Functional Convergence Research Articles

Anatomical description of neornithine stomach with implications on neornithine stomach morphology.

Neornithines, the most diversified extant tetrapods, have been a classic example for understanding form-function relationships, particularly in the context of the interaction between dietary ecology and neornithine phenotypic evolution. While the previous studies have primarily focused on beak morphology, the significance of the neornithine stomach, which serves as a functional analog of mammalian dentition, is expected to play an important role as well. However, current knowledge on neornithine stomachs is predominantly biased toward poultry and birds of prey, leading to a significant underappreciation of its impact on macroevolution. Here, we provide detailed descriptions of neornithine stomachs represented by 115 species of major orders and test if and how neornithine stomachs are related to their dietary ecology. We identified four morphotypes among neornithine stomachs, which are strongly constrained phylogenetically. While the neornithine diet demonstrates strong associations with stomach morphotypes, the associations are small or absent when accounting for the phylogeny in statistical evaluations. Similarly, the neornithine diet has negligible effects on their ventriculus mass under the analyses with phylogenetic correction. The results resemble a recent finding that a neornithine diet has no effect on intestine length when accounting for phylogeny, but rather flight performance does. Thus, the present study further supports the previous findings that dietary specialization in neornithine birds closely follows phylogeny, making functional convergence across taxa difficult to detect.

A second order difference method combined with time two-grid algorithm for two-dimensional time-fractional Fisher equation

In this paper, a finite difference (FD) scheme based on time two-grid algorithm is proposed for solving the two-dimensional time-fractional Fisher equation (2D-TFFE). Firstly, the Caputo fractional derivative and the spatial derivative are discretized by the L 2 − 1 σ formula and the central difference formula, respectively. In order to improve the efficiency of computation, the time two-grid algorithm is then constructed. Secondly, based on the cut-off function technic, stability and convergence of the time two-grid FD scheme are obtained by the energy method, and the global convergence order is O ( τ F 2 + τ C 4 + h x 2 + h y 2 ) , where τ F and τ C represent time-step sizes on the fine and coarse grid, respectively, while h x and h y represent the space-step sizes. Finally, numerical experiments are presented to show the feasibility and efficiency of the algorithm.

Weighted approximations by sampling type operators: recent and new results

In this paper, we collect some recent results on the approximation properties of generalized sampling operators and Kantorovich operators, focusing on pointwise and uniform convergence, rate of convergence, and Voronovskaya-type theorems in weighted spaces of functions. In the second part of the paper, we introduce a new generalization of sampling Durrmeyer operators including a special function $\rho$ which satisfies certain assumptions. For the family of newly constructed operators, we obtain pointwise convergence, uniform convergence and rate of convergence for functions belonging to weighted spaces of functions.

Widespread convergence towards functional optimization in the lower jaws of crocodile-line archosaurs.

Extant crocodilian jaws are subject to functional demands induced by feeding and hydrodynamics. However, the morphological and ecological diversity of extinct crocodile-line archosaurs is far greater than that of living crocodilians, featuring repeated convergence towards disparate ecologies including armoured herbivores, terrestrial macropredators and fully marine forms. Crocodile-line archosaurs, therefore, present a fascinating case study for morphological and functional divergence and convergence within a clade across a wide range of ecological scenarios. Here, we build performance landscapes of two-dimensional theoretical jaw shapes to investigate the influence of strength, speed and hydrodynamics in the morphological evolution of crocodile-line archosaur jaws, and test whether ecologically convergent lineages evolved similarly optimal jaw function. Most of the 243 sampled jaw morphologies occupy optimized regions of theoretical morphospace for either rotational efficiency, resistance to Von Mises stress, hydrodynamic efficiency or a trade-off between multiple functions, though some seemingly viable shapes remain unrealized. Jaw speed is optimized only in a narrow region of morphospace whereas many shapes possess optimal jaw strength, which may act as a minimum boundary rather than a strong driver for most taxa. This study highlights the usefulness of theoretical morphology in assessing functional optimality, and for investigating form-function relationships in diverse clades.

Long noncoding RNA GAS5 acts as a competitive endogenous RNA to regulate GSK-3β and PTEN expression by sponging miR-23b-3p in Alzheimer's disease.

Long noncoding RNA and microRNA are regulatory noncoding RNAs that are implicated in Alzheimer's disease, but the role of long noncoding RNA-associated competitive endogenous RNA has not been fully elucidated. The long noncoding RNA growth arrest-specific 5 (GAS5) is a member of the 5'-terminal oligopyrimidine gene family that may be involved in neurological disorders, but its role in Alzheimer's disease remains unclear. This study aimed to investigate the function of GAS5 and construct a GAS5-associated competitive endogenous RNA network comprising potential targets. RNA sequencing results showed that GAS5 was upregulated in five familial Alzheimer's disease (5×FAD) mice, APPswe/PSEN1dE9 (APP/PS1) mice, Alzheimer's disease-related APPswe cells, and serum from patients with Alzheimer's disease. Functional experiments with targeted overexpression and silencing demonstrated that GAS5 played a role in cognitive dysfunction and multiple Alzheimer's disease-associated pathologies, including tau hyperphosphorylation, amyloid-beta accumulation, and neuronal apoptosis. Mechanistic studies indicated that GAS5 acted as an endogenous sponge by competing for microRNA-23b-3p (miR-23b-3p) binding to regulate its targets glycogen synthase kinase 3beta (GSK-3β) and phosphatase and tensin homologue deleted on chromosome 10 (PTEN) expression in an Argonaute 2-induced RNA silencing complex (RISC)-dependent manner. GAS5 inhibited miR-23b-3p-mediated GSK-3β and PTEN cascades with a feedforward PTEN/protein kinase B (Akt)/GSK-3β linkage. Furthermore, recovery of GAS5/miR-23b-3p/GSK-3β/PTEN pathways relieved Alzheimer's disease-like symptoms in vivo, indicated by the amelioration of spatial cognition, neuronal degeneration, amyloid-beta load, and tau phosphorylation. Together, these findings suggest that GAS5 promotes Alzheimer's disease pathogenesis. This study establishes the functional convergence of the GAS5/miR-23b-3p/GSK-3β/PTEN pathway on multiple pathologies, suggesting a candidate therapeutic target in Alzheimer's disease.

The Eyes Absent family: At the intersection of DNA repair, mitosis, and replication

The Eyes Absent family (EYA1–4) are a group of dual function proteins that act as both tyrosine phosphatases and transcriptional co-activators. EYA proteins play a vital role in development, but are also aberrantly overexpressed in cancers, where they often confer an oncogenic effect. Precisely how the EYAs impact cell biology is of growing interest, fuelled by the therapeutic potential of an expanding repertoire of EYA inhibitors. Recent functional studies suggest that the EYAs are important players in the regulation of genome maintenance pathways including DNA repair, mitosis, and DNA replication. While the characterized molecular mechanisms have predominantly been ascribed to EYA phosphatase activities, EYA co-transcriptional activity has also been found to impact the expression of genes that support these pathways. This indicates functional convergence of EYA phosphatase and co-transcriptional activities, highlighting the emerging importance of the EYA protein family at the intersection of genome maintenance mechanisms. In this review, we discuss recent progress in defining EYA protein substrates and transcriptional effects, specifically in the context of genome maintenance. We then outline future directions relevant to the field and discuss the clinical utility of EYA inhibitors.

An Efficient Quadratic Programming Method for Kinematic Control of Redundant Manipulators under Joint Velocity Constraints

This paper presents an efficient inverse kinematics solution for redundant robotic arms. The proposed method combines the principles of continuation methods, improves the instability of the computation time by increasing the convergence of the kinematics function, and improves the efficiency of traditional numerical methods. The effectiveness and efficient performance of the method are demonstrated through comparative experiments. The computational speed of the method is twice as fast as the Newton–Raphson method under joint limit constraints and equal solution accuracy.

Diverse origins of near-identical antifreeze proteins in unrelated fish lineages provide insights into evolutionary mechanisms of new gene birth and protein sequence convergence.

Determining the origins of novel genes and the genetic mechanisms underlying the emergence of new functions is challenging yet crucial for understanding evolutionary innovations. The convergently evolved fish antifreeze proteins provide excellent opportunities to investigate evolutionary origins and pathways of new genes. Particularly notable is the near-identical type I antifreeze proteins (AFPI) in four phylogenetically divergent fish taxa. This study tested the hypothesis of protein sequence convergence beyond functional convergence in three unrelated AFPI-bearing fish lineages, revealing different paths by which a similar protein arose from diverse genomic resources. Comprehensive comparative analyses of de novo sequenced genome of the winter flounder and grubby sculpin, available high-quality genome of the cunner and 14 other relevant species found that the near-identical AFPI originated from a distinct genetic precursor in each lineage. Each independently evolved a coding region for the novel ice-binding protein while retaining sequence identity in the regulatory regions with their respective ancestor. The deduced evolutionary processes and molecular mechanisms are consistent with the Innovation-Amplification-Divergence (IAD) model applicable to AFPI formation in all three lineages, a new Duplication-Degeneration-Divergence (DDD) model we propose for the sculpin lineage, and a DDD model with gene fission for the cunner lineage. This investigation illustrates the multiple ways by which a novel functional gene with sequence convergence at the protein level could evolve across divergent species, advancing our understanding of the mechanistic intricacies in new gene formation.

ϵ$$ \epsilon $$‐Nash equilibrium of non‐cooperative Lagrangian dynamic games based on the average sub‐gradient robust integral sliding mode control

SummaryIn non‐cooperative multi‐player games, an average sub‐gradient (ASG) strategy for finding an ‐Nash equilibrium. For convex (but not necessarily strictly convex) individual cost functions, the function convergence of the multi‐player game is demonstrated. Applying Tanaka's formula that characterizes the Nash equilibrium leads to finding the strategy for each player. A min‐max formulation defines the corresponding solution for each player. The main result is proving the reachability of the desired regime, obtaining an explicit upper bound for Tanaka's function decrement. Detailed analyses for two‐player and multi‐player games are developed. For a class of two‐player games with a convex performance function, a set of numerical studies shows the applicability of the proposed method. So, the tracking of the arm in 3‐links robot is considered as an illustrative example.

The osteology of the wrist of Heyuannia huangi (Oviraptorosauria) and its implications for the wrist folding mechanism

The wrist of extant birds is highly specialized which permits folding of the forelimb in order to protect the pennaceous feathers when they are relaxed. This mechanism is absent in most non-avian theropods and is unknown in oviraptorosaurs because of the rarity of the specimens with well-preserved wrist. Here we give a detailed description of the wrist of two three-dimensionally preserved oviraptorosaurian Heyuannia huangi specimens from the Upper Cretaceous in Southern China. Heyuannia huangi possesses a highly specialized wrist with a strongly dorsoventrally compressed distal ulna, a larger radiale angle and a strongly convex semilunate carpal. The morphology of its wrist suggests that the distal ulna would not hinder the rotation of the manus, resulting in the smallest angle between the manus and the ulna being less than 90 degrees. The combination of the morphology of the wrist of oviraptorosaurs and the phylogenetic result indicates functional convergence in the wrist of oviraptorids and extant birds.

Generalizing the Mittag-Leffler Function for Fractional Differentiation and Numerical Computation

This work aims to investigate fractional differential equations using the Magnus Gösta Mittag-Leffler (GML) function and compare the finding with convention calculus approaches. It examines the solutions with one, two, and three parameters using the GML function for different values of α, β, and γ. We also test the convergence of the GML function of two parameters and check the validity and the computational time complexity. Moreover, we extend the GML function into three dimensions within the domain of complex variables utilizing numerical computing software. Graphs of the single-parameter GML E α (x), illustrates diverse disintegration rates across various α values, emphasizing dominant asymptotic trends over time periods.

An efficient hybrid conjugate gradient method with an adaptive strategy and applications in image restoration problems

In this study, we introduce a novel hybrid conjugate gradient method with an adaptive strategy called asHCG method. The asHCG method exhibits the following characteristics. (i) Its search direction guarantees sufficient descent property without dependence on any line search. (ii) It possesses strong convergence for the uniformly convex function using a weak Wolfe line search, and under the same line search, it achieves global convergence for the general function. (iii) Employing the Armijo line search, it provides an approximate guarantee for worst-case complexity for the uniformly convex function. The numerical results demonstrate promising and encouraging performances in both unconstrained optimization problems and image restoration problems.

IDP-FL: A fine-grained and privacy-aware federated learning framework for deep neural networks

Federated learning (FL), as a distributed machine learning paradigm, essentially promises that multiple parties can jointly train the model collaboratively without sharing local data. Recent research demonstrates that the adversary can deduce the sensitive data through shared model updates. To protect the data privacy of the participants, differential privacy (DP) is deployed in various FL scenarios due to the lightweight computational overhead. However, the trade-off between the availability and privacy of local models is the fundamental problem that needs to be solved in DP applications. In this paper, we propose a fine-grained and privacy-aware FL framework (iDP-FL) to enable training data and model parameters to satisfy confidentiality while markedly improving the model's prediction accuracy. Specifically, we first design an individualized perturbation noise (IPN) algorithm that adds different artificial noises dependent on the importance of each participant's model weight. Then, we propose a perturbation mechanism on the aggregator side, a DP protection method under the premise of loss function convergence, which prevents the global model parameters from being stolen by malicious adversaries. Moreover, to achieve lightweight protection throughout the learning, we present an advanced bilateral perturbation (ABP) protocol to perform iterative training. Theoretical analysis indicates that iDP-FL provides the DP guarantee, which yields superior prediction accuracy and excellent privacy-preserving with the same privacy level. Finally, extensive experiments conducted on real-world datasets demonstrate that our approach shows significant advantages with limited privacy budgets, especially at small privacy losses.

Three cassava A20/AN1 family genes, Metip3 (5, and 7), can bestow on tolerance of plants to multiple abiotic stresses but show functional convergence and divergence

A20/AN1 zinc-finger domain-containing genes are very promising candidates in improving plant tolerance to abiotic stresses, but considerably less is known about functions and mechanisms for many of them. In this study, Metip3 (5, and 7), cassava (Manihot esculenta) A20/AN1 genes carrying one A20 domain and one AN1 domain, were functionally characterized at different layers. Metip3 (5, and 7) proteins were all located in the nucleus. No interactions were found between these three proteins. Metip3 (5, and 7)-expressing Arabidopsis was more tolerant to multiple abiotic stresses by Na, Cd, Mn, Al, drought, high temperature, and low temperature. Metip3- and Metip5-expressing Arabidopsis was sensitive to Cu stress, while Metip7-expressing Arabidopsis was insensitive. The H2O2 production significantly decreased in all transgenic Arabidopsis, however, O2·- production significantly decreased in Metip3- and Metip5-expressing Arabidopsis but did not significantly changed in Metip7-expressing Arabidopsis under drought. Metip3 (5, and 7) expression-silenced cassava showed the decreased tolerance to drought and NaCl, presented significant decreases in superoxide dismutase and catalase activities and proline content, and displayed a significant increase in malondialdehyde content under drought. Taken together with transcriptome sequencing analysis, it is suggested that Metip5 gene can not only affect signal transduction related to plant hormone, mitogen activated protein kinases, and starch and sucrose metabolism, DRE-binding transcription factors, and antioxidants, conferring the drought tolerance, but also might deliver the signals from DREB2A INTERACTING PROTEIN1, E3 ubiquitin-protein ligases to proteasome, leading to the drought intolerance. The results are informative not only for further study on evolution of A20/AN1 genes but also for development of climate resilient crops.

Testing the Nonlinear Long- and Short-Run Distributional Asymmetries Effects of Bitcoin Prices on Bitcoin Energy Consumption: New Insights through the QNARDL Model and XGBoost Machine-Learning Tool

This study investigates the asymmetric impacts of Bitcoin prices on Bitcoin energy consumption. Two series are shown to be chaotic and non-linear using the BDS Independence test. To take into consideration this nonlinearity, we employed the QNARDL model as a traditional technique and Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGBoost) as non-conventional approaches to study the link between Bitcoin energy usage and Bitcoin prices. Referring to QNARDL estimates, results show that the relationship between Bitcoin energy use and prices is asymmetric. Additionally, results demonstrate that changes in Bitcoin prices have a considerable effect, both short- and long-run, on energy consumption. As a result, any upsurge in the price of Bitcoin leads to an immediate boost in energy use. Furthermore, the short-term drop in Bitcoin values causes an increase in energy use. However, higher Bitcoin prices reduce energy use in the long run. Otherwise, every decline in Bitcoin prices leads to a long-term reduction in energy use. In addition, the performance metrics and convergence of the cost function provide evidence that the XGBoost model dominates the SVM model in terms of Bitcoin energy consumption forecasting. In addition, we analyze the effectiveness of several modeling approaches and discover that the XGBoost model (MSE: 0.52%; RMSE: 0.72 and R2: 96%) outperforms SVM (MSE: 4.89; RMSE: 2.21 and R2: 75%) in predicting. Results indicate that the forecast of Bitcoin energy consumption is more influenced by positive shocks to Bitcoin prices than negative shocks. This study gives insights into the policies that should be implemented, such as increasing the sustainable capacity, efficiency, and flexibility of mining operations, which would allow for the reduction of the negative impacts of Bitcoin price shocks on energy consumption.

Physics-informed machine learning for moving load problems

Abstract This paper presents a new approach to simulate forward and inverse problems of moving loads using physics-informed machine learning (PIML). Physics-informed neural networks (PINNs) utilize the underlying physics of moving load problems and aim to predict the deflection of beams and the magnitude of the loads. The mathematical representation of the moving load considered involves a Dirac delta function, to capture the effect of the load moving across the structure. Approximating the Dirac delta function with PINNs is challenging because of its instantaneous change of output at a single point, causing difficulty in the convergence of the loss function. We propose to approximate the Dirac delta function with a Gaussian function. The incorporated Gaussian function physical equations are used in the physics-informed neural architecture to simulate beam deflections and to predict the magnitude of the load. Numerical results show that PIML is an effective method for simulating the forward and inverse problems for the considered model of a moving load.

Investigation of longitudinal dynamics of vehicles in disordered traffic

Vehicles in developing countries have wide variations in their static and dynamic characteristics, and drivers tend to not follow lane discipline. Models for driving behavior under such disordered traffic conditions need to include the vehicle dynamics and their interactions with the surrounding environment. Calibration of those models is necessary to evaluate their predictive power and suitability for analyzing traffic flow under disordered traffic. The present study aims to calibrate a longitudinal dynamics model, the High-Speed Social-Force Model (HSFM) using a vehicle trajectory dataset collected from Chennai city. The HSFM was calibrated by minimizing the deviations between the simulated and observed longitudinal coordinates of vehicles using a genetic algorithm. The observed and simulated vehicle trajectories were compared using a goodness of fit function of the positions. The convergence of the objective function has been illustrated with the help of fitness landscapes. The calibration errors were found to be within the acceptable range and the optimal parameter values were found to be consistent. The outcomes of the study indicate that the model can capture the influence of non-overlapping leaders under disordered traffic conditions.

Functional Segregation of Resource Utilization Strategies between Invasive and Native Plants and Invasion Mechanisms in the Water Level Fluctuation Zone: A Case Study of Pengxi River in Three Gorges Reservoir, China

The ecosystem of the water level fluctuation (WLF) zone of the Three Gorges Reservoir (TGR) is highly vulnerable and sensitive due to its unique cyclical flooding and drought conditions. The ecological impact of biological invasion in this area is particularly severe, making it crucial to study the differences in resource utilization strategies between invasive plants (IPs) and native plants (NPs) using functional traits to explore the mechanisms of invasion. We selected the WLF zone of Pengxi River in the TGR area and conducted a multi-scale study along the elevation gradient. The results reveal that at the regional scale, IPs have a larger height and specific leaf area, smaller leaf tissue density, and specific root length compared to NPs, showing a preference for enhancing aboveground resource acquisition over leaf defense capabilities. They allocate more tissue construction resources to their roots to withstand environmental pressures, which may be the key to their successful intrusion, highlighting the role of niche differentiation. On the community scale, the H and SLA of IPs and NPs are positively correlated with elevation, while the LTD of IPs shows a negative correlation. At elevations of 175 m and below, IP and NP exhibit functional convergence, while above 175 m, functional divergence was observed. This indicates that although the different resource utilization strategies are crucial for successful IP invasion, the environmental filtering from periodic floods and drought pressures play a significant role in community assembly in the WLF zone, allowing IP to integrate into habitats with similar functional characteristics already inhabited by NP and establish their own communities.

Stochasticity, determinism, and contingency shape genome evolution of endosymbiotic bacteria

Evolution results from the interaction of stochastic and deterministic processes that create a web of historical contingency, shaping gene content and organismal function. To understand the scope of this interaction, we examine the relative contributions of stochasticity, determinism, and contingency in shaping gene inactivation in 34 lineages of endosymbiotic bacteria, Sodalis, found in parasitic lice, Columbicola, that are independently undergoing genome degeneration. Here we show that the process of genome degeneration in this system is largely deterministic: genes involved in amino acid biosynthesis are lost while those involved in providing B-vitamins to the host are retained. In contrast, many genes encoding redundant functions, including components of the respiratory chain and DNA repair pathways, are subject to stochastic loss, yielding historical contingencies that constrain subsequent losses. Thus, while selection results in functional convergence between symbiont lineages, stochastic mutations initiate distinct evolutionary trajectories, generating diverse gene inventories that lack the functional redundancy typically found in free-living relatives.

Influence of Host Plants and Tending Ants on the Cuticular Hydrocarbon Profile of a Generalist Myrmecophilous Caterpillar.

In myrmecophilous organisms, which live in symbiosis with ants, cuticular hydrocarbons (CHCs) play a pivotal role in interspecific communication and defense against chemical-oriented predators. Although these interactions form complex information webs, little is known about the influence of biotic environmental factors on the CHC profiles of myrmecophiles. Here, we analyzed the effect of different host plants and tending ants on the larval CHC profile of Synargis calyce (Lepidoptera: Riodinidae), a polyphagous species with facultative myrmecophily. Groups of caterpillars were fed individually with three host plant species (without tending ants), and with two tending ant species. Through gas chromatography analysis, we compared the cuticular profiles of treatments and found a high similarity between plants and caterpillars (65-82%), but a low similarity between caterpillars and their tending ants (30 - 25%). Cluster analysis showed that caterpillars, ants, and plants form distinct groups, indicating that S. calyce caterpillars have their own chemical profile. These results are similar to those observed for Lycaenidae caterpillars indicating that there is functional convergence in the chemical strategies used by myrmecophilous caterpillar species with similar ecology. Also, the results suggest that the cuticular compounds of S. calyce are primarily influenced by their host plants rather than their tending ants. Thus, we propose that these caterpillars present a trade-off between camouflage and directly informing their presence to ants, maintaining their unique chemical profile, though slightly affected by biotic environmental factors.