Decrease In Entropy Research Articles

Probing excitations and cooperatively rearranging regions in deeply supercooled liquids

Upon approaching the glass transition, the relaxation of supercooled liquids is controlled by activated processes, which become dominant at temperatures below the so-called dynamical crossover predicted by Mode Coupling theory (MCT). Two of the main frameworks rationalising this behaviour are dynamic facilitation theory (DF) and the thermodynamic scenario which give equally good descriptions of the available data. Only particle-resolved data from liquids supercooled below the MCT crossover can reveal the microscopic mechanism of relaxation. By employing state-of-the-art GPU simulations and nano-particle resolved colloidal experiments, we identify the elementary units of relaxation in deeply supercooled liquids. Focusing on the excitations of DF and cooperatively rearranging regions (CRRs) implied by the thermodynamic scenario, we find that several predictions of both hold well below the MCT crossover: for the elementary excitations, their density follows a Boltzmann law, and their timescales converge at low temperatures. For CRRs, the decrease in bulk configurational entropy is accompanied by the increase of their fractal dimension. While the timescale of excitations remains microscopic, that of CRRs tracks a timescale associated with dynamic heterogeneity, {t}^{*} sim {tau }_{alpha }^{0.8}. This timescale separation of excitations and CRRs opens the possibility of accumulation of excitations giving rise to cooperative behaviour leading to CRRs.

Energetic cost of feedback control

Successful feedback control of small systems allows for the rectification of thermal fluctuations, converting them into useful energy; however, control itself requires work. This paper emphasizes the fact that the controller is a physical entity interacting with the feedback-controlled system. For a specifically designed class of controllers, reciprocal interactions become nonreciprocal due to large timescale separation, which considerably simplifies the situation. We introduce a minimally dissipative controller model, illustrating the findings using a simple example. We find that the work required to run the controller must at least compensate for the decrease in entropy due to the control operation.

The Nanometer-Scale Proximity of Bilayers Facilitates Intermembrane Lipid Transfer.

Biological membranes approach one another in various biological phenomena, such as lipid transport at membrane contact sites and membrane fusion. The proximity of two bilayers may cause environmental changes in the interbilayer space and alter the dynamics of lipid molecules. Here, we investigate the structure and dynamics of vesicles aggregated due to the depletion attraction caused by polyethylene glycol (PEG) through static and dynamic small-angle neutron scattering. Manipulation of the interbilayer distance using PEG-conjugated lipids reveals that lipid molecules rapidly transfer between vesicles when the opposing bilayers are within ∼2 nm of each other. This distance corresponds to a region in which water molecules are more structured than in bulk water. Kinetic analysis suggests that the decrease in water entropy is responsible for the progression of lipid transfer. These results provide a basis for understanding the dynamic function of biomembranes in confined regions.

Estimating uncertainties in 3-D models of complex fold-and-thrust belts: A case study of the Eastern Alps triangle zone

Geological modeling commonly results in a single prescribed geometric representation of the subsurface with no consideration of uncertainties. Accounting for uncertainties is of particular importance in the triangle zone at the leading edge of deformation of the foreland fold-thrust belt of the European Alps, the Subalpine Molasse. Here, interpretations of the complex structures are limited to 2D and are based almost exclusively on subsurface data, lacking the constraint of surface data.Implicit modeling can be used to create automated 3D model realizations considering parameter uncertainty. In this sense, multiple possible models can be assessed within the uncertainty range assigned. As implicit modeling often yields artifacts or geologically unfeasible scenarios, the concept of geological topology can be used to constrain the modeling outputs, so that only models without artifacts are considered into the final model ensemble.Two experiments are designed to test out this workflow. The methodology is first tested using a very simple synthetic model, and later applied to a portion of the Subalpine Molasse, where different 2-D subsurface geometries have been proposed. For the first time, a 3D implicit model ensemble incorporating a full assessment of uncertainties is built in this area. Results show that it is feasible to use topological information for posterior model constraint, even in models of high structural complexity. To eliminate all non-meaningful models, however, it is necessary to use more than one topological constraint. A comparison of the prior and posterior model ensembles shows a correlation between model parameters and a shift in parameter probability density curves in the synthetic model experiment, and a decrease in entropy for both experiments. A topological constraint should thus be applied routinely when building a stochastic implicit model ensemble.

Particle size impact on pyrolysis of multi-biomass: a solid-state reaction modeling study

ABSTRACT Pyrolysis has gained significant attention due to its generation of value-added products from waste feeds in an environmentally friendly manner. The primary purpose of this study is to understand the effect of different particle sizes of biomass wastes – date stones (DS), cow manure (CM), and spent coffee grounds (SCG) – to understand better and design a biomass pyrolysis system. Thermogravimetric analysis of four different sizes of DS, SCG, and CM (range 1 mm to 125 μm) and a mixed sample (for each feed) was conducted at a heating rate of 10K/min from room temperature to 1173.15 K at inert conditions and employed model-based Coats–Redfern equations to understand the kinetic and thermodynamic parameters of the pyrolysis process. All the particle sizes except 355–125 μm for DS and SCG have the best-fit reaction mechanism of Ginstling-Brounshtein (D4). Both activation energy and pre-exponential factor decreased from 18.78 to 5.57 kJ/mol and 1.16 E+10 to 1.48 E+08 with reducing particle sizes. The onset degradation temperature, activation energy, change in enthalpy, and entropy decrease with particle sizes. The product formation is favored for all feeds and particle sizes, as the difference between the enthalpy and activation energies (Ea) is below 10 kJ/mol. As a result of their substantially lower activation energies and better reaction thermodynamics, mixed and smaller particle-sized biomass are favored.

A Law for Irreversible Thermodynamics? Synergy Increases Free Energy by Decreasing Entropy

Synergy is defined as an interaction giving rise to a whole that is greater than the simple sum of its parts. Here I explore empirically some thermodynamic properties of phenomena that are intuitively recognized as synergetic in a wide range of disciplines, searching for common features. In all cases studied, a decrease in entropy (S) was coupled to an increase in free energy (G). This is congruent with the assumption of the first and second law of thermodynamics that the total energy in a closed system is constant and is the sum of G and S. As no law of thermodynamics was deduced by theory but originated by pure empirical data, I propose a law for open synergistic systems that states that increases in G are coupled to decreases in S, allowing to thermodynamically recognize synergy. Open systems where S decreases without increases in G are not synergetic. This insight can be applied in a wide range of disciplines in natural and social sciences.

Research on cumulative effect and diagnosis method of transformer short-circuit impulse

After transformers suffer from short-circuit impact, their mechanical performance decreases significantly. This article establishes a two-wire vibration model to represent the coupling between forces and mechanics and analyzes the transient vibration signals of a 400 V transformer during 22 short-circuits impact. To illustrate the cumulative effect of short-circuits, the vibration entropy, and energy ratio of the main vibration frequency and half frequency are adopted. The results show that transient vibration signals of transformer in short-circuits contain half frequency components, such as 25 Hz and 75, etc., and with the increase of the number of short-circuits, plastic deformation exists in insulation material, which leads to the loss of winding clamping pressure, the reduction of natural frequency, and the upsurge of parametric resonance. With the increase of short circuits, the vibration entropy and half-frequency energy ratio increase, and the main frequency energy ratio decreases. After winding completely lose the axial stability, the vibration entropy and half frequency ratio decrease, and the main frequency ratio increases. The conclusion is of great significance to the analysis of the cumulative effect of short circuits on power transformers.

Information–energy equivalence and the emergence of self-replicating biological systems

Biological processes are characterized by a decrease in entropy in apparent violation of the second law of thermodynamics. Information stored in genomes help to solve this paradox when interpreted under the relationship between information and energy stated by Brillouin in the 1950’s. However, the origins of living forms from inanimate matter which have no information storage device remains an open question. In this paper, a theoretical approach is developed on this issue. The replication of a simple entity with a binary genome is assumed to require an information-equivalent energy in addition to the standard activation energy. It is found that, in some conditions, a decrease in entropy can be accomplished together with a decrease in Gibbs free energy. An equation of the total energy for the replication of this entity is derived. Three factors are predicted to lower this energy: a small number of states of the coding sequence, a lower temperature, and a high ratio of the reaction on diffusion coefficients. These factors may have favoured the emergence of evolutionary demons—information storage devices that are able to decrease entropy. It is evaluated that some short, single-stranded RNA sequences made only of G and of C may conform to this model. The consequences of this model and its predictions on the origins of life on Earth and on other planets are discussed.

Evolution is driven by natural autoencoding: reframing species, interaction codes, cooperation and sexual reproduction.

The continuity of life and its evolution, we proposed, emerge from an interactive group process manifested in networks of interaction. We term this process survival of the fitted. Here, we reason that survival of the fitted results from a natural computational process we term natural autoencoding. Natural autoencoding works by retaining repeating biological interactions while non-repeatable interactions disappear. (i) We define a species by its species interaction code, which consists of a compact description of the repeating interactions of species organisms with their external and internal environments. Species interaction codes are descriptions recorded in the biological infrastructure that enables repeating interactions. Encoding and decoding are interwoven. (ii) Evolution proceeds by natural autoencoding of sustained changes in species interaction codes. DNA is only one element in natural autoencoding. (iii) Natural autoencoding accounts for the paradox of genome randomization in sexual reproduction-recombined genomes are analogous to the diversified inputs required for artificial autoencoding. The increase in entropy generated by genome randomization compensates for the decrease in entropy generated by organized life. (iv) Natural autoencoding and artificial autoencoding algorithms manifest defined similarities and differences. Recognition of the importance of fittedness could well serve the future of a humanly livable biosphere.

Heterogeneity of fibroblasts is a hallmark of age-associated erectile dysfunction.

The prevalence of age-associated erectile dysfunction (ED) increases pronouncedly with age. However, the cellular composition and transcriptomic changes of aging penile corpus cavernosum remain largely unclear. Herein, we performed single cell sequencing penile corpus cavernosum from five young with normal erectile response and five old rats with ED. Clustering analysis identified 19 cell types, such as fibroblasts, myofibroblasts and immune cells. We next revealed their transcriptomic alterations and investigated novel subpopulations of major cell types. Among them, fibroblasts possessed the largest cell number and showed apparent heterogeneity. By performing single-cell entropy analysis on fibroblasts, we observed the age-associated decrease of entropy, and aged fibroblasts were found to adopt senescent secretory phenotype, as evidenced by the high expression of genes associated with the senescence-associated secretory phenotype (SASP). Finally, we constructed a comprehensive intercellular communication network and highlighted key mediators of crosstalk between fibroblasts and other cell types. We plotted a cellular atlas of aging cells within penile corpus cavernosum, especially fibroblasts. Our work will deepen the understanding of the heterogeneity among certain cell types within aged penile corpus cavernosum, which will generate positive effects on the future treatment of age-associated ED.

Homogeneous Adaboost Ensemble Machine Learning Algorithms with Reduced Entropy on Balanced Data

Today's world faces a serious public health problem with cancer. One type of cancer that begins in the breast and spreads to other body areas is breast cancer (BC). Breast cancer is one of the most prevalent cancers that claim the lives of women. It is also becoming clearer that most cases of breast cancer are already advanced when they are brought to the doctor's attention by the patient. The patient may have the evident lesion removed, but the seeds have reached an advanced stage of development or the body's ability to resist them has weakened considerably, rendering them ineffective. Although it is still much more common in more developed nations, it is also quickly spreading to less developed countries. The motivation behind this study is to use an ensemble method for the prediction of BC, as an ensemble model aims to automatically manage the strengths and weaknesses of each of its separate models, resulting in the best decision being made overall. The main objective of this paper is to predict and classify breast cancer using Adaboost ensemble techniques. The weighted entropy is computed for the target column. Taking each attribute's weights results in the weighted entropy. Each class's likelihood is represented by the weights. The amount of information gained increases with a decrease in entropy. Both individual and homogeneous ensemble classifiers, created by mixing Adaboost with different single classifiers, have been used in this work. In order to deal with the class imbalance issue as well as noise, the synthetic minority over-sampling technique (SMOTE) was used as part of the data mining pre-processing. The suggested approach uses a decision tree (DT) and naive Bayes (NB), with Adaboost ensemble techniques. The experimental findings shown 97.95% accuracy for prediction using the Adaboost-random forest classifier.

Multiobjective optimization of free convection through a nonuniform cabinet filled with porous media

AbstractIn the current study, multiobjective optimization and numerical simulation were used to evaluate free convection through a nonuniform cabinet, which has several technical applications, such as cooling techniques, solar air collectors, and heat sinks. The new aspect of the current study is to compute the maximum free convection within an irregular L‐shaped cavity filled with porous media using both computational analysis and response surface methodology (RSM). Moreover, the impacts of constant coefficients, such as aspect ratios of the horizontal (ARh), vertical (ARv), and Darcy numbers (Da) on the Nusselt number (Nuave), Nusselt number maximization (NNM), the temperature of the surface (Ts), and entropy (S) are studied and discussed to evaluate their effect on the thermal performance. The results showed that when Da, ARh, and ARv increase, Nuave improves while the Ts and S decline and the largest desirability is achieved at ARh = 0.9, ARv = 0.9, and Da = 10−1. Additionally, when compared with the subpar design data, the largest gain in NNM was 26.7 times, while the biggest decreases in surface temperature and entropy were 59% and 97%, respectively. As a result, the combination of the numerical simulation and RSM study produces a novel strategy and insightful suggestions for the ideal cooling L‐shaped cabinet design.

Thermodynamic Basis of Coevolution and Self-optimization, and Ecosystem

First, Darwinian evolution and mutual help seem to conflict. Second, since the second law of thermodynamics is based on isolated-equilibrium systems, it is in fact very limited. But, in essence, the vast majority of systems in the universe and nature are constantly changing and evolving with “life”. We proposed possible entropy decrease in isolated system due to internal interactions, etc. Based on biophysics, we research coevolution from thermodynamics and entropy by unified method. Let the entropy change dSA of a subsystem A is a set of its elements dSi , which may have various internal interactions with cooperation and complementary each other, so entropy may be decrease. This corresponds to the principle of least action of entropy change. It includes self evolution, and competition each other, etc. Third, evolution may combine self-optimization and selforganization, etc. Brain control of the body is the most typical of an internal interaction. No one would think that this only leads to an entropy increase. Fourth, we discuss the biological synergetics, ecosystem, and sustainable development. The cooperation-competition is a common phenomenon in the ecosystem. Coevolution is the more general evolution-development law of biological and active systems. This can unify natural competition and mutual help in biology, and is an important model for human development direction.

A case for chaos theory inclusion in neuropsychoanalytic modeling

ABSTRACT This paper provides a review of the current evidence of chaoticity at various scales of the brain–mind as well as the application of nonlinear tools in clinical practice. Based on these data, a hypothesis is formulated that the brain–mind at various scales can operate in linear, nonlinear, or hybrid modes, such as chaotic functioning accompanied by noise. A thesis formulated by Mark Solms that living systems must minimize Shannon’s entropy of physical states (sensory entropy) is considered. Based on the data presented in this paper, minimization of entropy in that sense appears to be describing only a part of the complex brain–mind dynamics. Studies evaluating measures of entropy specifically developed for real living systems such as discrete timescale entropy (ApEn) suggest that a decrease in EEG entropy can be observed in some neuronal processes (e.g. progression from wakefulness to deep sleep); however, EEG entropy is observed to be increasing at other times and in other modes of brain–mind functioning (e.g. progression from deep sleep to REM to wakefulness; and from vegetative state to wakefulness). The clinical implications are discussed. This paper proposes that it would be theoretically and clinically beneficial for future revisions of neuropsychoanalytic models to consider including the chaos theory framework.

Hypercycle of Geoscience, Nonlinear Whole Geoscience and Possible Entropy Decrease

First, based on the many levels and their cycles in geoscience, we research the hypercycle of geoscience. This is the hypercycle as a tool of self-organization applied to geoscience. It may form from a level to other higher levels. These levels influence each other and the co-evolution. Second, we discuss some possible mathematical methods, which include graph, vector, matrix, some equations, similar theories, etc. This method can be developed and perfected. Third, we propose the nonlinear whole geoscience and its three basic laws. Fourth, we discuss thermodynamics of geoscience, and in which possible entropy decrease under some sates, such as evolution and cycles of Earth, etc. Sustainable development of society must study the mode from high entropy to low entropy. Various cycles in geoscience cannot all be entropy increases, and cannot all be originated from the external interactions.

3D morphology and growth mechanism of primary Al3Ni in directionally solidified Al-16 wt% Ni alloy

The growth pattern and three-dimensional (3D) morphology of primary Al3Ni in directionally solidified Al-16 wt% Ni at different pulling rates were quantitatively and qualitatively investigated by synchrotron tomography. With the increasing cooling rate, Al3Ni crystals developed from faceted prism to non-faceted dendrites with V-shaped faceted arm ends. Faceted Al3Ni grows along [100] bounded by {011} facets, and the growth direction of non-faceted Al3Ni dendrites changes from [011̅] to [010]. The weakening of the faceted growth characteristics in the slow cooled sample is mainly due to the decrease of entropy of fusion caused by low Ni content in the liquid. A multi-layer atom model is established to describe and reveal the formation mechanism of faceted/non-faceted mixed structure at high cooling rate.

Consciousness alteration in focal epilepsy is related to loss of signal complexity and information processing

Alteration of awareness is a main feature of focal epileptic seizures. In this work, we studied how the information contained in EEG signals was modified during temporal lobe seizures with altered awareness by using permutation entropy (PE) as a measure of the complexity of the signal. PE estimation was performed in thirty-six seizures of sixteen patients with temporal lobe epilepsy who underwent SEEG recordings. We tested whether altered awareness (based on the Consciousness Seizure Score) was correlated with a loss of signal complexity. We estimated global changes in PE as well as regional changes to gain insight into the mechanisms associated with awareness impairment. Our results reveal a positive correlation between the decrease of entropy and the consciousness score as well as the existence of a threshold on entropy that could discriminate seizures with no alteration of awareness from seizures with profound alteration of awareness. The loss of signal complexity was diffuse, extending bilaterally and to the associative cortices, in patients with profound alteration of awareness and limited to the temporal mesial structures in patients with no alteration of awareness. Thus PE is a promising tool to discriminate between the different subgroups of awareness alteration in TLE.

Introduction to Biological Dark Energy: Experimental Evidence of Information Transfer under the Influence of Taheri Consciousness Fields and Investigating the Effects of the Fields on the Properties/Behavior of Water and a Biological Cell

The effects of Taheri Consciousness Fields (TCFs) on living organisms and non-living materials have been investigated. Since there is no physical intervention in applying TCFs, the findings suggested that the information transmitted from the Cosmic Consciousness Network is crucial in affecting the subjects under the study. The authors performed two experimental studies prior to this research. In the first experiment, the pH of pure water decreased significantly under the influence of TCFs. In the second experiment, the effect of TCFs on the Adenosine Triphosphate (ATP) production in the human HEK 293 cell line was investigated. It was found that the treated cells were able to generate a much greater amount of ATP compared to the control. This energy was released within a short period of TCF treatment (one hour) without sufficient glucose as the predominant fuel for cells. This study discusses the effects of TCFs by calculating the amount of information exchanged in the previous two experiments. According to Taheri, receiving information from TCFs requires a mental body. In other words, the behavior of water, and the human cell line alters under the influence of these fields because of receiving information through their mental body. Moreover, the shortage of time and resources to produce ATP in the TCFs treated cell strongly suggests that regardless of biological pathways, there is an alternative way to increase ATP in the immediate time, which is associated with an increase in information and a decrease in entropy of the system. This kind of energy is introduced and named “Biological Dark Energy” by Taheri.

Sensorimotor Cortical Activity during Respiratory Arousals in Obstructive Sleep Apnea.

Intensity of respiratory cortical arousals (RCA) is a pathophysiologic trait in obstructive sleep apnea (OSA) patients. We investigated the brain oscillatory features related to respiratory arousals in moderate and severe OSA. Raw electroencephalography (EEG) data recorded during polysomnography (PSG) of 102 OSA patients (32 females, mean age 51.6 ± 12 years) were retrospectively analyzed. Among all patients, 47 had moderate (respiratory distress index, RDI = 15−30/h) and 55 had severe (RDI > 30/h) OSA. Twenty RCA per sleep stage in each patient were randomly selected and a total of 10131 RCAs were analyzed. EEG signals obtained during, five seconds before and after the occurrence of each arousal were analyzed. The entropy (approximate (ApEn) and spectral (SpEn)) during each sleep stage (N1, N2 and REM) and area under the curve (AUC) of the EEG signal during the RCA was computed. Severe OSA compared to moderate OSA patients showed a significant decrease (p < 0.0001) in the AUC of the EEG signal during the RCA. Similarly, a significant decrease in spectral entropy, both before and after the RCA was observed, was observed in severe OSA patients when compared to moderate OSA patients. Contrarily, the approximate entropy showed an inverse pattern. The highest increase in approximate entropy was found in sleep stage N1. In conclusion, the dynamic range of sensorimotor cortical activity during respiratory arousals is sleep-stage specific, dependent on the frequency of respiratory events and uncoupled from autonomic activation. These findings could be useful for differential diagnosis of severe OSA from moderate OSA.

Mechanochemical route for carboxy substituted Schiff-Base polymer coated MWCNT composite as an efficient adsorbent for the removal of Methylene Blue dye: Kinetics, Isotherms and Thermodynamic studies

In the present investigation, we report a rapid and green mechanochemical approach for the synthesis of carboxy substituted Schiff-Base polymer (cPSB) and MWCNT coated with cPSB composite (cPSB@MWCNTs) as an efficient adsorbent for cationic methylene blue MB dye. The as-synthesized cPSB and cPSB@MWCNTs were characterized by Fourier-transformed infrared spectrometer (FTIR), X-ray diffraction (XRD) and Scanning electron microscopy (SEM) to analyze the structure, size and morphology. Effects of different variables such as catalyst loading, contact time, effect of initial dye concentration and pH of the medium during the process of dye adsorption were studied. Adsorption was in agreement with the pseudo-second-order and is a chemisorption process according to the kinetic analysis. The adsorption equilibrium data for the dye adsorption process fitted well with the Langmuir model. In cPSB@MWCNTs, the removal efficiency of MB was found to be 99 % in 90 min at pH 7. The adsorption of dyes on cPSB@MWCNTs from thermodynamic data was found to be spontaneous and endothermic with a continuous decrease in entropy. Further cPSB@MWCNTs composite demonstrated admirable maximum adsorption capacity towards both MB (96.9 mg g−1) indicating cPSB@MWCNTs as an efficient cationic dye adsorbent.