Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation

What information-processing strategies and general principles are sufficient to enable self-organized morphogenesis in embryogenesis and regeneration? We designed and analyzed a minimal model of self-scaling axial patterning consisting of a cellular network that develops activity patterns within implicitly set bounds. The properties of the cells are determined by internal ‘genetic’ networks with an architecture shared across all cells. We used machine-learning to identify models that enable this virtual mini-embryo to pattern a typical axial gradient while simultaneously sensing the set boundaries within which to develop it from homogeneous conditions—a setting that captures the essence of early embryogenesis. Interestingly, the model revealed several features (such as planar polarity and regenerative re-scaling capacity) for which it was not directly selected, showing how these common biological design principles can emerge as a consequence of simple patterning modes. A novel “causal network” analysis of the best model furthermore revealed that the originally symmetric model dynamically integrates into intercellular causal networks characterized by broken-symmetry, long-range influence and modularity, offering an interpretable macroscale-circuit-based explanation for phenotypic patterning. This work shows how computation could occur in biological development and how machine learning approaches can generate hypotheses and deepen our understanding of how featureless tissues might develop sophisticated patterns—an essential step towards predictive control of morphogenesis in regenerative medicine or synthetic bioengineering contexts. The tools developed here also have the potential to benefit machine learning via new forms of backpropagation and by leveraging the novel distributed self-representation mechanisms to improve robustness and generalization.

Computational Analysis of Symmetric and Cambered Blade Darrieus Vertical Axis Wind Turbine With Bio-Mimicked Blade Design

Vertical axis wind turbine suffers from low performance, and the need for improvement is a challenge. This work addresses this problem by using computational fluid dynamics. This chapter aims to analyze and compare symmetric and cambered Darrieus turbine. These analyses are usually carried for straight leading-edge blades, and cambered resembles more the natural shape of the wing of birds and other aquatic mammals, which helps them generate extra lift during movement. Moreover, recent studies suggest better performance was observed for NACA0018 symmetric aerofoil blades, and a similar trend has been observed for NACA2412 cambered aerofoil profiles. Turbine models having symmetric NACA0018 and cambered NACA2412 profiles have been studied. By comparing the symmetric model with cambered blade models, differences in coefficient of torque have been presented. OpenFOAM is used for performing the 2D simulation with dynamicOverset-FvMesh for motion solver with overset mesh method. Meshed geometry was constructed with GMSH codes and the simulation uses overPimpleDyMFoam algorithm as a solver.

Flavored leptogenesis and neutrino mass with A4 symmetry

We propose a minimal A4 flavor symmetric model, assisted by Z2× Z3 symmetry, which can naturally takes care of the appropriate lepton mixing and neutrino masses via Type-I seesaw. It turns out that the framework, originated due to a specific flavor structure, favors the normal hierarchy of light neutrinos and simultaneously narrows down the range of Dirac CP violating phase. It predicts an interesting correlation between the atmospheric mixing angle and the Dirac CP phase too. While the flavor structure indicates an exact degeneracy of the right-handed neutrino masses, renormalization group running of the same from a high scale is shown to make it quasi-degenerate and a successful flavor leptogenesis takes place within the allowed parameter space obtained from neutrino phenomenology.

Resonant leptogenesis and TM$$_1$$ mixing in minimal type-I seesaw model with S$$_4$$ symmetry

We present an S$$_4$$ 4 flavour symmetric model within a minimal seesaw framework resulting in mass matrices that leads to TM$$_1$$ 1 mixing. Minimal seesaw is realized by adding two right-handed neutrinos to the Standard Model. The model predicts Normal Hierarchy (NH) for neutrino masses. Using the constrained six-dimensional parameter space of the model, we have evaluated the effective Majorana neutrino mass, which is the parameter of interest in neutrinoless double beta decay experiments. The possibility of explaining baryogenesis via resonant leptogenesis is also examined within the model. A non-zero, resonantly enhanced CP asymmetry generated from the decay of right-handed neutrinos at the TeV scale is studied, considering flavour effects. The evolution of lepton asymmetry is discussed by solving the set of Boltzmann equations numerically and obtain the value of baryon asymmetry to be $$|\eta _B| = 6.3 \times 10^{-10}$$ | η B | = 6.3 × 10 - 10 with the choice of right-handed neutrino mass, $$M_1 = 10$$ M 1 = 10 TeV and mass splitting, $$d \simeq 10^{-8}$$ d ≃ 10 - 8 .

Continuous Dissipative Phase Transitions with or without Symmetry Breaking

The paradigm of second-order phase transitions (PTs) induced by spontaneous symmetry breaking (SSB) in thermal and quantum systems is a pillar of modern physics that has been fruitfully applied to out-of-equilibrium open quantum systems. Dissipative phase transitions (DPTs) of second order are often connected with SSB, in close analogy with well-known thermal second-order PTs in closed quantum and classical systems. That is, a second-order DPT should disappear by preventing the occurrence of SSB. Here, we prove this statement to be wrong, showing that, surprisingly, SSB is not a necessary condition for the occurrence of second-order DPTs in \textit{out-of-equilibrium open quantum systems}. We analytically prove this result using the Liouvillian theory of dissipative phase transitions, and demonstrate this anomalous transition in two exemplary models: a paradigmatic laser model, where we can arbitrarily remove SSB while retaining criticality, and a $Z_2$-symmetric model of a two-photon Kerr resonator.

Joint estimation of selection intensity and mutation rate under balancing selection withapplications to HLA

A composite likelihood method is introduced for jointly estimating the intensity of selection and the rate of mutation, both scaled by the effective population size, when there is balancing selection at a single multi-allelic locus in an isolated population at demographic equilibrium. The performance of the method is tested using simulated data. Average estimated mutation rates and selection intensities are close to the true values but there is considerable variation about the averages. Allowing for both population growth and population subdivision do not result in qualitative differences but the estimated mutation rates and selection intensities do not in general reflect the current effective population size. The method is applied to three class I (HLA-A, HLA-B and HLA-C) and two class II loci (HLA-DRB1 and HLA-DQA1) in the 1000 Genomes populations. Allowing for asymmetric balancing selection has only a slight effect on the results from the symmetric model. Mutations that restore symmetry of the selection model are preferentially retained because of the tendency of natural selection to maximize average fitness. However, slight differences in selective effects result in much longer persistence time of some alleles. Trans-species polymorphism (TSP), which is characteristic of MHC in vertebrates, is more likely when there are small differences in allelic fitness than when complete symmetry is assumed. Therefore, variation in allelic fitness expands the range of parameter values consistent with observations of TSP.

Parity–Time Symmetric Model and Analysis for Stable Multi-Load Wireless Power Transfer

A noticeable challenge for a multi-load wireless power transfer system is to achieve stable power transfer under a dynamic change in coupling conditions. It was proposed that the parity–time symmetric wireless power transfer (PT-WPT) system can achieve stable output efficiency for a single receiver when tuned at the purely real eigenfrequency. However, in the case of higher order, PT symmetric systems usually cannot maintain the real eigenfrequency. To address the issue, a high-order PT-WPT model was established using coupled mode theory (CMT) theory in this paper, and the eigenfrequency of the multi-load PT-WPT system was analyzed. Here, we propose that, theoretically, the system can work at the purely real eigenfrequency by impedance matching. The transfer efficiency of the multi-load PT-WPT system when the system works at the real eigenfrequency was analyzed. The results of the numerical simulation show that the multi load PT-WPT system can maintain stable output efficiency under a dynamic change in coupling conditions. In the long run, our work provides a new possibility for the stable transmission of the multi-load wireless power transfer system.

A low-energy perspective on the minimal left-right symmetric model

We perform a global analysis of the low-energy phenomenology of the minimal left-right symmetric model (mLRSM) with parity symmetry. We match the mLRSM to the Standard Model Effective Field Theory Lagrangian at the left-right-symmetry breaking scale and perform a comprehensive fit to low-energy data including mesonic, neutron, and nuclear β-decay processes, ∆F = 1 and ∆F = 2 CP-even and -odd processes in the bottom and strange sectors, and electric dipole moments (EDMs) of nucleons, nuclei, and atoms. We fit the Cabibbo-Kobayashi-Maskawa and mLRSM parameters simultaneously and determine a lower bound on the mass of the right-handed WR boson. In models where a Peccei-Quinn mechanism provides a solution to the strong CP problem, we obtain $$ {M}_{W_R} $$ M W R ≳ 5.5 TeV at 95% C.L. which can be significantly improved with next-generation EDM experiments. In the P-symmetric mLRSM without a Peccei-Quinn mechanism we obtain a more stringent constraint $$ {M}_{W_R} $$ M W R ≳ 17 TeV at 95% C.L., which is difficult to improve with low-energy measurements alone. In all cases, the additional scalar fields of the mLRSM are required to be a few times heavier than the right-handed gauge bosons. We consider a recent discrepancy in tests of first-row unitarity of the CKM matrix. We find that, while TeV-scale WR bosons can alleviate some of the tension found in the Vud,us determinations, a solution to the discrepancy is disfavored when taking into account other low-energy observables within the mLRSM.

Pandemic and Indonesia Stock Market Performance

This study aims to analyze the impact of the COVID-19 pandemic on Indonesia’s stock market performance. Considering the characteristics of daily stock return data that shows the characteristics of volatility clustering, the analytical method used is to develop a heteroscedastic model specification whose parameters are estimated using the maximum likelihood method. Based on data from March 2020 to January 2021, this study finds that the Exponential-GARCH asymmetric model is the best model compared to the Standard-GARCH symmetric model or the asymmetric Threshold-GARCH model. The inference analysis conducted on the Exponential-GARCH asymmetric model in this study shows that the stock market's performance that is significantly affected by this pandemic is the volatility of its returns. Stock price volatility is one of the important variables in stock market performance. This study produces empirical findings that government policies on social restrictions contribute significantly to suppressing stock market volatility. As for government policies in mitigating the risk of the spread of the epidemic, in this study, it is measured through a stringency index. This index was released by the Oxford COVID-19 Government Response Tracker (OxCGRT) which monitors the government's response to the coronavirus in 160 countries and is a parameter that evaluates the policies taken by a country's government based on nine metrics. This index does not measure the effectiveness of a country's government response, but only the level of tightness. However, the results of the tests carried out in this study did not find a significant impact of pandemic indicators, the number of cases, and the number of daily deaths related to COVID-19 on stock returns.