The document describes labelled variables in logic programming. It introduces labelled variables as a way to extend logic programming with domain-specific computational models. Labelled variables allow logic variables to be associated with labels that constrain their possible values. The paper presents a formal model for labelled variables in logic programming, including unification rules and semantics. It defines a fixpoint semantics based on the immediate consequence operator and an operational semantics as a labelled machine. Examples are provided to illustrate hybrid computations combining logic programming and labelled variables.
College Magsys Project simulating taxis in a stochastic real-world environment to make optimal taxi assignments (minimizing delay time).
We try various strategies including machine learned localization, pre-emption, and the hungarian method. We then run Netlogo simulations across various scenario and present results.
This attempts empirical simulations of the Dynamic Task Allocation Problem.
Ontology-mediated query answering with data-tractable description logicsINRIA-CEDAR
Ā
Recent years have seen an increasing interest in ontology-mediated query answering, in which the semantic knowledge provided by an ontology is exploited when querying data. Adding an ontology has several advantages (e.g. simplifying query formulation, integrating data from different sources, providing more complete answers to queries), but it also makes the query answering task more difficult. In this tutorial, we will give a brief introduction to ontology-mediated query answering using description logic (DL) ontologies. Our focus will be on DLs for which query answering scales polynomially in the size of the data, as these are best suited for applications requiring large amounts of data. We will describe the challenges that arise when evaluating different natural types of queries in the presence of such ontologies, and we will present algorithmic solutions based upon two key concepts, namely, query rewriting and saturation. The lecture will conclude with an overview of recent results and active areas of ongoing research.
A Note on the Generalization of the Mean Value Theoremijtsrd
Ā
In this paper, a new generalization of the mean value theorem is firstly established. Based on the Rolleās theorem, a simple proof is provided to guarantee the correctness of such a generalization. Some corollaries are evidently obtained by the main result. It will be shown that the mean value theorem, the Cauchyās mean value theorem, and the mean value theorem for integrals are the special cases of such a generalized form. We can simultaneously obtain the upper and lower bounds of certain integral formulas and verify inequalities by using the main theorems. Finally, two examples are offered to illustrate the feasibility and effectiveness of the obtained results. Yeong-Jeu Sun "A Note on the Generalization of the Mean Value Theorem" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38258.pdf Paper URL : https://www.ijtsrd.com/mathemetics/calculus/38258/a-note-on-the-generalization-of-the-mean-value-theorem/yeongjeu-sun
Kotlin: forse ĆØ la volta buona (Trento)Davide Cerbo
Ā
Il codice di esempio e disponibile qui: https://github.com/jesty/kotlin-fossavotabona
La variazione col DAO al posto del repository ĆØ disponibile qui:
https://github.com/jesty/kotlin-fossavotabona/tree/dao-companion-object
In classical data analysis, data are single values. This is the case if you consider a dataset of n patients which age and size you know. But what if you record the blood pressure or the weight of each patient during a day ? Then, for each patient, you do not have a single-valued data but a set of values since the blood pressure or the weight are not constant during the day.
Suppose now that you do not want to record blood pressure a thousand times for each patient and to store it into a database because your memory space is limited. Therefore, you need to aggregate each set of values into symbols: intervals (lower and upper bounds only), box plots, histograms or even distributions (distribution law with mean and variance)...
Thus, the issue is to adapt classical statistical tools to symbolic data analysis. More precisely, this article is aimed at proposing a method to fit a regression on Gaussian distributions. This paper is divided as follows: first, it presents the computation of the maximum likelihood estimator and then it compares the new approach with the usual least squares regression.
College Magsys Project simulating taxis in a stochastic real-world environment to make optimal taxi assignments (minimizing delay time).
We try various strategies including machine learned localization, pre-emption, and the hungarian method. We then run Netlogo simulations across various scenario and present results.
This attempts empirical simulations of the Dynamic Task Allocation Problem.
Ontology-mediated query answering with data-tractable description logicsINRIA-CEDAR
Ā
Recent years have seen an increasing interest in ontology-mediated query answering, in which the semantic knowledge provided by an ontology is exploited when querying data. Adding an ontology has several advantages (e.g. simplifying query formulation, integrating data from different sources, providing more complete answers to queries), but it also makes the query answering task more difficult. In this tutorial, we will give a brief introduction to ontology-mediated query answering using description logic (DL) ontologies. Our focus will be on DLs for which query answering scales polynomially in the size of the data, as these are best suited for applications requiring large amounts of data. We will describe the challenges that arise when evaluating different natural types of queries in the presence of such ontologies, and we will present algorithmic solutions based upon two key concepts, namely, query rewriting and saturation. The lecture will conclude with an overview of recent results and active areas of ongoing research.
A Note on the Generalization of the Mean Value Theoremijtsrd
Ā
In this paper, a new generalization of the mean value theorem is firstly established. Based on the Rolleās theorem, a simple proof is provided to guarantee the correctness of such a generalization. Some corollaries are evidently obtained by the main result. It will be shown that the mean value theorem, the Cauchyās mean value theorem, and the mean value theorem for integrals are the special cases of such a generalized form. We can simultaneously obtain the upper and lower bounds of certain integral formulas and verify inequalities by using the main theorems. Finally, two examples are offered to illustrate the feasibility and effectiveness of the obtained results. Yeong-Jeu Sun "A Note on the Generalization of the Mean Value Theorem" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38258.pdf Paper URL : https://www.ijtsrd.com/mathemetics/calculus/38258/a-note-on-the-generalization-of-the-mean-value-theorem/yeongjeu-sun
Kotlin: forse ĆØ la volta buona (Trento)Davide Cerbo
Ā
Il codice di esempio e disponibile qui: https://github.com/jesty/kotlin-fossavotabona
La variazione col DAO al posto del repository ĆØ disponibile qui:
https://github.com/jesty/kotlin-fossavotabona/tree/dao-companion-object
In classical data analysis, data are single values. This is the case if you consider a dataset of n patients which age and size you know. But what if you record the blood pressure or the weight of each patient during a day ? Then, for each patient, you do not have a single-valued data but a set of values since the blood pressure or the weight are not constant during the day.
Suppose now that you do not want to record blood pressure a thousand times for each patient and to store it into a database because your memory space is limited. Therefore, you need to aggregate each set of values into symbols: intervals (lower and upper bounds only), box plots, histograms or even distributions (distribution law with mean and variance)...
Thus, the issue is to adapt classical statistical tools to symbolic data analysis. More precisely, this article is aimed at proposing a method to fit a regression on Gaussian distributions. This paper is divided as follows: first, it presents the computation of the maximum likelihood estimator and then it compares the new approach with the usual least squares regression.
AN IMPROVED DECISION SUPPORT SYSTEM BASED ON THE BDM (BIT DECISION MAKING) ME...ijmpict
Ā
Based on the BDM (Bit Decision Making) method, the present work presents two contributions: first, the
illustration of the use of the technique known as SOP (Sum Of Products) in order to systematize the
process to obtain the correlation function for sub-systemās mathematical modelling, and second,the provision of capacity to manage a greater than binary but a finite - discrete set of possible subjective qualifications of suppliers at any criterion.
Sat4j: from the lab to desktop computers. OW2con'15, November 17, Paris. OW2
Ā
The aim of the Sat4j library is to solve Boolean satisfaction and optimization problems. Those problems have received considerable attention in the last two decades, mainly due to its use in hardware verification.Sat4j started as a research project to experiment ideas about while providing an efficient Boolean reasoning engine to the Java community.
Formulas for Surface Weighted Numbers on Graphijtsrd
Ā
The boundary value problem differential operator on the graph of a specific structure is discussed in this article. The graph has degree 1 vertices and edges that are linked at one common vertex. The differential operator expression with real valued potentials, the Dirichlet boundary conditions, and the conventional matching requirements define the boundary value issue. There are a finite number of eig nv lu s in this problem.The residues of the diagonal elements of the Weyl matrix in the eigenvalues are referred to as weight numbers. The ig nv lu s are monomorphic functions with simple poles.The weight numbers under consideration generalize the weight numbers of differential operators on a finite interval, which are equal to the reciprocals of the squared norms of eigenfunctions. These numbers, along with the eig nv lu s, serve as spectral data for unique operator reconstruction. The contour integration is used to obtain formulas for surfacethe weight numbers, as well as formulas for the sums in the case of superficial near ig nv lu s. On the graphs, the formulas can be utilized to analyze inverse spectral problems. Ghulam Hazrat Aimal Rasa "Formulas for Surface Weighted Numbers on Graph" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49573.pdf Paper URL: https://www.ijtsrd.com/mathemetics/calculus/49573/formulas-for-surface-weighted-numbers-on-graph/ghulam-hazrat-aimal-rasa
Catalan Tau Collocation for Numerical Solution of 2-Dimentional Nonlinear Par...IJERA Editor
Ā
Tau method which is an economized polynomial technique for solving ordinary and partial differential
equations with smooth solutions is modified in this paper for easy computation, accuracy and speed. The
modification is based on the systematic use of āCatalan polynomialā in collocation tau method and the
linearizing the nonlinear part by the use of Adomianās polynomial to approximate the solution of 2-dimentional
Nonlinear Partial differential equation. The method involves the direct use of Catalan Polynomial in the solution
of linearizedPartial differential Equation without first rewriting them in terms of other known functions as
commonly practiced. The linearization process was done through adopting the Adomian Polynomial technique.
The results obtained are quite comparable with the standard collocation tau methods for nonlinear partial
differential equations.
Labelled Variables in Logic Programming: A First Prototipe in tuPrologRoberta Calegari
Ā
We present the first prototype of Labelled tuProlog, an extension of tuProlog exploiting labelled variables to enable a sort of multi- paradigm / multi-language programming aimed at pervasive systems.
Building WordSpaces via Random Indexing from simple to complex spacesPierpaolo Basile
Ā
This presentation describes two approaches to compositional semantics in distributional semantic spaces.
Both approaches conceive the semantics of complex structures, such as phrases or sentences, as being other than
the sum of its terms.
Syntax is the plus used as a glue to compose words.
The former kind of approach encodes information about syntactic dependencies directly into distributional spaces, the latter exploits compositional operators reflecting the syntactic role of words.
Introducing a Tool for Concurrent ArgumentationCarlo Taticchi
Ā
Agent-based modelling languages naturally implement concurrency for handling complex interactions between communicating agents. On the other hand, the field of Argumentation Theory lacks of instruments to explicitly model concurrent behaviours. In this paper we intro- duce a tool for dealing with concurrent argumentation processes and that can be used, for instance, to model agents debating, negotiating and persuading. The tool implements operations as expansion, contraction and revision. We also provide a web interface exposing the functionalities of the tool and allowing for a more careful study of concurrent processes.
Distributed Ledger and Robust Consensus for AgreementsMiguel Rebollo
Ā
Word presented in EUMAS-AT '18 conference at Bergen (NO). Proposes a robust consensus model that allows detecting cheating nodes. Application to distributed ledger (DLT)
A POSSIBLE RESOLUTION TO HILBERTāS FIRST PROBLEM BY APPLYING CANTORāS DIAGONA...mathsjournal
Ā
We present herein a new approach to the Continuum hypothesis CH. We will employ a string conditioning,
a technique that limits the range of a string over some of its sub-domains for forming subsets K of R. We
will prove that these are well defined and in fact proper subsets of R by making use of Cantorās Diagonal
argument in its original form to establish the cardinality of K between that of (N,R) respectively.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
AN IMPROVED DECISION SUPPORT SYSTEM BASED ON THE BDM (BIT DECISION MAKING) ME...ijmpict
Ā
Based on the BDM (Bit Decision Making) method, the present work presents two contributions: first, the
illustration of the use of the technique known as SOP (Sum Of Products) in order to systematize the
process to obtain the correlation function for sub-systemās mathematical modelling, and second,the provision of capacity to manage a greater than binary but a finite - discrete set of possible subjective qualifications of suppliers at any criterion.
Sat4j: from the lab to desktop computers. OW2con'15, November 17, Paris. OW2
Ā
The aim of the Sat4j library is to solve Boolean satisfaction and optimization problems. Those problems have received considerable attention in the last two decades, mainly due to its use in hardware verification.Sat4j started as a research project to experiment ideas about while providing an efficient Boolean reasoning engine to the Java community.
Formulas for Surface Weighted Numbers on Graphijtsrd
Ā
The boundary value problem differential operator on the graph of a specific structure is discussed in this article. The graph has degree 1 vertices and edges that are linked at one common vertex. The differential operator expression with real valued potentials, the Dirichlet boundary conditions, and the conventional matching requirements define the boundary value issue. There are a finite number of eig nv lu s in this problem.The residues of the diagonal elements of the Weyl matrix in the eigenvalues are referred to as weight numbers. The ig nv lu s are monomorphic functions with simple poles.The weight numbers under consideration generalize the weight numbers of differential operators on a finite interval, which are equal to the reciprocals of the squared norms of eigenfunctions. These numbers, along with the eig nv lu s, serve as spectral data for unique operator reconstruction. The contour integration is used to obtain formulas for surfacethe weight numbers, as well as formulas for the sums in the case of superficial near ig nv lu s. On the graphs, the formulas can be utilized to analyze inverse spectral problems. Ghulam Hazrat Aimal Rasa "Formulas for Surface Weighted Numbers on Graph" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49573.pdf Paper URL: https://www.ijtsrd.com/mathemetics/calculus/49573/formulas-for-surface-weighted-numbers-on-graph/ghulam-hazrat-aimal-rasa
Catalan Tau Collocation for Numerical Solution of 2-Dimentional Nonlinear Par...IJERA Editor
Ā
Tau method which is an economized polynomial technique for solving ordinary and partial differential
equations with smooth solutions is modified in this paper for easy computation, accuracy and speed. The
modification is based on the systematic use of āCatalan polynomialā in collocation tau method and the
linearizing the nonlinear part by the use of Adomianās polynomial to approximate the solution of 2-dimentional
Nonlinear Partial differential equation. The method involves the direct use of Catalan Polynomial in the solution
of linearizedPartial differential Equation without first rewriting them in terms of other known functions as
commonly practiced. The linearization process was done through adopting the Adomian Polynomial technique.
The results obtained are quite comparable with the standard collocation tau methods for nonlinear partial
differential equations.
Labelled Variables in Logic Programming: A First Prototipe in tuPrologRoberta Calegari
Ā
We present the first prototype of Labelled tuProlog, an extension of tuProlog exploiting labelled variables to enable a sort of multi- paradigm / multi-language programming aimed at pervasive systems.
Building WordSpaces via Random Indexing from simple to complex spacesPierpaolo Basile
Ā
This presentation describes two approaches to compositional semantics in distributional semantic spaces.
Both approaches conceive the semantics of complex structures, such as phrases or sentences, as being other than
the sum of its terms.
Syntax is the plus used as a glue to compose words.
The former kind of approach encodes information about syntactic dependencies directly into distributional spaces, the latter exploits compositional operators reflecting the syntactic role of words.
Introducing a Tool for Concurrent ArgumentationCarlo Taticchi
Ā
Agent-based modelling languages naturally implement concurrency for handling complex interactions between communicating agents. On the other hand, the field of Argumentation Theory lacks of instruments to explicitly model concurrent behaviours. In this paper we intro- duce a tool for dealing with concurrent argumentation processes and that can be used, for instance, to model agents debating, negotiating and persuading. The tool implements operations as expansion, contraction and revision. We also provide a web interface exposing the functionalities of the tool and allowing for a more careful study of concurrent processes.
Distributed Ledger and Robust Consensus for AgreementsMiguel Rebollo
Ā
Word presented in EUMAS-AT '18 conference at Bergen (NO). Proposes a robust consensus model that allows detecting cheating nodes. Application to distributed ledger (DLT)
A POSSIBLE RESOLUTION TO HILBERTāS FIRST PROBLEM BY APPLYING CANTORāS DIAGONA...mathsjournal
Ā
We present herein a new approach to the Continuum hypothesis CH. We will employ a string conditioning,
a technique that limits the range of a string over some of its sub-domains for forming subsets K of R. We
will prove that these are well defined and in fact proper subsets of R by making use of Cantorās Diagonal
argument in its original form to establish the cardinality of K between that of (N,R) respectively.
Similar to Labelled Variables in Logic Programming: Foundations (20)
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
Ā
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana LuĆsa Pinho
Ā
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Ā
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.Ā
Ā Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
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 āsmallā 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 .
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Ioās 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 Ioās 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 Ioās surface using adaptive
optics at visible wavelengths.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
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 Leberās 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 Mendelās 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 Oāclock 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.
11. Scope & Goals Examples
Standard LP extension Comparison I
Constraint Logic Programming
The computational model is supported
Computational eļ¬ciency is not comparable
interval(X):- X^[-1,4].
interval(X):- X^[6,10].
Labels used to represent the integer interval over which the logic variable
values span: take the form X^[min,max ]
?- X^[2,7], interval(X).
yes.
X^[2,4] ;
yes.
X^[6,7]
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 11 / 31
12. Scope & Goals Examples
Standard LP extension Comparison II
Integers with a Neighbourhood
The expressiveness of LVLP
easily move to more complex domains
integers with a neighbourhood
neighbourhood(X):- X^[-1,4], X=3.
neighbourhood(X):- X^[6,10], X=8.
?- X^[2,7], neighbourhood(X).
yes. X / 3
X^[2,4]
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 12 / 31
13. The Labelled Variables Model in Logic Programming
Outline
1 Scope & Goals
Context & Motivation
Examples
2 The Labelled Variables Model in Logic Programming
Formal Model
Uniļ¬cation rules
3 Semantics
Fixpoint Semantics
Operational Semantics
Semantics Equivalence
4 Architecture
5 Conclusions & Further Work
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 13 / 31
14. The Labelled Variables Model in Logic Programming Formal Model
Labelled Variables Model in Logic Programming: LVLP
A set B = {Ī²1, . . . , Ī²n} of basic labels that are the basic entities of
the domain of labels
A set L ā ā(B) of labels, where each ā L is a subset of B
A set of variables V , where v ā V is the generic variable
A labelling: a set of pairs vi , i , associating the label i to the
variable vi
A (label-)combining function fL, synthesising a new label from two
fL : L Ć L āā L
A compatibility function fC to check the compatibility between a term
t ā H and a label ā L
fC : H Ć L āā {true, false}
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 14 / 31
15. The Labelled Variables Model in Logic Programming Formal Model
LVLP Uniļ¬cation & Rules
Program Rule
Head ā Labellings, Body.
Head is an atomic formula
Labellings is the list of Variable/Label associations in the clause
Body is a list of atomic formulas
Uniļ¬cation of two labelled variables
(true/false ā§ fC (Ī, A), Ī, A)
true/false represents if there is an answer
fC (Ī, A) compatibility between variable values and their labels
Ī represents the most general substitution for all variables
A represents the corresponding label-variable associations
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 15 / 31
16. The Labelled Variables Model in Logic Programming Uniļ¬cation rules
Uniļ¬cation Rules
constant c2 variable v2 labelled variable v2, 2 compound term s2
constant if c1 = c2 true, {v2/c1} if fC (c1, 2) = true false
c1 then true then true, {v1/c2}, 1
else false else false
variable true, {v1/c2} true, {v1/v2} true, {v1/v2}, 2 if v1 does not occur in s2
v1 then true, {v1/s2}
else false
labelled variable if fC (c2, 1) = true true, {v1/v2}, 1 if fL( 1, 2) = ā if v1 does not occur in s2 and
v1, 1 then true, {v1/c2}, 1 then true, {v1/v2}, fL( 1, 2) fL( 1, fL( 2, . . . , fL( nā1, n) . . . )) = ā
else false else false where 2, ... n are labels
of variables in s2
then true, {v1/s2},
fL( 1, fL( 2, . . . , fL( nā1, n) . . . ))
else false
compound term false if v2 does not occur in s1 if v2 does not occur in s1 and if s1 and s2
s1 then true, {v2/s1} fL( 1, fL( 2, . . . , fL( nā1, n) . . . )) = ā have same functor and arity
else false where 2, ... n are labels and arguments
of variables in s1 (recursively) unify
then true, {v2/s1}, then true
fL( 1, fL( 2, . . . , fL( nā1, n) . . . )) else false
else false
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 16 / 31
17. Semantics
Outline
1 Scope & Goals
Context & Motivation
Examples
2 The Labelled Variables Model in Logic Programming
Formal Model
Uniļ¬cation rules
3 Semantics
Fixpoint Semantics
Operational Semantics
Semantics Equivalence
4 Architecture
5 Conclusions & Further Work
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 17 / 31
18. Semantics Fixpoint Semantics
Fixpoint Semantics
Denotational Semantics based on TP
TP(I) = p(t), :
r = p(x) ā Īx | b1, . . . , bn (1)
where r is a fresh renaming of a rule of P,
v is a valuation on H such that v(x) = t, (2)
n
i=1 ā i s.t. v(bi ), i ā I, (3)
X |= Īt ā§ n
i=1 fC v(bi ), i , (4)
= fL r, Īt, 1, Ā· Ā· Ā· , n (5)
where Īt = v(Īx ) = [ t1, 1 , . . . , tn, m ] if Īx = [ x1, 1 , . . . , xm, m ]
Soundness and Completeness of TP
We demonstrate that
TP is a monotonic and continuous mapping on partial orders
ā fL is required to be ACI
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 18 / 31
19. Semantics Operational Semantics
Operational Semantics
Labelled-Machine State Ļ = t0 t1...tn, W , Ī
t0 t1...tn is the list of terms (goals)
W is the current list of variables bindings
Ī is the set of the current labelling associations on W
Inference Step by Program Rule s0 ā Ī , s1, s2, . . . , sm
conditions
ā mgu Īø such that Īø(t0) = Īø(s0)
fĪøL(Ī, Īø(Ī )) = ā
ļ¬nal state
Ļ = Īø(s1, . . . , sm, t1, . . . , tn), W = W ā¦ Īø, Ī = fĪøL(Ī, Īø(Ī ))
Labelled-Machine Final State Ļf = ( , Wf , Īf )
is the empty sequence, Wf is the ļ¬nal list of variables and bindings, Īf is the
corresponding labelling associations set
A sequence of applications of inference steps is said a derivation
A derivation is successful if it ends in a ļ¬nal state, failing if it ends in a non-ļ¬nal state
where no inference step is possible
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 19 / 31
20. Semantics Semantics Equivalence
Semantics Equivalence
Proposition
Let p(x) be an atom, v a valuation on H such that v(x) = t where t are
ground terms, and a list of labels
Then there is a successful derivation for p(t), v, v(x), iļ¬
p(t), ā TP ā Ļ
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 20 / 31
21. Architecture
Outline
1 Scope & Goals
Context & Motivation
Examples
2 The Labelled Variables Model in Logic Programming
Formal Model
Uniļ¬cation rules
3 Semantics
Fixpoint Semantics
Operational Semantics
Semantics Equivalence
4 Architecture
5 Conclusions & Further Work
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 21 / 31
24. Conclusions & Further Work
Outline
1 Scope & Goals
Context & Motivation
Examples
2 The Labelled Variables Model in Logic Programming
Formal Model
Uniļ¬cation rules
3 Semantics
Fixpoint Semantics
Operational Semantics
Semantics Equivalence
4 Architecture
5 Conclusions & Further Work
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 24 / 31
25. Conclusions & Further Work
Conclusions
Deļ¬nition of the LVLP theoretical framework
Domain-speciļ¬c computational models can be expressed via labelled
variables
Present the ļ¬xpoint and operational semantics, discuss correctness,
completeness, and equivalence
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 25 / 31
26. Conclusions & Further Work
Future Work
Further development of the Labelled tuProlog [Denti et al., 2005]
prototype
Design and implementation of a full-ļ¬edged middleware for tuProlog
and LVLP
Deeper exploration and better understanding of the consequences of
applying labels to formulas
Application of the LVLP framework to diļ¬erent scenarios and
approaches (probabilistic [Skarlatidis et al., 2015], distributed ASP
reasoning [Dovier and Pontelli, 2009],...)
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 26 / 31
27. Conclusions & Further Work
Thanks
Thank you for your attention
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 27 / 31
28. References
References I
Denti, E., Omicini, A., and Ricci, A. (2005).
Multi-paradigm Java-Prolog integration in tuProlog.
Science of Computer Programming, 57(2):217ā250.
Dovier, A. and Pontelli, E. (2009).
Present and future challenges for ASP systems.
In Erdem, E., Lin, F., and Schaub, T., editors, Logic Programming and Nonmonotonic
Reasoning. 10th International Conference, LPNMR 2009, Potsdam, Germany, September
14-18, 2009. Proceedings, pages 622ā624. Springer.
Gabbay, D. M. (1996).
Labelled Deductive Systems, Volume 1.
Clarendon Press, Oxford Logic Guides 33.
Holzbaur, C. (1992).
Metastructures vs. attributed variables in the context of extensible uniļ¬cation.
In Bruynooghe, M. and Wirsing, M., editors, Programming Language Implementation and
Logic Programming, volume 631 of Lecture Notes in Computer Science, pages 260ā268.
Springer.
4th International Symposium (PLILPā92) Leuven, Belgium, August 26ā28, 1992
Proceedings.
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 28 / 31
29. References
References II
Mariani, S. and Omicini, A. (2015).
Coordinating activities and change: An event-driven architecture for situated MAS.
Engineering Applications of Artiļ¬cial Intelligence, 41:298ā309.
Skarlatidis, A., Artikis, A., Filippou, J., and Paliouras, G. (2015).
A probabilistic logic programming event calculus.
Theory and Practice of Logic Programming, 15(Special Issue 02 (Probability, Logic and
Learning)):213ā245.
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 29 / 31
30. Extras
URLs
Slides
On APICe
ā http://apice.unibo.it/xwiki/bin/view/Talks/Label2pCilc016
On SlideShare
ā http://www.slideshare.net/rcalegari1/
labelled-variables-in-logic-programming-foundations
Paper
On APICe
ā http://apice.unibo.it/xwiki/bin/view/Publications/Label2pCilc016
On CEUR
ā http://ceur-ws.org/Vol-1645/paper 7.pdf
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 30 / 31
31. Labelled Variables in Logic Programming:
Foundations
Roberta Calegari1, Enrico Denti1, Agostino Dovier2 Andrea Omicini1
{roberta.calegari, enrico.denti, andrea.omicini}@unibo.it
agostino.dovier@uniud.it
1Dipartimento di Informatica, Scienza e IngegneriaāUniversit`a di Bologna
2Dipartimento di Scienze Matematiche, Informatiche e FisicheāUniversit`a di Udine
Talk @ 31th Annual Conference of GULP (CILC 2016)
Universit`a di Milano-Bicocca, Italy
20 June 2016
Calegari, Denti, Dovier, Omicini Labelled Variables in Logic Programming CILC 2016, 20/6/2016 31 / 31
