
2. NMRShiftDB, http://nmrshiftdb.ice.mpg.de/
3. C. Steinbeck, S. Krause, and S. Kuhn, J. Chem. Inf. Comput. Sci. 43, 1733-1739 (2003)
4. C. Steinbeck and S. Kuhn, Phytochemistry 65, 2711–2717 (2004)
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5. Information available on NMRShiftDB as of May 7 , 2007.
6. http://nmrpredict.orc.univie.ac.at/csearchlite/enjoy_its_free.html
7. http://www.modgraph.co.uk/product_nmr.htm
8. http://nmrshiftdb.pharmazie.uni-marburg.de/nmrshiftdbhtml/NmrshiftdbWithSignals.sdf.zip
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