1. The document reports on a study that used quantitative electroencephalography (qEEG) and event-related potentials (ERPs) to analyze brain activation during verbal cognition tasks involving nouns and verbs.
2. The study found that recognizing a correct noun meaning activated Broca's area, while a close noun meaning activated the frontal lobe, and a distant noun meaning activated Broca's area. For verbs, a correct meaning activated the frontal lobe, a close meaning activated the right occipital lobe, and a distant meaning activated the frontal and left parietal lobes.
3. Response time data showed that correct meanings were processed fastest in most brain areas, close meanings were fast in the left temporal area
Verbal cognition: vector space analysis by Chuluundorj.B /University of the H...Buyankhishig Sunduijav
Neuro-cognitive and psychological linguistics present important area of multidisciplinary research.
In this paper we have described some possible applications of mathematical methods to neuro-cognitive linguistics. In neuro-cognitive study of language, neural architecture and neuropsychological mechanism of verbal cognition are basis of a vector–based modeling. A comparison of human mental space to a vector space is an effective way of analyzing of human semantic vocabulary, mental representations and rules of clustering and mapping in typologically different languages.
Euclidean and non-Euclidean spaces can be applied for a description of human semantic vocabulary and high order structures reflecting internal and external features of object and action (event). Vector analysis of word meaning and basic syntax structures offers new methodological opportunities to interpret effect of semantic and pragmatic forces at morphology and syntax levels.
Non-linear and metaphoric transformations present specific complex phenomenon to be described in 3D and other N-dimensional spaces in the framework of quantum semantics.
Keywords: Mental mapping, human mental lexicon, embodied and symbolic cognition, verbal cognition, semantic space, scalar, vector space, mental transformation, semantic gravity.
Marcelo Funes-Gallanzi - Simplish - Computational intelligence unconferenceDaniel Lewis
At the computational intelligence unconference 2014, Marcelo Funes-Gallanzi presented Simplish, a system for the conversion of text into Simple English. Here are his slides.
An Entity-Driven Recursive Neural Network Model for Chinese Discourse Coheren...ijaia
Chinese discourse coherence modeling remains a challenge taskin Natural Language Processing
field.Existing approaches mostlyfocus on the need for feature engineering, whichadoptthe sophisticated
features to capture the logic or syntactic or semantic relationships acrosssentences within a text.In this
paper, we present an entity-drivenrecursive deep modelfor the Chinese discourse coherence evaluation
based on current English discourse coherenceneural network model. Specifically, to overcome the
shortage of identifying the entity(nouns) overlap across sentences in the currentmodel, Our combined
modelsuccessfully investigatesthe entities information into the recursive neural network
freamework.Evaluation results on both sentence ordering and machine translation coherence rating
task show the effectiveness of the proposed model, which significantly outperforms the existing strong
baseline.
2007. Introduction to the panel 'Pragmatic Interfaces' organised by the authors at the International Pragmatics Conference (IPRA) in Goteborg (Sweden), July 2007. Didier Maillat and Louis de Saussure
Verbal cognition: vector space analysis by Chuluundorj.B /University of the H...Buyankhishig Sunduijav
Neuro-cognitive and psychological linguistics present important area of multidisciplinary research.
In this paper we have described some possible applications of mathematical methods to neuro-cognitive linguistics. In neuro-cognitive study of language, neural architecture and neuropsychological mechanism of verbal cognition are basis of a vector–based modeling. A comparison of human mental space to a vector space is an effective way of analyzing of human semantic vocabulary, mental representations and rules of clustering and mapping in typologically different languages.
Euclidean and non-Euclidean spaces can be applied for a description of human semantic vocabulary and high order structures reflecting internal and external features of object and action (event). Vector analysis of word meaning and basic syntax structures offers new methodological opportunities to interpret effect of semantic and pragmatic forces at morphology and syntax levels.
Non-linear and metaphoric transformations present specific complex phenomenon to be described in 3D and other N-dimensional spaces in the framework of quantum semantics.
Keywords: Mental mapping, human mental lexicon, embodied and symbolic cognition, verbal cognition, semantic space, scalar, vector space, mental transformation, semantic gravity.
Marcelo Funes-Gallanzi - Simplish - Computational intelligence unconferenceDaniel Lewis
At the computational intelligence unconference 2014, Marcelo Funes-Gallanzi presented Simplish, a system for the conversion of text into Simple English. Here are his slides.
An Entity-Driven Recursive Neural Network Model for Chinese Discourse Coheren...ijaia
Chinese discourse coherence modeling remains a challenge taskin Natural Language Processing
field.Existing approaches mostlyfocus on the need for feature engineering, whichadoptthe sophisticated
features to capture the logic or syntactic or semantic relationships acrosssentences within a text.In this
paper, we present an entity-drivenrecursive deep modelfor the Chinese discourse coherence evaluation
based on current English discourse coherenceneural network model. Specifically, to overcome the
shortage of identifying the entity(nouns) overlap across sentences in the currentmodel, Our combined
modelsuccessfully investigatesthe entities information into the recursive neural network
freamework.Evaluation results on both sentence ordering and machine translation coherence rating
task show the effectiveness of the proposed model, which significantly outperforms the existing strong
baseline.
2007. Introduction to the panel 'Pragmatic Interfaces' organised by the authors at the International Pragmatics Conference (IPRA) in Goteborg (Sweden), July 2007. Didier Maillat and Louis de Saussure
A Natural Logic for Artificial Intelligence, and its Risks and Benefits gerogepatton
This paper is a multidisciplinary project proposal, submitted in the hopes that it may garner enough interest to launch it with members of the AI research community along with linguists
and philosophers of mind and language interested in constructing a semantics for a natural logic for AI. The paper outlines some of the major hurdles in the way of “semantics-driven” natural language processing based on standard predicate logic and sketches out the steps to be
taken toward a “natural logic”, a semantic system explicitly defined on a well-regimented (but indefinitely expandable) fragment of a natural language that can, therefore, be “intelligently” processed by computers, using the semantic representations of the phrases of the fragment.
Conceptual Spaces for Cognitive Architectures: A Lingua Franca for Different ...Antonio Lieto
We claim that Conceptual Spaces offer a lingua franca that allows to unify and generalize many aspects of the symbolic, sub-symbolic and diagrammatic approaches (by overcoming some of their typical problems) and to integrate them on a common ground. In doing so we extend and detail some of the arguments explored by Gardenfors [23] for defending the need of a conceptual, intermediate, representation level between
the symbolic and the sub-symbolic one. Additionally, we argue that Conceptual Spaces could offer a unifying framework for interpreting many kinds of diagrammatic and analogical representations. As a consequence, their adoption could also favor the integration of diagrammatical representation and
reasoning in Cognitive Architectures
Extending the knowledge level of cognitive architectures with Conceptual Spac...Antonio Lieto
Extending the knowledge level of cognitive architectures with Conceptual Spaces (+ a case study with Dual-PECCS: a hybrid knowledge representation system for common sense reasoning). Talk given at Stockholm, September 2016.
A Natural Logic for Artificial Intelligence, and its Risks and Benefits gerogepatton
This paper is a multidisciplinary project proposal, submitted in the hopes that it may garner enough interest to launch it with members of the AI research community along with linguists
and philosophers of mind and language interested in constructing a semantics for a natural logic for AI. The paper outlines some of the major hurdles in the way of “semantics-driven” natural language processing based on standard predicate logic and sketches out the steps to be
taken toward a “natural logic”, a semantic system explicitly defined on a well-regimented (but indefinitely expandable) fragment of a natural language that can, therefore, be “intelligently” processed by computers, using the semantic representations of the phrases of the fragment.
Conceptual Spaces for Cognitive Architectures: A Lingua Franca for Different ...Antonio Lieto
We claim that Conceptual Spaces offer a lingua franca that allows to unify and generalize many aspects of the symbolic, sub-symbolic and diagrammatic approaches (by overcoming some of their typical problems) and to integrate them on a common ground. In doing so we extend and detail some of the arguments explored by Gardenfors [23] for defending the need of a conceptual, intermediate, representation level between
the symbolic and the sub-symbolic one. Additionally, we argue that Conceptual Spaces could offer a unifying framework for interpreting many kinds of diagrammatic and analogical representations. As a consequence, their adoption could also favor the integration of diagrammatical representation and
reasoning in Cognitive Architectures
Extending the knowledge level of cognitive architectures with Conceptual Spac...Antonio Lieto
Extending the knowledge level of cognitive architectures with Conceptual Spaces (+ a case study with Dual-PECCS: a hybrid knowledge representation system for common sense reasoning). Talk given at Stockholm, September 2016.
Tensor-based models of natural language semantics provide a conceptually motivated procedure to compute the meaning of a sentence, given its grammatical structure and a vectorial representation of the meaning of its parts. The main characteristic of these models is that words with relational nature, such as adjectives and verbs, become (multi-)linear maps acting on vectors representing words of atomic types, e.g. nouns and noun phrases. On the practical side, the tensor-based framework has been proved useful in a number of NLP tasks. On the theoretical side, its rigorous mathematical foundations provide a test-bed for studying compositional aspects of language at a level deeper than most practically-oriented approaches would allow; for example, mathematical structures such as Frobenius algebras and bialgebras have been used to allow the explication of functional words such as relative pronouns, to model linguistic aspects such as coordination and intonation, and to provide accounts of quantification in distributional models. Furthermore, the deep structural similarity of the framework to concepts that explain the behaviour of quantum-mechanical systems has enabled a unique perspective in approaching language-related problems, such as lexical ambiguity and entailment, by leveraging the model to the realm of density operators and complete positive maps via Selinger's CPM construction. This talk aims at providing a comprehensive introduction to this emerging field by presenting the mathematical foundations, discussing important extensions and recent work, and (time permitted) touching implementation issues and practical applications.
The sophisticated signal processing techniques developed during last years for structural and functional imaging methods allow us to detect abnormalities of brain connectivity in brain disorders with unprecedented detail. Interestingly, recent works shed light on both functional and structural underpinnings of musical anhedonia (i.e., the individual's incapacity to enjoy listening to music). On the other hand, computational models based on brain simulation tools are being used more and more for mapping the functional consequences of structural abnormalities. The latter could help to better understand the mechanism that is impaired in people unable to derive pleasure from music, and formulate hypotheses on how music acquired reward value. The presentation gives an overview of today's studies and proposes a possible simulation pipeline to reproduce such scenario.
Early l2 learning advantageous in processing of syntactic violation in biling...Chuluundorj Begz
Brain processing of syntactic material can be altered by bilingualism [1] (i.e. mastering of two languages simultaneously). According to Piaget J., cognitive development of children depends on their age and can be divided into 4 stages: sensorimotor, preoperational, concrete operational and formal operational. However, the effect of bilingualism on brain processing of sentence grammar and structure violations during these development stages in Mongolian bilinguals is not well known. The recent study aimed to investigate brain function in processing of syntactic information by analysing brain peak waves, such as LAN (left anterior negativity), N400 and P600 in Mongolian monolinguals (control group) and bilinguals.
Early l2 learning advantageous in processing of syntactic violation in biling...Chuluundorj Begz
Brain processing of syntactic material can be altered by bilingualism [1] (i.e. mastering of two languages simultaneously). According to Piaget J., cognitive development of children depends on their age and can be divided into 4 stages: sensorimotor, preoperational, concrete operational and formal operational. However, the effect of bilingualism on brain processing of sentence grammar and structure violations during these development stages in Mongolian bilinguals is not well known. The recent study aimed to investigate brain function in processing of syntactic information by analysing brain peak waves, such as LAN (left anterior negativity), N400 and P600 in Mongolian monolinguals (control group) and bilinguals.
The effect of bilingualism on syntactic and semantic recognition in children ...Chuluundorj Begz
Bilingualism is beneficial in development of cognitive function in children. The benefits are not limited to improvements in social communication skills, sensitivity to language structures, details, grammar, conflict solving, creativity, analogical reasoning, classification, cognitive flexibility, inhibition and dementia prevention. However, bilingualism effect on cognitive processing of syntactic and semantic violations is not well understood yet. This study aimed to determine the effect of bilingualism on event related potentials (ERP) during semantic and syntactic violation tasks in children and adolescents.
The effect of bilingualism on syntactic and semantic recognition in children...Chuluundorj Begz
Bilingualism is beneficial in development of cognitive function in children. The benefits are not limited to improvements in social communication skills, sensitivity to language structures, details, grammar, conflict solving, creativity, analogical reasoning, classification, cognitive flexibility, inhibition and dementia prevention. However, bilingualism effect on cognitive processing of syntactic and semantic violations is not well understood yet. This study aimed to determine the effect of bilingualism on event related potentials (ERP) during semantic and syntactic violation tasks in children and adolescents.
The effect of bilingualism on syntactic and semantic recognition in childrenChuluundorj Begz
Bilingualism is beneficial in development of cognitive function in children. The benefits are not limited to improvements in social communication skills, sensitivity to language structures, details, grammar, conflict solving, creativity, analogical reasoning, classification, cognitive flexibility, inhibition and dementia prevention. However, bilingualism effect on cognitive processing of syntactic and semantic violations is not well understood yet. This study aimed to determine the effect of bilingualism on event related potentials (ERP) during semantic and syntactic violation tasks in children and adolescents.
Verbal cognition: vector space analysis by Chuluundorj.BChuluundorj Begz
Neuro-cognitive and psychological linguistics present important area of multidisciplinary research.
In this paper we have described some possible applications of mathematical methods to neuro-cognitive linguistics. In neuro-cognitive study of language, neural architecture and neuropsychological mechanism of verbal cognition are basis of a vector–based modeling. A comparison of human mental space to a vector space is an effective way of analyzing of human semantic vocabulary, mental representations and rules of clustering and mapping in typologically different languages.
Euclidean and non-Euclidean spaces can be applied for a description of human semantic vocabulary and high order structures reflecting internal and external features of object and action (event). Vector analysis of word meaning and basic syntax structures offers new methodological opportunities to interpret effect of semantic and pragmatic forces at morphology and syntax levels.
Non-linear and metaphoric transformations present specific complex phenomenon to be described in 3D and other N-dimensional spaces in the framework of quantum semantics.
Keywords: Mental mapping, human mental lexicon, embodied and symbolic cognition, verbal cognition, semantic space, scalar, vector space, mental transformation, semantic gravity.
(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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
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.
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 .
Richard's aventures in two entangled wonderlandsRichard 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.
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.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
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.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
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.
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.
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.
Verbal cognition vector space analysis by Chuluundorj.B
1. 1
Verbal cognition: vector
space analysis
Chuluundorj. B
University of the Humanities, Mongolia
THE 11TH INTERNATIONAL
CONGRESS OF MONGOLISTS
ULAANBAATAR, 2016
2. Quantum brain – Quantum mind
Brain energy transmission – wave/particle duality
Human mental space – quantum semantic space
Deep structures – Mental structures
(Chomsky. N 2000. New horizons in the study
of language and mind. Cambridge)
2
3. Mental lexicon – semantic organization of vocabulary –
human semantic memory
Research question:
Universal principles of mental lexicon – embedding in neural
associative sets
3
6. qEEG and ERP
(quantitative electro-encephalo-graphy and event related potentials)
Assess: amount, time, frequency, localization of brain
activation and behavioral responses during verbal
thinking
Assumptions:
Connection of different classes of words with different
regions of the brain
Neural networks – different classes of words
N – static features
V – dynamic features
Open class of words
Closed class of words
6
7. 7
Brain electric waves involved in verbal thinking:
P300 – word and object recognition, working memory,
semantic congruity, decision making, novelty processing,
lie detection
P600 – word and semantic memory, syntactic congruity
N100 – cognitive flexibility, stimuli matching, expectancy
N200 - word and object recognition, semantic congruity,
cognitive inhibition
N400 – semantic congruity, semantic memory, word
decision, comprehension
P200 – working memory, verbal memory
10. 10
Correct word Close meaning Distant meaning
Some results from our study:
P300 wave in brain mapping
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
11. 11
Correct word Close meaning Distant meaning
Conclusion:
P300 wave in brain mapping
Word processing & expression - active in distant word recognition
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
12. 12
Correct word Close meaning Distant meaning
Some results from our study:
N400 wave in brain mapping
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
13. 13
Correct word Close meaning Distant meaning
Some results from our study:
N400 wave in brain mapping
14. 14
Correct word Close meaning Distant meaning
Conclusion:
N400 wave in brain mapping
Confusion by word’s close meaning activates frontal area
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
16. Correct and distant noun meanings activated Broca’s area,
Close noun activated frontal lobe (confusing noun)
16Some results from our study:
NOUN: max power (μV)
“Шил” correct meaning “Толь” close meaning “Арал” distant meaning
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
17. Correct noun - processed fast in most areas,
Close noun – fast in left temporal area,
Distant noun – slow in most areas
17Some results from our study:
NOUN: Reaction Time (sec)
“Шил” correct meaning “Толь” close meaning “Арал” distant meaning
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
18. Correct verb meaning activated frontal,
Close verb – right occipital,
Distant verb – frontal, left parietal areas
18Some results from our study:
VERB: max power (μV)
“Дуулах” correct “Хѳгжимдѳх” close “Унтах” distant
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
19. Correct verb meaning – fastest in left parietal,
Close verb – slow in most,
Distant verb – fast in most, slow in temporal & frontal areas
19Some results from our study:
VERB: Reaction Time (sec)
“Дуулах” correct “Хѳгжимдѳх” close “Унтах” distant
Broca’s
expressive
area
Wernicke’s
perceptive
area
Broca’s
area
Wernicke’s
area
Broca’s
area
Wernicke’s
area
20. 20Some results from our study:
Noun and verb: P300 power
“Шил”
“Толь”
“Дуулах”
“Унтах” “Хѳгжимдѳх”
“Арал”
Broca’s expressive area
Wernicke’s perceptive area
21. 21Some results from our study:
Noun and verb: Reaction time (sec)
“Шил”
“Толь”
“Дуулах”
“Унтах” “Хѳгжимдѳх”
“Арал”
Broca’s expressive area
Wernicke’s perceptive area
23. Object, action (event) tectonics and its characteristics -
Sequence regularities - Neural recurrent networks
Research question:
Mental syntax primitives - Universality in mental mechanism
of blending
23
24. Assumptions
Semantic relationships between nouns, verbs and
adjectives are a reflection of knowledge sequence
represented in prefrontal association cortex.
Phrase structure rules are a reflection of knowledge
sequence in perisylvian pattern-associator networks.
24
26. Word
Sentence
Number processing is similar to syntactic processing.
In numeral grammar, some words combine additively - forty-
three (40+3), whereas others combine multiplicatively:
seven hundred (7x100).
(David, L., Naoch, S., & Aleah, 2013.
Estimating large number C37).
Complex numbers - Complex nouns
“Хар бал” (additively),
“Хар шөнө” (multiplicatively),
“Хар санаа” (multiplicatively)
26
structure - mental blending 40+3
7x100
27. Similar features of object (noun reference) – scalar
multiplication
“Шар, улаан, ногоон бөмбөлөг”
Same direction, but different distances (magnitude)
Main reason → intrinsic and extrinsic features differ in
terms of strength of the association
27
28. “Төмөр хаалгатай модон хашаа”
Same direction, but different magnitude – vector addition
28
𝑅 𝑥=𝐴 𝑥+𝐵𝑥
𝑅 𝑦=𝐴 𝑦+𝐵𝑦
Magnitude of resultant:
𝑅 = 𝑅 𝑥
2
+ 𝑅 𝑦
2
Direction of resultant:
𝜃 𝑅= 𝑡𝑎𝑛−1
𝑅 𝑦
𝑅 𝑥
29. Complex scalar field – perceptual geometry.
High diving – прыжок в воду.
Complex scalar field – vector dot or cross product
29
31. Non-linear thinking - Non-linearity in mental syntax
Superposition and semantic transformation - metaphor
Complex effect of semantic pragmatic forces – vector dot
product
ном
авах оноо
санаа
хар
31
32. ном (book) – weak cohesion, linear association
санаа (idea) – strong cohesion, non-linear association
засах no semantic change, linear
semantically transformed
булаалдах no semantic change
semantically transformed (linear)
a ball (linear)
a disease (non-linear)
32
авах
ширээ
(table)
catch
34. Typologically different languages –
Coordinates of verbal cognition (perceptual geometry) –
mental superposition in multi-dimensional tensor space
“од харвах”
“звезда упала”
“а star is falling”
Mental superposition – a phenomenon related to human
verbal cognition and object of analysis in quantum
semantics
34
35. Conclusions
Vector analysis method in combination with
experimental study is a powerful tool for modeling of
localization of different classes of words in semantic
memory, and of connections of these classes with
different regions of the brain.
Interpretation of word sequences in vector space is an
effective way for analysis of basic rules which regulate
these sequences in typologically different languages.
35
36. References:
1. Chuluundorj, B. 2013. Mathematical Approaches to
Cognitive Linguistics. International Journal of Applied
Linguistics & English literature. Vol. 2 No.4. Australian
International Academic Centre. Australia
2. Chuluundorj, B. 2014. Vector-Based Approach to Verbal
Cognition. Global Journal of Human-Social Science: Arts &
Humanities – Psychology. Vol.14, Issue 3/1.0 Global
Journals Inc. USA.
3. Chuluundorj, B. 2016. Vector Field Analysis of Verbal
Structures. British Journal of Applied Science &
Technology 12(3): 1-7. Science Domain International. UK.
36