Branching Model Research Articles

Genomic analysis and adaptive evolution of the RIG-I-like and NOD-like receptors in reptiles

Pattern recognition receptors (PRRs) play a crucial role in the host's innate immune system. Among the PPRs, the RIG-I-like (RLRs) and NOD-like receptors (NLRs) are two important subgroups. To understand the role of RLRs (RIG-I, MDA5, LGP2) and NLRs (NOD1, NLRC3, NLRX1, NOD2) in reptilian evolution, we identified six genes from reptilian genomes. A total of 168 putative genes were identified from 28 reptile species, including 141 intact genes, 25 partial genes and two pseudogenes. Interestingly, the NOD2 gene was absent in all reptile species. Phylogenetic results showed that all genes were divided into four major clades corresponding to their traditional taxonomic groups, indicating that these genes are conserved in reptiles. Evolutionary analyses detected positive selection in six genes. Most of the positively selected sites (50/76) were located in known functional domains, reflecting their critical and particular contributions to host defense during reptilian evolution. Branch model analysis showed that NLRs were under different evolutionary forces, while the RLRs were not, suggesting that semiaquatic species and terrestrial species faced different environmental pathogens, leading to different adaptations. Moreover, the positively selected sites identified in MDA5 using the branch-site model among semiaquatic reptiles, suggested their involvement in adaptation to semiaquatic environments.

AGB dust and gas ejecta in extremely metal-poor environments

We present asymptotic giant branch (AGB) models of metallicity $Z=10^{-4}$ and $Z=3\times 10^{-4}$, with the aim of understanding how the gas enrichment and the dust production change in very metal-poor environments and to assess the general contribution of AGB stars to the cosmic dust yield. The stellar yields and the dust produced are determined by the change in the surface chemical composition, with a transition occurring at $\sim 2.5~M_{\odot}$. Stars of mass $M < 2.5~M_{\odot}$ reach the carbon stage and produce carbon dust, whereas their higher mass counterparts produce mainly silicates and alumina dust; in both cases the amount of dust manufactured decreases towards lower metallicities. The $Z=10^{-4}$ models show a complex and interesting behaviour on this side, because the efficient destruction of the surface oxygen favours the achievement of the C-star stage, independently of the initial mass. The present results might indicate that the contribution from this class of stars to the overall dust enrichment in metal-poor environments is negligible at redshifts $z>5$.

Continuous-state HMMs for modeling time-series single-cell RNA-Seq data.

Methods for reconstructing developmental trajectories from time-series single-cell RNA-Seq (scRNA-Seq) data can be largely divided into two categories. The first, often referred to as pseudotime ordering methods are deterministic and rely on dimensionality reduction followed by an ordering step. The second learns a probabilistic branching model to represent the developmental process. While both types have been successful, each suffers from shortcomings that can impact their accuracy. We developed a new method based on continuous-state HMMs (CSHMMs) for representing and modeling time-series scRNA-Seq data. We define the CSHMM model and provide efficient learning and inference algorithms which allow the method to determine both the structure of the branching process and the assignment of cells to these branches. Analyzing several developmental single-cell datasets, we show that the CSHMM method accurately infers branching topology and correctly and continuously assign cells to paths, improving upon prior methods proposed for this task. Analysis of genes based on the continuous cell assignment identifies known and novel markers for different cell types. Software and Supporting website: www.andrew.cmu.edu/user/chiehl1/CSHMM/. Supplementary data are available at Bioinformatics online.

Knowledge Management Models. State of the Art

In this article knowledge management models are classified into the following groups: 1. Resource models. 1.1. Holistic models. 1.2. Pyramidal models. 2.Process models. 2.1. Knowledge value chain models. 2.2. Branch models of organizational processes. 2.3. Spiral models. 3. Knowledge creation models. 4. Semantic models. As the summary the operationalization of knowledge management models is presented.

Optimal Design of Plant Canopy Based on Light Interception: A Case Study With Loquat.

Canopy architecture determines the light distribution and light interception in the canopy. Reasonable shaping and pruning can optimize tree structure; maximize the utilization of land, space and light energy; and lay the foundation for achieving early fruiting, high yield, health and longevity. Due to the complexity of loquat canopy architecture and the multi-year period of tree growth, the variables needed for experiments in canopy type training are hardly accessible through field measurements. In this paper, we concentrated on exploring the relationship between branching angle and light interception using a three-dimensional (3D) canopy model in loquat (Eriobotrya japonica Lindl). First, detailed 3D models of loquat trees were built by integrating branch and organ models. Second, the morphological models of different loquat trees were constructed by interactive editing. Third, the 3D individual-tree modeling software LSTree integrated with the OpenGL shadow technique, a radiosity model and a modified rectangular hyperbola model was used to calculate the silhouette to total area ratio, the distribution of photosynthetically active radiation within canopies and the net photosynthetic rate, respectively. Finally, the influence of loquat tree organ organization on the light interception of the trees was analyzed with different parameters. If the single branch angle between the level 2 scaffold branch and trunk is approximately 15° and the angles among the level 2 scaffold branches range from 60 to 90°, then a better light distribution can be obtained. The results showed that the branching angle has a significant impact on light interception, which is useful for grower manipulation of trees, e.g., shoot bending (scaffold branch angle). Based on this conclusion, a reasonable tree structure was selected for intercepting light. This quantitative simulation and analytical method provides a new digital and visual method that can aid in the design of tree architecture.

PROJECTS FOR PROACTICE EDUCATIONAL TECHNOLOGY FOR DEVELOPMENT OF EMOTIONAL INTELLIGENCE IN PRESCHOOL AND HIGHER EDUCATION

The inclusion of emotional education at every stage of a person's learning process is becoming increasingly popular and recognizable in the field of education sciences nowadays. The paper presents two proactive educational technologies for the development of emotional intelligence. The first technology has already been tested and aims at developing the emotional intelligence of 6-7 year old children through the perception of music. The hierarchical structure of emotional intelligence provides clear consistency in the elaborate of musical tasks in proactive pedagogical technology. The methodology is aimed at identifying children's knowledge and skills to recognize, name and express emotions as the first base level and the main source of empathy formation and manifestation. “Interacting smoothly with others” appears as an ability in a process of development and at the same time as the ultimate highest result of the previous two levels - recognition and expression of emotions and empathy. At the same time, specific relations and interdependence are traced in the course of musical training to be used in favor of stimulating the development of emotional intelligence in its entirety. The second one is an on-going project whose goal is to elaborate a methodology for developing the emotional intelligence of students in the conditions of Bulgarian higher pedagogical education. This methodology is based on the principles of the constructivist approach in the context of the subject "Music projects in the kindergarten" and presents stages, tasks, expectations and effects of its potential usage. Based on that approach and starting from "four branches model" by Meyer and Salovey, the tasks that can be put into future development of learning strategies for the development of emotional intelligence of students should form skills for: 1. “Perception, Appraisal, and Expression of Emotion; 2. Emotional Facilitation of Thinking; 3. Understanding and Analyzing Emotions; Employing Emotional Knowledge; 4. Reflective Regulation of Emotions to Promote Emotional and Intellectual Growth;”

Strong selection of the TLR2 coding region among the Lagomorpha suggests an evolutionary history that differs from other mammals.

Toll-like receptors (TLRs) are one of the first lines of defense against pathogens and are crucial for triggering an appropriate immune response. Among TLRs, TLR2 is functional in all vertebrates and has high ability in detecting bacterial and viral pathogen ligands. The mammals' phylogenetic tree of TLR2 showed longer branches for the Lagomorpha clade, raising the hypothesis that lagomorphs experienced an acceleration of the mutation rate. This hypothesis was confirmed by (i) Tajima's test of neutrality that revealed different evolutionary rates between lagomorphs and the remaining mammals with lagomorphs presenting higher nucleotide diversity; (ii) genetic distances were similar among lagomorphs and between lagomorphs and other mammals; and (iii) branch models reinforced the existence of an acceleration of the mutation rate in lagomorphs. These results suggest that the lagomorph TLR2 has been strongly involved in pathogen recognition, which probably caused a host-pathogen arms race that led to the observed acceleration of the mutation rate.

A rational framework for dynamic homogenization at finite wavelengths and frequencies.

In this study, we establish an inclusive paradigm for the homogenization of scalar wave motion in periodic media (including the source term) at finite frequencies and wavenumbers spanning the first Brillouin zone. We take the eigenvalue problem for the unit cell of periodicity as a point of departure, and we consider the projection of germane Bloch wave function onto a suitable eigenfunction as descriptor of effective wave motion. For generality the finite wavenumber, finite frequency homogenization is pursued in via second-order asymptotic expansion about the apexes of 'wavenumber quadrants' comprising the first Brillouin zone, at frequencies near given (acoustic or optical) dispersion branch. We also consider the junctures of dispersion branches and 'dense' clusters thereof, where the asymptotic analysis reveals several distinct regimes driven by the parity and symmetries of the germane eigenfunction basis. In the case of junctures, one of these asymptotic regimes is shown to describe the so-called Dirac points that are relevant to the phenomenon of topological insulation. On the other hand, the effective model for nearby solution branches is found to invariably entail a Dirac-like system of equations that describes the interacting dispersion surfaces as 'blunted cones'. For all cases considered, the effective description turns out to admit the same general framework, with differences largely being limited to (i) the eigenfunction basis, (ii) the reference cell of medium periodicity, and (iii) the wavenumber-frequency scaling law underpinning the asymptotic expansion. We illustrate the analytical developments by several examples, including Green's function near the edge of a band gap and clusters of nearby dispersion surfaces.

EasyCodeML: A visual tool for analysis of selection using CodeML.

The genomic signatures of positive selection and evolutionary constraints can be detected by analyses of nucleotide sequences. One of the most widely used programs for this purpose is CodeML, part of the PAML package. Although a number of bioinformatics tools have been developed to facilitate the use of CodeML, these have various limitations. Here, we present a wrapper tool named EasyCodeML that provides a user‐friendly graphical interface for using CodeML. EasyCodeML has a custom running mode in which parameters can be adjusted to meet different requirements. It also offers a preset running mode in which an evolutionary analysis pipeline and publication‐quality tables can be exported by a single click. EasyCodeML allows visualized, interactive tree labelling, which greatly simplifies the use of the branch, branch‐site, and clade models of selection. The program allows comparison of major codon‐based models for analyses of selection. EasyCodeML is a stand‐alone package that is supported in Windows, Mac, and Linux operating systems, and is freely available at https://github.com/BioEasy/EasyCodeML.

Cell lineage inference from SNP and scRNA-Seq data.

Several recent studies focus on the inference of developmental and response trajectories from single cell RNA-Seq (scRNA-Seq) data. A number of computational methods, often referred to as pseudo-time ordering, have been developed for this task. Recently, CRISPR has also been used to reconstruct lineage trees by inserting random mutations. However, both approaches suffer from drawbacks that limit their use. Here, we develop a method to detect significant, cell type specific, sequence mutations from scRNA-Seq data. We show that only a few mutations are enough for reconstructing good branching models. Integrating these mutations with expression data further improves the accuracy of the reconstructed models. As we show, the majority of mutations we identify are likely RNA editing events indicating that such information can be used to distinguish cell types.

Stochastic equations and limit results for some two-type branching models

A class of binary state, asymmetric, continuous time Markov branching processes are analyzed under supercritical conditions. Stochastic equations are provided, and limit results for the long time asymptotics as well as for the behavior of the model under rescaling are reviewed. Extensions are presented for model variations, such as population size dependence, with the purpose of promoting further use of these models for applications.

Quantum channel simulation of phylogenetic branching models

Quantum channel simulations constructing probability tensors for biological multi-taxa in phylogenetics are proposed. These are given in terms of positive trace preserving maps (quantum channels), operating on quantum density matrices, using evolving systems of quantum walks with multiple walkers. Simulation of a variety of standard phylogenetic branching models, applying on trees of various topologies, is constructed using appropriate decoherent quantum circuits. For the sequences of biological characters so modelled, quantum simulations of statistical inference for them are constructed, given appropriate aligned molecular sequence data. This is achieved by the introduction of a quantum pruning map, operating on likelihood operator observables, utilizing state-observable duality and quantum measurement theory. More general stategies for related quantum simulation targets are also discussed.

Helium enrichment in intermediate-age Magellanic Clouds clusters: towards an ubiquity of multiple stellar populations?

Intermediate-age star clusters in the Magellanic Clouds harbour signatures of the multiple stellar populations long thought to be restricted to old globular clusters. We compare synthetic horizontal branch models with Hubble Space Telescope photometry of clusters in the Magellanic Clouds, with age between ~2 and ~10 Gyr, namely NGC 121, Lindsay 1, NGC 339, NGC 416, Lindsay 38, Lindsay 113, Hodge 6 and NGC 1978. We find a clear signature of initial helium abundance spreads (delta(Y)) in four out of these eight clusters (NGC 121, Lindsay 1, NGC 339, NGC 416) and we quantify the value of delta(Y). For two clusters (Lindsay 38, Lindsay 113) we can only determine an upper limit for delta(Y), whilst for the two youngest clusters in our sample (Hodge 6 and NGC 1978) no conclusion about the existence of an initial He spread can be reached. Our delta(Y) estimates are consistent with the correlation between maximum He abundance spread and mass of the host cluster found in Galactic globular clusters. This result strengthens the emerging view that the formation of multiple stellar populations is a standard process in massive star clusters, not limited to a high redshift environment.

Applicability of semi-destructive method to derive allometric model for estimating aboveground biomass and carbon stock in the Hill zone of Bangladesh

Biomass estimation using allometric models is a nondestructive and popular method. Selection of an allometric model can influence the accuracy of biomass estimation. Bangladesh Forest Department initiated a nationwide forest inventory to assess biomass and carbon stocks in trees and forests. The relationship between carbon storage and sequestration in a forest has implications for climate change mitigation in terms of the carbon sink in Bangladesh. As part of the national forest inventory, we aimed to derive multi-species biomass models for the hill zone of Bangladesh and to determine the carbon concentration in tree components (leaves, branches, bark and stem). In total, 175 trees of 14 species were sampled and a semi-destructive method was used to develop a biomass model, which included development of smaller branch (base dia < 7 cm) biomass allometry and volume estimation of bigger branches and stems. The best model of leaf, branches, and bark showed lower values for adjusted R2 (0.3152–0.8043) and model efficiency (0.436–0.643), hence these models were not recommended to estimate biomass. The best fit model of stem and total aboveground biomass (TAGB) showed higher model efficiency 0.948 and 0.837, respectively, and this model was recommended for estimation of tree biomass for the hill zone of Bangladesh. The best fit allometric biomass model for stem was Ln (Stem) = − 10.7248 + 1.6094*Ln (D) + 1.323*Ln (H) + 1.1469*Ln (W); the best fit model for TAGB was Ln (TAGB) = − 6.6937 + 0.809*Ln (D^2*H*W), where DBH = Diameter at Breast Height, H = Total Height, W = Wood density. The two most frequently used pan-tropical biomass models showed lower model efficiency (0.667 to 0.697) compared to our derived TAGB model. The best fit TAGB model proved applicable for accurate estimation of TAGB for the hill zone of Bangladesh. Carbon concentration varied significantly (p < 0.05) by species and tree components. Higher concentration (48–49%) of carbon was recorded in the tree stem.

Modelling Trait-dependent Speciation with Approximate Bayesian Computation

Phylogeny is the field of modelling the temporal discrete dynamics of speciation. Complex models can nowadays be studied using the Approximate Bayesian Computation approach which avoids likelihood calculations. The field's progression is hampered by the lack of robust software to estimate the numerous parameters of the speciation process. In this work we present an R package, pcmabc, based on Approximate Bayesian Computations, that implements three novel phylogenetic algorithms for trait-dependent speciation modelling. Our phylogenetic comparative methodology takes into account both the simulated traits and phylogeny, attempting to estimate the parameters of the processes generating the phenotype and the trait. The user is not restricted to a predefined set of models and can specify a variety of evolutionary and branching models. We illustrate the software with a simulation-reestimation study focused around the branching Ornstein-Uhlenbeck process, where the branching rate depends non-linearly on the value of the driving Ornstein-Uhlenbeck process. Included in this work is a tutorial on how to use the software.

Parton Branching Process with Supersymmetric Particles at LHC Energies

A 2-step parton branching model is proposed to describe the potential presence of supersymmetric particles in multiplicity distributions. This model gives a reasonable description of the data obtained at 13TeV by the ATLAS Collaboration across the maximum pseudorapidity range of η&lt;= 2.5.

Growth model and visualization of a virtual jujube tree

Numerous experimental observations and data analyses were conducted to simulate the growth of jujube trees. Accordingly, the growth model of jujube was simulated using the logistic model, which was obtained by building this particular growth model. Simultaneously, the branch model based on the turtle interpretation, which simulates the curved shape of the jujube branch and enhances the effect of 3D visualization, was proposed to effectively simulate the morphological structure of the jujube tree. Thereafter, a novel L-system based on the substructure algorithm is developed when jujube is visualized. A substructure algorithm is introduced in an L-system, thereby solving the problem of the same multiple calculation and multi-construction of the structure. Lastly, the morphological structure and growth process of jujube can be controlled through the relevant parameter settings based on the Visual C++ development environment and OpenGL functions. Consequently, a virtual jujube tree modeling and mapping can be achieved.

Prosperity Prediction in Czech Manufacturing Industries

There are many ways to determine financial health of a company. Classic tools of financial analysis emphasize data in financial statements. When trying to reach an overall classification of a company, e.g. from the point of view of an investor, indicators of profitability, liquidity, leverage and activity might generate contradictory clues regarding financial health of the company. Such analysis does not only generate ambiguous results, but is also lengthy. Therefore, the IN05 financial model was created for particular specifics of Czech Republic economic environment to predict prosperity of companies. It measures the prosperity on the base of economic value added (EVA), in that this model is globally unique. More than ten years have passed since the launch of the IN05 index and the Czech Republic and the world have in the meantime weathered a global economic crisis. The aim of this study is to quantify contemporary prediction strength of the IN05 index on a sample of 500 companies. Moreover, an effort was made to enhance the accuracy of the model for particular branches of manufacturing industries. It was found that contemporary explanatory power of the index IN05 is 48.58% when applying the original evaluation scale, and 70.79% when assessing 68.62% of the sample except the gray zone. The accuracy of the model was enhanced by author in all categories, i.e. a higher accuracy (correct prediction probability) without considering the gray zone and higher accuracy (conditioned correct prediction probability) using the gray zone in all branches of manufacturing industries. Second aim is confirmation of branch influence on accuracy of prosperity prediction. It was found a different IN05 model accuracy for selected branches with statistical significance. DOI: http://dx.doi.org/10.5755/j01.ee.29.5.18231

Unified method for optimal power flow of AC/DC system with PET based on extended branch model

Unified method for optimal power flow of AC/DC system with PET based on extended branch model

Explaining the Multiple Populations in Globular Clusters by Multiple Episodes of Star Formation and Enrichment without Gas Expulsion from Massive Star Feedback

Abstract In order to investigate the origin of multiple stellar populations found in globular clusters (GCs) in the halo and bulge of the Milky Way, we have constructed chemical evolution models for their putative low-mass progenitors. In light of recent theoretical developments, we assume that supernova blast waves undergo blowout without expelling the pre-enriched ambient gas, while relatively slow winds of massive stars (WMSs), together with the winds and ejecta from low- to high-mass asymptotic giant branch stars, are all locally retained in these less massive systems. Interestingly, we find that the observed Na–O anti-correlations in metal-poor GCs can be reproduced when multiple episodes of starburst and enrichment are allowed to continue in these subsystems. A specific form of star formation history with decreasing time intervals between the successive stellar generations, however, is required to obtain this result, which is in good agreement with the parameters obtained from synthetic horizontal branch models. The “mass budget problem” is also much alleviated by our models without ad hoc assumptions on star formation efficiency, initial mass function, and the preferential loss of first-generation stars. We also apply these models to investigate the origin of super-He-rich red clump stars in the metal-rich bulge suggested by Lee et al. We find that chemical enrichment by the WMSs can naturally reproduce the required strong He enhancement in metal-rich subsystems. Our results further underscore that gas expulsion or retention is a key factor in understanding the multiple populations in GCs.