Variation Of Structural Parameters Research Articles

Integrated study of the structural and magnetic characteristics of Nd(Mn, Cr)0.5O3: exploring perovskite material

In this work, a perovskite material, Nd(Mn,Cr)0.5O3, is synthesized by a sol–gel chemical route method, and the structural and magnetic properties of the prepared samples were studied for a range of annealing temperatures. The variation of structural parameters against annealing temperatures is analyzed via Rietveld refinement, and it exhibits orthorhombic cubic geometry with non-monotonically increasing lattice parameters. lattice strain is due to canting in the Cr3+ and Mn3+ ions and the presence of strain is also confirmed by the shifting of XRD peaks towards a higher 2θ angle. The obtained Goldschmidt tolerance factor is 0.87, which confirms the stability of the perovskite structure. The magnetic properties of the prepared samples show the ferromagnetic transition temperature ranging from 86.5 K to 82.2 K due to super-exchange interaction between Cr3+ and Mn3+ ions via oxygen ions. The stability in crystal structure, lower value of strain, and ferromagnetic nature at low temperature for the samples annealed up to1000 °C may make this material applicable for magnetic data storage.

Leading-edge tubercles as an alternative to increasing a Francis turbine torque generation

Hydroelectricity accounts for 63.8% of Brazilian electricity, but several of the country’s power plants require modernization. For this, the insertion of leading-edge tubercles is an alternative since this device improves wind and tidal turbines. Surprisingly, no study explored the device’s potential for hydraulic turbine improvement. To address this gap, numerical simulations were conducted in Ansys CFX to assess the tubercles’ effects on the performance of Francis turbines. For this, the current study validated the simulations and tested the impacts of the tubercle structural parameters variation over the benchmarking turbine Francis-99 and applied the device in a non-modernized runner blade to evaluate its effects on equipment performance. The parameters test revealed that variations in tubercle amplitude and waviness ratio improved the torque generation up to 0.34% despite elevating the net head up to 0.43%. In the non-modernized blade, the device increased the torque generation and net head up to 1.77% and 4.13%, respectively, proving that the tubercles are an alternative for hydraulic turbine improvement. Also, the flow field analysis exhibits that the device creates vortices that influence the blade pressure side, delaying boundary layer detachment, agreeing with other results in the literature.

Electrochemical Capacitance Traces with Interlayer Spacing in Two‐dimensional Conductive Metal–Organic Frameworks

AbstractElectrically conductive metal–organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double‐layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure‐function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene‐based 2D layered conductive MOFs with variable alkyl functional groups, Ni3(HIR3‐TAT)2 (TAT=triazatruxene; R=H, Et, n‐Bu, n‐Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in‐plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double‐layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni3(HIH3‐TAT)2 to Ni3(HIBu3‐TAT)2. Partial exfoliation of Ni3(HIBu3‐TAT)2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox‐active sites may motivate further design and engineering of electrode materials for EC.

Electrochemical Capacitance Traces with Interlayer Spacing in Two-dimensional Conductive Metal-Organic Frameworks.

Electrically conductive metal-organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double-layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure-function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene-based 2D layered conductive MOFs with variable alkyl functional groups, Ni3(HIR3-TAT)2 (TAT=triazatruxene; R=H, Et, n-Bu, n-Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in-plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double-layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni3(HIH3-TAT)2 to Ni3(HIBu3-TAT)2. Partial exfoliation of Ni3(HIBu3-TAT)2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox-active sites may motivate further design and engineering of electrode materials for EC.

Characteristics analysis and structure optimization of a hybrid micro-jet impingement/micro-channel heat sink

To solve the heat dissipation problem of high-power electronics, a novel hybrid micro-jet impingement/micro-channel heat sink is proposed in this work. Different from the continuous and straight rectangular micro-channel, the inclined and interrupted channel walls (fins) are adopted to enhance the fluid disturbance inside the heat sink. To obtain the thermal–hydraulic performance of the hybrid heat sink, an overall 3D modeling and numerical simulations are conducted instead of local cell numerical simulation. In addition, to further improve the heat transfer and flow resistance performance, the effects of variation of structural parameters on heat transfer and flow resistance properties are investigated, including the fin inclination angle, fin length and fin height. The results of structural parametric analysis reveal that there are interactions between different structural parameters, but with different levels of significance for different evaluation indicators. Then, to obtain the optimal combinations of structural parameters for different applications, the multi-objective genetic algorithm coupled with artificial neural network (ANN) is utilized to search for the optimal value of each structural parameter. The heat transfer thermal resistance, pressure drop and mean absolute temperature deviation of the heated surface are utilized as the optimization objectives to evaluate the cooling and resistance characteristics. The optimization results obtained by three-objective optimization and two-objective optimization are analyzed and compared. Finally, seven optimal compromise solutions are selected from the Pareto front by using TOPSIS algorithm with different weight factor matrices. For the optimal compromise solutions, the maximum relative errors between the predicted values of the ANN and numerical simulation values are only 3%, which further demonstrates the accuracy of the artificial neural network model and the effectiveness of using multi-objective optimization to guide heat sink design.

Widely tunable single-mode interband cascade lasers based on V-coupled cavities and dependence on design parameters

We report an investigation of V-coupled cavity interband cascade (IC) lasers (ICLs) emitting in the 3-μm wavelength range, employing various waveguide structures and coupler sizes. Type-II ICL devices with double-ridge waveguides exhibited wide tuning ranges exceeding 153 nm. Type-I ICL devices with deep-etched waveguides achieved single-mode emission with wavelength tunable over 100 nm at relatively high temperatures up to 250 K. All devices exhibited a side-mode suppression ratio higher than 30 dB. By comparing the performance of all devices with different sizes and configurations, a good tolerance against the structural parameter variations of the V-coupled cavity laser (VCCL) design is demonstrated, validating the advantages of the VCCL to achieve single-mode emission with wide tunability.

Detection of liquid chemical analytes using a novel PCF-SPR sensor based on the wavelength sensitivity measurement method

This paper proposes a novel, highly sensitive, dual-coated PCF-SPR sensor for harmful chemical detection. The sensor’s performance is investigated based on the measurement of the wavelength sensitivity method. Silver (Ag) is a plasmonic material, and Ta2O5 is used as an overlayer to enhance its performance. The impact of Ta2O5 thickness and structural parameter variation on sensor performance is also measured. The proposed plasmonic sensor measured the maximum wavelength sensitivity of 23000 nm/RIU. This investigation undoubtedly provides a new approach to designing a PCF-SPR sensor that tunes the range of chemical refractive indices by changing Ta2O5 thickness. Besides, the simplicity, flexibility, and fabrication-friendly design make it applicable for chemical analyte sensing.

Investigation of pressure impact on physical characteristics of FeSe chalcogenide superconductor: Insights from first principles calculation

Understanding the high-pressure physical characteristics of iron selenium (FeSe) superconductors is crucial to comprehending their superconducting abilities. First-principles Density Functional Theory has been computed in the present calculations to analyze the pressure impact on structural, mechanical, electronic and superconducting characteristics along with the Debye and melting temperatures of tetragonal FeSe. The analysis of mechanical characteristics suggests that this compound remains mechanically stable up to a pressure of 20 GPa. The applied hydrostatic pressure is observed to have a significant impact on the elastic moduli and the anisotropic behaviour of FeSe at all pressure conditions. Similarly, the first indication of ductility is observed approximately at 8 GPa and then it increases as pressure rises. At 0 GPa, the optimized structural values are seen to line up with the available data. The variation of structural parameters and electronic factors of FeSe with applied pressure is also mentioned here. Moreover, the assessment of the compound’s electronic characteristics provides strong evidence for its metallic nature and the rise in a number of states at the Fermi energy level with applied pressure may be the cause for the increase in the superconducting critical temperature of FeSe with pressure.

Analyzing monopole sources modeling with structural variations and material contrast: An analytical perspective

This study presents a comprehensive analysis of modeling acoustic radiation from monopole sources within waveguides, considering variations in structural parameters, including backward passage and the use of sound-absorbent materials. The investigation employs analytical techniques, including mode-matching methods and Fourier transforms, to address the intricate boundary value problem governing acoustic behavior in waveguides. Eigenfunction expansions are utilized to describe acoustic responses in various segments, leading to systems of linear algebraic equations that are numerically solved after truncation. The research examines the influence of critical factors such as frequency, thickness of absorbent materials, and chamber length on power components, including reflection, absorption, transmission, and propagation, across different regions of the waveguide. Notably, the choice of sound-absorbent material emerges as a significant factor affecting scattering characteristics, with A-Glass outperforming E-Glass and Steel Wool in various scenarios. These insights offer valuable knowledge for optimizing acoustic systems in engineering applications, facilitating the design and enhancement of sound control mechanisms within waveguides.

Impact of Nanowire Radius and Channel Thickness with High-k Gate Dielectric in GAA-JLT

As the transistor’s size becomes smaller, degradation in the short-channel effects (SCEs) becomes more apparent. This leads to research work on multi-gate transistors such as the Fin-Field Effect Transistor (FinFET) and Gate-All-Around (GAA) transistor, where the 3D architecture have been shown to have superior performance as compared to conventional planar transistor. Transistor without junctions (JLT) which realizes a single type of doping has also been gaining popularity for biosensor applications due to its superior electrostatic performances in terms of Drain-Induced Barrier Lowering (DIBL), off-state leakage current (Ioff) and Subthreshold Slope (SS). In this work, the impact of changes in parameters such as the gate oxide material, nanowire radius and channel thickness toward the performance of a Gate-all-around JLT (GAA-JLT) have been studied using TCAD simulator. It was found that smaller nanowire radius and thicker channel produces lower DIBL, Ioff and SS, with the use of HfO2 as gate oxide materials shows better results than Si3N4. Meanwhile, the impact of parameters variations seemed to be negligible on the on-state current (Ion). The outcome of this work can be used as a basis to understand the impact of structural parameters variations towards the performance of a more complex GAA-JLT structure.

Design of tunable photothermal porous thermal emitter based on nonreciprocal effect

Tunable thermal emitters have become a research hotspot for high-efficiency, low-loss novel thermal radiation devices. It has been found that the tunability of thermal radiation devices can be greatly strengthened and the efficiency of photothermal conversion enhanced through the tuning of the radiation temperature by magneto-optical microstructures. In this paper, a novel porous thermal emitter for the mid-infrared band is designed and the interconnection between nonreciprocal radiation and photothermal conversion is investigated for the first time. The three-hole column (THC) porous structure is optimized from the traditional one-hole column (OHC) porous structure. Through detailed analysis of the light incident angle, external magnetic field strength, and hole diameter, it is shown that the strong nonreciprocal radiation is due to the variation of the cavity structure parameters, which enhances the microcavity resonance effect, thereby enhancing the surface plasmon resonance (SPR) on the porous surface. The electric field contours at different positions also visualize the enhancement mechanism of SPR for nonreciprocal radiation. It has been investigated that different magnetic field strengths and porous structures have significant impact on nonreciprocal thermal tuning. The nonreciprocal system can be used to tune the local heat around the hole, and the temperature difference increase as nonreciprocal effects is greater as the magnetic field strength and input power increases. This work also provides new ideas for the application of thermal emitters and the design of energy conversion devices.

Cognitively healthy Indians with higher Framingham Cardiovascular Risk Scores have higher WMH burden with lesser grey matter, white matter and hippocampal volumes

AbstractBackgroundIncreasing evidence indicates the important role of cardiovascular risk factors in dementia risk, particularly in Indians. It is known that cardiovascular risk factors tend to cluster together, and a widely used multivariable risk scoring is the Framingham Cardiovascular Risk Score (FRS). However, very little is known about the association between FRS and structural brain MRI parameters in cognitively healthy Indians.MethodBaseline clinical and brain MRI data of 487 cognitively healthy Indians (Clinical Dementia Rating score of ‘0’), who are part of two ongoing, large, aging cohort studies in India – Srinivaspura Aging, Neuro Senescence and COGnition study (SANSCOG) study (n = 200) and Tata Longitudinal Study of Aging (TLSA, n = 289) were utilized. FRS was calculated using clinical and blood biochemistry data, whereas brain MRI scans were performed on 3T MRI scanners. White matter hyperintensity (WMH) lesion segmentation was performed using Lesion Segmentation Toolbox (LST) and brain volumes (total grey matter, total white matter, 3rd ventricle, right and left hippocampus) were derived using FreeSurfer software and normalized according to total intracranial volumes of the respective subjects. Linear regression analysis was performed with FRS as independent variable and various structural MRI parameters as dependent variables. A p value of <0.05 was considered significant.ResultUrban subjects with higher FRS had significantly higher WMH volume (β = 0.00011, p<0.001, R2 = 0.130), lower grey matter (β = ‐0.00285, p<0.001, R2 = 0.206), white matter (β = ‐0.00180, p<0.001, R2 = 0.106), right hippocampal (β = ‐0.00004, p<0.001, R2 = 0.180), left hippocampal (β = ‐0.00003, p<0.001, R2 = 0.156) volumes and higher 3rd ventricle volumes (β = 0.00003, p<0.001, R2 = 0.150). Rural subjects higher FRS had lower grey matter (β = ‐0.00166, p<0.001, R2 = 0.118, white matter (β = ‐0.0011, p<0.001, R2 = 0.060), right hippocampal (β = ‐0.00002, p<0.001, R2 = 0.087), left hippocampal (β = ‐0.00002, p<0.001, R2 = 0.084) volumes and higher 3rd ventricle volumes (β = 0.00004, p<0.001, R2 = 0.264) but no significant association was seen with WMH volume.ConclusionThese findings indicate that cardiovascular risk is associated with structural brain changes in cognitively healthy Indians. Since cardiovascular risk can be reduced through cost‐effective community level strategies, such as lifestyle‐based interventions, promptly addressing this risk in Indians could be an important part of dementia prevention strategies.

Effects of calcination and sintering processes on structural profile parameters of modified BNKT-based ferroelectric ceramics

We have carried out a detailed study of synthesis and variations of structural profile parameters: lattice constants, unit cell volume, densities, porosity, crystallite size, dislocation density and micro-strain of BMZ modified BNKT (1-x) Bi0.5(Na0.70K0.30)0.5TiO3-xBiMg0.5Zr0.5O3 for x=0, 0.03, 0.06, 0.09 and 0.12 using x-ray diffraction. The conventional solid-state reaction method was used to synthesize BNKT samples. The BNKT powders were calcined at an optimized temperature of 850 °C for 2 hours. Keeping the calcination temperature fixed, optimized sintering temperature and time were also determined to be 11400C for 2 hours, based on the sharpness of the peaks and densification. The nature of the XRD patterns is qualitatively similar to that observed for calcined powders, however, the reflections are sharper in sintered samples presumably due to an increase in particle size. The XRD profile reveals an almost pure perovskite structure with cubic symmetries for all samples in both calcined powders as well as sintered samples. The crystallite size, dislocation densities, and micro-strain were determined by using William-Hall plots as well as Scherrer formula. It is observed that the maximum bulk density was found to be 5.88 gm/cm3 for x=0.03 which is 96.39 % of the theoretical density. The crystallite size varies from 19.84 - 44.15 nm with compositions for calcined powders and from 57.01- 62.69 nm for sintered samples. The very low value of crystallite sizes of calcined powder indicates that the particle size is comparably very low to that of sintered samples. The dislocation densities and micro-strain for calcined and sintered powders were observed in the range (5.1- 25.4)´10-4nm-2, and (2.54 - 3.1) ´10-4 nm-2 and (1.3 -4.8) ´10-3 and (8.93 - 9.90) ´10-4 respectively which are determined using William-Hall plot method. These results are also confirmed by the results obtained from the Scherrer method. Both results show improved profile parameters in sintered compositions than in calcination. This verifies that sintered BMZ-doped BNKT powders are promising candidates for many dielectric-based energy storage applications.

Influence of iron substitution on structural, magnetic, and magnetocaloric properties of Tb2Fe17−xAlx compounds synthesized by arc melting

In the present work, the structure and magnetic and magnetocaloric properties of the Tb2Fe17−xAlx compounds with x=0,0.25,0.5,0.75, and 1 were studied. These compounds were synthesized by arc furnace without subsequent annealing. Their crystal structure is a Th2Ni17 hexagonal structure with a P63/mmc space group. The Rietveld refinement of the X-ray diffractograms allowed for determining the structural parameter variations with different amounts of aluminum. Lattice parameters and the unit cell volume increase with aluminum amounts while the c/a ratio remains nearly constant. The Tb2Fe17−xAlx compounds exhibit a second-order magnetic phase transition from a ferromagnetic state to a paramagnetic state. The Curie temperature (TC) increases with the aluminum content, the observed effect is due to the magnetovolumic effect. The saturation magnetization (MS) decreases with the increase of Al content. Magnetic entropy and relative cooling power (RCP) decrease as the aluminum content increases. Tb2Fe17−xAlx compounds have a moderate magnetocaloric effect and a tunable operating temperature interval.

Structural Control of Plasmon Resonance in Molecularly Linked Metal Oxide Nanocrystal Gel Assemblies.

Nanocrystal gels exhibit collective optical phenomena based on interactions among their constituent building blocks. However, their inherently disordered structures have made it challenging to understand, predict, or design properties such as optical absorption spectra that are sensitive to the coupling between the plasmon resonances of the individual nanocrystals. Here, we bring indium tin oxide nanocrystal gels under chemical control and show that their infrared absorption can be predicted and systematically tuned by selecting the nanocrystal sizes and compositions and molecular structures of the link-mediating surface ligands. Thermoreversible assemblies with metal-terpyridine links form reproducible gel architectures, enabling us to derive a plasmon ruler that governs the spectral shifts upon gelation, predicated on the nanocrystal and ligand compositions. This empirical guide is validated using large-scale, many-bodied simulations to compute the optical spectra of gels with varied structural parameters. Based on the derived plasmon ruler, we design and demonstrate a nanocrystal mixture whose spectrum exhibits distinctive line narrowing upon assembly.

First-principles calculations on electronic, superconducting, mechanical, and thermodynamic properties for the superhard compound Tc2C under pressure

This study presents a theoretical investigation on the electronic, superconducting, mechanical, and thermodynamic properties of the superhard compound Tc2C up to 100 GPa. The investigation is conducted via the first-principles plane-wave pseudopotential method. Furthermore, to treat the exchange-correlation potential for the total energy calculations, the revised Perdew–Burke–Ernzerhof formulation stemming from the generalized gradient approximation is employed. The results suggest that Tc2C is a potential hard compound due to the robust covalent bonding between Tc and C atoms. Moreover, the electronic structure and electron–phonon coupling reveal that Tc2C is a superconducting material with Tc of 0.59 K at 0 GPa. Additionally, using the quasi-harmonic Debye model, the variation of crucial structural parameters, such as the volume thermal expansion coefficient, heat capacity, and isothermal bulk modulus and its pressure derivatives, is predicted in terms of temperature and pressure. The results demonstrate that temperature and pressure have contrasting effects on the volume thermal expansion coefficient and heat capacity, and the effect of temperature is larger than that of pressure, especially at low temperatures. The isothermal bulk modulus decreases with increasing temperature but increases with increasing pressure. The first and second pressure derivatives of the isothermal bulk modulus for Tc2C are not the assumed constants in the equation of state study at high pressures and temperatures. To our knowledge, this study presents the first quantitative theoretical prediction of the pressure and temperature dependence of the thermodynamic parameters for Tc2C, which is essential for understanding the basic physical properties of similar transition metal carbides.

Correlating pH-controlled green synthesis of NiO nanoparticles with their magnetic properties and catalytic performance

Nickel oxide nanoparticles (NiO) were prepared through environmentally friendly methods, using Nigella sativa seed extract as a stabilizing agent and different pH for the working solutions (pH=7, 9 and 11, respectively). In a second step, these NiO NPs were characterized with various and complementary techniques, as X-ray diffraction (XRD), Fourier transfer infrared spectroscopy (FTIR), Brunauer–Emmett–Teller method (BET), scanning electron microscopy (SEM) with EDS profiles, and a vibrating sample magnetometer (VSM). XRD patterns confirmed the one and only formation of NiO, as revealed by the Rietveld refinement procedure. The use of Williamson equation showed a significant variation in structural and microstructural parameters. Fourier transfer infrared spectroscopy (FTIR) analysis revealed vibration modes specific to Ni-O nanomaterials at 470 cm−1. On the other hand, magnetic investigations highlighted the fact that NiO, obtained in a solution with a pH equal to 9,called NiO-9, has the highest Ms and Mr values, of the order of 1.524 and 0.084 emu/g respectively, thus improving its ferromagnetic performance. Moreover, in the presence of NaBH4 and with the aim to reduce 4-nitrophenol to 4-aminophenol, in the case of water treatment, it appeared that the total time for the catalytic activity of NiO-9 was the lowest, i.e., 30 min. Moreover, NiO-9 was characterized by the faster rate constant, namely 0.29 min−1, which could be linked to intrinsic properties of this material (microstrain, electroactive sites and generated carrier charges).

Machine learning modeling of lung mechanics: Assessing the variability and propagation of uncertainty in respiratory-system compliance and airway resistance

Background and ObjectiveTraditional assessment of patient response in mechanical ventilation relies on respiratory-system compliance and airway resistance. Clinical evidence has shown high variability in these parameters, highlighting the difficulty of predicting them before the start of ventilation therapy. This motivates the creation of computational models that can connect structural and tissue features with lung mechanics. In this work, we leverage machine learning (ML) techniques to construct predictive lung function models informed by non-linear finite element simulations, and use them to investigate the propagation of uncertainty in the lung mechanical response. MethodsWe revisit a continuum poromechanical formulation of the lungs suitable for determining patient response. Based on this framework, we create high-fidelity finite element models of human lungs from medical images. We also develop a low-fidelity model based on an idealized sphere geometry. We then use these models to train and validate three ML architectures: single-fidelity and multi-fidelity Gaussian process regression, and artificial neural networks. We use the best predictive ML model to further study the sensitivity of lung response to variations in tissue structural parameters and boundary conditions via sensitivity analysis and forward uncertainty quantification. Codes are available for download at https://github.com/comp-medicine-uc/ML-lung-mechanics-UQ ResultsThe low-fidelity model delivers a lung response very close to that predicted by high-fidelity simulations and at a fraction of the computational time. Regarding the trained ML models, the multi-fidelity GP model consistently delivers better accuracy than the single-fidelity GP and neural network models in estimating respiratory-system compliance and resistance (R2∼0.99). In terms of computational efficiency, our ML model delivers a massive speed-up of ∼970,000× with respect to high-fidelity simulations. Regarding lung function, we observed an almost matched and non-linear behavior between specific structural parameters and chest wall stiffness with compliance. Also, we observed a strong modulation of airways resistance with tissue permeability. ConclusionsOur findings unveil the relevance of specific lung tissue parameters and boundary conditions in the respiratory-system response. Furthermore, we highlight the advantages of adopting a multi-fidelity ML approach that combines data from different levels to yield accurate and efficient estimates of clinical mechanical markers. We envision that the methods presented here can open the way to the development of predictive ML models of the lung response that can inform clinical decisions.

Dynamic amplification factor and interactions of a beam under compressive axial force and load travelling at varying velocity

In this article, the deflection profile and response characteristic of axially prestressed continuous beam under the actions of load travelling at non-uniform velocity is explored. To achieve this, The governing equation is transformed using weighted residual method to obtain a set of coupled second-order Ordinary Differential Equations (ODEs) governing the amplitude factors of the beam-mass system. This set of ODEs is further simplified by applying a modified asymptotic method of Struble. Impulse response function is finally employed to obtain solutions representing the responses of this structural member to accelerating masses. Dynamic time history is carried out. Deformation and responses due to the stress in the structure are evaluated for different parameters. Dynamic effects of decelerating, accelerating and uniform velocity-type of motions on the dynamic amplification factor (DAF) and response characteristics are extensively studied for various vital structural parameters such as the beam span length, foundation stiffness, prestress, rotatory inertia correction factor, load position and velocity. The values of the amplification factors (DAF) against various pertinent parameters are presented in plotted curves for the pinned-pinned beam. It is found that, for accelerating, decelerating and constant velocity-type of motion, the value of the dynamic amplification factor increases as the values of axial force, foundation subgrade, and rotatory inertia factor increase. Various useful results in perfect agreement with existing studies are presented. It is further established that variations of the various structural parameters of interest significantly alter the response characteristics of the vibrating system.

On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks

Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We use biologically plausible mathematical models to extensively study the effects of multiple key factors on overall balance of a network. We characterize a network’s baseline balanced state by certain functional properties, and demonstrate how variations in physiological and structural parameters of the network deviate this balance and, in particular, result in transitions in spontaneous activity of the network to high-amplitude slow oscillatory regimes. We show that deviations from the reference balanced state can be continuously quantified by measuring the ratio of mean excitatory to mean inhibitory synaptic conductances in the network. Our results suggest that the commonly observed ratio of the number of inhibitory to the number of excitatory neurons in local cortical networks is almost optimal for their stability and excitability. Moreover, the values of inhibitory synaptic decay time constants and density of inhibitory-to-inhibitory network connectivity are critical to overall balance and stability of cortical networks. However, network stability in our results is sufficiently robust against modulations of synaptic quantal conductances, as required by their role in learning and memory. Our study based on extensive bifurcation analyses thus reveal the functional optimality and criticality of structural and physiological parameters in establishing the baseline operating state of local cortical networks.