What do you give for free to your competitor when you ex-
hibit a product line? This paper addresses this question
through several cases in which the discovery of trade secrets
of a product line is possible and can lead to severe conse-
quences. That is, we show that an outsider can understand
the variability realization and gain either confidential busi-
ness information or even some economical direct advantage.
For instance, an attacker can identify hidden constraints and
bypass the product line to get access to features or copy-
righted data. This paper warns against possible naive mod-
eling, implementation, and testing of variability leading to
the existence of product lines that jeopardize their trade se-
crets. Our vision is that defensive methods and techniques
should be developed to protect specifically variability – or
at least further complicate the task of reverse engineering it.
Many real-world product lines are only represented as non-hierarchical collections of distinct products, described by their configuration values. As the manual preparation of feature models is a tedious and labour-intensive activity, some techniques have been proposed to automatically generate boolean feature models from product descriptions. However , none of these techniques is capable of synthesizing feature attributes and relations among attributes, despite the huge relevance of attributes for documenting software product lines. In this paper, we introduce for the first time an algorithmic and parametrizable approach for computing a legal and appropriate hierarchy of features, including feature groups, typed feature attributes, domain values and relations among these attributes. We have performed an empirical evaluation by using both randomized configuration matrices and real-world examples. The initial results of our evaluation show that our approach can scale up to matrices containing 2,000 attributed features, and 200,000 distinct configurations in a couple of minutes.
Paper has been presented at SPLC'15 (Nashville, USA)
The use of Feature Models (FMs) to define the valid combinations of features in Software Product Lines (SPL) is becoming commonplace.
To enhance the scalability of FMs, support for composing FMs
describing different SPL aspects is needed.
Some composition operators, with interesting property preservation
capabilities, have already been defined but a comprehensive and efficient implementation is still to be proposed.
In this paper, we systematically compare strengths and weaknesses of different
implementation approaches.
The study provides some evidence that using generic model
composition frameworks are not helping much in the
realization, whereas a specific solution is finally necessary and clearly stands out by its qualities.
Software Product Line (SPL) engineering is a paradigm shift towards modeling and developing software system families rather than individual systems. It focuses on the means of efficiently producing and maintaining multiple similar software products, exploiting what they have in common and managing what varies among them. This is analogous to what is practiced in the automotive industry, where the focus is on creating a single production line, out of which many customized but similar variations of a car model are produced. Feature models (FMs) are a fundamental formalism for specifying and reasoning about commonality and variability of SPLs. FMs are becoming increasingly complex, handled by several stakeholders or organizations, used to describe features at various levels of abstraction and related in a variety of ways. In different contexts and application domains, maintaining a single large FM is neither feasible nor desirable. Instead, multiple FMs are now used. In this thesis, we develop theoretical foundations and practical support for managing multiple FMs. We design and develop a set of composition and decomposition operators (aggregate, merge, slice) for supporting separation of concerns. The operators are formally defined, implemented with a fully automated algorithm and guarantee properties in terms of sets of configurations. We show how the composition and decomposition operators can be combined together or with other reasoning and editing operators to realize complex tasks. We propose a textual language, FAMILIAR (for FeAture Model scrIpt Language for manIpulation and Automatic Reasoning), which provides a practical solution for managing FMs on a large scale. An SPL practitioner can combine the different operators and manipulate a restricted set of concepts (FMs, features, configurations, etc.) using a concise notation and language facilities. FAMILIAR hides implementation details (e.g., solvers) and comes with a development environment. We report various applications of the operators and usages of FAMILIAR in different domains (medical imaging, video surveillance) and for different purposes (scientific workflow design, variability modeling from requirements to runtime, reverse engineering), showing the applicability of both the operators and the supporting language. Without the new capabilities brought by the operators and FAMILIAR, some analysis and reasoning operations would not be made possible in the different case studies. To conclude, we discuss different research perspectives in the medium term (regarding the operators, the language and validation elements) and in the long term (e.g., relationships between FMs and other models).
Variability is omnipresent in numerous kinds of artefacts (e.g., source code, product matrices) and in different shapes (e.g., conditional compilation, differences among product descriptions). For understanding, reasoning about, maintaining or evolving variability, practitioners usually need an explicit encoding of variability (ie a variability model). As a result, numerous techniques have been developed to reverse engineer variability (e.g., through the mining of features and constraints from source code) or for migrating a set of products as a variability system. In this talk we will first present tool-supported techniques for synthesizing variability models from constraints or product descriptions.
Practitioners can build Boolean feature models with an interactive environment for selecting a meaningful and sound hierarchy.
Attributes can also be synthesized for encoding numerical values and constraints among them.
We will present key results we obtain through experiments with the SPLOT repository and product comparison matrices coming from Wikipedia and BestBuy.
Finally we will introduce OpenCompare.org a recent initiative for editing, reasoning, and mining product comparison matrices.
This talk has been done at REVE'15 workshop co-located with SPLC'15 (software product line conference): http://www.isse.jku.at/reve2015/program.html
Product Derivation is a key activity in Software Product Line Engineering. During this process, derivation operators modify or create core assets (e.g., model elements, source code instructions, components) by adding, removing or substituting them according to a given configuration. The result is a derived product that generally needs to conform to a programming or modeling language. Some operators lead to invalid products when applied to certain assets, some others do not; knowing this in advance can help to better use them, however this is challenging, specially if we consider assets expressed in extensive and complex languages such as Java. In this paper, we empirically answer the following question: which product line operators, applied to which program elements, can synthesize variants of programs that are incorrect, correct or perhaps even conforming to test suites? We implement source code transformations, based on the derivation operators of the Common Variability Language. We automatically synthesize more than 370,000 program variants from a set of 8 real large Java projects (up to 85,000 lines of code), obtaining an extensive panorama of the sanity of the operations.
Paper was presented at SPLC'15
Product comparison matrices (PCMs) provide a
convenient way to document the discriminant features of a family of related products and now abound on the internet. Despite their apparent simplicity, the information present in existing PCMs can be very heterogeneous, partial, ambiguous, hard to exploit by users who desire to choose an appropriate product. Variability Models (VMs) can be employed to formulate in a more precise way the semantics of PCMs and enable automated reasoning such as assisted configuration. Yet, the gap between PCMs and VMs should be precisely understood and automated techniques should support the transition between the two. In this paper, we propose
variability patterns that describe PCMs content and conduct an empirical analysis of 300+ PCMs mined from Wikipedia. Our findings are a first step toward better engineering techniques for maintaining and configuring PCMs.
Many real-world product lines are only represented as non-hierarchical collections of distinct products, described by their configuration values. As the manual preparation of feature models is a tedious and labour-intensive activity, some techniques have been proposed to automatically generate boolean feature models from product descriptions. However , none of these techniques is capable of synthesizing feature attributes and relations among attributes, despite the huge relevance of attributes for documenting software product lines. In this paper, we introduce for the first time an algorithmic and parametrizable approach for computing a legal and appropriate hierarchy of features, including feature groups, typed feature attributes, domain values and relations among these attributes. We have performed an empirical evaluation by using both randomized configuration matrices and real-world examples. The initial results of our evaluation show that our approach can scale up to matrices containing 2,000 attributed features, and 200,000 distinct configurations in a couple of minutes.
Paper has been presented at SPLC'15 (Nashville, USA)
The use of Feature Models (FMs) to define the valid combinations of features in Software Product Lines (SPL) is becoming commonplace.
To enhance the scalability of FMs, support for composing FMs
describing different SPL aspects is needed.
Some composition operators, with interesting property preservation
capabilities, have already been defined but a comprehensive and efficient implementation is still to be proposed.
In this paper, we systematically compare strengths and weaknesses of different
implementation approaches.
The study provides some evidence that using generic model
composition frameworks are not helping much in the
realization, whereas a specific solution is finally necessary and clearly stands out by its qualities.
Software Product Line (SPL) engineering is a paradigm shift towards modeling and developing software system families rather than individual systems. It focuses on the means of efficiently producing and maintaining multiple similar software products, exploiting what they have in common and managing what varies among them. This is analogous to what is practiced in the automotive industry, where the focus is on creating a single production line, out of which many customized but similar variations of a car model are produced. Feature models (FMs) are a fundamental formalism for specifying and reasoning about commonality and variability of SPLs. FMs are becoming increasingly complex, handled by several stakeholders or organizations, used to describe features at various levels of abstraction and related in a variety of ways. In different contexts and application domains, maintaining a single large FM is neither feasible nor desirable. Instead, multiple FMs are now used. In this thesis, we develop theoretical foundations and practical support for managing multiple FMs. We design and develop a set of composition and decomposition operators (aggregate, merge, slice) for supporting separation of concerns. The operators are formally defined, implemented with a fully automated algorithm and guarantee properties in terms of sets of configurations. We show how the composition and decomposition operators can be combined together or with other reasoning and editing operators to realize complex tasks. We propose a textual language, FAMILIAR (for FeAture Model scrIpt Language for manIpulation and Automatic Reasoning), which provides a practical solution for managing FMs on a large scale. An SPL practitioner can combine the different operators and manipulate a restricted set of concepts (FMs, features, configurations, etc.) using a concise notation and language facilities. FAMILIAR hides implementation details (e.g., solvers) and comes with a development environment. We report various applications of the operators and usages of FAMILIAR in different domains (medical imaging, video surveillance) and for different purposes (scientific workflow design, variability modeling from requirements to runtime, reverse engineering), showing the applicability of both the operators and the supporting language. Without the new capabilities brought by the operators and FAMILIAR, some analysis and reasoning operations would not be made possible in the different case studies. To conclude, we discuss different research perspectives in the medium term (regarding the operators, the language and validation elements) and in the long term (e.g., relationships between FMs and other models).
Variability is omnipresent in numerous kinds of artefacts (e.g., source code, product matrices) and in different shapes (e.g., conditional compilation, differences among product descriptions). For understanding, reasoning about, maintaining or evolving variability, practitioners usually need an explicit encoding of variability (ie a variability model). As a result, numerous techniques have been developed to reverse engineer variability (e.g., through the mining of features and constraints from source code) or for migrating a set of products as a variability system. In this talk we will first present tool-supported techniques for synthesizing variability models from constraints or product descriptions.
Practitioners can build Boolean feature models with an interactive environment for selecting a meaningful and sound hierarchy.
Attributes can also be synthesized for encoding numerical values and constraints among them.
We will present key results we obtain through experiments with the SPLOT repository and product comparison matrices coming from Wikipedia and BestBuy.
Finally we will introduce OpenCompare.org a recent initiative for editing, reasoning, and mining product comparison matrices.
This talk has been done at REVE'15 workshop co-located with SPLC'15 (software product line conference): http://www.isse.jku.at/reve2015/program.html
Product Derivation is a key activity in Software Product Line Engineering. During this process, derivation operators modify or create core assets (e.g., model elements, source code instructions, components) by adding, removing or substituting them according to a given configuration. The result is a derived product that generally needs to conform to a programming or modeling language. Some operators lead to invalid products when applied to certain assets, some others do not; knowing this in advance can help to better use them, however this is challenging, specially if we consider assets expressed in extensive and complex languages such as Java. In this paper, we empirically answer the following question: which product line operators, applied to which program elements, can synthesize variants of programs that are incorrect, correct or perhaps even conforming to test suites? We implement source code transformations, based on the derivation operators of the Common Variability Language. We automatically synthesize more than 370,000 program variants from a set of 8 real large Java projects (up to 85,000 lines of code), obtaining an extensive panorama of the sanity of the operations.
Paper was presented at SPLC'15
Product comparison matrices (PCMs) provide a
convenient way to document the discriminant features of a family of related products and now abound on the internet. Despite their apparent simplicity, the information present in existing PCMs can be very heterogeneous, partial, ambiguous, hard to exploit by users who desire to choose an appropriate product. Variability Models (VMs) can be employed to formulate in a more precise way the semantics of PCMs and enable automated reasoning such as assisted configuration. Yet, the gap between PCMs and VMs should be precisely understood and automated techniques should support the transition between the two. In this paper, we propose
variability patterns that describe PCMs content and conduct an empirical analysis of 300+ PCMs mined from Wikipedia. Our findings are a first step toward better engineering techniques for maintaining and configuring PCMs.
There are multiple reasons why Open Source Software OSS is a benefit for all organisations and in particular in Public Sector.
All of the organisations represented on this call will be tasked with delivering solutions for specific requirements and at great speed. Why create those solutions from generic platforms and be dependent on their long release cycles to evolve the solutions when you can develop just what is needed and then share that with other PS orgs who can modify to suit their requirements which makes for rapid development and lack of redundancy
Ultimately you will be able to control your own destiny and set your own pace for delivering exactly what is needed.
Leveraging Open Source Opportunity in the Public Sector Without the RiskProtecode
Open source software presents a huge opportunity for public sector organisations in the UK. Adopting open source solutions allows assets to be shared and re-used; freeing organisations from massively expensive, inflexible “lock-in” solutions. To ensure that this potential is realised, it is imperative that organisations adopt a process for managing potential licensing, security and encryption content associated with open source code.
Join us as we share our tips for streamlining the open source adoption and management process and removing uncertainties around third party software vulnerabilities.
Software audit strategies: how often is enough? Protecode
With the widespread use of open source software in proprietary software projects, organizations are looking for ways to mitigate licensing, security and quality vulnerabilities related to open source code. These organizations are increasing deploying software audits which involve scanning a software portfolio to uncover all software packages as well as their associated licensing and copyright obligations, security vulnerabilities and other code attribute information.
This coming 1st of June 2022, 5:00 PM (AEST). We will be having our IN-PERSON Brisbane MuleSoft Meetup.
Brian Fraser from Capgemini will be discussing how to automate code quality review using SonarQube. Fuguo Wei PhD from Super Retail Group will be discussing how to catalogue APIs and enable their discoverability and consumability using MuleSoft Exchange
So, you want to build a hardware product?
Every so often, a device comes along that changes the way we live our daily lives and things are never the same again. With today’s digital technology, such devices may come more frequently than in the past – personal gadgets you cannot live without. What’s inside? What makes it tick? How do you find out?
In this sharing session, Mark will provide an introduction to hardware hacking and why it matters, going through some quick tips on getting cosy with hardware to find out what makes it tick.
Join us for a webinar on securing the DevOps lifecycle with GitOps. Explore the best defenses for common security threats to code repositories, and see how to apply GitOps best practices to your CICD pipelines for Kubernetes.
The adoption of GitOps already increases the security and stability of your Kubernetes deployment pipelines, keeping your deployment credentials and other secrets inside of the cluster. Although GitOps improves CICD pipeline security, it shifts the security burden to Git itself.
For organizations who wish to defend themselves from malicious internal or external actors, or who operate under high compliance requirements, implementing additional security measures to Git provides identity guarantees, automation of change control, and detailed audit trails.
In this webinar, we’ll discuss 4 common Git attacks and how to mitigate them:
1. User impersonation
2. Malicious user tampering with the repository’s history
3. Malicious user attacking the Git platform
4. Historical attacks on Git clients and their impact
Splunk All the Things: Our First 3 Months Monitoring Web Service APIs - Splun...Dan Cundiff
A presentation titled "Splunk All the Things: Our First 3 Months Monitoring Web Service APIs" that Dan Cundiff and Eric Helgeson from Target Corporation gave at Splunk .conf2012.
As you know, component shortages are impacting product lead times around the world. Advanced smart battery packs and chargers are no exception. Over recent years, electronic circuit functionality has been consolidated into smaller ICs that can manage a lot of functionality into small, easy-to-use single ICs. Unfortunately, these ICs are single-sourced ICs with lead times stretching beyond 80 weeks. These extremely long lead times can kill projects and companies.
In this webinar, we reviewed methods that we use to minimize or eliminate these single-sourced components used in battery pack manufacturing. Along with ways to layout circuit boards to allow component flexibility preventing redesigns, and methods to use firmware to reduce dependencies on sole-sourced parts.
For more information on our custom battery pack solutions, visit https://www.epectec.com/batteries.
There are multiple reasons why Open Source Software OSS is a benefit for all organisations and in particular in Public Sector.
All of the organisations represented on this call will be tasked with delivering solutions for specific requirements and at great speed. Why create those solutions from generic platforms and be dependent on their long release cycles to evolve the solutions when you can develop just what is needed and then share that with other PS orgs who can modify to suit their requirements which makes for rapid development and lack of redundancy
Ultimately you will be able to control your own destiny and set your own pace for delivering exactly what is needed.
Leveraging Open Source Opportunity in the Public Sector Without the RiskProtecode
Open source software presents a huge opportunity for public sector organisations in the UK. Adopting open source solutions allows assets to be shared and re-used; freeing organisations from massively expensive, inflexible “lock-in” solutions. To ensure that this potential is realised, it is imperative that organisations adopt a process for managing potential licensing, security and encryption content associated with open source code.
Join us as we share our tips for streamlining the open source adoption and management process and removing uncertainties around third party software vulnerabilities.
Software audit strategies: how often is enough? Protecode
With the widespread use of open source software in proprietary software projects, organizations are looking for ways to mitigate licensing, security and quality vulnerabilities related to open source code. These organizations are increasing deploying software audits which involve scanning a software portfolio to uncover all software packages as well as their associated licensing and copyright obligations, security vulnerabilities and other code attribute information.
This coming 1st of June 2022, 5:00 PM (AEST). We will be having our IN-PERSON Brisbane MuleSoft Meetup.
Brian Fraser from Capgemini will be discussing how to automate code quality review using SonarQube. Fuguo Wei PhD from Super Retail Group will be discussing how to catalogue APIs and enable their discoverability and consumability using MuleSoft Exchange
So, you want to build a hardware product?
Every so often, a device comes along that changes the way we live our daily lives and things are never the same again. With today’s digital technology, such devices may come more frequently than in the past – personal gadgets you cannot live without. What’s inside? What makes it tick? How do you find out?
In this sharing session, Mark will provide an introduction to hardware hacking and why it matters, going through some quick tips on getting cosy with hardware to find out what makes it tick.
Join us for a webinar on securing the DevOps lifecycle with GitOps. Explore the best defenses for common security threats to code repositories, and see how to apply GitOps best practices to your CICD pipelines for Kubernetes.
The adoption of GitOps already increases the security and stability of your Kubernetes deployment pipelines, keeping your deployment credentials and other secrets inside of the cluster. Although GitOps improves CICD pipeline security, it shifts the security burden to Git itself.
For organizations who wish to defend themselves from malicious internal or external actors, or who operate under high compliance requirements, implementing additional security measures to Git provides identity guarantees, automation of change control, and detailed audit trails.
In this webinar, we’ll discuss 4 common Git attacks and how to mitigate them:
1. User impersonation
2. Malicious user tampering with the repository’s history
3. Malicious user attacking the Git platform
4. Historical attacks on Git clients and their impact
Splunk All the Things: Our First 3 Months Monitoring Web Service APIs - Splun...Dan Cundiff
A presentation titled "Splunk All the Things: Our First 3 Months Monitoring Web Service APIs" that Dan Cundiff and Eric Helgeson from Target Corporation gave at Splunk .conf2012.
As you know, component shortages are impacting product lead times around the world. Advanced smart battery packs and chargers are no exception. Over recent years, electronic circuit functionality has been consolidated into smaller ICs that can manage a lot of functionality into small, easy-to-use single ICs. Unfortunately, these ICs are single-sourced ICs with lead times stretching beyond 80 weeks. These extremely long lead times can kill projects and companies.
In this webinar, we reviewed methods that we use to minimize or eliminate these single-sourced components used in battery pack manufacturing. Along with ways to layout circuit boards to allow component flexibility preventing redesigns, and methods to use firmware to reduce dependencies on sole-sourced parts.
For more information on our custom battery pack solutions, visit https://www.epectec.com/batteries.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
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 .
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.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
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.
1. Product Lines Can Jeopardize
Their Trade Secrets
Mathieu Acher, Guillaume Bécan, Benoit Combemale,
Benoit Baudry and Jean-Marc Jézéquel
IRISA, Inria, University of Rennes 1, France
2. Product Lines Can Jeopardize Their Trade Secrets 2
Motivating example
Configurator
Final product
Options
3. Product Lines Can Jeopardize Their Trade Secrets 3
Motivating example
Configurator
Final product
Options
Different
configuration
Different
car
4. Product Lines Can Jeopardize Their Trade Secrets 4
Motivating example
● Customers
– Activate/deactivate options
● Competitors
– Understand the options and their constraints
– Create a “better” product line
● Contractors
– Create, change or extend options
– Access software without specialized tools (e.g.
for diagnostic)
What if the product line is not protected?
5. Product Lines Can Jeopardize Their Trade Secrets 5
Trade secrets are in...
6. Product Lines Can Jeopardize Their Trade Secrets 6
Security for sofware product lines
● Software Product Lines (SPL) are everywhere !
● Naive implementation of SPL
– No security
– Trade secrets become available to attackers
– Need to secure implementation mechanisms
● New research domain: security for SPL
● What's different from traditional software security?
– Combinatorial explosion
– Restrict access or hide some options of the SPL
– Hide marketing/business constraints
– Open world: new and unplanned options to protect
– Protect the significant effort to create an SPL
7. Product Lines Can Jeopardize Their Trade Secrets 7
Concrete example: online video generator
● 3 steps
– Enter your name
– Choose your 3 favorite shows of Canal+
– Watch YOUR episode of Bref (famous
humorous TV show of Canal+)
● This is a product line
(French TV channel)
8. Product Lines Can Jeopardize Their Trade Secrets 8
Online video generator
Configurator
Final product
(Complete video)
Options
(Chunks of videos)
random choices+
...
9. Product Lines Can Jeopardize Their Trade Secrets 9
Let's hack it !
● 3 days of work
● Manual analysis of HTTP request
– Videos are made of 18 sequences
– For each sequence, there are several possible variants
– Video variants are directly accessible
● Ask for many episodes (bash script, wget)
– List possible variants for each sequence
– Download all video variants
● Statistics (R script)
– Detect mandatory variants
– 0.1% chance of getting a special variant
10. Product Lines Can Jeopardize Their Trade Secrets 10
Let's reengineer a configurator !
● 2 days of work
● Complete configurator
● No random choices
● Videos are hosted on the original service
11. Product Lines Can Jeopardize Their Trade Secrets 11
Threats
● Only one week of work
● Download all video sequences which are
protected by copyright
● Re-engineer a new configurator
– Kill the original idea (e.g. no random choices)
– No advertising
● Find all the codes hidden in the video
sequences and win the contest !
12. Product Lines Can Jeopardize Their Trade Secrets 12
Trade secrets are in...
13. Product Lines Can Jeopardize Their Trade Secrets 13
RD1: Protection of positive variability
● Compositional approach
– Options are composed on demand
– Clean modular design
● Ease the identification of options and how they can be
composed
● How to secure positive variability?
– Obfuscate the variability and modularity in the source code or
data
– Obfuscate the mapping between options and corresponding
artifacts
● Challenge: develop techniques for diversifying the mapping
– non intrusive for the developers
– agnostic to a domain
14. Product Lines Can Jeopardize Their Trade Secrets 14
RD2: Protection of negative variability
● Exhibit all variants and content at once
● Activate/deactivate variants depending on
some conditions
● How to secure negative variability?
– Improve mechanism used to remove or
activate variants
– Obfuscate pre-defined variants
15. Product Lines Can Jeopardize Their Trade Secrets 15
RD3: Barriers to master configuration space
● A configuration set can also contain trade
secrets
● Crawling the configuration space reveals
these secrets
● A comprehensive visit offers a global view
of the options and their constraints
● Challenge: develop barriers to limit the
exploration of the configuration space
16. Product Lines Can Jeopardize Their Trade Secrets 16
Conclusion
● Variability should be protected
● Usual cost/benefit tradeoff
● New research domain: security in SPL
● Cross-fertilize research results in software
product line and security
● Challenge: diversify or vary variability
