Papers by Policarpo Y . Ulianov
Physics & Astronomy International Journal, 2025
Aim: This is a prospective study reporting on the safety and feasibility of an iodinated hydrogel... more Aim: This is a prospective study reporting on the safety and feasibility of an iodinated hydrogel tissue fiducial marker (IH TFM) for image guided radiation therapy in the treatment of muscle invasive bladder cancer. Materials and Methods: From September 2015 to July 2017, four patients diagnosed with muscle invasive unifocal transitional cell carcinoma (TCC) bladder cancer were included in the study. Under general anaesthetic, patients underwent cystoscopic injection of IH into their tumour base. Patients subsequently underwent image guided RT. The total prescription was 64.0-66.0 Gy in 2.0Gy per fraction. Daily online cone-beam CT (CBCT) matching to IH TFM were performed throughout the course of radiation therapy (RT) to verify the extent of daily treatment shifts. IH volume, its stability and visibility were also evaluated. Results: The volume of IH TFM remained consistent over the course of bladder radiotherapy. IH TFM match recorded the largest variations in the supero-inferior (SI) and antero-posterior (AP) directions with the largest geometrical shift of 5 mm was recorded. If bony landmark was used, a margin of up to 17.4 mm in the AP direction would be required to ensure adequate clinical target volume (CTV) coverage. In this study, we found IH TFM to be well tolerated and feasible, with no major adverse events noted as a result of injection. Conclusion: This study demonstrates that IH TFM can be safely injected into the bladder mucosa and can be considered as a fiducial marker for bladder cancer.
To Be Publisher in Int. Journal of Modern Physics D (IJMPD)
This article introduces the Ulianov Gravitational Model (UGM), which provides a novel interpretat... more This article introduces the Ulianov Gravitational Model (UGM), which provides a novel interpretation of gravitational interactions through the Higgs Ulianov Perfect Liquid (HUPL). By deducing Newton's gravitational law and the gravitational constant G from first principles, the UGM bridges empirical observations with fundamental Planck constants. The model also explores the concept of Ulianov wormholes, offering a unified framework that links large-scale phenomena, such as black holes and galaxy clusters, with quantum-scale structures like Planck-length entities. These insights suggest a new path towards a unification theory that may integrates Newtonian mechanics, General Relativity, and Quantum Mechanics.
Physics & Astronomy International Journal, 2024
This paper presents a novel analysis of galaxy formation through the lens of the Small
Bang Mod... more This paper presents a novel analysis of galaxy formation through the lens of the Small
Bang Model, which posits the existence of two distinct types of galaxies generated
by micro black holes: matter galaxies generated by antimatter supermassive black
holes (SMBHs) and antimatter galaxies generated by matter SMBHs. The relationship
between the mass of galaxies and their respective SMBHs is explored, leading to the
derivation of two specific mass ratios: 918 for matter galaxies and 324 for antimatter
galaxies. By using a dataset of 100 galaxies from a reliable source, the research
identifies two separate subsets of galaxies with low measurement error, totaling 41
galaxies. Among these, 31 galaxies (77%) are identified as matter galaxies with a mass
ratio of 918, while 10 galaxies (23%) are classified as antimatter galaxies with a mass
ratio of 324. The analysis reveals that, despite measurement noise, the data aligns
closely with the theoretical predictions for these two distinct types of galaxies.
The research provides a strong indication that galaxies and their SMBHs are governed
by fixed mass relationships, challenging the idea that these relationships are random or nonlinear. This supports the Small Bang Model, which offers a compelling alternative to the Big Bang Model, with no initial singularity and a universe emerging from a lowenergy state. The findings suggest that this model not only explains the formation of spiral galaxies but also accounts for the origin of supermassive black holes at the center of each galaxy. Further study is encouraged, as this discovery opens new avenues for understanding the role of antimatter in the universe and the formation of galaxies.
Physics & Astronomy International Journal, 2024
This article synthesizes insights from three seminal works: Georges-Louis Le Sage's 1783 paper, A... more This article synthesizes insights from three seminal works: Georges-Louis Le Sage's 1783 paper, Albert Einstein's 1935 paper, and Peter Higgs' 1964 paper, along with Isaac Asimov's 1966 paper, which presents a model for the origin of matter and explains the absence of antimatter in our universe. These four foundational works were integrated into the Ulianov Theory, developed by Dr. Policarpo Yoshin Ulianov. The Ulianov Theory proposes a new model of fundamental particles and interactions, leading to a novel theoretical equation for calculating Newton's universal gravitational constant G. This theoretical framework not only addresses criticisms of the Higgs boson model but also provides a robust method for calculating gravitational forces and the value of G .
Begin presente to be published in JHEP , 2004
This article presents a comprehensive examination of Newton's Universal gravitational constant G.... more This article presents a comprehensive examination of Newton's Universal gravitational constant G. We explore recent experimental measurements of G, highlighting the discrepancies between different methods and proposing a new standard value based on a theoretical model developed by Dr. Policarpo Yoshin Ulianov. The Ulianov Gravitational Model integrates principles from seminal works by Georges-Louis Le Sage, Albert Einstein, and Peter Higgs, and introduces an empirical theoretical equation for G that aligns closely with the most accurate experimental values. By analyzing these findings, we aim to resolve the ongoing debate over the precise value of G and suggest a unified approach for future measurements.
Applied Optics, 1998
A filtering algorithm is proposed for processing images generated by TV holography that contain p... more A filtering algorithm is proposed for processing images generated by TV holography that contain phase jumps and a high noise level. This algorithm first performs phase unwrapping without removing the noise. After that, it removes the noise by use of a conventional low-pass filter. The new approach allows for using low-pass filters with narrow passbands, leading to a better signal-to-noise ratio in the desired signal. Simulation results are presented and discussed. The new algorithm has been applied successfully under real conditions in a holographic station.
Journal of Mathematical Techniques and Computational Mathematics, 2024
This paper introduces a groundbreaking advancement in the field of trigonometry: the development ... more This paper introduces a groundbreaking advancement in the field of trigonometry: the development of Elliptical Trigonometry, a new area of mathematics founded on the Ulianov Elliptical Transform. By redefining traditional trigonometric functions to fit elliptical geometries, this research establishes a new framework for understanding and calculating angles, distances, and trajectories in elliptical shapes. These functions—elliptical cosine and sine—extend beyond the traditional applications, providing tools for more precise modeling in fields such as astrophysics, designer, and aerospace engineering. The potential impact of this discovery, akin to the historical significance of prime numbers and Boolean logic, opens new pathways in mathematical research and applied sciences.
Journal of Modern Physics, 2016
This article presents a new type of whitening filter (allowing the “passing” of some noise source... more This article presents a new type of whitening filter (allowing the “passing” of some noise sources) applied to process the data recorded in LIGO’s GW150914 and GW151226 events. This new analysis shows that in the GW150914 event, the signals from the collision of two black holes are very similar to the 32.5 Hz noise sources observed in both of LIGO’s detectors. It also points out that these 32.5 Hz noise sources are powered by a 30 Hz sub harmonic, coming from the 60 Hz power system.
In the GW1226 event, the same analysis points out that the NR template is very similar to the 120 Hz noise source. Therefore, the signals recorded in these events were probably generated by some small changes with the 60 Hz frequency in the US power grid. This can be caused, for example, by a power variation in the DC link, which can appear in both detectors in the same 10 ms time window. As this kind of power grid occurrence did not change the voltage levels, it may have gone unnoticed by LIGO’s electrical power supply’s monitoring system.
Physics & Astronomy International Journal - In publishing phase, 2024
This paper presents the Ulianov Orbital Model (UOM), a simplified approach to two-body orbital me... more This paper presents the Ulianov Orbital Model (UOM), a simplified approach to two-body orbital mechanics. Unlike the traditional Keplerian or Newtonian models, which require six parameters to describe an orbit, the Ulianov model uses only five parameters because the ellipse shape is achieved through the Ulianov Ellipse parameter \(U_e\), which encapsulates the influence of the primary body's mass and gravitational constant, as well as the shape of the orbit (which can define an ellipse, parabola, or hyperbola).
The Ulianov model is particularly advantageous for scenarios involving collisions or close encounters, or the launch of probes and satellites where the minimum orbital distance and maximum orbital velocity are critical factors directly provided as basic parameters in the UOM. Additionally, the UOM defines a numerical procedure that can calculate elliptical orbits without using gravitational forces or accelerations, allowing for larger time intervals to be used in simulations. This avoids the error increase that typically occurs in Newtonian numerical procedures when the time interval is not very small.
The UOM also provides equations to calculate the standard ellipse parameters (a and b) and orbital trajectories and velocities from three UOM basic parameters (Ue, R0 and V_0). It introduces a new kind of elliptical trigonometric functions, named the Ulianov Elliptical Cosine and Ulianov Elliptical Sine, which simplify plotting orbital trajectories and their velocities over time and in elliptical angular steps.
All these innovative results were obtained using a new mathematical tool called the Ulianov Elliptic Transform (UET). The UET, using only arithmetic operations, generates an impressive effect of rotating and scaling an ellipse, transferring its center from one of the foci to the geometric center of the ellipse. The UET offers a new and easy way to create and manipulate ellipses using both numerical and analytical methods.
To be published, 2024
The Proton Size Enigma refers to the discrepancy in measured proton radii when using different pr... more The Proton Size Enigma refers to the discrepancy in measured proton radii when using different probing particles-electrons versus muons. While traditional measurements using electron-proton scattering provided a standard value for the proton radius, recent experiments involving muonic hydrogen have revealed a significantly smaller proton radius. This discrepancy has sparked considerable debate and prompted further investigation into the true size of the proton. This paper addresses the issue using the Ulianov Theory, which integrates concepts from classical and modern physics to propose a unified framework. By examining the structural and dynamic properties of protons within this theory, we aim to reconcile the differing experimental results and offer a novel theoretical solution to the Proton Size Puzzle.
To be published, 2024
This article presents a comprehensive examination of Newton's universal gravitational constant G.... more This article presents a comprehensive examination of Newton's universal gravitational constant G. We explore recent experimental measurements of G, highlighting the discrepancies between different methods and proposing a new standard value based on a theoretical model developed by Dr. Policarpo Yoshin Ulianov. The Ulianov Gravitational Model integrates principles from seminal works by Georges-Louis Le Sage, Albert Einstein, and Peter Higgs, and introduces an empirical theoretical equation for G that aligns closely with the most accurate experimental values. By analyzing these findings, we aim to resolve the ongoing debate over the precise value of G and suggest a unified approach for future measurements.
To Be Published
The Proton Size Enigma refers to the discrepancy in measured proton radii when using different pr... more The Proton Size Enigma refers to the discrepancy in measured proton radii when using different probing particles-electrons versus muons. While traditional measurements using electron-proton scattering provided a standard value for the proton radius, recent experiments involving muonic hydrogen have revealed a significantly smaller proton radius. This discrepancy has sparked considerable debate and prompted further investigation into the true size of the proton. This paper addresses the issue using the Ulianov Theory, which integrates concepts from classical and modern physics to propose a unified framework. By examining the structural and dynamic properties of protons within this theory, we aim to reconcile the differing experimental results and offer a novel theoretical solution to the Proton Size Puzzle.
Physics & Astronomy International Journal , 2024
which presents a model for the origin of matter and explains the absence of antimatter in our uni... more which presents a model for the origin of matter and explains the absence of antimatter in our universe. These four foundational works were integrated into the Ulianov Theory, developed by Dr. Policarpo Yoshin Ulianov. The Ulianov Theory proposes a new model of fundamental particles and interactions, leading to a novel theoretical equation for calculating Newton's universal gravitational constant G. This theoretical framework not only addresses criticisms of the Higgs boson model but also provides a robust method for calculating gravitational forces and the value of G.
TO BE PUBLISHED, 2024
The Ulianov Atomic Model (UAM) presents a revolutionary approach to understanding atomic structur... more The Ulianov Atomic Model (UAM) presents a revolutionary approach to understanding atomic structures and interactions, diverging significantly from traditional models reliant on W and Z bosons and strong and weak nuclear forces. This paper explores the UAM, which replaces these forces with the Strong Gravitational Contact Force (SGCF) and utilizes the true shapes of proton and electron membranes to provide a more profound understanding of atomic behavior. In the Ulianov Atomic Model, atomic nucleons are modeled by Kepler Ulianov Proton Trees (KUPT), and electrons follow a Ulianov Electron Distribution (UED). By examining the UAM, we gain insights into the formation of hydrogen and helium atoms, the stability of nucleons, and the potential applications of this model in nuclear reactors and the creation of room-temperature superconductors.
TO BE PUBLISHED
This paper presents a new model of gravitation based on Le Sage's 1782 model of gravitational pre... more This paper presents a new model of gravitation based on Le Sage's 1782 model of gravitational pressure, the Higgs field, and the concepts of Ulianov Wormholes (UWH). This model proposes that the universe is filled with a Higgs Ulianov Perfect Liquid (HUPL) under Planck pressure. Building on historical and contemporary theories, the Ulianov Gravitational Model integrates and extends the works of Le Sage, Einstein, and Higgs to form the foundational pillars of this new framework. This paper is based in the high pressure of the HUPL, that is reduced by space-times distortions generated by Ulianov Wormholes, and deduce fundamental physical laws, including Newton's Law of Gravitation and the Schwarzschild metric. The criticisms of Le Sage's gravitational model are addressed by examining the behavior of the Higgs Ulianov Perfect Liquid under pressure and the spacetime distortions provided by the Einstein-Rosen bridges. By addressing the limitations of previous models, the Ulianov Gravitational Model aims to provide a comprehensive framework that bridges General Relativity, Quantum Mechanics, and Newtonian Mechanics. This model potentially lays the groundwork for a new unified theory or Theory of Everything, offering explanations for various observable phenomena and contributing to the advancement of theoretical physics.
TO BE PUBLISHED IN A BOOK , 2024
This article introduces several conceptual bridges that connect ancient theories with modern and ... more This article introduces several conceptual bridges that connect ancient theories with modern and contemporary frameworks in physics. These bridges link general relativity with quantum mechanics, Newtonian mechanics, and string theory. They connect protons and neutrons within atomic nuclei, electrons in orbitals, and molecular bonds, potentially leading to the concept of superelectrons. They also explain the fusion of heavy hydrogen atoms in the solar core to form helium. The Einstein-Rosen-Ulianov bridges connect four parallel universes in the Asimov-Ulianov Universe and integrate them into the General Oct-Dimension Universe (GODU). This collection of models, termed the Ulianov Theory (UT), comprises the following components:
TO BE PUBLISHED, 2024
Einstein's 1935 paper, "The Particle Problem in the General Theory of Relativity," is a notable a... more Einstein's 1935 paper, "The Particle Problem in the General Theory of Relativity," is a notable attempt to develop a Unified Theory or a "Theory of Everything," introducing the concept of wormholes. Critics suggested Einstein might have been senile towards the end of his life, as he dismissed the necessity of nuclear forces to obtain a Unified Theory, because, for Einstein, nuclear forces were unnecessary. In 2024, Dr. Ulianov's comprehensive Ulianov Theory (UT) continued the Einstein-Rosen bridge concept with Ulianov Wormholes, integrating the high pressure generated by the Higgs field and introducing a new String Theory that models the proton masses on the proton sphere surface, allowing two proton masses to come into contact at distances on the order of the Planck length. This proton model introduces the concept of the Strong Gravitational Contact Force (SGCF), explaining the bonding of protons and neutrons in atomic nucleons and leading to a new model for the organization of protons and neutrons in layers inside atomic nucleons. The SGCF, which emerges when particle masses come into direct contact, also explains the pairing of two electrons within the same atomic orbital and the formation of molecules and metallic structures from electron mass connections, further vindicating Einstein's view on the redundancy of nuclear forces.
To be pubblished, 2024
This article synthesizes insights from two seminal works: Einstein's 1935 paper, "The Particle Pr... more This article synthesizes insights from two seminal works: Einstein's 1935 paper, "The Particle Problem in the General Theory of Relativity," and Higgs' 1964 paper that introduced the Higgs boson. Einstein's work, a notable attempt to develop a Unified Theory or a "Theory of Everything", introduced the concept of wormholes but failed to unify all forces because it exclude nuclear forces. Critics suggested Einstein might have been senile towards the end of his life, as he dismissed the necessity of nuclear forces. In contrast, Higgs' work completed the Standard Model of particles by assigning mass to particles through the Higgs boson, although it did not enable the calculation of particle masses or fundamental physical laws. In 1966, Isaac Asimov proposed a model of the universe shaped like a four-leaf clover with four parallel universes, which Dr. Ulianov expanded in 2007, naming the spaces and associating elastic holes with time and space walls, calling them Ulianov Holes (Uholes). These expanded into Planck Ulianov Spheres (PUS), forming a network that behaves like a perfect Ulianov liquid (UPL) under Planck pressure and density. By 2024, Dr. Ulianov's comprehensive Ulianov Theory (UT) continued the Einstein-Rosen bridge concept with Ulianov Wormholes, integrating the high pressure generated by the Higgs field. UT bridges General Relativity, Quantum Mechanics, and Newtonian Mechanics, using the Higgs boson to create a Higgs Ulianov Perfect Liquid (HUPL). This unified model allows for the deduction of classical physics, GR, and QM equations, and also resolves classical physics problems and enigmas, potentially forming a new path that can lead to the Theory of Everything. Criticisms of excluding nuclear forces in the Einstein-Rosen bridge model are addressed by demonstrating that SGCF (Strong Gravitational Contact Forces) emerge when proton and neutron masses come into direct contact, offering a more complete atomic nucleus model and vindicating Einstein's view on the redundancy of nuclear forces.
National Library of Brazil,, 2007
This book presents a model named Ulianov Theory (UT) that creates a fictional universe in a "slow... more This book presents a model named Ulianov Theory (UT) that creates a fictional universe in a "slow" process named “Small Bang”. The UT is based on three basic concepts: a) General Octo-Dimension Universe (GODU) - Space/time of eight dimensions where four of them are “normal dimensions” and four are “wraps dimensions”, and the time is a complex variable. The GODU also can be represented like for sub-spaces (each one whit three space dimensions and one complex time dimension) separated from each other by “time walls” and “space walls”. b) Sphere Ulianov (Usphere) - Eight dimension spheres placed in GODU that held together to form special networks. c) Hole Ulianov (Uhole) – The Uhole is an Usphere with zero radius and behaves as an elastic hole. One Uhole in a “time wall” have a mass propriety and “resist” to move in space. One Uhole in a “space wall” have a electrical charge propriety and “resist” to move in time. The Small Bang begin whit one Uhole compressed by a radial force field (General Octo-Dimension Hole Force or GODHF). When the GODHF is removed, the Uhole expand and form one Usphere. Like the Usphere “wall” is made of Uholes, it’s also expand forming a Ulianov SpereNetworks (USN). Like the USN initially expands only in imaginary time, to an observer in real time the “Small Bang Process” is instantaneous and will look like a Big Bang . The UT model is defined over a complete scope, were the concepts of, force (Ulianov Force) and energy (Ulianov Energy) are defined from the Uhole elasticity propriety. Based on these concepts the UT generated a fictional universe that begins in a Small Bang, from which arise particles similar to photons (Ulianov foton) electrons (Ulianov electron), protons (Ulianov proton), neutrons (Ulianov neutron), and neutrinos (Ulianov neutrino). The UT model does a series of equations who are linked to laws observed in our universe, as the formulas of Newton gravitation law and Einstein's relativistic equations. On this way the author note that despite the UT model is set to create a universe fictional, coincidentally it’s generated one universe that is very close to the universe in which we live… This book was written in 2005 and registered in the National Library of Brazil, on 10.05.2007, with registration number 404616, in Book 754, Page 276. The text of the book is in Portuguese.
Annals of Computational Physics and Material Science, 2024
The Small Bang Model (SBM) introduces a revolutionary framework for the genesis of the universe, ... more The Small Bang Model (SBM) introduces a revolutionary framework for the genesis of the universe, challenging conventional cosmological theories. By suggesting the universe originated from a zero-mass state, facilitated by antimatter black holes, the SBM provides fresh insights into galaxy formation and the distribution of matter and antimatter. This paper outlines the SBM's foundational principles, contrasts it with the Big Bang theory, and highlights its potential to resolve longstanding cosmological puzzles. Notably, it presents empirical validations demonstrating distinct mass relationships between supermassive black holes and their host galaxies, supporting a novel classification into matter and antimatter galaxies. The Small Bang model is founded on two pivotal concepts: the theory of Cosmic Inflation and the principle of 'Shunyata Universe's Gene-sis' (or 'Emptiness Universe's Genesis'), a framework envisioning the universe's inception as small, empty, and cold, entirely devoid of matter or energy. These SBM findings offer a groundbreaking perspective on the early universe's dynamics and the distribution of cosmic matter, deepening our understanding of cosmic inflation. Consequently, we invite physicists to study, comprehend, and assess the new cosmological model proposed by the Small Bang Model.
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Papers by Policarpo Y . Ulianov
Bang Model, which posits the existence of two distinct types of galaxies generated
by micro black holes: matter galaxies generated by antimatter supermassive black
holes (SMBHs) and antimatter galaxies generated by matter SMBHs. The relationship
between the mass of galaxies and their respective SMBHs is explored, leading to the
derivation of two specific mass ratios: 918 for matter galaxies and 324 for antimatter
galaxies. By using a dataset of 100 galaxies from a reliable source, the research
identifies two separate subsets of galaxies with low measurement error, totaling 41
galaxies. Among these, 31 galaxies (77%) are identified as matter galaxies with a mass
ratio of 918, while 10 galaxies (23%) are classified as antimatter galaxies with a mass
ratio of 324. The analysis reveals that, despite measurement noise, the data aligns
closely with the theoretical predictions for these two distinct types of galaxies.
The research provides a strong indication that galaxies and their SMBHs are governed
by fixed mass relationships, challenging the idea that these relationships are random or nonlinear. This supports the Small Bang Model, which offers a compelling alternative to the Big Bang Model, with no initial singularity and a universe emerging from a lowenergy state. The findings suggest that this model not only explains the formation of spiral galaxies but also accounts for the origin of supermassive black holes at the center of each galaxy. Further study is encouraged, as this discovery opens new avenues for understanding the role of antimatter in the universe and the formation of galaxies.
In the GW1226 event, the same analysis points out that the NR template is very similar to the 120 Hz noise source. Therefore, the signals recorded in these events were probably generated by some small changes with the 60 Hz frequency in the US power grid. This can be caused, for example, by a power variation in the DC link, which can appear in both detectors in the same 10 ms time window. As this kind of power grid occurrence did not change the voltage levels, it may have gone unnoticed by LIGO’s electrical power supply’s monitoring system.
The Ulianov model is particularly advantageous for scenarios involving collisions or close encounters, or the launch of probes and satellites where the minimum orbital distance and maximum orbital velocity are critical factors directly provided as basic parameters in the UOM. Additionally, the UOM defines a numerical procedure that can calculate elliptical orbits without using gravitational forces or accelerations, allowing for larger time intervals to be used in simulations. This avoids the error increase that typically occurs in Newtonian numerical procedures when the time interval is not very small.
The UOM also provides equations to calculate the standard ellipse parameters (a and b) and orbital trajectories and velocities from three UOM basic parameters (Ue, R0 and V_0). It introduces a new kind of elliptical trigonometric functions, named the Ulianov Elliptical Cosine and Ulianov Elliptical Sine, which simplify plotting orbital trajectories and their velocities over time and in elliptical angular steps.
All these innovative results were obtained using a new mathematical tool called the Ulianov Elliptic Transform (UET). The UET, using only arithmetic operations, generates an impressive effect of rotating and scaling an ellipse, transferring its center from one of the foci to the geometric center of the ellipse. The UET offers a new and easy way to create and manipulate ellipses using both numerical and analytical methods.
Bang Model, which posits the existence of two distinct types of galaxies generated
by micro black holes: matter galaxies generated by antimatter supermassive black
holes (SMBHs) and antimatter galaxies generated by matter SMBHs. The relationship
between the mass of galaxies and their respective SMBHs is explored, leading to the
derivation of two specific mass ratios: 918 for matter galaxies and 324 for antimatter
galaxies. By using a dataset of 100 galaxies from a reliable source, the research
identifies two separate subsets of galaxies with low measurement error, totaling 41
galaxies. Among these, 31 galaxies (77%) are identified as matter galaxies with a mass
ratio of 918, while 10 galaxies (23%) are classified as antimatter galaxies with a mass
ratio of 324. The analysis reveals that, despite measurement noise, the data aligns
closely with the theoretical predictions for these two distinct types of galaxies.
The research provides a strong indication that galaxies and their SMBHs are governed
by fixed mass relationships, challenging the idea that these relationships are random or nonlinear. This supports the Small Bang Model, which offers a compelling alternative to the Big Bang Model, with no initial singularity and a universe emerging from a lowenergy state. The findings suggest that this model not only explains the formation of spiral galaxies but also accounts for the origin of supermassive black holes at the center of each galaxy. Further study is encouraged, as this discovery opens new avenues for understanding the role of antimatter in the universe and the formation of galaxies.
In the GW1226 event, the same analysis points out that the NR template is very similar to the 120 Hz noise source. Therefore, the signals recorded in these events were probably generated by some small changes with the 60 Hz frequency in the US power grid. This can be caused, for example, by a power variation in the DC link, which can appear in both detectors in the same 10 ms time window. As this kind of power grid occurrence did not change the voltage levels, it may have gone unnoticed by LIGO’s electrical power supply’s monitoring system.
The Ulianov model is particularly advantageous for scenarios involving collisions or close encounters, or the launch of probes and satellites where the minimum orbital distance and maximum orbital velocity are critical factors directly provided as basic parameters in the UOM. Additionally, the UOM defines a numerical procedure that can calculate elliptical orbits without using gravitational forces or accelerations, allowing for larger time intervals to be used in simulations. This avoids the error increase that typically occurs in Newtonian numerical procedures when the time interval is not very small.
The UOM also provides equations to calculate the standard ellipse parameters (a and b) and orbital trajectories and velocities from three UOM basic parameters (Ue, R0 and V_0). It introduces a new kind of elliptical trigonometric functions, named the Ulianov Elliptical Cosine and Ulianov Elliptical Sine, which simplify plotting orbital trajectories and their velocities over time and in elliptical angular steps.
All these innovative results were obtained using a new mathematical tool called the Ulianov Elliptic Transform (UET). The UET, using only arithmetic operations, generates an impressive effect of rotating and scaling an ellipse, transferring its center from one of the foci to the geometric center of the ellipse. The UET offers a new and easy way to create and manipulate ellipses using both numerical and analytical methods.
As these uBH grew, they became supermassive black holes (SMBH) that played a fundamental role in the generation of galaxies. The SMBHs of antimatter, by consuming antimatter, expelled matter in large spirals, forming the observed spiral galaxies, such as the Milky Way. This process resulted in galaxies composed predominantly of matter, while antimatter remained confined within the SMBHs.
The Small Bang model offers explanations for several unanswered questions by the Big Bang model, including the origin of matter and the observed absence of antimatter in the universe. Additionally, it provides a rationale for the presence of supermassive black holes at the center of each spiral galaxy and why the mass of these black holes is significantly less than the mass of the galaxies they originated.
Analyses of astronomical data support the Small Bang model, showing that the mass of galaxies is approximately 1,000 times greater than that of SMBHs in matter galaxies and 200 times greater in antimatter galaxies. This result aligns with the theoretical predictions of the model, reinforcing its viability as a new theory to understand the structure of the universe.
In summary, the Small Bang model emerges as a promising theory, capable of providing valuable insights into the formation of the universe, the distribution of matter and antimatter, and the role of black holes in cosmic evolution, challenging established paradigms and paving the way for new discoveries in cosmology.
Conforme esses uBH cresceram, tornaram-se buracos negros supermassivos (SMBH) que desempenharam um papel fundamental na geração das galáxias. Os SMBH de antimatéria, ao consumirem antimatéria, expeliram matéria em grandes espirais, formando as galáxias espirais observadas, como a Via Láctea. Este processo resultou em galáxias compostas majoritariamente por matéria, enquanto a antimatéria permaneceu confinada dentro dos SMBH.
O modelo Small Bang oferece explicações para várias questões não resolvidas pelo modelo do Big Bang, incluindo a origem da matéria e a ausência observada de antimatéria no universo. Adicionalmente, ele fornece uma justificativa para a presença de buracos negros supermassivos no centro de cada galáxia espiral e a razão pela qual a massa desses buracos negros é significativamente menor do que a massa das galáxias que eles originaram.
Análises de dados astronômicos sustentam o modelo Small Bang, mostrando que a massa das galáxias é aproximadamente 1.000 vezes maior do que a dos SMBH em galáxias de matéria e 200 vezes maior em galáxias de antimatéria. Este resultado está em concordância com as previsões teóricas do modelo, reforçando sua viabilidade como uma nova teoria para entender a estrutura do universo.
Em resumo, o modelo Small Bang emerge como uma teoria promissora, capaz de fornecer insights valiosos sobre a formação do universo, a distribuição de matéria e antimatéria e o papel dos buracos negros na evolução cósmica, desafiando os paradigmas estabelecidos e abrindo caminho para novas descobertas na cosmologia.
"... IIf in the future there is some type of SCPS that is characterized as a “Strong AI”, (that passes the Turing test with users thinking that they are talking to a person, not realizing that they are conversing via text or natural language with a digital computer) , can be constructed, this SCPS will probably be based on the connectionist paradigm. ANNs with hundreds of layers (with thousands or even millions of connections in each layer) must be used, organized in several interconnected blocks in innovative ways and with a great capacity for symbolic information processing, combined with ways of interacting with the world through means of processing and generating audio (natural language) and video (including still images and handwritten texts) and iteration with robotic mechanisms. This SCPS must actually perceive the real world and act on it to become a “Strong AI”. As in the connectionist model, information is spread throughout the network, the greater the number of neurons and layers, the more information can be stored. The human brain, for example, has almost 100 million neurons, with a typical neuron having 100 to 1000 connections, generating a total of between 10 and 100 billion connections. The connectionist “Strong AI” system that we are envisioning must have at least the capacity to retain information equivalent to that which a human brain stores. If it is a smaller amount of information, the ANN cannot become intelligent, in the same way that a cat's neural network is too small for a cat to be intelligent (like the talking cats in children's stories) because the size of the cat's brain is much smaller than the human brain and therefore, it will never be able to retain enough information for the cat to become intelligent. Estimating that a properly trained ANN can be 100 times more efficient than a human brain in encoding information, due to the more specific training process used in the ANN (training of smaller parts with backpropagation, something that obviously does not exist in a human brain), A “smart” ANN must have at least a number of neural connections (network weights, with each weight being stored in one or two bytes of information) equal to 1% of the connections existing in a human brain. This would be in the range of 100 million to a billion connections, in a total of 1 to 10 million neurons. Along this path, the big problem to be faced will be how to organize the hundreds of layers of individual networks, as these 10 million neurons cannot be integrated into a single network, but must be divided into something like, for example, a thousand blocks with 10 thousand neurons each, and with hundreds of layers of neurons in each block. Furthermore, new training schemes must be developed, as it is impossible to use any type of backpropagation training on a set of one billion connections. The blocks or sub-blocks will probably be trained separately and in this smaller context backpropagation training techniques can be implemented. An interesting fact that should happen in the case of an SCPS formed by an ANN containing between 1 and 10 million neurons becomes a “Strong AI”, is that the creators of the network will not be able to explain where the ANN stores the symbols or how the symbols are processed inside the network, nor how ANN actually became intelligent, in the same way that we cannot explain how the human brain stores and encodes the symbols it uses, or how human intelligence emerges from the natural neural network that exists in our brains. . "
This text written in 1997 became reality 25 years later with OpenAI's Chat-GPT.
See the full text in Portuguese of 175 pages in the attached PDF.
The first contribution is a methodology to define scales for the measurement of parameters related to the degree of natural and artificial intelligence of cognitive agents. Such a measurement type is of fundamental importance for the effective improvement of intelligent systems, since it permits to quantify certain classes of "intelligence".
The second and the most important contribution of this thesis is the development of a processing model based on an approach termed "transition schemes". This model breaks the traditional paradigm of the signal processing systems (input-system-output), which does not make distinction between inputs and outputs. The proposed model permits a hierarchy of the control structures of a cognitive agent, which can be separately trained making it possible to learn very quickly complex procedures; such procedures could not be effectively carried out by traditional models.
Finally, in the third part of this thesis, we have introduced a new memory model named holographic associative memory. This type of memory presents comparable characteristics to that of a human memory, which can be implemented through artificial neural networks using a data configuration based on random weight patterns to store the desired information.
The results obtained in this study are consequences of the use of a holistic approach, which, besides from the traditional areas of engineering and computation, have borrowed from other areas as psychology, philosophy and human sciences, by using both the Jean Piaget's constructivist model and Charles Pierce's semiotic model.
Texto em portugues.
Three new algorithms for Electronic Holography image processing are presented:
i) an Amplitude Weighting Filter, that optimizes the filtering process, based on the noise level of each pixel;
ii) an Unwrapping by Phase Error Energy Minimization Algorithm, that removes the phase jumps using the information of all pixels at the same time;
iii) a Filtering After Unwrapping Algorithm, which uses a narrow-band low pass filter to eliminate the phase noise.
In the Amplitude Weighting Filter a new low-pass filter structure is proposed. This structure is generic and can be applied to processing signals with weighting noise. A new mathematical model for the noise in Electronic Holography is also presented.
These algorithms are considered original and present better results than the conventional algorithms. The algorithms were developed analytically and evaluated by computing simulation and also experimentally on a holographic station.
"... IIf in the future there is some type of SCPS that is characterized as a “Strong AI”, (that passes the Turing test with users thinking that they are talking to a person, not realizing that they are conversing via text or natural language with a digital computer) , can be constructed, this SCPS will probably be based on the connectionist paradigm. ANNs with hundreds of layers (with thousands or even millions of connections in each layer) must be used, organized in several interconnected blocks in innovative ways and with a great capacity for symbolic information processing, combined with ways of interacting with the world through means of processing and generating audio (natural language) and video (including still images and handwritten texts) and iteration with robotic mechanisms. This SCPS must actually perceive the real world and act on it to become a “Strong AI”. As in the connectionist model, information is spread throughout the network, the greater the number of neurons and layers, the more information can be stored. The human brain, for example, has almost 100 million neurons, with a typical neuron having 100 to 1000 connections, generating a total of between 10 and 100 billion connections. The connectionist “Strong AI” system that we are envisioning must have at least the capacity to retain information equivalent to that which a human brain stores. If it is a smaller amount of information, the ANN cannot become intelligent, in the same way that a cat's neural network is too small for a cat to be intelligent (like the talking cats in children's stories) because the size of the cat's brain is much smaller than the human brain and therefore, it will never be able to retain enough information for the cat to become intelligent. Estimating that a properly trained ANN can be 100 times more efficient than a human brain in encoding information, due to the more specific training process used in the ANN (training of smaller parts with backpropagation, something that obviously does not exist in a human brain), A “smart” ANN must have at least a number of neural connections (network weights, with each weight being stored in one or two bytes of information) equal to 1% of the connections existing in a human brain. This would be in the range of 100 million to a billion connections, in a total of 1 to 10 million neurons. Along this path, the big problem to be faced will be how to organize the hundreds of layers of individual networks, as these 10 million neurons cannot be integrated into a single network, but must be divided into something like, for example, a thousand blocks with 10 thousand neurons each, and with hundreds of layers of neurons in each block. Furthermore, new training schemes must be developed, as it is impossible to use any type of backpropagation training on a set of one billion connections. The blocks or sub-blocks will probably be trained separately and in this smaller context backpropagation training techniques can be implemented. An interesting fact that should happen in the case of an SCPS formed by an ANN containing between 1 and 10 million neurons becomes a “Strong AI”, is that the creators of the network will not be able to explain where the ANN stores the symbols or how the symbols are processed inside the network, nor how ANN actually became intelligent, in the same way that we cannot explain how the human brain stores and encodes the symbols it uses, or how human intelligence emerges from the natural neural network that exists in our brains. . "
This text written in 1997 became reality 25 years later with OpenAI's Chat-GPT.
See the full text in Portuguese of 175 pages in the attached PDF.