Ratio of Quark Masses in Duality Theories

We consider N=2 SU(2) Seiberg-Witten duality theory for models with N_f=2 and N_f=3 quark flavors. We investigate arbitrary large bare mass ratios between the two or three quarks at the singular points. For N_f=2 we explore large bare mass ratios corresponding to a singularity in the strong coupling region. For N_f=3 we determine the location of both strong and weak coupling singularities that produce specific large bare mass ratios.Comment: 12 pages. Standard Latex. Version appearing in Mod. Phys. Lett.

Investigation of Quasi--Realistic Heterotic String Models with Reduced Higgs Spectrum

Quasi--realistic heterotic-string models in the free fermionic formulation typically contain an anomalous U(1), which gives rise to a Fayet-Iliopolous term that breaks supersymmetry at the one--loop level in string perturbation theory. Supersymmetry is restored by imposing F- and D-flatness on the vacuum. In Phys. Rev. D 78 (2008) 046009, we presented a three generation free fermionic standard-like model which did not admit stringent F- and D-flat directions, and argued that the all the moduli in the model are fixed. The particular property of the model was the reduction of the untwisted Higgs spectrum by a combination of symmetric and asymmetric boundary conditions with respect to the internal fermions associated with the compactified dimensions. In this paper we extend the analysis of free fermionic models with reduced Higgs spectrum to the cases in which the SO(10) symmetry is left unbroken, or is reduced to the flipped SU(5) subgroup. We show that all the models that we study in this paper do admit stringent flat directions. The only examples of models that do not admit stringent flat directions remain the strandard-like models of reference Phys. Rev. D 78 (2008) 046009.Comment: 38 pages, 1 figur

Learning Functions Generated by Randomly Initialized MLPs and SRNs

In this paper, nonlinear functions generated by randomly initialized multilayer perceptrons (MLPs) and simultaneous recurrent neural networks (SRNs) and two benchmark functions are learned by MLPs and SRNs. Training SRNs is a challenging task and a new learning algorithm - PSO-QI is introduced. PSO-QI is a standard particle swarm optimization (PSO) algorithm with the addition of a quantum step utilizing the probability density property of a quantum particle. The results from PSO-QI are compared with the standard backpropagation (BP) and PSO algorithms. It is further verified that functions generated by SRNs are harder to learn than those generated by MLPs but PSO-QI provides learning capabilities of these functions by MLPs and SRNs compared to BP and PSO

Learning Nonlinear Functions with MLPs and SRNs

In this paper, nonlinear functions generated by randomly initialized multilayer perceptrons (MLPs) and simultaneous recurrent neural networks (SRNs) are learned by MLPs and SRNs. Training SRNs is a challenging task and a new learning algorithm - DEPSO is introduced. DEPSO is a standard particle swarm optimization (PSO) algorithm with the addition of a differential evolution step to aid in swarm convergence. The results from DEPSO are compared with the standard backpropagation (BP) and PSO algorithms. It is further verified that functions generated by SRNs are harder to learn than those generated by MLPs but DEPSO provides better learning capabilities for the functions generated by MLPs and SRNs as compared to BP and PSO. These three algorithms are also trained on several benchmark functions to confirm results

Initial Systematic Investigations of the Landscape of Low Layer NAHE Extensions

The discovery that the number of physically consistent string vacua is on the order of 10^500 has prompted several statistical studies of string phenomenology. Contained here is one such study that focuses on the Weakly Coupled Free Fermionic Heterotic String (WCFFHS) formalism. Presented are systematic extensions of the well-known NAHE (Nanopoulos, Antoniadis, Hagelin, Ellis) set of basis vectors, which have been shown to produce phenomenologically realistic models. Statistics related to the number of U(1)'s, gauge group factors, non-Abelian singlets, ST SUSYs, as well as the gauge groups themselve are discussed for the full range of models produced as well as models containing GUT groups only. Prior results of other large-scale investigations are compared with these regarding the aforementioned quantities. Statistical coupling between the gauge groups and the number of ST SUSYs is also discussed, and it was found that for order-3 extensions there are more models with enhanced ST SUSY when there is an exceptional group present. Also discussed are some three-generation GUT models found in the data sets. These models are unique because they come from basis vectors which still have a geometric interpretation -- there are no "rank-cuts" in these models.Comment: 65 Pages, 31 Tables, 31 Figure

Stringent Phenomenological Investigation into Heterotic String Optical Unification

For the weakly coupled heterotic string (WCHS) there is a well-known factor of twenty conflict between the minimum string coupling unification scale, Lambda_H ~5x10^(17) GeV, and the projected MSSM unification scale, Lambda_U ~ 2.5x10^(16) GeV, assuming an intermediate scale desert (ISD). Renormalization effects of intermediate scale MSSM-charged exotics (ISME) (endemic to quasi-realistic string models) can resolve this issue, pushing the MSSM scale up to the string scale. However, for a generic string model, this implies that the projected Lambda_U unification under ISD is accidental. If the true unification scale is 5.0x10^(17) GeV, is it possible that illusionary unification at 2.5x10^(17) GeV in the ISD scenario is not accidental? If it is not, then under what conditions would the assumption of ISME in a WCHS model imply apparent unification at Lambda_U when ISD is falsely assumed? Geidt's "optical unification" suggests that Lambda_U is not accidental, by offering a mechanism whereby a generic MSSM scale Lambda_U < Lambda_H is guaranteed. A WCHS model was constructed that offers the possibility of optical unification, depending on the availability of anomaly-cancelling flat directions meeting certain requirements. This paper reports on the systematic investigation of the optical unification properties of the set of stringent flat directions of this model. Stringent flat directions can be guaranteed to be F-flat to all finite order (or to at least a given finite order consistent with electroweak scale supersymmetry breaking) and can be viewed as the likely roots of more general flat directions. Analysis of the phenomenology of stringent flat directions gives an indication of the remaining optical unification phenomenology that must be garnered by flat directions developed from them.Comment: standard latex, 18 pages of tex

Leveraging natural language processing for comprehensive studies of science student projects

Student research projects are a crucial part of the Australian and New South Wales (NSW) High School Curriculum. In NSW, the extension science course offered for the Higher School Certificate is an example of an extensive project performed by students. The objective of the course is to provide students the opportunity to authentically apply scientific research skills. Extension science and related courses for high school students are commonly assessed through scientific reports submitted as a final summative assessment (Science Extension | NSW Education Standards, n.d.). This gives rise to large volumes of disparate data which can potentially be analysed for insights to improve science teaching and learning. Understanding these insights are especially important for priority groups to increase accessibility and equity and reduce academic attainment gaps in science. Previous research analysing student projects has been limited to studying small numbers of projects, due to the availability of data and the time taken for manual data analysis. This also limits analyses to single diversity variables, such as ethnicity (Carlone &amp; Johnson, 2007). There is an opportunity to be realised in the data from student projects that may inform how teachers can better cater for the needs of students in various priority groups moving forward. This study outlines a method to address this research gap, by employing artificial intelligence (AI) capabilities, particularly natural language processing (NLP) techniques, to examine large sets of science high school students' final project reports such as those retained by student science fairs. A range of AI techniques have been evaluated to enable us to process and analyse sizable datasets to explore the rich information they contain. NLP techniques have been developed to classify and analyse projects along various dimensions, such as the alignment with the Field of Research (FoR) codes, the research themes. The dimensions identified will then be analysed and correlated with demographics relating to priority groups. These methods are informing the development of a reliable and repeatable AI-powered framework to analyse research themes, amongst other variables contained within science students’ final project reports. The goal of this framework is to inform the learning design of science projects to increase accessibility, student engagement and inclusion. REFERENCES Carlone, H. B., &amp; Johnson, A. (2007). Understanding the science experiences of successful women of color: Science identity as an analytic lens. Journal of Research in Science Teaching, 44(8), 1187–1218. https://doi.org/10.1002/tea.20237  Science Extension | NSW Education Standards. (n.d.). Retrieved 22 May 2023, from https://educationstandards.nsw.edu.au/wps/portal/nesa/11-12/stage-6-learning-areas/stage-6-science/science-extension-syllabus

An Evaluation of Antibiotic Resistance: Structure-Activity Relationship Studies of Tetracyclic Indolines as A Novel Class of Resistance-Modifying Agents for MRSA & Analysis of Recent FDA Regulations on Antibiotic Use in Livestock

While the rate at which resistance develops against antimicrobials rises, research and development for new antimicrobials declines. By placing selective pressure on bacteria we are inadvertently forcing bacteria into expressing and propagating genes conferring high levels of resistance. Continued misuse and overuse of antibiotics, in light of the evident problem developing, must be resolved. To find a resolve, a multidisciplinary and multifaceted approach must be taken which involves 1) research and development of novel antimicrobial agents and 2) governmental regulation. Strides in new antimicrobial drug development largely revolve around making old antibiotics usable again. Resistance-Modifying Agents (RMAs) act to re-sensitize resistant bacteria to antibiotics through a variety of mechanisms, although currently most target bacterial resistance mechanisms themselves, such as &beta; - lactamases. Foreseeably, while these compounds have shown efficacy and certainly are of value in the present crisis, it is a short-term solution in light of the evidently rapid and dynamic capability of bacteria to respond evolutionarily. Nonetheless, a new class of RMAs, currently being researched and developed at Wang lab, hope to extend RMA lifespan through a model of synthetic compound development that targets gene expression. Both clinically and community-acquired resistance contribute to the demolishment of a critical building block (antibiotics) of modern medicine. Arguably the most nonsensical piece of the puzzle is subtherapeutic antibiotic use in livestock, which accounts for 80% of all antibiotic use in the United States12. FDA regulations are seemingly the only feasible way to fix the problem, and yet their efforts in recent regulatory measures not only contain major loopholes, but seem altogether to be largely barren of any significant resolutions.</p