Deep learning @ Edge using Intel's Neural Compute Stickgeetachauhan
Talk @ Intel Global IoT DevFest, Nov 2017
The new generation of hardware accelerators are enabling rich AI driven, Intelligent IoT solutions @ the edge.
The talk showcased how to use Intel's latest Nervana Compute Stick for accelerating deep learning IoT solutions. It also covered use cases and code details for running Deep Learning models on Intel's Nervana Compute Stick.
LEGaTO poster presented by Omar ali at ACACES 2019 (Summer School on Advanced Computer Architecture and Compilation for High-performance Embedded Systems).
Secure Cloud - Secure Big Data Processing in Untrusted CloudsEUBrasilCloudFORUM .
Congresso Sociedade Brasileira de Computação CSBC2016 Porto Alegre (Brazil)
Workshop on Cloud Networks & Cloudscape Brazil
SecureCloud | Andrey Brito, Federal University of Campina Grande, Brazil
Funded jointly by the European Commission (EC) and the Ministry of Science, Technology and Innovation; Portuguese: Ministério da Ciência, Tecnologia e Inovação (MCTI) of Brazil, the EUBrasilCloudFORUM project supports EU-BR collaborative projects in the collection and promotion of their results and activities. The results will be used to draft a research Roadmap on cloud computing, identifying collaboration needs and opportunities between Europe and Brazil for the European Commission and to MCTI, thus contributing to the definition of future cooperation priorities between the two regions.
8 th International Conference on Advances in Computer Science and Information...ijcseit
8
th International Conference on Advances in Computer Science and Information Technology
(ACSTY 2022) will provide an excellent international forum for sharing knowledge and results in
theory, methodology and applications of Computer Science, Engineering and Information
Technology. The conference looks for significant contributions to all major fields of the Computer
Science, Engineering and Information Technology in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the following areas, but are not limited to.
An introductory project in the domain Wireless Sensor Network.
A system which can communicate from one remote location to another using radio frequency, no need of Internet connectivity and bluetooth.
Deep learning @ Edge using Intel's Neural Compute Stickgeetachauhan
Talk @ Intel Global IoT DevFest, Nov 2017
The new generation of hardware accelerators are enabling rich AI driven, Intelligent IoT solutions @ the edge.
The talk showcased how to use Intel's latest Nervana Compute Stick for accelerating deep learning IoT solutions. It also covered use cases and code details for running Deep Learning models on Intel's Nervana Compute Stick.
LEGaTO poster presented by Omar ali at ACACES 2019 (Summer School on Advanced Computer Architecture and Compilation for High-performance Embedded Systems).
Secure Cloud - Secure Big Data Processing in Untrusted CloudsEUBrasilCloudFORUM .
Congresso Sociedade Brasileira de Computação CSBC2016 Porto Alegre (Brazil)
Workshop on Cloud Networks & Cloudscape Brazil
SecureCloud | Andrey Brito, Federal University of Campina Grande, Brazil
Funded jointly by the European Commission (EC) and the Ministry of Science, Technology and Innovation; Portuguese: Ministério da Ciência, Tecnologia e Inovação (MCTI) of Brazil, the EUBrasilCloudFORUM project supports EU-BR collaborative projects in the collection and promotion of their results and activities. The results will be used to draft a research Roadmap on cloud computing, identifying collaboration needs and opportunities between Europe and Brazil for the European Commission and to MCTI, thus contributing to the definition of future cooperation priorities between the two regions.
8 th International Conference on Advances in Computer Science and Information...ijcseit
8
th International Conference on Advances in Computer Science and Information Technology
(ACSTY 2022) will provide an excellent international forum for sharing knowledge and results in
theory, methodology and applications of Computer Science, Engineering and Information
Technology. The conference looks for significant contributions to all major fields of the Computer
Science, Engineering and Information Technology in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the following areas, but are not limited to.
An introductory project in the domain Wireless Sensor Network.
A system which can communicate from one remote location to another using radio frequency, no need of Internet connectivity and bluetooth.
8th International conference on Advanced Computing (ADCOM 2022)ijasuc
8th International conference on Advanced Computing (ADCOM 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference focuses on all technical and practical aspects of high performance computing, green computing, pervasive computing, cloud computing etc.
Anomaly Detection using Deep Auto-Encoders | Gianmario SpacagnaData Science Milan
One of the determinants for a good anomaly detector is finding smart data representations that can easily evince deviations from the normal distribution. Traditional supervised approaches would require a strong assumption about what is normal and what not plus a non negligible effort in labeling the training dataset. Deep auto-encoders work very well in learning high-level abstractions and non-linear relationships of the data without requiring data labels. In this talk we will review a few popular techniques used in shallow machine learning and propose two semi-supervised approaches for novelty detection: one based on reconstruction error and another based on lower-dimensional feature compression.
OCRE Workshop: Shaping the Earth Observation Services Market for Research. Session 3: Presentations from DIAS and eoMALL.
This workshop aims to bring the EO service providers closer to the research community, capture their needs and develop fit for purpose EO services.
The event will be the 4th OCRE Requirements Gathering Workshop. Researchers and Earth Observation Service Providers will be asked to provide inputs to help us shape OCRE's tender.
The OCRE project aims to provide the first end-to-end instance of organised, large-scale market pull for EO services in Europe. These services will be provided for free to EU researchers through the European Open Science Cloud. To ensure that the services meet the actual needs of the research community we invite both the demand and the supply side, to share their views and engage in a productive dialogue. Our aim is to capture the needs of EU researchers and inform the EO service providers so that they make available services that effectively address them. We will also explain how the OCRE process will work, how the different stakeholders should be involved and how to make the most of the foreseen benefits.
"How Pirelli uses Domino and Plotly for Smart Manufacturing" by Alberto Arrig...Data Science Milan
"How Pirelli uses Domino and Plotly for Smart Manufacturing" by Alberto Arrigoni, Senior Data Scientist, Pirelli (pirelli.com)
Abstract:
Pirelli, a global performance tire manufacturer, uses data science in its 20 factories to improve quality and efficiency, and reduce energy consumption. For this “Smart Manufacturing” initiative, Pirelli’s data science team has developed predictive models and analytics tools to monitor processes, machines and materials on the factory floors. In this talk we will show some of the solutions we deploy, demonstrate how we used Domino’s data science platform and Plot.ly to build these solutions, and discuss the next steps in this journey towards predictive maintenance.
Bio:
Alberto Arrigoni is a data scientist at Pirelli, where he works to process sensors and telemetry data for IoT, Smart Factories and connected-vehicle applications.
He works closely with all major business units such as R&D, industrial engineering and BI to develop tailored machine learning algorithms and production systems.
He holds a PhD in biostatistics from the University of Milan Bicocca and prior to joining Pirelli was a staff data scientist at the National Institute of Molecular Genetics (Milan), as well as a Fulbright student at the Santa Clara University and visiting PhD student at Pacific Biosciences (Menlo Park, CA).
Best Practices for On-Demand HPC in Enterprisesgeetachauhan
Traditionally HPC has been popular in Scientific domains, but not in most other Enterprises. With the advent of on-demand-HPC in cloud and growing adoption of Deep Learning, HPC should now be a standard platform for any Enterprise leading with AI and Machine Learning. This session will cover the best practices for building your own on-demand HPC cluster for Enterprise workloads along with key use cases where Enterprises will benefit from HPC solution.
The main goal of the SecureCloud project is to enable novel big-data applications that can use sensitive data in the cloud without compromising data security and privacy.
Presentation by Philippe O.A. Navaux, professor at the Universidade Federal of Rio Grande do Sul and Computer Science Area Director of CAPES at Cloudscape Brazil 2017 & WCN 2017
10th International Conference of Advanced Computer Science & Information Tech...IJCSEA Journal
10th International Conference of Advanced Computer Science & Information Technology
(ACSIT 2022) will act as a major forum for the presentation of innovative ideas, approaches,
developments, and research projects in the area advanced Computer Science and information
technology. It will also serve to facilitate the exchange of information between researchers and
industry professionals to discuss the latest issues and advancement in the area of advanced CS & IT.
Core areas of advanced IT and multi-disciplinary and its applications will be covered during the
conferences.
Master's degree thesis testing algorithms for image & video understandingEnrico Busto
In the last few years, many algorithms with remarkable effectiveness for Object Detection have been published but still some comparative metrics haven’t been defined.
The difficulties in making this comparison arise from the fact that different algorithms are based on different Feature Extractors (VGGs, Residual Networks, etc.), different base resolution and different implementation on specific platforms.
VEDLIOT – Accelerated AIoT. Jens Hagemeyer. 2nd Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2023, Toulouse, France, January 2023
8th International conference on Advanced Computing (ADCOM 2022)ijasuc
8th International conference on Advanced Computing (ADCOM 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference focuses on all technical and practical aspects of high performance computing, green computing, pervasive computing, cloud computing etc.
Anomaly Detection using Deep Auto-Encoders | Gianmario SpacagnaData Science Milan
One of the determinants for a good anomaly detector is finding smart data representations that can easily evince deviations from the normal distribution. Traditional supervised approaches would require a strong assumption about what is normal and what not plus a non negligible effort in labeling the training dataset. Deep auto-encoders work very well in learning high-level abstractions and non-linear relationships of the data without requiring data labels. In this talk we will review a few popular techniques used in shallow machine learning and propose two semi-supervised approaches for novelty detection: one based on reconstruction error and another based on lower-dimensional feature compression.
OCRE Workshop: Shaping the Earth Observation Services Market for Research. Session 3: Presentations from DIAS and eoMALL.
This workshop aims to bring the EO service providers closer to the research community, capture their needs and develop fit for purpose EO services.
The event will be the 4th OCRE Requirements Gathering Workshop. Researchers and Earth Observation Service Providers will be asked to provide inputs to help us shape OCRE's tender.
The OCRE project aims to provide the first end-to-end instance of organised, large-scale market pull for EO services in Europe. These services will be provided for free to EU researchers through the European Open Science Cloud. To ensure that the services meet the actual needs of the research community we invite both the demand and the supply side, to share their views and engage in a productive dialogue. Our aim is to capture the needs of EU researchers and inform the EO service providers so that they make available services that effectively address them. We will also explain how the OCRE process will work, how the different stakeholders should be involved and how to make the most of the foreseen benefits.
"How Pirelli uses Domino and Plotly for Smart Manufacturing" by Alberto Arrig...Data Science Milan
"How Pirelli uses Domino and Plotly for Smart Manufacturing" by Alberto Arrigoni, Senior Data Scientist, Pirelli (pirelli.com)
Abstract:
Pirelli, a global performance tire manufacturer, uses data science in its 20 factories to improve quality and efficiency, and reduce energy consumption. For this “Smart Manufacturing” initiative, Pirelli’s data science team has developed predictive models and analytics tools to monitor processes, machines and materials on the factory floors. In this talk we will show some of the solutions we deploy, demonstrate how we used Domino’s data science platform and Plot.ly to build these solutions, and discuss the next steps in this journey towards predictive maintenance.
Bio:
Alberto Arrigoni is a data scientist at Pirelli, where he works to process sensors and telemetry data for IoT, Smart Factories and connected-vehicle applications.
He works closely with all major business units such as R&D, industrial engineering and BI to develop tailored machine learning algorithms and production systems.
He holds a PhD in biostatistics from the University of Milan Bicocca and prior to joining Pirelli was a staff data scientist at the National Institute of Molecular Genetics (Milan), as well as a Fulbright student at the Santa Clara University and visiting PhD student at Pacific Biosciences (Menlo Park, CA).
Best Practices for On-Demand HPC in Enterprisesgeetachauhan
Traditionally HPC has been popular in Scientific domains, but not in most other Enterprises. With the advent of on-demand-HPC in cloud and growing adoption of Deep Learning, HPC should now be a standard platform for any Enterprise leading with AI and Machine Learning. This session will cover the best practices for building your own on-demand HPC cluster for Enterprise workloads along with key use cases where Enterprises will benefit from HPC solution.
The main goal of the SecureCloud project is to enable novel big-data applications that can use sensitive data in the cloud without compromising data security and privacy.
Presentation by Philippe O.A. Navaux, professor at the Universidade Federal of Rio Grande do Sul and Computer Science Area Director of CAPES at Cloudscape Brazil 2017 & WCN 2017
10th International Conference of Advanced Computer Science & Information Tech...IJCSEA Journal
10th International Conference of Advanced Computer Science & Information Technology
(ACSIT 2022) will act as a major forum for the presentation of innovative ideas, approaches,
developments, and research projects in the area advanced Computer Science and information
technology. It will also serve to facilitate the exchange of information between researchers and
industry professionals to discuss the latest issues and advancement in the area of advanced CS & IT.
Core areas of advanced IT and multi-disciplinary and its applications will be covered during the
conferences.
Master's degree thesis testing algorithms for image & video understandingEnrico Busto
In the last few years, many algorithms with remarkable effectiveness for Object Detection have been published but still some comparative metrics haven’t been defined.
The difficulties in making this comparison arise from the fact that different algorithms are based on different Feature Extractors (VGGs, Residual Networks, etc.), different base resolution and different implementation on specific platforms.
VEDLIOT – Accelerated AIoT. Jens Hagemeyer. 2nd Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2023, Toulouse, France, January 2023
How Can AI and IoT Power the Chemical Industry?Xiaonan Wang
AI, IoT and Blockchain tech briefing to the industry to showcase our research at NUS.
by Dr. Xiaonan Wang
Assistant Professor
NUS Department of Chemical & Biomolecular Engineering
AccML, co-located with HiPEAC 2021_Pedro Trancoso presentationVEDLIoT Project
Project Summary
The ever increasing performance of computer systems in general and IoT systems, in particular, delivers the capability to solve increasingly challenging problems, pushing automation to improve the quality of our life. This triggers the need for a next-generation IoT architecture, satisfying the demand for key sectors like transportation (e.g. self-driving cars), industry (e.g. robotization or predictive maintenance), and our homes (e.g. assisted living). Such applications require building systems of enormous complexity, so that traditional approaches start to fail. The amount of data collected and processed is huge, the computational power required is very high, and the algorithms are too complex allowing for the computation of solutions within the tight time constraints. In addition, security, privacy, or robustness for such systems becomes a critical challenge.
TANGO Project is a new initiative undartaken by a group of european organizations and institutions to fullfil one purpose: Simplify the way developers approach the development of next-generation applications based in heterogeneous hardware architectures, configurations and software systems including heterogeneous clusters, chips and programmable logic devices.
HiPEAC 2020: Energy-aware Task Scheduling in LEGaTO: Low Energy Toolset for H...LEGATO project
Approach:
-Starting with Made-in-Europe mature software stack, and
optimizing this stack to support energy-efficiency
-Integrated software stack supporting task-based programming model
-Computing on a commercial cutting-edge European-developed
CPU–GPU–FPGA heterogeneous hardware substrate and FPGA-based Dataflow Engines (DFE)
-Three use-cases (Smart home/city, AI, health) to test
the integrated stack
TANGO Project is a new initiative undartaken by a group of european organizations and institutions to fullfil one purpose: Simplify the way developers approach the development of next-generation applications based in heterogeneous hardware architectures, configurations and software systems including heterogeneous clusters, chips and programmable logic devices.
Scrooge Attack: Undervolting ARM Processors for ProfitLEGATO project
Malicious cloud provider can intentionally undervolt cloud infrastructure for additional savings on the electricity bill. ARM processors are low power processors which can lead to substantial energy saving for cloud providers. In our scenario we consider a scrooge cloud provider which undervolts its ARM
infrastructure for profit. The instances can be undervolted in a stealthy manner by avoiding critical voltage regions.
Applications running under critical undervolting conditions can
malfunction. These conditions can be exploited by a cloud user to uncover the undervolted instances. For this novel attack scenario we present a detection method for cloud users. The detection method injects non-selectively faults into processes with the intend to crash the cloud instance. Even if the cloud
provider can spoof temperature and voltage readings of the processor, the cloud user is capable to uncover undervolted instances. By crashing instances simultaneously using the detection method, the cloud user is covered by the service licence agreement and exposes the scrooge cloud provider.
TEEMon: A continuous performance monitoring framework for TEEsLEGATO project
LEGaTO paper presented at ACM Middleware 2020 by Robert Krahn, Donald Dragoti, Franz Gregor, Do Le Quoc, Valerio Schiavoni, Pascal Felber, Clenimar Souza, Andrey Brito and Christof Fetzer
LEGaTO: Low-Energy Heterogeneous Computing Use of AI in the projectLEGATO project
Presentation by Osman Unsal and Pirah Noor Soomro at the webinar AI4EU WebCafé: 'Energy-efficient AI, a perspective from the LEGaTO project' on 28 October 2020
Presentation given by Jens Hagemeyer (Bielefeld University) at the ‘Low-Energy Heterogeneous Computing Workshop’ on 16 October 2020 within HiPEAC CSW Autumn 2020
TZ4Fabric: Executing Smart Contracts with ARM TrustZoneLEGATO project
Paper presented by Christian Göttel at SRDS'20.
Abstract: Transparency in blockchains can be an advantage and a disadvantage, in particular if confidential information such as assets or business interactions are exposed. There are no confidentiality guarantees in blockchain systems to protect the logic of a smart contract or the data it processes. One solution to this problem can be trusted execution environments (TEE) which are an emerging technology for example available in edge or mobile-grade processors (e.g., ARM TrustZone) or in server-grade processors (e.g., Intel SGX). In this presentation we introduce TZ4Fabric, an extension of Hyperledger Fabric which leverages ARM TrustZone to shield the execution of smart contracts from compromised systems and powerful attackers. TZ4Fabric exploits the open source OP-TEE framework to enable ARM TrustZone features. We evaluate our prototype on the Raspberry Pi platform and highlight energy and performance trade-offs.
Infection Research with Maxeler Dataflow ComputingLEGATO project
Presentation given by Tobias Becker (Maxeler) at the LEGaTO Final Event: Low-Energy Heterogeneous Computing Workshop on 4 September 2020
This event was collocated with FPL 2020
Presentation given by Nils Kucza (Bielefeld University) at the LEGaTO Final Event: Low-Energy Heterogeneous Computing Workshop on 4 September 2020
This event was collocated with FPL 2020
FPGA Undervolting and Checkpointing for Energy-Efficiency and Error-ResiliencyLEGATO project
Tutorial by Behzad Salami, Osman Unsal and Leonardo Bautista at 30th International Conference on Field-Programmable Logic and Applications (FPL2020), 3 September 2020
Scheduling Task-parallel Applications in Dynamically Asymmetric EnvironmentsLEGATO project
Presentation by Jing Chen and Pirah Noor Soomro (Chalmers University of Technology) at the 16th International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems (SRMPDS 2020) on 17 August 2020.
SRMPDS was a virtual event and collocated with ICPP’20 - 2020 International Conference on Parallel Processing.
RECS – Cloud to Edge Microserver Platform for Energy-Efficient ComputingLEGATO project
Abstract:Today, application developers and data center operators face the challenging task to achieve high performance while at the same time needing to reduce the total cost of ownership, which is especially driven by the energy consumption of the server itself.
This poster shows the RECS Microserver platform, developed by Christmann and Bielefeld University. RECS simplifies the combined use of heterogeneous target architectures to achieve high performance and superior energy-efficiency.
Poster presented by Martin Kaiser at the LEGaTO Final Event: 'Low-Energy Heterogeneous Computing Workshop'
HiPerMAb: A statistical tool for judging the potential of short fat dataLEGATO project
Abstract: Common statistical approaches are not designed to deal with so-called “short fat data” in biomarker pilot studies, where the number of biomarker candidates exceeds the sample size by magnitudes. Because of the high cost and long time to collect and prepare the data in this type of study, researchers prefer to check the potential of the large set of biomarker candidates in a small pilot study.
The aim of the pilot study is to answer the question whether it is worthwhile to extend the study to a larger study and to obtain information about the required sample size. HiPerMAb tool is proposed as method to judge the potential in a small biomarker pilot study without the need to explicitly identifying and confirming a specific subset of biomarkers. It allows to evaluate pilot studies based on performance measures like multiclass AUC, entropy, area above the cost curve, hypervolume under manifold and misclassification rate. Entropy is a useful tool in machine learning and became one of the most exciting developments in biology today. However, it has no closed form solution like area under the ROC curve (AUC) to estimate the required p-values for HiPerMAb. The possible solution is the simulations, Monte Carlo simulations, and with such number of biomarker candidates in such studies the number of simulation become significantly large, computational cost, and energy consuming. By using Maxeller DFE on Jülich testbed, we are able to look at study with more than 50,000 biomarkers so we need to estimate a probability smaller than 1/50000, which means we need to run up to 50 million simulations. Then number of “good” biomarker candidates is compared to the expected number of “good” biomarker candidates in a dataset with no association to the considered disease states to judge if the study is worthy to be extended with appropriate sample size to find and evaluate a final combination of biomarkers with high predictive value.
Poster presented by Amani Al-Mekhlafi at the LEGaTO Final Event: 'Low-Energy Heterogeneous Computing Workshop'
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
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 .
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.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
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THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Predicting property prices with machine learning algorithms.pdf
Secure Task-Based Programming with OmpSs and SGX
1. The LEGaTO project has received funding from the European Union’s Horizon 2020 research and innovation
programme under the grant agreement No 780681. This work has been supported by the Ministry of Science
and Innovation, under the project "Computación de Altas Prestaciones VIII" (PID2019-107255GB).
www.legato-project.eu
• E3-1275 CPU with 8 cores
• Intel SGX SDK version 2.8
Isabelly Rocha1, Marcelo Pasin1, Valerio Schiavoni1, Pascal Felber1,
Xavier Martorell2,3, Osman Unsal2
1University of Neuchâtel, 2Barcelona Supercomputing Center, 3Universitat Politècnica de Catalunya
Secure Task-Based Programming with OmpSs and SGX
OmpSs Programming Model Intel Software Guard Extensions (SGX)+
Goals
Matrix MultiplicationDot Product
STREAM Benchmark*
Evaluation Settings
Applications
Asynchronous
Parallelism
Hardware
Heterogeneity
Secure
Computation
Microbenchmarks
Note: Solid and dashed bars correspond to runtime and energy, respectively.
OS (Linux) + SGX SDK
OmpSs@SGX
Application
Programmer adapts
tasks to SGX
(with calls to Nanos++ runtime)
Source Code
+
Annotations
Mercurium
Compiler
External Kernals
1
2
Create Enclave
CallTrusted()
Untrusted
Environment
Trusted
Environment
Process
Secrets
3
4
Cont.
Return
OmpSs
DFiant HDL
SGX Compiler
MaxJ
CUDA
Enclave
Kernals
GCC
Nanos Enclave
Support
SMP
OmpSs.elf
Oriented to shared memory
environments, with a runtime that
leverages low-level APIs and
manages data dependencies
Security-related instruction codes
that are built into some modern Intel
central processing units (CPUs)
Support task parallelism and heterogeneity
under secure mechanisms
Approach
Evaluate performance and energy impacts of
our approach under different task-related
configurations: input and graph size, number
of threads and scheduling algorithm
1
2
*measures sustainable memory bandwidth and the
corresponding computation rate for vector kernels
0
0.5
1
1.5
2
2.5
3
small medium large
Tasks Graph Size Energy and Performance Impact
RatioSGXtoNonSGX
Tasks Graph Size
matmul dot-prod stream
0
2
4
6
8
10
12
small medium large
Tasks Input Size Energy and Performance Impact
RatioSGXtoNonSGX
Tasks Input Size
matmul dot-prod stream
0
0.5
1
1.5
2
2.5
3
Breadth First Work First
Scheduler Energy and Performance Impact
RatioSGXtoNonSGX
Scheduler
matmul dot-prod stream
0
0.5
1
1.5
2
2.5
3
3.5
1 2 4 8
Number of Threads Energy and Performance Impact
RatioSGXtoNonSGX
matmul dot-prod stream