Complexity Of Function Research Articles

Automatic Abelian Complexities of Parikh-Collinear Fixed Points

AbstractParikh-collinear morphisms have the property that all the Parikh vectors of the images of letters are collinear, i.e., the associated adjacency matrix has rank 1. In the conference DLT–WORDS 2023 we showed that fixed points of Parikh-collinear morphisms are automatic. We also showed that the abelian complexity function of a binary fixed point of such a morphism is automatic under some assumptions. In this note, we fully generalize the latter result. Namely, we show that the abelian complexity function of a fixed point of an arbitrary, possibly erasing, Parikh-collinear morphism is automatic. Furthermore, a deterministic finite automaton with output generating this abelian complexity function is provided by an effective procedure. To that end, we discuss the constant of recognizability of a morphism and the related cutting set.

Shell biomechanics suggests an aquatic palaeoecology at the dawn of turtle evolution

The turtle shell is a remarkable structure that has intrigued not only evolutionary biologists but also engineering and material scientists because of its multi-scale complexity and various functions. Although protection is its most apparent role, the carapace and plastron are also related to many physiological functions and their shape influences hydrodynamics and self-righting ability. As such, analysing the functional morphology of the shell could help understanding the ecology of Triassic stem-turtles, which will contribute to the century-long debate on the evolutionary origins of turtles. Here, we used 3D imaging techniques to digitize the shells of two of the earliest stem-turtle taxa, Proganochelys and Proterochersis, and submitted their models to biomechanical and shape analyses. We analysed the strength performance under five predation scenarios and tested the function of two morphological traits found in stem-turtles, the epiplastral processes and an attached pelvic girdle. The latter, also present in the crown-lineage of side-necked turtles, has been suggested to increase load-bearing capacity of the shell or to improve swimming in pleurodires. Our results do not confirm the shell-strengthening hypothesis and, together with the results of our shape analyses, suggest that at least one of the first stem-turtles (Proterochersis) was an aquatic animal.

Peptide-Based Biomimetic Condensates via Liquid-Liquid Phase Separation as Biomedical Delivery Vehicles.

Biomolecular condensates are dynamic liquid droplets through intracellular liquid-liquid phase separation that function as membraneless organelles, which are highly involved in various complex cellular processes and functions. Artificial analogs formed via similar pathways that can be integrated with biological complexity and advanced functions have received tremendous research interest in the field of synthetic biology. The coacervate droplet-based compartments can partition and concentrate a wide range of solutes, which are regarded as attractive candidates for mimicking phase-separation behaviors and biophysical features of biomolecular condensates. The use of peptide-based materials as phase-separating components has advantages such as the diversity of amino acid residues and customized sequence design, which allows for programming their phase-separation behaviors and the physicochemical properties of the resulting compartments. In this Perspective, we highlight the recent advancements in the design and construction of biomimicry condensates from synthetic peptides relevant to intracellular phase-separating protein, with specific reference to their molecular design, self-assembly via phase separation, and biorelated applications, to envisage the use of peptide-based droplets as emerging biomedical delivery vehicles.

A genetic algorithm to solve the production lot-sizing problem with capacity adjustment

When dynamic production capacity is considered in production lot-sizing plans, it becomes very challenging to efficiently determine the optimal production plan. Many papers apply “at most one fractional production period” to develop efficient algorithms, but those algorithms are still time consuming. In this paper, in a special situation where costs are non-speculative, we provide a novel proposal based on “at least one balance period”, in which the products made in this period not only satisfy the demands in this period but also backlogged demands and some demands after this period, to obtain an efficient algorithm. This algorithm complexity is one level lower than the algorithm without non-speculative cost assumptions in the literature regarding the number of periods in their time complexity function. Then, in a general situation, we propose a combination of two complementary algorithms as an efficient heuristic method. Moreover, in the literature, the estimation of computation time complexity in searching for the optimal production plan considers only the number of capacity levels and production periods on theoretical view. However, with numerical experiments, we observe that demand variation could also have significant effects on the computation time in practice.

Filter generators with variable transition functions over finite fields of characteristic 2

Filter generators are a traditional basis for creating synchronous stream ciphers. They are built with the help of linear shift registers (usually over a field of two elements) and nonlinear complexity functions, which are subject to a number of requirements in terms of the generators security against known attacks. Intensive researches of filter generators during the last decades show that meeting these requirements without degrading the performance of the generators is a very difficult task. Despite a large number of publications devoted to the construction of complexity functions with known “good cryptographic properties”, the usage of such functions in practice often becomes unacceptable due to the bulkiness of their constructions, which slows down the functioning of the corresponding generators, especially during software implementation. The way to overcome the noted difficulties by using an additional secret parameter that determines the appearance of the generator transitions’ function is proposed. Such a modification makes it possible to increase the security of generator (compared to traditional filter generators) against known attacks without increasing the length of its initial state. In particular, a specific version of a generator construction with a complexity function, which is determined with the help of substitutions used in the “Kalyna” encryption scheme, is considered. A lower estimate of the output sequences periods of the proposed generators was obtained. A research of their security to known attacks, in particular, Babbage-Golic balancing attack; an attack associated with a small number of terms in the polynomial representation of the complexity function (which negatively affects the value of the equivalent linear complexity of the output sequences of the generator); a natural correlation attack associated with the specifics of the proposed generator construction scheme; algebraic attacks of the Courtois-Mayer type were also conducted. At the end of the article, it is indicated how to choose the components of the proposed generators to ensure their security at a predetermined level.

Complexity function of jammed configurations of Rydberg atoms

Complexity function of jammed configurations of Rydberg atoms

Adrenal insufficiency in pediatric kidney transplantation recipients.

Immunosuppression of pediatric kidney transplant (PKT) recipients often includes corticosteroids. Prolonged corticosteroid exposure has been associated with secondary adrenal insufficiency (AI); however, little is known about its impact on PKT recipients. This was a retrospective cohort review of PKT recipients to evaluate AI prevalence, risk factors, and adverse effects. AI risk was assessed using morning cortisol (MC) and diagnosis confirmed by an ACTH stimulation test. Potential risk factors and adverse effects were tested for associations with MC levels and AI diagnosis. Fifty-one patients (60.8% male, age 7.4 (IQR 3.8, 13.1) years; 1 patient counted twice for repeat transplant) were included. Patients at risk for AI (MC < 240 nmol/L) underwent definitive ACTH stimulation testing, confirming AI in 13/51 (25.5%) patients. Identified risk factors for AI included current prednisone dosage (p = .001), 6-month prednisone exposure (p = .02), daily prednisone administration (p = .002), and rejection episodes since transplant (p = .001). MC level (2.5 years (IQR 1.1, 5.1) post-transplant) was associated with current prednisone dosage (p < .001), 6-month prednisone exposure (p = .001), daily prednisone administration (p = .006), rejection episodes since transplant (p = .003), greater number of medications (β = -16.3, p < .001), 6-month hospitalization days (β = -3.3, p = .013), creatinine variability (β = -2.4, p = .025), and occurrence of acute kidney injury (β = -70.6, p = .01). Greater corticosteroid exposure was associated with a lower MC level and confirmatory diagnosis of AI noted with an ACTH stimulation test. Adverse clinical findings with AI included greater medical complexity and kidney function lability. These data support systematic clinical surveillance for AI in PKT recipients treated with corticosteroids.

B-type natriuretic peptide levels predict long-term mortality in a large cohort of adults with congenital heart disease.

Many adult patients with congenital heart disease (ACHD) are still afflicted by premature death. Previous reports suggested natriuretic peptides may identify ACHD patients with adverse outcome. The study investigated prognostic power of B-type natriuretic peptide (BNP) across the spectrum of ACHD in a large contemporary cohort. The cohort included 3392 consecutive ACHD patients under long-term follow-up at a tertiary ACHD centre between 2006 and 2019. The primary study endpoint was all-cause mortality. A total of 11 974 BNP measurements were analysed. The median BNP at baseline was 47 (24-107) ng/L. During a median follow-up of 8.6 years (29 115 patient-years), 615 (18.1%) patients died. On univariable and multivariable analysis, baseline BNP [hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.15-1.18 and HR 1.13, 95% CI 1.08-1.18, respectively] and temporal changes in BNP levels (HR 1.22, 95% CI 1.19-1.26 and HR 1.19, 95% CI 1.12-1.26, respectively) were predictive of mortality (P < .001 for both) independently of congenital heart disease diagnosis, complexity, anatomic/haemodynamic features, and/or systolic systemic ventricular function. Patients within the highest quartile of baseline BNP (>107 ng/L) and those within the highest quartile of temporal BNP change (>35 ng/L) had significantly increased risk of death (HR 5.8, 95% CI 4.91-6.79, P < .001, and HR 3.6, 95% CI 2.93-4.40, P < .001, respectively). Baseline BNP and temporal BNP changes are both significantly associated with all-cause mortality in ACHD independent of congenital heart disease diagnosis, complexity, anatomic/haemodynamic features, and/or systolic systemic ventricular function. B-type natriuretic peptide levels represent an easy to obtain and inexpensive marker conveying prognostic information and should be used for the routine surveillance of patients with ACHD.

Complexity of non-abelian cut-and-project sets of polytopal type I: special homogeneous Lie groups

Abstract The aim of this paper is to determine the asymptotic growth rate of the complexity function of cut-and-project sets in the non-abelian case. In the case of model sets of polytopal type in homogeneous two-step nilpotent Lie groups, we can establish that the complexity function asymptotically behaves like $r^{{\mathrm {homdim}}(G) \dim (H)}$ . Further, we generalize the concept of acceptance domains to locally compact second countable groups.

Characterizing heterogeneous forest structure in ponderosa pine forests via UAS-derived structure from motion

Increasingly, dry conifer forest restoration has focused on reestablishing horizontal and vertical complexity and ecological functions associated with frequent, low-intensity fires that characterize these systems. However, most forest inventory approaches lack the resolution, extent, or spatial explicitness for describing tree-level spatial aggregation and openings that were characteristic of historical forests. Uncrewed aerial system (UAS) structure from motion (SfM) remote sensing has potential for creating spatially explicit forest inventory data. This study evaluates the accuracy of SfM-estimated tree, clump, and stand structural attributes across 11 ponderosa pine-dominated stands treated with four different silvicultural prescriptions. Specifically, UAS-estimated tree height and diameter-at-breast-height (DBH) and stand-level canopy cover, density, and metrics of individual trees, tree clumps, and canopy openings were compared to forest survey data. Overall, tree detection success was high in all stands (F-scores of 0.64 to 0.89), with average F-scores > 0.81 for all size classes except understory trees (< 5.0 m tall). We observed average height and DBH errors of 0.34 m and − 0.04 cm, respectively. The UAS stand density was overestimated by 53 trees ha−1 (27.9%) on average, with most errors associated with understory trees. Focusing on trees > 5.0 m tall, reduced error to an underestimation of 10 trees ha−1 (5.7%). Mean absolute errors of bole basal area, bole quadratic mean diameter, and canopy cover were 11.4%, 16.6%, and 13.8%, respectively. While no differences were found between stem-mapped and UAS-derived metrics of individual trees, clumps of trees, canopy openings, and inter-clump tree characteristics, the UAS method overestimated crown area in two of the five comparisons. Results indicate that in ponderosa pine forests, UAS can reliably describe large- and small-grained forest structures to effectively inform spatially explicit management objectives.

Astrocytic Slc4a4 regulates blood-brain barrier integrity in healthy and stroke brains via a CCL2-CCR2 pathway and NO dysregulation

Astrocytes play vital roles in blood-brain barrier (BBB) maintenance, yet how they support BBB integrity under normal or pathological conditions remains poorly defined. Recent evidence suggests that ion homeostasis is a cellular mechanism important for BBB integrity. In the current study, we investigated the function of an astrocyte-specific pH regulator, Slc4a4, in BBB maintenance and repair. We show that astrocytic Slc4a4 is required for normal astrocyte morphological complexity and BBB function. Multi-omics analyses identified increased astrocytic secretion of CCL2 coupled with dysregulated arginine-NO metabolism after Slc4a4 deletion. Using a model of ischemic stroke, we found that loss of Slc4a4 exacerbates BBB disruption, which was rescued by pharmacological or genetic inhibition of the CCL2-CCR2 pathway invivo. Together, our study identifies the astrocytic Slc4a4-CCL2 and endothelial CCR2 axis as a mechanism controlling BBB integrity and repair, while providing insights for a therapeutic approach against BBB-related CNS disorders.

Minimally monophyletic genera are the cast-iron building blocks of evolution

Detailed evaluation is provided for the statistical methods intrinsic to interlocking Sequential Bayes analysis, which allows estimation of evidential support for stem-taxon dendrograms charting the macroevolution of taxa. It involves complexity functions, such as fractal evolution, to generate well-supported evolutionary trees. Required are data on trait changes from ancestral species to descendant species, which is facilitated by reduction of large genera to the smallest included monophyletic groups (one inferred ancestral species each). The genus is here defined as the smallest monophyletic unit, which turns out to be monothetic at least for the direct descendant species. The key fact is that the most-recently acquired traits of the single ancestral species are apparently selectively inviolate and passed on without change to each immediate descendant species. The details of sequential Bayesian analysis were clarified by comparing support of the optimal model with summed support of the alternative models. Because analysis is confined to optimal arrangements of only immediate branches from ancestral species to descendant species, conjugate priors were found to operate such that all alternative models are simply one minus the probability of the optimal model. Such analysis demonstrated that the optimum arrangement of ancestor and descendant species leads to high support values for fitting evolutionary theory, comparable to statistical support levels reported for molecular evolutionary trees, and conjugate priors may be assumed for similar model-building. The method is simple, free of special computer analysis, and well-suited to standard taxonomic practice.

Development of Modified ECC-Based Secured FoG-Assisted Healthcare Data Management System in IoT-Enabled WSN

The Internet of Things (IoT) consists of a massive count of connected devices with different sensing support, particularly in medical health constraints sensing. In these summaries, secure communication and data collection to centralized servers is rather difficult for preventing the occurrence of diverse attacks for illegal data access. To tackle these problems, this task plans to design and implement the FoG-based secure data management system in IoT-WSN using adaptive encryption and decryption processes. As the FoG server is away from the corresponding aggregator node, it is transmitted via the other nodes using the proposed modified Elliptic Curve Cryptography (ECC)-based encryption process. For secured data transmission the designed method undergoes two main stages as message receiving stage, and the message-extraction stage. The hybridized meta-heuristic algorithm termed Jaya-Galactic Swarm Optimization (J-GSO) is used for modifying the ECC with an optimized key. From the simulation findings, the performance of the suggested scheme at the data size of three bytes is 3.08%, 3.22%, 3.65%, and 3.33% better than the MFO-m-ECC, PSO-m-ECC, GSO-m-ECC, and JA-m-ECC at the ECC curve variation of “secp192r1”. Experimental results reveal the superiority of the designed method when tested with baseline schemes regarding time complexity, space complexity, and cost function.

Thymic Atrophy and Immune Dysregulation in Infants with Complex Congenital Heart Disease

Congenital heart disease (CHD) is the most common birth defect, and up to 50% of infants with CHD require cardiovascular surgery early in life. Current clinical practice often involves thymus resection during cardiac surgery, detrimentally affecting T-cell immunity. However, epidemiological data indicate that CHD patients face an elevated risk for infections and immune-mediated diseases, independent of thymectomy. Hence, we examined whether the cardiac defect impacts thymus function in individuals with CHD. We investigated thymocyte development in 58 infants categorized by CHD complexity. To assess the relationship between CHD complexity and thymic function, we analyzed T-cell development, thymic output, and biomarkers linked to cardiac defects, stress, or inflammation. Patients with highly complex CHD exhibit thymic atrophy, resulting in low frequencies of recent thymic emigrants in peripheral blood, even prior to thymectomy. Elevated plasma cortisol levels were detected in all CHD patients, while high NT-proBNP and IL-6 levels were associated with thymic atrophy. Our findings reveal an association between complex CHD and thymic atrophy, resulting in reduced thymic output. Consequently, thymus preservation during cardiovascular surgery could significantly enhance immune function and the long-term health of CHD patients.

Estimating groundwater recharge rates in the Upper Awash Basin, Ethiopia under different combinations of model complexity and objective functions

Abstract This study addresses the critical need for reliable groundwater recharge quantification by investigating the uncertainty associated with recharge estimation based on various combinations of model complexity and objective functions. Focusing on the Hombele catchment in the upper Awash Basin, Ethiopia, the research aims to analyze parameter sensitivity under different model complexities and objectives while estimating groundwater recharge for the period 1986–2013. Employing a Monte-Carlo-based calibration scheme, the study fine-tunes model parameters using objective functions like KGE, NSE, LogNSE, R2, and VE across 10 combinations of model complexity and objective functions. Results identify FC, LP, and BETA as highly sensitive parameters, while UZL, K0, and MAXBAS show limited influence in all model complexity and objective function scenarios. The semi-distributed HBV-light model achieves calibration, validation, and overall period KGE (NSE) values of 0.89 (0.80), 0.80 (0.73), and 0.87 (0.77), respectively. Sensitivity analyses reveal significant impacts on model parameters and recharge estimation based on the chosen objective function and model complexity levels. Average annual recharge rates range from 185.9–280.5 mm when the HBV-light model is semi-distributed, contrasting with 185.3–321.7 mm under lumped model conditions, emphasizing the importance of considering these factors in groundwater resource assessments.

A Novel Hybrid Optimization-based Backstepping Fractional Order Sliding Mode Proportional-integral-derivative Controller for Nonlinear Biological System

Nowadays, the role of the control system in the bioengineering field plays a major part due to its significant improvement and demand. Usually, if there are any changes in the parameter of a biological system, then it tends to cause crucial diseases in humans. Previously, various control algorithms have been developed; however, the proper control process failed due to the high error rate, slow convergence, Computational Complexity, Tuning Complexity and inaccurate function. The proposed control strategy should ensure accurate tracking of the desired trajectory or reference signal, even in the presence of uncertainties and disturbances. The control system should be capable of adapting to changes in the system dynamics and maintaining stable operation. This complexity can lead to high computational requirements, making the controller computationally expensive and potentially unsuitable for real-time applications or systems with limited computing resources. To overcome these issues, in this work, the novel Hybrid Ant Lion Moth Flame Optimization (HALMFO) based Backstepping Fractional-Order Sliding mode Proportional-Integral-Derivative (BFO-SPID) controller is proposed for different nonlinear biological systems. The proposed method enhances the efficiency, improved performance, robustness, convergence speed, and solution quality of the optimization process. This paper addresses the challenge of controlling nonlinear biological systems by proposing a novel hybrid optimization-based backstepping approach combined with a fractional order sliding mode proportional-integral-derivative (PID) controller. This work’s essential contribution lies in addressing existing control strategies’ limitations by integrating multiple control techniques to achieve robust tracking performance and disturbance rejection. This system proposes predictive control with state estimation based on the backstepping sliding mode method. The gain parameters of the developed controller are optimized using the HALMFO method. The proposed control approach performance has been tested under biological systems such as Protein, Pancreas, and Genetic Regulatory Network (GRN). The execution of this proposed model is done in MATLAB/Simulink. Furthermore, the performance of the proposed control technique is compared with various state-of-the-art methods in terms of accuracy, Mean Average Error (MAE), Mean Square Error (MSE), settling time, overshoot, and rise time. The comparison illustrates that the projected controller has reached a steady condition with the least error rate in the control application. Thus the developed controller regulates the parameter variations in the biological system as per the desired level, providing significant effective outcomes to complex problems.

Reminiscences on the honeybee genome project and the rise of epigenetic concepts in insect science.

The sequencing of the honeybee genome in 2006 was an important technological and logistic achievement experience. But what benefits have flown from the honeybee genome project? What does the annotated genomic assembly mean for the study of behavioural complexity and organismal function in honeybees? Here, I discuss several lines of research that have arisen from this project and highlight the rapidly expanding studies on insect epigenomics, emergent properties of royal jelly, the mechanism of nutritional control of development and the contribution of epigenomic regulation to the evolution of sociality. I also argue that the term 'insect epigenetics' needs to be carefully redefined to reflect the diversity of epigenomic toolkits in insects and the impact of lineage-specific innovations on organismal outcomes. The honeybee genome project helped pioneer advances in social insect molecular biology, and fuelled breakthrough research into the role of flexible epigenomic control systems in linking genotype to phenotype.

Comparative Site-Specific O-Glycosylation Analysis of the Milk Fat Globule Membrane Proteome in Donkey Colostrum and Mature Milk.

Donkey milk fat globule membrane (MFGM) proteins are a class of membrane-bound secreted proteins with broad-spectrum biofunctional activities; however, their site-specific O-glycosylation landscapes have not been systematically mapped. In this study, an in-depth MFGM O-glycoproteome profile of donkey milk during lactation was constructed based on an intact glycopeptide-centered, label-free glycoproteomics pipeline, with 2137 site-specific O-glycans from 1121 MFGM glycoproteins and 619 site-specific O-glycans from 217 MFGM glycoproteins identified in donkey colostrum and donkey mature milk, respectively. As lactation progressed, the number of site-specific O-glycans from three glycoproteins significantly increased, whereas that of 11 site-specific O-glycans from five glycoproteins significantly decreased. Furthermore, donkey MFGM O-glycoproteins with core-1 and core-2 core structures and Lewis and sialylated branch structures may be involved in regulating apoptosis. The findings of this study reveal the differences in the composition of donkey MFGM O-glycoproteins and their site-specific O-glycosylation modification dynamic change rules during lactation, providing a molecular basis for understanding the complexity and biological functions of donkey MFGM protein O-glycosylation.

Simultaneous and site-specific profiling of heterogeneity and turnover in protein S-acylation by intact S-acylated peptide analysis with a cleavable bioorthogonal tag.

Protein S-acylation is an important lipid modification characteristic for heterogeneity in the acyl chain and dynamicity in the acylation/deacylation cycle. Most S-acylproteomic research has been limited by indirect identification of modified proteins/peptides without attached fatty acids, resulting in the failure to precisely characterize S-acylated sites with attached fatty acids. The study of S-acylation turnover is still limited at the protein level. Herein, aiming to site-specifically profile both the heterogeneity and the turnover of S-acylation, we first developed a site-specific strategy for intact S-acylated peptide analysis by introducing an acid cleavable bioorthogonal tag into a metabolic labelling method (ssMLCC). The cleavable bioorthogonal tag allowed for the selective enrichment and efficient MS analysis of intact S-acylated peptides so that S-acylated sites and their attached fatty acids could be directly analysed, enabling the precise mapping of S-acylated sites, as well as circumventing false positives from previous studies. Moreover, 606 S-palmitoylated (C16:0) sites of 441 proteins in HeLa cells were identified. All types of S-acylated peptides were further characterized by an open search, providing site-specific profiling of acyl chain heterogeneity, including S-myristoylation, S-palmitoylation, S-palmitoleylation, and S-oleylation. Furthermore, site-specific monitoring of S-palmitoylation turnover was achieved by coupling with pulse-chase methods, facilitating the detailed observation of the dynamic event at each site in multi-palmitoylated proteins, and 85 rapidly cycling palmitoylated sites in 79 proteins were identified. This study provided a strategy for the precise and comprehensive analysis of protein S-acylation based on intact S-acylated peptide analysis, contributing to the further understanding of its complexity and biological functions.

Heavy metal contamination impacts the structure and co-occurrence patterns of bacterial communities in agricultural soils.

Heavy metal (HM) contamination caused by mining and smelting activities can be harmful to soil microbiota, which are highly sensitive to HM stress. Here, we explore the effects of HM contamination on the taxonomic composition, predicted function, and co-occurrence patterns of soil bacterial communities in two agricultural fields with contrasting levels of soil HMs (i.e., contaminated and uncontaminated natural areas). Our results indicate that HM contamination does not significantly influence soil bacterial α diversity but changes the bacterial community composition by enriching the phyla Gemmatimonadetes, Planctomycetes, and Parcubacteria and reducing the relative abundance of Actinobacteria. Our results further demonstrate that HM contamination can strengthen the complexity and modularity of the bacterial co-occurrence network but weaken positive interactions between keystone taxa, leading to the gradual disappearance of some taxa that originally played an important role in healthy soil, thereby possibly reducing the resistance of bacterial communities to HM toxicity. The predicted functions of bacterial communities are related to membrane transport, amino acid metabolism, energy metabolism, and carbohydrate metabolism. Among these, functions related to HM detoxification and antioxidation are enriched in uncontaminated soils, while HM contamination enriches functions related to metal resistance. This study demonstrated that microorganisms adapt to the stress of HM pollution by adjusting their composition and enhancing their network complexity and potential ecological functions.