Behavior Of System Research Articles

Protocell Effects on RNA Folding, Function, and Evolution.

ConspectusCreating a living system from nonliving matter is a great challenge in chemistry and biophysics. The early history of life can provide inspiration from the idea of the prebiotic "RNA World" established by ribozymes, in which all genetic and catalytic activities were executed by RNA. Such a system could be much simpler than the interdependent central dogma characterizing life today. At the same time, cooperative systems require a mechanism such as cellular compartmentalization in order to survive and evolve. Minimal cells might therefore consist of simple vesicles enclosing a prebiotic RNA metabolism.The internal volume of a vesicle is a distinctive environment due to its closed boundary, which alters diffusion and available volume for macromolecules and changes effective molecular concentrations, among other considerations. These physical effects are mechanistically distinct from chemical interactions, such as electrostatic repulsion, that might also occur between the membrane boundary and encapsulated contents. Both indirect and direct interactions between the membrane and RNA can give rise to nonintuitive, "emergent" behaviors in the model protocell system. We have been examining how encapsulation inside membrane vesicles would affect the folding and activity of entrapped RNA.Using biophysical techniques such as FRET, we characterized ribozyme folding and activity inside vesicles. Encapsulation inside model protocells generally promoted RNA folding, consistent with an excluded volume effect, independently of chemical interactions. This energetic stabilization translated into increased ribozyme activity in two different systems that were studied (hairpin ribozyme and self-aminoacylating RNAs). A particularly intriguing finding was that encapsulation could rescue the activity of mutant ribozymes, suggesting that encapsulation could affect not only folding and activity but also evolution. To study this further, we developed a high-throughput sequencing assay to measure the aminoacylation kinetics of many thousands of ribozyme variants in parallel. The results revealed an unexpected tendency for encapsulation to improve the better ribozyme variants more than worse variants. During evolution, this effect would create a tilted playing field, so to speak, that would give additional fitness gains to already-high-activity variants. According to Fisher's Fundamental Theorem of Natural Selection, the increased variance in fitness should manifest as faster evolutionary adaptation. This prediction was borne out experimentally during in vitro evolution, where we observed that the initially diverse ribozyme population converged more quickly to the most active sequences when they were encapsulated inside vesicles.The studies in this Account have expanded our understanding of emergent protocell behavior, by showing how simply entrapping an RNA inside a vesicle, which could occur spontaneously during vesicle formation, might profoundly affect the evolutionary landscape of the RNA. Because of the exponential dynamics of replication and selection, even small changes to activity and function could lead to major evolutionary consequences. By closely studying the details of minimal yet surprisingly complex protocells, we might one day trace a pathway from encapsulated RNA to a living system.

Evaluation of the Synergistic Oil Displacement Effect of a CO2 Low Interfacial Tension Viscosity-Increasing System in Ultra-Low Permeability Reservoirs

In addressing the issue of poor control over gas permeability during the CO2 flooding process in ultra-low permeability reservoirs, this study proposes the use of a low interfacial tension viscosity-increasing system as a substitute for water in CO2–water alternating flooding to enhance CO2 mobility control and increase oil recovery. The performance of the system was evaluated through tests of viscosity, interfacial tension, wettability, and emulsification properties, and the injection behavior and gas channeling prevention effect of the viscosity-increasing system with CO2 alternate flooding were investigated. The results indicate that the low interfacial tension viscosity-increasing fluid exhibits good thickening properties, interfacial activity, hydrophilic wettability, and oil–water emulsification performance, also demonstrating strong environmental adaptability. The CO2–low interfacial tension viscosity-increasing fluid alternate flooding shows good injectivity in ultra-low permeability cores (1.085 mD). Following water flooding in heterogeneous ultra-low permeability cores, the implementation of CO2 low interfacial tension viscosity-increasing fluid alternate flooding can lead to a 15.91% increase in overall recovery compared to water flooding, outperforming CO2 flooding and CO2–water alternating flooding. The mechanisms by which the CO2 low interfacial tension viscosity-increasing fluid enhances oil recovery include reducing interfacial tension, improving mobility ratio, altering rock surface wettability, and emulsification effects. The low interfacial tension viscosity-increasing systems demonstrate effective mobility control and oil displacement capabilities and synergistically enhance the efficiency of CO2, presenting potential application prospects in the development of CO2 flooding in ultra-low permeability reservoirs.

Effects of Capsanthin on the Dopamine System and Dopamine-Related Social Behavior

Effects of Capsanthin on the Dopamine System and Dopamine-Related Social Behavior

An analytical model to ascertain A.C. electrical conductivity of metal matrix composites

ABSTRACT With regard to an inherent understanding of electrical conductivity exhibited by monolithic metals and alloys system and metal matrix composite system under alternating current field, a long-standing unresolved issue, an analytical model is developed following classical free electron theory along with a typical conceptualisation of ‘effective relaxation time’ that combines conventional relaxation time (in view of collision of free electrons with lattice defects) and the time between successive cyclic reversals of electric field (the inverse of frequency). Two prime phenomena (electron scattering and polarisation at particle–matrix interface) are further conceived for metal matrix composite system containing particles. The developed model is found to closely follow (% deviation << 10) the available experimental result in the literature on A.C. electrical conductivity of 6063Al alloy and 6063Al–TiO2 composite systems. The model further ascertains certain system-specific parameters; such as, relaxation time under A.C. field, effective scattering factor and effective relaxation time aid from interface polarisation to specify the system behaviour under alternating current field. Accordingly, the model adequately explains the declining trend of A.C. electrical conductivity with increasing frequency in monolithic alloy system and an enhancement of A.C. electrical conductivity in metal matrix composite system in the presence of particles together with a non-declining trend even on increasing frequency.

Human Visual System applied to Facial Recognition

Research in the field of biometrics is constantly expanding. Numerous studies have been carried out to develop different techniques with the aim of ensuring reliable and efficient recognition systems. Of our five senses, vision takes up the most of the neurons in our brain. This makes the visual approach challenging. This paper proposes to develop a new facial recognition technique based on the concept of Human Visual System in order to simulate or imitate human perception. Our approach exploits the behavior of the Human Visual System in biometric systems to improve individual recognition. It focuses on Perceptual Channel Decomposition in order to generate images, confined around a certain frequency range, perfectly uncorrelated. For the extraction of characteristic vectors, our technique uses the Principal Component Analysis. The principle of the visual approach consists of exploiting one or more characteristics of the peripheral parts of the Human Visual System. These characteristics can integrate the sensitivity of the Human Visual System to spatial frequencies, its sensitivity to local contrast. The Principal Component Analysis uses a set of seventeen channels, each adjusted to a band of given radial frequencies and orientation. The seventeen output images contain the same spatial information but are perfectly uncorrelated from a spectral point of view. In the implementation phase, we limited ourselves to explore this technique by using only four frequency rings. The results obtained are conclusive and satisfactory.

Mimicking classical noise in ion channels by quantum decoherence

The mechanism of selectivity in ion channels is still an open question in biology. Recent studies suggest that the selectivity filter may exhibit quantum coherence, which could help explain how ions are selected and conducted. However, environmental noise causes decoherence and loss of quantum effects. It is hoped that the effect of classical noise on ion channels can be modeled using the framework provided by quantum decoherence theory. In this paper, the behavior of the ion channel system was simulated using two models: the Spin–Boson model and the stochastic Hamiltonian model under classical noise. Additionally, using a different approach, the system’s evolution was modeled as a two-level Spin–Boson model with tunneling, interacting with a bath of harmonic oscillators, based on decoherence theory. We investigated under what conditions the decoherence model approaches and deviates from the noise model. Specifically, we examined Gaussian noise and Ornstein-Uhlenbeck noise in our model. Gaussian noise shows a very good agreement with the decoherence model. By examining the results, it was found that the Spin–Boson model at a high hopping rate of potassium ions can simulate the behavior of the system in the classical noise approach for Gaussian noise.

Tropospheric ozone effect on olfactory perception and olfactory bulb dopaminergic interneuron excitability

Ozone (O3) forms in the Earth’s atmosphere, both naturally and by reactions of man-made air pollutants. Deleterious effects of O3 have been found in the respiratory system. Here, we examine whether O3 alters olfactory behavior and cellular properties in the olfactory system. For this purpose, mice were exposed to O3 at a concentration found in highly polluted city air [0.8 ppm], and the behavior elicited by social and non-social odors in habituation/dishabituation tests was assessed. In addition, the electrical responses of dopaminergic olfactory bulb (OB) neurons were also evaluated. O3 differentially compromises olfactory perception to odors: it reduces responses to social and non-social odors in Swiss Webster mice, while this effect was observed in C57BL/6J mice only for some non-social odors. Additionally, O3 reduced the rate of spontaneous spike firing in periglomerular dopaminergic cells (PG-DA) of the OB. Because this effect could reflect changes in excitability and/or synaptic inputs, the ability of O3 to alter PG-DA spontaneous activity was also tested together with cell membrane resistance, membrane potential, rheobase and chronaxia. Taken together, our data suggest the ability of O3 to affect olfactory perception.

Fabrication characterization and compression failure analysis of Ni-based alloy ABD-900AM TMPS structures via laser powder bed fusion

The novel high-strength and high-temperature nickel-based alloy developed for additive manufacturing, i.e., ABD-900AM, shows great potential in next-generation aircraft engines. However, there are limited investigations about the printing capability of ABD-900AM with complex structure as well as compression behaviors of this new alloy system. To meet the lightweight requirement, ABD-900AM with triply periodic minimal surface (TPMS) is fabricated by selective laser melting (SLM) in the present work, and the printing quality and compression performance of different TPMS structures are analyzed utilizing both experimental and computational methods. First, six types of TPMS structures are designed, and the external contours fabricated by SLMed ABD-900AM are detected through 3D optical scanning. In general, high fabrication quality is achieved with the proper process parameters, while the positive deviations are observed at the lateral surfaces and edges, and the negative deviations are observed at the upper regions of the cellular structures. Further, compression tests of SLMed ABD-900AM TPMS structures are conducted, and the failure mechanisms are evaluated. The equivalent elastic modulus is ranked as Diamond > Split-P > Primitive > Gyroid > I-WP > Lidinoid. The SLMed ABD-900AM TPMS structures shows advantages compared to these TPMS structures fabricated using typical metal alloys. Finally, the computational models of SLMed ABD-900AM TPMS structures are built up in the commercial software ABAQUS. The stress-strain behaviors and the failure process of different SLMed ABD-900AM TPMS structures are successfully reproduced.

The Awkward Sharing Economy: Its Status Quo and Prospect

This paper comprehensively analyzes the origins, current situation, and prospects of the sharing economy. The primary purpose is to present the issues and challenges confronting the sharing economy at its current, awkward stage of development and to make reasonable speculations about its future. The research is based on academic literature on the sharing economy from both domestic and international sources. The findings indicate that despite current shortcomings in the regulatory system, industry structure, and user behavior, the scope of the sharing economy’s applications could still expand, and its technology could continue to advance. Overall, the prospects for the sharing economy are likely to be promising.

Hopf bifurcation and patterns formation in a diffusive two prey-one predator system with fear in preys and help

Recognizing the relationship between the spatial patterns in species concentrations and ecological heterogeneity is crucial for understanding demographics and species governance in a given domain, as ecological patterning processes are believed to be imitated in real ecosystems. In this present article, we have considered a two-prey-one-predator system with Holling type-II functional response where both the preys have fear of predator and compete in the absence of predator. Additionally, we have assumed that both the prey help each other when the predator attacks them. We have incorporated self-diffusion in this system under Neumann boundary conditions. The existence and stability conditions of different equilibria are discussed. We have studied the Hopf bifurcation around positive offset and derived the stability and direction of periodic solution. We have done a series of numerical simulations to ensure our theoretical finding. Diffusion-driven instability conditions are obtained. Different instability regions and fascinating patterns, such as spots, mixtures, and stripes, are depicted. Spatiotemporal dynamics also reflects that prey populations are located in isolated areas of low population concentration with increasing level of fear, whereas an increase in handling time forms lower-density stripes. But with increasing help, prey becomes more concentrated in some stripe regions. In the Hopf-Turing region, it is observed that the diffusion coefficient of predators can stabilize the system. Overall, pattern creation in predator-prey systems can help anticipate long-term system behaviour and analyze the influence of ecological factors on system dynamics.

Machine learning-based uncertainty analysis in power system planning: Insights and pathways for decarbonization

This study performs an extensive uncertainty analysis of decarbonization pathways for the Canadian power system. By leveraging machine learning (ML) techniques, we represent complexities and nonlinear behaviors of the power system, which are challenging to observe using traditional modeling methods due to computational limitations. We further utilize K-means clustering and statistical methods to identify correlations, investigate the effects of uncertainty in key parameters (capital costs, demand, and carbon tax), and identify opportunities for diversification of the power generation mix. Key findings include the increased flexibility of gas combined cycle (generation mean 4.8 TWh, installed capacity mean 4.8 GW) over gas simple cycle (generation mean 22.3 GWh, 0 installed capacity) in response to carbon tax, highlighting its role in a low-carbon future. Variations in solar and wind deployment rates, influenced by capacity factors and location-specific costs, underscore the necessity of a flexible grid system. This analysis reveals important correlations between renewable deployment, and transmission expansion and gas combined cycle reliance. The results also highlight minimal sensitivity of hydroelectric power generation (∼ 43 % of scenarios) to changes in input parameters. The novelty of our work lies in proposing a comprehensive approach which uses ML techniques to go beyond the capabilities of existing models, specifically by performing extensive uncertainty analysis and provides key insights into system behavior, causative factors, and an expanded breadth of potential pathways. Taken together, this proposed approach lays a foundation for strategic planning and policy formulation.

The effect of SSRIs on unconditioned anxiety: a systematic review and meta-analysis of animal studies.

Selective serotonin reuptake inhibitors (SSRIs) are the first choice of treatment for anxiety-like disorders. However, which aspects of anxiety are affected by SSRIs is not yet fully understood. We aimed to systematically review the effect of six clinically effective SSRIs on four aspects of unconditioned anxiety: approach-avoidance behaviour (elevated plus maze), repetitive behaviour (marble burying), distress behaviour (ultrasonic vocalization), and activation of the autonomous nervous system (stress-induced hyperthermia). We identified publications by searching Medline and Embase databases and assessed the risk of bias. A random effects meta-analysis was performed and moderator effects were analysed with Bayesian penalized meta-regression. Our search yielded 105 elevated plus maze, 63 marble burying, 11 ultrasonic vocalization, and 7 stress-induced hyperthermia articles. Meta-analysis suggested that SSRIs reduce anxiety-like behaviour in the elevated plus maze, marble burying and ultrasonic vocalization test and that effects are moderated by pre-existing stress conditions (elevated plus maze) and dose dependency (marble burying) but not by duration of treatment or type of SSRI. The reporting quality was low, publication bias was likely, and heterogeneity was high. SSRIs seem to reduce a broad range of unconditioned anxiety-associated behaviours. These results should be interpreted with caution due to a high risk of bias, likely occurrence of publication bias, substantial heterogeneity and limited moderator data availability. Our review demonstrates the importance of including bias assessments when interpreting meta-analysis results. We further recommend improving the reporting quality, the conduct of animal research, and the publication of all results regardless of significance.

Complete critical bound region of the generalized exponential cosine screened Coulomb potential

The complete critical bound region of the generalized exponential cosine screened Coulomb potential (ECSCP) V(r)=−r−1e−(βcos⁡θ)rcos⁡[(βsin⁡θ)r] is investigated by employing the generalized pseudospectral method. Highly accurate critical screening parameters are determined over the entire parameter space, spanning from the exponential screened Coulomb potential (θ = 0), via the oscillatory ECSCP ( θ=π/4 ), to the strongest oscillatory cosine Coulomb potential (CCP) ( θ=π/2 ). With an efficient extrapolation technique, the critical screening parameter for the CCP is estimated at about βc=2.34 . By analyzing the variation of the ground state energy in the critical bound region, we separate the parameter space into two regions, i.e. the exponential region at small and moderate values of θ where the exponential screening term dominates the critical behavior of system, and the cosine region for θ close to π/4 where the oscillatory cosine term dominates.

Heparosan biosynthesis in recombinant Bacillus megaterium: Influence of N-acetylglucosamine supplementation and kinetic modeling.

Heparosan, an unsulfated polysaccharide, plays a pivotal role as a primary precursor in the biosynthesis of heparin-an influential anticoagulant with diverse therapeutic applications. To enhance heparosan production, the utilization of metabolic engineering in nonpathogenic microbial strains is emerging as a secure and promising strategy. In the investigation of heparosan production by recombinant Bacillus megaterium, a kinetic modeling approach was employed to explore the impact of initial substrate concentration and the supplementation of precursor sugars. The adapted logistic model was utilized to thoroughly analyze three vital parameters: the B. megaterium growth dynamics, sucrose utilization, and heparosan formation. It was noted that at an initial sucrose concentration of 30gL-1 (S1), it caused an inhibitory effect on both cell growth and substrate utilization. Intriguingly, the inclusion of N-acetylglucosamine (S2) resulted in a significant 1.6-fold enhancement in heparosan concentration. In addressing the complexities of the dual substrate system involving S1 and S2, a multi-substrate kinetic models, specifically the double Andrew's model was employed. This approach not only delved into the intricacies of dual substrate kinetics but also effectively described the relationships among the primary state variables. Consequently, these models not only provide a nuanced understanding of the system's behavior but also serve as a roadmap for optimizing the design and management of the heparosan production method.

Heparosan biosynthesis in recombinant Bacillus megaterium: Influence of N-acetylglucosamine supplementation and kinetic modeling.

Heparosan, an unsulfated polysaccharide, plays a pivotal role as a primary precursor in the biosynthesis of heparin-an influential anticoagulant with diverse therapeutic applications. To enhance heparosan production, the utilization of metabolic engineering in nonpathogenic microbial strains is emerging as a secure and promising strategy. In the investigation of heparosan production by recombinant Bacillus megaterium, a kinetic modeling approach was employed to explore the impact of initial substrate concentration and the supplementation of precursor sugars. The adapted logistic model was utilized to thoroughly analyze three vital parameters: the B. megaterium growth dynamics, sucrose utilization, and heparosan formation. It was noted that at an initial sucrose concentration of 30gL-1 (S1), it caused an inhibitory effect on both cell growth and substrate utilization. Intriguingly, the inclusion of N-acetylglucosamine (S2) resulted in a significant 1.6-fold enhancement in heparosan concentration. In addressing the complexities of the dual substrate system involving S1 and S2, a multi-substrate kinetic models, specifically the double Andrew's model was employed. This approach not only delved into the intricacies of dual substrate kinetics but also effectively described the relationships among the primary state variables. Consequently, these models not only provide a nuanced understanding of the system's behavior but also serve as a roadmap for optimizing the design and management of the heparosan production method.

Modeling of impact of operations and maintenance on safety, availability, capacity, and cost of Railways-A System dynamics approach

the transport infrastructure, particularly the railway infrastructure plays a vital role in the delivery of freight and the transportation of people. The ability and reliability of the railway infrastructure to deliver goods and transport people are challenged by train derailments and collisions caused by infrastructure breakdowns. Lack of maintenance has been identified as one of the causes of infrastructure breakdowns leading to accidents. The current paper proposes that if the railway infrastructure safety, availability, capacity, and cost are modeled using system dynamics, the impact of infrastructure operation and maintenance on safety can be predicted more accurately. The paper follows systems thinking approach that aims to understand the railway infrastructure as a system, by defining the system structure, system component relationships, and system behavior. The impact on railway infrastructure is modeled using system dynamics by developing causal loop diagrams and stock and flow diagrams which define the system structure, and system component relationships, and models the system behavior of safety, availability, capacity, and cost.

Evaluation of the Transfemoral Bone-Implant Interface Properties Using Vibration Analysis.

Evaluating the bone-implant interface (BII) properties of osseointegrated transfemoral (TFA) implants is important for early failure detection and prescribing loads during rehabilitation. The objective of this work is to derive and validate a 1D finite element (FE) model of the Osseointegrated Prosthetic Limb (OPL) TFA system that can: (1) model its dynamic behaviour and (2) extract the BII properties. The model was validated by: (1) comparing the 1D FE formulation to the analytical and 3D FE solutions for a simplifiedcylinder, (2) comparing the vibration modes of the actual TFA geometry using 1D and 3D FE models, and (3) evaluating the BII properties for three extreme conditions (LOW, INTERMEDIATE, and HIGH) generated using 3D FE and experimental (where the implant was embedded, using different adhesives, in synthetic femurs) signals for additional validation. The modes predicted by the 1D FE model converged to the analytical and the 3D FE solutions for the cylinder. The 1D model also matched the 3D FE solution with a maximum frequency difference of 2.02% for the TFA geometry. Finally, the 1D model extracted the BII stiffness and the system's damping properties for the three conditions generated using the 3DFE simulations and the experimental INTERMEDIATE and HIGH signals. The agreement between the 1D FE and the 3D FE solutions for the TFA geometry indicates that the 1D model captures the system's dynamic behaviour. Distinguishing between the different BII conditions demonstrates the 1D model's potential usefor the non-invasive clinical evaluation of the TFA BII properties.

FEINT: Automated Framework for Efficient INsertion of Templates/Trojans into FPGAs

Field-Programmable Gate Arrays (FPGAs) play a significant and evolving role in various industries and applications in the current technological landscape. They are widely known for their flexibility, rapid prototyping, reconfigurability, and design development features. FPGA designs are often constructed as compositions of interconnected modules that implement the various features/functionalities required in an application. This work develops a novel tool FEINT, which facilitates this module composition process and automates the design-level modifications required when introducing new modules into an existing design. The proposed methodology is architected as a “template” insertion tool that operates based on a user-provided configuration script to introduce dynamic design features as plugins at different stages of the FPGA design process to facilitate rapid prototyping, composition-based design evolution, and system customization. FEINT can be useful in applications where designers need to tailor system behavior without requiring expert FPGA programming skills or significant manual effort. For example, FEINT can help insert defensive monitoring, adversarial Trojan, and plugin-based functionality enhancement features. FEINT is scalable, future-proof, and cross-platform without a dependence on vendor-specific file formats, thus ensuring compatibility with FPGA families and tool versions and being integrable with commercial tools. To assess FEINT’s effectiveness, our tests covered the injection of various types of templates/modules into FPGA designs. For example, in the Trojan insertion context, our tests consider diverse Trojan behaviors and triggers, including key leakage and denial of service Trojans. We evaluated FEINT’s applicability to complex designs by creating an FPGA design that features a MicroBlaze soft-core processor connected to an AES-accelerator via an AXI-bus interface. FEINT can successfully and efficiently insert various templates into this design at different FPGA design stages.

Expanding model transparency and learning potential through structural and behavioural debriefings

AbstractSimulation‐based learning environments have been recommended by researchers as educational tools to support learning in complex domains. However, studies have evidenced that subjects may nevertheless have great difficulty understanding and managing dynamic systems, with several assertions are being made regarding the impact of employing transparent model simulations on learning and performance outcomes. This research, therefore, examines the moderating impacts of structural and behavioural debriefings, which are concentrated respectively on critical variables and relations, and on the connection between model structure, action patterns and system behaviour. We propose a series of hypotheses regarding the impact of model transparency and prior debriefing conditions on participants' performance and their comprehension of the system dynamics. Three out of the six hypotheses were validated: prior structural debriefing alongside model transparency positively impacts performance; prior behavioural debriefing, when combined with model transparency and prior structural debriefing, positively impacts both the comprehension of model dynamics and performance.

Expanding model transparency and learning potential through structural and behavioural debriefings

AbstractSimulation‐based learning environments have been recommended by researchers as educational tools to support learning in complex domains. However, studies have evidenced that subjects may nevertheless have great difficulty understanding and managing dynamic systems, with several assertions are being made regarding the impact of employing transparent model simulations on learning and performance outcomes. This research, therefore, examines the moderating impacts of structural and behavioural debriefings, which are concentrated respectively on critical variables and relations, and on the connection between model structure, action patterns and system behaviour. We propose a series of hypotheses regarding the impact of model transparency and prior debriefing conditions on participants' performance and their comprehension of the system dynamics. Three out of the six hypotheses were validated: prior structural debriefing alongside model transparency positively impacts performance; prior behavioural debriefing, when combined with model transparency and prior structural debriefing, positively impacts both the comprehension of model dynamics and performance.