135 research outputs found
Interactions of Self-organizing Systems in Nature
No full textNature essentially consists of complex systems. The paper presents a conceptual framework to understand how complex systems interact with each other in nature. All natural systems are thermodynamically open and physically adaptive. The process of adaptation and continual self-organization cause these systems to interact continuously with the environment and compete against such similar systems for limited resources
Magnetic properties and coupled spin-phonon behavior in quasi-one-dimensional screw-chain compound BaMn2V2O8
No full textSpin-chain compounds are known to exhibit fascinating magnetic properties, which mostly display magnetic ordering at very low temperatures or remain dynamic even at 0 K. In contrast, the present quasi-one-dimensional spin-chain system BaMn2V2O8 exhibits a collinear antiferromagnetic (AFM) long-range ordering at a relatively higher temperature TN∼37 K, wherein the nearest-neighbor spins have AFM coupling along the spin chain, i.e., along the c axis. The present study also reveals a short-range magnetic ordering prevailing at considerably elevated temperatures above its TN. Temperature-dependent Raman spectroscopy demonstrates an occurrence of spin-phonon coupling below TN at least for two phonon modes, whereas the study also shows an unusual thermal evolution of the Raman modes above
TN, which is apparently associated to the short-range magnetic ordering. Furthermore, extensive ab initio density functional theory calculations accompanied with classical Heisenberg model based theoretical calculations of various exchange interaction parameters (J0–J5) suggest an AFM ground state, which matches well with the experimentally obtained spin structure
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Studies on the Emergence of Order in Out-of-equilibrium Systems
No full textA challenge in fundamental physics and especially in thermodynamics is to understand emergent order in far-from-equilibrium systems. While at equilibrium, temperature plays the role of a key thermodynamic variable whose uniformity in space and time defines the equilibrium state the system is in, this is not the case in a far-from-equilibrium driven system. When energy flows through a finite system at steady-state, temperature takes on a time-independent but spatially varying character. In this study, the convection patterns of a Rayleigh-Bénard fluid cell at steady-state is used as a prototype system where the temperature profile and fluctuations are measured spatio-temporally. The thermal data is obtained by performing high-resolution real-time infrared calorimetry on the convection system as it is first driven out-of-equilibrium when the power is applied, achieves steady-state, and then as it gradually relaxes back to room temperature equilibrium when the power is removed. This work provides new experimental data on the non-trivial nature of thermal fluctuations when stable complex convective structures emerge. The thermal analysis of these convective cells at steady-state further yield local equilibrium-like statistics as the temperature manifold bifurcates into regions of emergent order (sources) and disorder (sink). These localized domains which coexist together, reveal equilibrium-like fluctuations for the temperature scalar. We extend these experimental results to derive a thermodynamic equation of state for a driven system with emergent order from the first principles. We present a field theoretic formalism by defining the Lagrangian density as a function of a generic thermodynamic scalar. Our definition of the thermodynamic Lagrangian density involves two components, the internal work or the coherent part which gives rise to emergent order, and the internal dissipation or the incoherent part which acts as the internal sink. The salient feature of this formulation is that it takes into account the spatial and temporal gradients of the thermodynamic scalar as the system is driven out-of-equilibrium, similar to the Rayleigh-Bénard system. The action functional defined on this scalar manifold connects local equilibrium-like domains. On minimizing the action and solving the Euler-Lagrange equation, we obtain a generalized thermodynamic equation of state for a driven system with emergent order. In conclusion, these results correlate the spatial ordering of the convective cells with the evolution of the system's temperature manifold
Alternative Provision of Tenure Security and Rights to the Urban Poor: A Case Study from Ahmedabad
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Axial elongation associated with biomechanical factors during near work
No full textPurpose: To investigate the changes occurring in the axial length, choroidal thickness and anterior biometrics of the eye during a 10 minute near task performed in downward gaze. \ud
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Methods: Twenty young adult subjects (10 emmetropes and 10 myopes) participated in this study. To measure ocular biometrics in downward gaze, an optical biometer was inclined on a custom built, height and tilt adjustable table. Baseline measures were collected after each subject performed a distance primary gaze control task for 10 mins, to provide wash-out period for prior visual tasks before each of three different accommodation/gaze conditions. These other three conditions included a near task (2.5 D) in primary gaze, and a near (2.5 D) and a far (0 D) accommodative task in downward gaze (25°), all for 10 mins duration. Immediately after, and then 5 and 10 mins from the commencement of each trial, measurements of ocular biometrics (e.g. anterior biometrics, axial length, choroidal thickness and retinal thickness) were obtained. \ud
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Results: Axial length increased with accommodation and was significantly greater for downward gaze with accommodation (mean change ± SD 23 ± 13 µm at 10 mins) compared to primary gaze with accommodation (mean change 8 ± 15 µm at 10 mins) (p < 0.05). A small amount of choroidal thinning was also found during accommodation that was statistically significant in downward gaze (13 ± 14 µm at 10 mins, p < 0.05). Accommodation in downward gaze also caused greater changes in anterior chamber depth and lens thickness compared to accommodation in primary gaze.\ud
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Conclusion: Axial length, choroidal thickness and anterior eye biometrics change significantly during accommodation in downward gaze as a function of time. These changes appear to be due to the combined influence of biomechanical factors (i.e. extraocular muscle forces, ciliary muscle contraction) associated with near tasks in downward gaze
Changes in ocular biometrics and refraction during near work in downward gaze over time
No full textPURPOSE\ud
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To investigate changes in the characteristics of the corneal optics, total optics, anterior biometrics and axial length of the eye during a near task, in downward gaze, over 10 min. \ud
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METHODS\ud
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Ten emmetropes (mean - 0.14 ± 0.24 DS) and 10 myopes (mean - 2.26 ± 1.42 DS) aged from 18 to 30 years were recruited. To measure ocular biometrics and corneal topography in downward gaze, an optical biometer (Lenstar LS900) and a rotating Scheimpflug camera (Pentacam HR) were inclined on a custom built, height and tilt adjustable table. The total optics of the eye were measured in downward gaze with binocular fixation using a modified Shack-Hartmann wavefront sensor. Initially, subjects performed a distance viewing task at primary gaze for 10 min to provide a "wash-out" period for prior visual tasks. A distance task (watching video at 6 m) in downward gaze (25°) and a near task (watching video on a portable LCD screen with 2.5 D accommodation demand) in primary gaze and 25°downward gaze were then carried out, each for 10 min in a randomized order. During measurements, in dichoptic view, a Maltese cross was fixated with the right (untested) eye and the instrument’s fixation target was fixated with the subject’s tested left eye. Immediately after (0 min), 5 and 10 min from the commencement of each trial, measurements of ocular parameters were acquired in downward gaze. \ud
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RESULTS\ud
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Axial length exhibited a significant increase with downward gaze and accommodation over time (p<0.05). The greatest axial elongation was observed in downward gaze with 2.5 D accommodation after 10 min (mean change from baseline 23±3 µm). Downward gaze also caused greater changes in anterior chamber depth (ACD) and lens thickness (LT) with accommodation (ACD mean change -163±12µm at 10 min; LT mean change 173±17 µm at 10 min) compared to primary gaze with accommodation (ACD mean change -138±12µm at 10 min; LT mean change 131±15 µm at 10 min). Both corneal power and total ocular power changed by a small but significant amount with downward gaze (p<0.05), resulting in a myopic shift (~0.10 D) in the spherical power of the eye compared with primary gaze. \ud
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CONCLUSION\ud
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The axial length, anterior biometrics and ocular refraction change significantly with accommodation in downward gaze as a function of time. These findings provide new insights into the optical and bio-mechanical changes of the eye during typical near tasks
Causality in Discrete Time Physics Derived from Maupertuis Reduced Action Principle
No full textCausality describes the process and consequences from an action: a cause has an effect. Causality is preserved in classical physics as well as in special and general theories of relativity. Surprisingly, causality as a relationship between the cause and its effect is in neither of these theories considered a law or a principle. Its existence in physics has even been challenged by prominent opponents in part due to the time symmetric nature of the physical laws. With the use of the reduced action and the least action principle of Maupertuis along with a discrete dynamical time physics yielding an arrow of time, causality is defined as the partial spatial derivative of the reduced action and as such is position- and momentum-dependent and requests the presence of space. With this definition the system evolves from one step to the next without the need of time, while (discrete) time can be reconstructed
Novel Approaches for Offline Data-Driven Evolutionary Multiobjective Optimization
No full textMost multiobjective evolutionary algorithms (MOEAs) assume that analytical functions or simulation models are available while solving a multiobjective optimization problem (MOP). However, in some cases we must start with data and build approximation models known as surrogates that are later used to solve the MOP by an MOEA. These types of problems are called data-driven MOPs. This
thesis is devoted to solving so-called offline data-driven MOPs that are particularly challenging as no new data is available during the optimization process.
The author first presents approaches to utilize the uncertainty in the prediction of Kriging or Gaussian process (GP) surrogates as additional objectives. However, these approaches increase the complexity of the MOP being solved. Hence, the author proposes probabilistic selection approaches that can be embedded in a decomposition-based MOEA without further analytical derivations.
These approaches utilize Monte Carlo sampling and kernel density estimation to calculate the probability of selection criterion of the MOEA and later select individuals based on them. Next, the author proposes an interactive optimization framework that utilizes decision maker’s preferences for uncertainties in addition to preferences for objective values. The framework was further extended to use probabilistic selection approaches for a decomposition-based MOEA and a custom reference vector adaptation technique to consider uncertainty in the solutions during the adaptation process.
Building GPs with all the provided data becomes computationally expensive when the size of the data is large. Hence, the author finally proposes treed GP surrogates for multiobjective optimization (TGP-MO). They can be built with a relatively low computational cost and have a good accuracy exclusively in the regions around the optimal solutions. This thesis provides multiple novel approaches
and detailed experimental studies for solving offline data-driven MOPs with decision support that will enhance real-world problem-solving capabilities.
Keywords: metamodelling, surrogates, Pareto optimality, Kriging, Gaussian processes, evolutionary algorithm, decision making, uncertainty, interactive methods, preference informationunknown accessibilityei tietoa saavutettavuudest
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